Monitoring encrypted network traffic flows in a virtual environment using dynamic session key acquisition techniques

Information

  • Patent Grant
  • 11489666
  • Patent Number
    11,489,666
  • Date Filed
    Wednesday, November 25, 2020
    3 years ago
  • Date Issued
    Tuesday, November 1, 2022
    a year ago
Abstract
A method executed by a dynamic session key acquisition (DSKA) engine residing in a virtual environment includes receiving session decryption information extraction instructions that configure the DSKA engine to obtain session decryption information for at least one communication session involving a virtual machine and obtaining the session decryption information from the virtual machine in accordance with the session decryption information extraction instructions. The session decryption information includes cryptographic keys utilized by an application server instance in the virtual machine to establish the at least one communication session. The session decryption information obtained from the virtual machine is stored and provided to a network traffic monitoring (NTM) agent. The NTM agent utilizes the session decryption information to decrypt copies of encrypted network traffic flows belonging to the at least one communication session involving the virtual machine.
Description
TECHNICAL FIELD

The subject matter described herein relates to passive monitoring of network traffic communications in a virtual environment. More specifically, the subject matter relates to monitoring encrypted network traffic flows in a virtual environment using dynamic session key acquisition techniques.


BACKGROUND

The monitoring and processing of secure sockets layer (SSL) traffic is a computationally expensive task that places a large burden on a virtual network's resources. Many network visibility tools handle SSL traffic (e.g., SSL records communicated via packets) by acting as a Man-In-The-Middle (MITM) entity, thereby decrypting and re-encrypting received SSL traffic while extracting a clear-text copy for associated network monitoring tools. In a typical virtual SSL proxy architecture, a client device or instance is configured to negotiate an encrypted connection for a secure session (e.g., SSL session) between itself and an SSL proxy instance. Likewise, a destination server instance and the SSL proxy instance subsequently negotiate a second encrypted connection in order to conduct a secure session between the destination server instance and the SSL proxy instance. Since the SSL proxy instance must decrypt and re-encrypt all network traffic (e.g., record traffic or packet traffic) before the traffic can be forwarded to the intended recipient, this method (often referred to as active SSL inspection or full SSL inspection) can introduce severe performance bottlenecks on the processing of live network traffic. More specifically, active SSL inspection methods frequently used today involve terminating the SSL connection at a MITM point, decrypting the encrypted traffic data, creating a copy of clear text data to be sent to the out-of-band analysis tool(s), and then re-encrypting the connection prior to sending the encrypted network traffic to its intended destination server.


Accordingly, a need exists for methods, systems, and computer readable media for monitoring encrypted network traffic flows in a virtual environment using dynamic session key acquisition techniques.


SUMMARY

Methods, systems, and computer readable for monitoring encrypted network traffic flows in a virtual environment using dynamic session key acquisition techniques are disclosed. According to one method executed by a dynamic session key acquisition (DSKA) engine residing in a virtual environment, the method includes receiving session decryption information extraction instructions that configure the DSKA engine to obtain session decryption information for at least one communication session involving a virtual machine and obtaining the session decryption information from the virtual machine in accordance with the session decryption information extraction instructions, wherein the session decryption information includes cryptographic keys utilized by an application server instance in the virtual machine to establish the at least one communication session. The method further includes storing the session decryption information obtained from the virtual machine and providing the session decryption information to a network traffic monitoring (NTM) agent, wherein the NTM agent utilizes the session decryption information to decrypt copies of encrypted network traffic flows belonging to the at least one communication session involving the virtual machine.


The subject matter described herein may be implemented in software in combination with hardware and/or firmware. For example, the subject matter described herein may be implemented in software executed by a processor. In one exemplary implementation, the subject matter described herein may be implemented using a non-transitory computer readable medium having stored therein computer executable instructions that when executed by the processor of a computer control the computer to perform steps. Exemplary non-transitory computer readable media suitable for implementing the subject matter described herein include non-transitory devices, such as disk memory devices, chip memory devices, programmable logic devices, field-programmable gate arrays, and application specific integrated circuits. In addition, a computer readable medium that implements the subject matter described herein may be located on a single device or computing platform or may be distributed across multiple devices or computing platforms.


As used herein, the term ‘node’ refers to a physical computing platform including one or more processors, network interfaces, and memory.


As used herein, each of the terms ‘engine’ and ‘agent’ refers to virtual components that are supported by underlying hardware and software for implementing the feature(s) being described.


As used herein, the term “packet” refers to a network packet or any formatted unit of data capable of being transmitted in a computer network, such as protocol data unit, a frame, a datagram, a user datagram protocol packet, a transport control protocol packet, an SSL record, a TLS record, or the like.





BRIEF DESCRIPTION OF THE DRAWINGS

The subject matter described herein will now be explained with reference to the accompanying drawings of which:



FIG. 1 is a block diagram illustrating a dynamic session key acquisition system that is configured to monitor encrypted network traffic flows in a virtual environment using dynamic session key acquisition techniques according to an embodiment of the subject matter described herein;



FIG. 2 is a block diagram illustrating a decryption session key acquisition system included in a virtual environment according to an embodiment of the subject matter described herein; and



FIG. 3 is flowchart illustrating a process for monitoring encrypted network traffic flows in a virtual environment using dynamic session key acquisition techniques according to an embodiment of the subject matter described herein.





DETAILED DESCRIPTION

The subject matter described herein relates to methods, systems, and computer readable media for monitoring encrypted network traffic flows in a virtual environment using dynamic session key acquisition techniques. In some embodiments, the disclosed subject matter includes a dynamic session key acquisition (DSKA) engine that is configured to communicate with network traffic monitoring (NTM) agent (e.g., a an SSL-aware network packet broker (NPB) element) and monitor communications in a virtual environment. In some examples, the NTM agent may comprise an extended Berkeley packet filter (eBPF)-based key acquisition mechanism that is configured to passively obtain SDI information without active involvement (e.g., proxy functionality) of an SSL key server instance. Specifically, the DSKA engine may be configured to detect per-session cryptographic key information session decryption information contained in packets or records communicated between a virtual SSL server instance and a virtual application server instance. Such per-session cryptographic key information (e.g., public and private pair key information) may be referred to herein as session decryption information (SDI). Alternatively, the DSKA engine may directly obtain session decryption information from the virtual SSL server instance (e.g., its local key store). Once obtained, the session decryption information may be provided to the NTM agent by the DSKA engine via a virtual tap interface. In some embodiments, the session decryption information associated with SSL sessions monitored by the DSKA system is sent via a secure communications tunnel (e.g., an IPsec tunnel) that is established between the NTM agent and a virtual tap instance. The NTM agent may then use the session decryption information to inspect copies of encrypted packets and perform a number of NPB functions, such as filtering, sampling, de-duplication, and data masking, at a much higher throughput rate than a network element that implements active SSL decrypt/encrypt inspection.


In some instances, the disclosed subject matter describes the encryption and decryption of packets as part of the monitoring of network traffic flows. Although the disclosed subject matter pertains largely to the encryption and decryption of SSL-based datagrams or records (which may be communicated via one or more packets), it is understood by persons skilled in the art of SSL communications that any description below of the encryption and decryption of packets corresponding to a monitored network traffic flow can involve the encryption and decryption of SSL-based records. In some embodiments, a record is a logical portioning at SSL level (above layer 4) and may span (i.e., be included in part via) multiple packets.


Embodiments of the disclosed subject matter illustrate exemplary deployments in the context of SSL communications. It will be appreciated that other embodiments of the disclosed subject matter can be deployed in a generally similar manner to provide the monitoring functionality in a transport layer security (TLS)-based or an IPsec-based encryption environment.


Reference will now be made in detail to various embodiments of the subject matter described herein, examples of which are illustrated in the accompanying drawings. Wherever possible, the same reference numbers will be used throughout the drawings to refer to the same or like parts.



FIG. 1 depicts a logical block diagram of one exemplary DSKA-based monitoring system that is described herein. As shown in FIG. 1, a network environment 100 includes at least one client device 102 that hosts a client application 103 (e.g., a web browser application). Client device 102 may comprise a user endpoint device, such as a smartphone, personal computer, laptop computer, Internet of things (IoT) device, or any other device that is configured to host and support client application 103. Alternatively, client device 102 may comprise a client instance that runs on a virtual machine hosted within a cloud-computing environment.


Network environment 100 may further include a computing platform 104 and an NTM agent 106. Computing platform 104 can comprise a DSKA engine 108 that is configured to communicate with virtual machine (VM) 110, which hosts an application server instance 112 and an SSL server instance 114. For example, each of application server instance 112 and SSL server instance 114 may comprise a virtual instance running on a virtual machine container hosted within a cloud-computing environment. In some embodiments, SSL server instance 114 may provide SSL service support for application server instance 112. For example, SSL server instance 114 may be configured to establish an SSL communication session with client device 102 in response to application server instance 112 receiving secure session requests (from client application 103). In some embodiments, the monitored communication session between client device 102 and an application server instance 112 may be established using a per-session encryption technique, such as elliptic curve Diffie-Hellman ephemeral (ECDHE). In other embodiments (not shown), the SSL server instance 114 and application server instance 112 may constitute the same entity (i.e., the application server is capable of conducting its own SSL key generation for a session with client application 103).


In some embodiments, SSL server instance 114 can be configured for creating, distributing, and storing session decryption information (e.g., ephemeral cryptographic security keys and associated session identification information) for communication sessions traversing a monitored network environment. For example, as used herein, session decryption information may include at least private and public cryptographic key pair information that is associated with a monitored session. In some embodiments, SSL server instance 114 is responsible for generating the cryptographic public and private key pairs for a monitored application server instance 112 that is establishing an SSL session with a requesting client application 103 and/or client device 102.


In one exemplary scenario, client application 103 may initiate an SSL session with application server instance 112. In such a scenario, application server instance 112 may send a message to SSL server instance 114 to request that session decryption information (e.g., public and private key pair data) for the client requested session be generated and stored by SSL server instance 114. In some embodiments, the generated session decryption information may include ECDHE cryptographic security keys (e.g., public and private key pair data). SSL server instance 114 may maintain a key store (not shown in FIG. 1) that is configured to store data that identifies monitored communication sessions (e.g., a session involving the application server instance 112) as well as the session decryption information corresponding to the monitored communication session. For example, SSL server instance 114 may include a key store database that contains entries that map public key and private key pairs to one or more monitored session identifiers. Exemplary session identifiers may include a client application identifier, a client device identifier, a monitored application identifier, a monitored application server identifier, a VLAN identifier, or a SSL-based identifier.


In some embodiments, DSKA engine 108 may be configured to the acquire session decryption information from the SSL server instance 114 that is hosted locally by virtual machine 110. As described in greater detail below and in FIG. 2, DSKA engine 108 may be adapted to monitor the communication sessions conducted between SSL server instance 114 and application server instance 112 and extract session decryption information contained within (e.g., using a hook function). Alternatively, DSKA engine 108 may be configured to obtain the session decryption information, via direct access, from the aforementioned key store. After obtaining the session decryption information, DSKA engine 108 can forward that information to NTM agent 106.


In some embodiments, NTM agent 106 comprises an SSL-aware network packet broker (NPB) device configured to monitor network traffic flow records (e.g., packets or records communicated between client device 102 and application server instance 112) in a passive manner. NTM agent 106 may also be configured to maintain a list of sessions that have been designated to be monitored. In some embodiments, a network operator may provision NTM agent 106 with session identifiers that indicate specific applications and/or sessions that require monitoring or surveillance. For example, a session list may include a number of entries, wherein each of the entries includes at least one session identifier, such as a client application identifier, a client device identifier, a monitored application identifier, a monitored application device identifier, a VLAN identifier, and/or an SSL-based identifier (e.g., a public cryptographic key value). Notably, the session list maintained by NTM agent 106 includes session identifiers that correspond to one or more of the session identifiers included in a key store database managed by SSL server instance 114 (as described below in FIG. 2).


In some embodiments, NTM agent 106 may be configured to receive copies of encrypted network traffic flows communicated between client device 102 and application server instance 112 (or a monitored application server) in computing platform 104. In some embodiments, NTM agent 106 may be connected (e.g., via a virtual network interface card as shown in FIG. 2) to one or more virtual tap (or probe) instances in computing platform 104 that are configured to identify and copy packets/records of specified network traffic flows. After identifying an encrypted packet or record associated with a network traffic flow that has been designated for monitoring, virtual tap instance 115 is configured to create a copy of the packet or record and forward the encrypted copies to NTM agent 106 via a secure interface connection 122. Similarly, the originally received packet or record (from which the copy was made) is forwarded to its intended destination by virtual tap instances 115. For example, NTM agent 106 can receive (from virtual tap instance 115) copies of encrypted network traffic flows that are communicated to/from virtual machine 110. Further, NTM agent 106 may be configured to inspect these network traffic flows communicated over sessions that have been designated for monitoring. In some embodiments, NTM agent 106 may also be provisioned with sufficient storage (or granted access to sufficient non-local storage) to store the copies of encrypted records and/or packets of the monitored sessions.


As indicated above, NTM agent 106 is further configured to establish a secure interface connection 122 with computing platform 104. In some embodiments, secure interface connection 122 is established as a separate and dedicated SSL session or an IPsec tunnel between NTM agent 106 and computing platform 104. Once established, secure interface connection 122 may be used by NTM agent 106 to receive session decryption information (e.g., public and private cryptographic key pair information) for a session originally requested by client device 102. In some embodiments, DSKA engine 108 may be configured to distribute the session decryption information obtained from server instance(s) in virtual machine 110 by automatically forwarding the collected session decryption information (e.g., private and public cryptographic key information and session identification information) to one or more subscribed/designated NTM agents (e.g., NTM agent 106) at or near the time when the public and private cryptographic key pairs are created. As previously indicated, DSKA engine 108 is configured to maintain an authorization list of encryption-aware NTM agents that are authorized or subscribed to receive session decryption information related to a monitored session. Specifically, NTM agents (e.g., NTM agent 106) included in the authorization list maintained by DSKA engine 108 are designated to receive the session decryption information in real-time (e.g., as the session decryption information is generated) or in accordance with a session decryption information provisioning schedule established by a network operator. For example, DSKA engine 108 may attempt to provide public and private key pair information to each subscribed NTM agent or device via separate secure interface connections (e.g., similar to secure interface connection 122) as soon as the public and private key information is generated and/or stored by SSL server instance 114.


After NTM agent 106 receives the session decryption information from DSKA engine 108 via virtual tap instance 115 and secure interface connection 122, NTM agent 106 may decrypt the packets and/or records of the copied encrypted traffic flow(s). In some embodiments, NTM agent 106 may receive a copy of encrypted traffic flow(s) from virtual tap instance 115. Notably, NTM agent 106 is configured to decrypt the copies of the obtained encrypted records using the session decryption information received from SSL server instance 114.


NTM agent 106 may then inspect the network traffic flow records and/or packets decrypted with the session decryption information (i.e., private key value) and perform NPB functions (e.g., filtering, sampling, de-duplication, and/or data masking) on the decrypted network traffic flow records and/or packets. For example, after the encrypted network traffic flow packets and/or records are decrypted by NTM agent 106 using the session decryption information provided by DSKA engine 108, the decrypted packets/records are subsequently processed by one or more packet broker filtering rules and/or sampling rules provisioned in NTM agent 106. In particular, the rules are used by NTM agent 106 to determine which packets and/or records are to be forwarded to one or more out-of-band network tools 116 (e.g., via NPB tool ports). NTM agent 106 may also apply processing operations that modify the packets/records or the associated network traffic flow (e.g., replication, de-duplication, data masking, etc.) prior to forwarding packets/records to the appropriate out-of-band network tools 116 (e.g., via the NPB tool ports). Notably, NPB functions performed by NTM agent 106 are conducted at a greater throughput rate as compared to a MITM network element that implements active SSL decrypt/encrypt inspection. After assessing and determining the proper network tool destinations, NTM agent 106 forwards the decrypted session records and/or flow metadata accordingly.


It will be appreciated that FIG. 1 is for illustrative purposes and that various depicted entities, their locations, and/or their functions described above in relation to FIG. 1 may be changed, altered, added, or removed without departing from the scope of the disclosed subject matter.



FIG. 2 depicts is a block diagram illustrating a dynamic session key acquisition system existing in a network environment 200 according to an embodiment of the subject matter described herein. As shown in FIG. 2, network environment 200 may comprise a physical computing platform 204 that supports a hypervisor 206 and at least one virtual machine 208. Computing platform 204 may also include underlying hardware components that support hypervisor 206 and virtual machine 208. For example, computer platform 204 may include a processor 205, memory 207, disk storage 209, a network interface card (not shown), and the like. Processor 205 may comprise a central processing unit (CPU), a microcontroller, or any other physical processing device for executing software instructions stored in memory 207. Memory 207 may comprise any suitable non-transitory storage medium that resides on a physical computing host device, such as random-access memory (RAM), flash memory, and the like. Disk storage 209 can include any physical storage unit configured to storing data on computing platform 204, such as a hard disk drive (HDD) or array, a solid state drive (SSD) or array, a portable flash drive, and the like.


As indicated above, computing platform 204 may include a hypervisor 206 and at least one virtual machine 208. Hypervisor 206 may either be a Type _1 hypervisor (e.g., a bare metal hypervisor) or a Type 2 hypervisor (e.g., a kernel-based VM hypervisor). In some examples, hypervisor 206 is a software program that enables multiple guest operating systems to share the physical resources of a single hardware host, i.e., computing platform 204. Notably, hypervisor 206 coordinates the assignment and allocation of hardware resources to establish tenant virtual machines. Further, hypervisor 206 may be responsible for establishing and managing one or machines (e.g., creating, deleting, migrating, restarting, and/or stopping virtual machines). For example, hypervisor 206 may allocate and/or emulate physical resources to establish and support virtual machine 208. Hypervisor 206 may create virtual machine environments and coordinate system calls for the processor, memory, hard disk, network, and other physical platform resources directly (e.g., Type 1 hypervisor) or via the computing platform operating system (e.g., Type 2 hypervisor). In some examples, hypervisor 206 may be configured to receive commands from a hypervisor controller (not shown) or some other entity that instructs hypervisor 206 as to how to manage and/or configure virtual machine 208.


Hypervisor 206 may be configured to support a DSKA engine 210 and an associated virtual network interface card 218. Notably, virtual network interface card 218 can be supported by an underlying physical hardware network interface card (not shown) installed on computing platform 204. In some embodiments, DSKA engine 210 may comprise a packet filter element (e.g., an enhanced Berkeley packet filter) that is used to manage the extraction of session decryption information communicated and/or utilized by server instances supported in virtual machine 208. DSKA engine 210 may also include a local database 224 that is configured to store session decryption information that the DSKA engine 210 has collected from virtual machine 208 (e.g., directly from key store 222 or from communication session 213). Local database 224 may also be used by DSKA engine 210 to maintain identification records of network traffic monitoring (NTM) agents that are subscribed to receive session decryption information. For example, DSKA engine 210 may be configured to maintain a log in database 224 of NTM agents that are configured to monitor a particular session and provide the session decryption information to the appropriate NTM agents.


Network environment 200 may further include a NTM agent 202. Although depicted in FIG. 2 as a separate network element located in network environment 200, NTM agent 202 may instead be hosted in virtual machine 208 or another virtual machine local to computing platform 204. Alternatively, NTM agent 202 may be supported by a separate virtual machine or application that resides on a different physical computing host device (not shown).


In some embodiments, DSKA engine 210 may be configured to receive session decryption information extraction instructions (e.g., from a network operator) via a virtual tap instance 216 or NTM agent 202. In some embodiments, DSKA engine 210 is initially provisioned with instructions or code by a network operator. For example, the extraction instructions or code may be delivered to DSKA engine 210 directly from virtual tap instance 216 or from NTM agent 202, via a secure connection 220, a virtual network interface card 218, and virtual tap instance 216. In such a scenario, virtual tap instance 216 or NTM agent 202 passes instructions to DSKA engine 210 that instruct the DSKA engine 210 to monitor for and obtain session decryption information communicated in network traffic sessions associated with particular virtual application server instance. For example, the extraction instructions may include a session identifier associated with the monitored application server instance 212.


As shown in FIG. 2, virtual tap instance 216 may comprise a virtual instance of a software-based monitoring agent application that is used to observe and generate copies of encrypted network traffic flow records and/or packets associated with a monitored session between a client (not shown) and monitored application server instance 212. In some embodiments, the records and/or packets are encrypted for communication between the client and application server instance 212 using ECDHE, or some other per-session, public and private cryptographic key encryption technique. Virtual tap instance 216 is interposed in virtual machine 208 so as to passively create encrypted copies of monitored record and/or packets associated with a secure communication session between the client and application server instance 212. The copied network traffic flow records and/or packets are relayed and/or forwarded by virtual tap instance 216 to NTM agent 202. Notably, the copied network traffic flow records and/or packets received by NTM agent 202 retain their original encryption. Further, virtual tap instance 216 may be deployed as a virtualized element in a cloud computing virtual environment, so as to be embodied by a virtual machine or virtual computing cluster. In some embodiments, a virtual tap instance 216 may be deployed in tandem with a virtual application server instance (e.g., application server instance 212) that is to be monitored, such that virtual tap instance 216 is capable of observing and passively creating copies of monitored network traffic flow records or packets associated with a secure communication session between a monitored client and application server instance 212. The copied monitored network traffic flow records and/or packets retain their original encryption and are relayed or forwarded to NTM agent 202 via virtual network interface card 218 and secure connection 220.


After receiving the session decryption information extraction instructions from either virtual tap instance 216 or NTM agent 202, DSKA engine 210 may attempt to obtain and record the requested session decryption information using a plurality of techniques. Notably, the manner in which DSKA engine 210 obtains the requested session decryption information may be based on its own local configuration or in accordance with a protocol designation included in the session decryption information extraction instructions itself. For example, the DSKA engine 210 may be configured to observe network traffic flow communications between the monitored application server instance 212 and SSL server instance 214 in virtual machine 208.


SSL server instance 214 may be configured to create, distribute, and store session-specific cryptographic key pairs that can be used to encrypt and decrypt SSL records and/or packets associated with a monitored SSL session. Monitored application server instance 212 is configured to communicate with SSL server instance 214 to obtain security key information corresponding to one or more communication sessions with a requesting client application and/or device. Specifically, SSL server instance 214 is configured to provide SSL services to a monitored application server instance 212, which is being monitored by the monitoring system (i.e., NTM agent 202, DSKA engine 210, and/or and virtual tap instance 216). For example, SSL server instance 214 can generate and store per-session private and public key information on behalf of a monitored application hosted by application server instance 212. Further, SSL server instance 214 may use database 224 to store session decrypt information that identifies the session (e.g., a session identifier, session identifier tuple, etc.), includes a public key value to be used by the application server instance 212 for establishing a secure session with a client instance or device (not shown), and includes a private key value to be used by application server instance 212 in establishing a secure session with the client instance or device.


In some embodiments, monitored application server instance 212 may receive a session request from a client (not shown) and be configured to establish an SSL session to securely communicate data via records or packets with the client. In such a scenario, SSL server instance 214 may be configured to generate and make available a public and private cryptographic key pair to monitored application server instance 212. For example, in instances where SSL server instance 214 and monitored application server instance 212 are the same entity (e.g., the same server), then SSL server instance 214 may communicate the public cryptographic key to the client and provide (e.g., “push”) session decryption information including the cryptographic key pair to one or more registered NTM agents, such as NTM agent 202.


In some embodiments, DSKA engine 210 may execute a hook function that accesses and inspects the packets or records that are communicated in the network traffic flow between application server instance 212 and SSL server instance 214 (as described below). Although monitored application server instance 212 and SSL server instance 214 are shown to reside on the same virtual machine in FIG. 2, the two server instances may reside on separate virtual machines hosted by computing platform 204 without departing from the scope of the disclosed subject matter.


In other embodiments, DSKA engine 210 may be configured to directly access and inspect session decryption information that is stored in key store 222 of SSL server instance 214. Key store 222 may be used by SSL server instance 214 may store all of the session decryption information corresponding to SSL sessions (with various application server instances) established by SSL server instance 214. Specifically, key store 222 may contain entries that include session identification data that identifies, or can be used to identify, a communications session between the monitored client and the monitored application server, as well as the public and private cryptographic keys associated with that session.


In some embodiments, DSKA engine 210 may utilize a query function that sends a request message to SSL server instance 214 and requests the corresponding session decryption information stored in key store 222. In some embodiments, DSKA engine 210 is able to execute a query function to directly access and view the key store 222 residing in SSL server instance 214. For example, DSKA engine 210 provides a session identifier that is included in the request message sent to key store 222 that identifies the session being monitored. In response to receiving such a request message from DSKA engine 210, SSL server instance 214 may forward the session decryption information corresponding to the provided session identifier to DSKA engine 210. In other embodiments, DSKA engine 210 may execute a hook function to directly access the key store 222 and extract the appropriate session decryption information per the extraction instructions (which contains the session identifier).


In some examples, DSKA engine 210 may be configured to monitor a communication session 213 established between application server instance 212 and SSL server instance 214. In some embodiments, communications session 213 may be implemented via an application programming interface (API). Notably, DSKA engine 210 can be configured by the received extraction instructions to inspect session 213 for communicated session decryption information. For instance, DSKA engine 210 may utilize a hook function to intercept packets or records that include a particular session identifier during transmission between the SSL server instance 214 and any application server instance (e.g., application server instance 212). Session identifiers utilized by DSKA engine 210 may include one or more of a destination address, a destination port number, an origination address, an origination port, and the like. Other session identifiers utilized by DSKA engine 210 may also include SSL based information, such as a public key pair value. In the event that DSKA engine 210 detects a defined session identifier in a packet or record communicated in session 213, DSKA engine 210 may copy that packet or record. DSKA engine 210 may subsequently extract and store the session decryption information contained in the copied packet or record in a database 224.


DSKA engine 210 is configured to create and maintain database 224, which may comprise any data structure that includes session decryption information that is observed in the communication session 213 between application server instance 212 and SSL server instance 214. Database 224 may also be used to store session decryption information extracted directly from key store 222. After successfully storing the session decryption information acquired from the server instance(s) hosted in virtual machine 208, DSKA engine 210 may be configured to forward the session decryption information to virtual tap instance 216. Fore example, DSKA engine 210 may generate and forward a report containing the session decryption information to virtual tap instance 216. Alternatively, database 224 may be accessed directly by virtual tap instance 216, which subsequently extracts the session decryption information.


After obtaining the session decryption information from the DSKA engine 210, virtual tap instance 216 is configured to relay or forward the session decryption information to NTM agent 202. In some embodiments, virtual tap instance 216 forwards the session decryption information to a virtual network interface card 218, which in turn directs the session decryption information to NTM agent 202 via a secure connection 220. For example, DSKA engine 210 may be configured to automatically send the session decryption information to NTM agent 202 at the time that the session decryption is obtained by DSKA engine 210. NTM agent 202 is configured to store the session decryption information acquired from DSKA engine 210 (via virtual tap instance 216) and to subsequently use this session decryption information to decrypt copies of monitored network traffic flow records (and/or packets) associated with the session, wherein the record copies are provided by the virtual tap instance 216 (or monitoring probes). In this manner, NTM agent 202 is configured to monitor, decrypt and inspect secure session traffic flow records in network environment 200, while avoiding the processing bottleneck(s) associated with prior active SSL monitoring/decryption approaches.


NTM agent 202 may subsequently inspect the network traffic flow records and/or packets decrypted with the session decryption information (i.e., private key value) and perform NPB functions (e.g., filtering, sampling, de-duplication, and/or data masking) on the decrypted network traffic flow records and/or packets. Similar to the manner described above with respect to FIG. 1, decrypted packets/records may be subsequently processed by one or more packet broker filtering rules and/or sampling rules provisioned in NTM agent 202. Namely, the rules are used by NTM agent 202 to determine which packets and/or records are to be forwarded to one or more out-of-band network tools (not shown in FIG. 2).



FIG. 3 is flowchart illustrating a process for monitoring encrypted network traffic flows in a virtual environment using dynamic session key acquisition techniques according to an embodiment of the subject matter described herein. In some embodiments, process 300, or portions thereof, may be performed by DSKA engine 108 and NTM agent 106 shown in FIG. 1 and/or DSKA engine 210 and NTM agent 202 shown in FIG. 2. In some embodiments, process 300 may include an algorithm comprising steps 302, 304, 306, and/or 308 that is stored in memory and executed by a processor (e.g., a CPU of computing platform 104 or 204).


In step 302, session decryption information extraction instructions that configure the DSKA engine to obtain session decryption information for at least one communication session involving a virtual machine are received. In some embodiments, one or more monitoring taps or an NTM agent is configured to upload session decryption information extraction instruction code to the DSKA engine.


In step 304, the session decryption information from the virtual machine is obtained in accordance with the session decryption information extraction instructions. For example, the session decryption information includes cryptographic keys utilized by an application server instance in the virtual machine to establish the at least one communication session. In some embodiments, DSKA engine obtains session decryption information directly from a key store associated with a SSL server instance executed by the virtual machine. In other embodiments, the DSKA engine monitors a communication session between a monitored application server instance and the SSL server instance. Notably, the DSKA engine may utilize a hook function that attempts to identify packets or records containing a session identifier Indicated in the previously received session decryption information extraction instructions.


In step 306, the session decryption information obtained from the virtual machine is stored. In some examples, the DSKA engine is configured to store the session decryption information obtained either directly from the SSL server key store or from the monitored communication session between the SSL server and the monitored application server instance. Notably, the DSKA engine stores the acquired session decryption information in local database 224.


In step 308, the session decryption information is provided to a NTM agent. In some embodiments, the NTM agent utilizes the session decryption information to decrypt copies of encrypted network traffic flows belonging to the at least one communication session involving the virtual machine. In addition, the NTM agent utilizes the session decryption information to decrypt copies of encrypted network traffic flows belonging to the at least one communication session involving the virtual machine. For example, the NTM agent may be configured to send the decrypted network traffic flows to at least one packet analyzer or out of band monitoring tool. In some embodiments, the packet analyzer is a virtual entity residing completely within the virtual network environment. In other embodiments, the package analyzer may be a hardware-based packet analyzer that is configured to receive unencrypted network traffic flows from the NTM agent.


It will be appreciated that process 300 is for illustrative purposes and that different and/or additional actions may be used. It will also be appreciated that various actions described herein may occur in a different order or sequence.


It should be noted that each of the DSKA engine, the NTM agent, and/or functionality described herein may constitute a special purpose computing device. Further, the DSKA engine, the NTM agent, and/or functionality described herein can improve the technological field of monitoring encrypted network traffic flows involving monitored devices and applications by implementing a passive inspection mechanism. For example, an NTM agent may be directly provided with public and private keys associated with a particular monitored session. Notably, the NTM agent does not need to decrypt and re-encrypt network traffic communicated involving a monitored device/application. As such, the session-aware NTM agent can inspect and perform NPB functions, such as filtering, sampling, de-duplication and data masking at a much higher throughput rate than a device that implements active SSL decryption.


It will be understood that various details of the subject matter described herein may be changed without departing from the scope of the subject matter described herein. Furthermore, the foregoing description is for the purpose of illustration only, and not for the purpose of limitation, as the subject matter described herein is defined by the claims as set forth hereinafter.

Claims
  • 1. A method comprising: by a dynamic session key acquisition (DSKA) engine residing in a virtual environment: receiving session decryption information extraction instructions that configure the DSKA engine to obtain session decryption information for at least one communication session involving a virtual machine;obtaining the session decryption information from a server instance hosted by the virtual machine in accordance with the session decryption information extraction instructions, wherein the session decryption information includes cryptographic keys utilized by an application server instance in the virtual machine to establish the at least one communication session, wherein the session decryption information is obtained by the DSKA engine from communications between a monitored application server instance hosted by the virtual machine and either a secure sockets layer (SSL) enabled server instance or a transport layer security (TLS) enabled service instance hosted by the virtual machine;storing the session decryption information obtained from the virtual machine; andproviding the session decryption information to a network traffic monitoring (NTM) agent, wherein the NTM agent utilizes the session decryption information to decrypt copies of encrypted network traffic flows belonging to the at least one communication session involving the virtual machine.
  • 2. The method of claim 1 wherein the session decryption information extraction instructions are received by the DSKA engine from a virtual tap instance or the NTM agent.
  • 3. The method of claim 1 wherein obtaining the session decryption information from the virtual machine includes acquiring the session decryption information via a direct access to a key store in the server instance hosted by the virtual machine.
  • 4. The method of claim 3 wherein the DSKA engine utilizes a query function that sends a request message to the server instance requesting the session decryption information stored in the key store.
  • 5. The method of claim 1 wherein the NTM agent is a virtual instance hosted by a second virtual machine in the virtual environment.
  • 6. The method of claim 1 wherein the NTM agent is configured to use the session decryption information to decrypt copies of encrypted network traffic flow records to produce decrypted network traffic flow records.
  • 7. The method of claim 1 wherein the DSKA engine is configured to forward the session decryption information to the NTM agent via at least one virtual tap instance and a virtual network interface card.
  • 8. A system comprising: a hardware processor of a computing platform supporting a virtual environment;at least one virtual tap instance residing in the virtual environment configured to capture encrypted network traffic flows belonging to at least one communication session involving an application server instance hosted by a virtual machine, wherein the at least one virtual tap instance is a virtual instance of a software-based monitoring agent application that executed by the hardware processor of a computing platform supporting the virtual environment; anda dynamic session key acquisition (DSKA) engine residing in the virtual environment configured to receive session decryption information extraction instructions that configure the DSKA engine to obtain session decryption information for at least one communication session involving a virtual machine, to obtain the session decryption information from a server instance hosted by the virtual machine in accordance with the session decryption information extraction instructions, wherein the session decryption information includes cryptographic keys utilized by the application server instance to establish the at least one communication session, wherein the session decryption information is obtained by the DSKA engine from communications between a monitored application server instance hosted by the virtual machine and either a secure sockets layer (SSL) enabled server instance or a transport layer security (TLS) enabled service instance hosted by the virtual machine, to store the session decryption information obtained from the virtual machine, and to provide the session decryption information to a network traffic monitoring (NTM) agent, wherein the NTM agent utilizes the session decryption information to decrypt copies of encrypted network traffic flows belonging to the at least one communication session involving the virtual machine.
  • 9. The system of claim 8 wherein the session decryption information extraction instructions are received by the DSKA engine from either a virtual tap instance or the NTM agent.
  • 10. The system of claim 8 wherein the DSKA engine is configured to acquire the session decryption information via a direct access to a key store in the server instance hosted by the virtual machine.
  • 11. The system of claim 10 wherein the DSKA engine is configured to utilize a query function that sends a request message to the server instance requesting the session decryption information stored in the key store.
  • 12. The system of claim 8 wherein the NTM agent is a virtual instance hosted by a second virtual machine in the virtual environment.
  • 13. The system of claim 8 wherein the NTM agent is configured to use the session decryption information to decrypt copies of encrypted network traffic flow records to produce decrypted network traffic flow records.
  • 14. The system of claim 8 wherein the DSKA engine is configured to forward the session decryption information to the NTM agent via at least one virtual tap instance and a virtual network interface card.
  • 15. A non-transitory computer readable medium having stored thereon executable instructions embodied in the computer readable medium that when executed by at least one processor of a computer cause the computer to perform steps comprising: by a dynamic session key acquisition (DSKA) engine residing in a virtual environment: receiving session decryption information extraction instructions that configure the DSKA engine to obtain session decryption information for at least one communication session involving a virtual machine;obtaining the session decryption information from a server instance hosted by the virtual machine in accordance with the session decryption information extraction instructions, wherein the session decryption information includes cryptographic keys utilized by an application server instance in the virtual machine to establish the at least one communication session, wherein the session decryption information is obtained by the DSKA engine from communications between a monitored application server instance hosted by the virtual machine and either a secure sockets layer (SSL)-enabled server instance or a transport layer security (TLS) enabled service instance hosted by the virtual machine;storing the session decryption information obtained from the virtual machine; andproviding the session decryption information to a network traffic monitoring (NTM) agent, wherein the NTM agent utilizes the session decryption information to decrypt copies of encrypted network traffic flows belonging to the at least one communication session involving the virtual machine.
  • 16. The non-transitory computer readable medium of claim 15 wherein obtaining the session decryption information from the virtual machine includes acquiring the session decryption information via a direct access to a key store in the server instance hosted by the virtual machine.
  • 17. The non-transitory computer readable medium of claim 16 wherein the DSKA engine utilizes a query function that sends a request message to the server instance requesting the session decryption information stored in the key store.
PRIORITY CLAIM

This application is a continuation of U.S. patent application Ser. No. 16/113,360, filed Aug. 27, 2018, which claims the benefit of U.S. Provisional Patent Application No. 62/550,558, filed Aug. 25, 2017, the disclosure of which is incorporated herein by reference in its entirety.

US Referenced Citations (200)
Number Name Date Kind
5557678 Ganesan Sep 1996 A
6240416 Immon et al. May 2001 B1
6330671 Aziz Dec 2001 B1
6480488 Huang Nov 2002 B1
6684331 Srivastava Jan 2004 B1
7340744 Chandwadkar et al. Mar 2008 B2
7363353 Ganesan et al. Apr 2008 B2
7373412 Colas et al. May 2008 B2
7421506 Ni et al. Sep 2008 B2
7562213 Timms Jul 2009 B1
7634650 Shah et al. Dec 2009 B1
7684414 Durst Mar 2010 B2
7701853 Malhotra et al. Apr 2010 B2
7778194 Yung Aug 2010 B1
7971240 Guo et al. Jun 2011 B2
8270942 Zabawskyj et al. Sep 2012 B2
8457126 Breslin et al. Jun 2013 B2
8514756 Ramachandra et al. Aug 2013 B1
8566247 Nagel et al. Oct 2013 B1
8595835 Kolton et al. Nov 2013 B2
8601152 Chou Dec 2013 B1
8654974 Anderson et al. Feb 2014 B2
8788805 Herne et al. Jul 2014 B2
8881282 Aziz et al. Nov 2014 B1
8929356 Pandey et al. Jan 2015 B2
8938611 Zhu et al. Jan 2015 B1
8953439 Lin et al. Feb 2015 B1
8964537 Brolin Feb 2015 B2
9065642 Zaverucha et al. Jun 2015 B2
9298560 Janakiraman et al. Mar 2016 B2
9380002 Johansson et al. Jun 2016 B2
9392010 Friedman et al. Jul 2016 B2
9407643 Bavington Aug 2016 B1
9565202 Kindlund et al. Feb 2017 B1
9660913 Newton May 2017 B2
9673984 Jiang et al. Jun 2017 B2
9680869 Buruganahalli et al. Jun 2017 B2
9800560 Guo et al. Oct 2017 B1
9807121 Levy et al. Oct 2017 B1
9860154 Balabine et al. Jan 2018 B2
9882929 Ettema et al. Jan 2018 B1
9893883 Chaubey et al. Feb 2018 B1
9906401 Rao Feb 2018 B1
9998955 MacCarthaigh Jun 2018 B1
10063591 Jiang et al. Aug 2018 B1
10079810 Moore et al. Sep 2018 B1
10079843 Friedman et al. Sep 2018 B2
10116553 Penno et al. Oct 2018 B1
10291651 Chaubey May 2019 B1
10326741 Rothstein et al. Jun 2019 B2
10404597 Bakshi Sep 2019 B2
10419965 Kadosh et al. Sep 2019 B1
10423774 Zelenov Sep 2019 B1
10482239 Liu et al. Nov 2019 B1
10516532 Taub et al. Dec 2019 B2
10749808 MacCarthaigh Aug 2020 B1
10855694 Majumder et al. Dec 2020 B2
10893030 Oprisan et al. Jan 2021 B2
10903985 Bergeron Jan 2021 B2
10931797 Ahn et al. Feb 2021 B2
10951660 Rogers et al. Mar 2021 B2
10992652 Patatunda et al. Apr 2021 B2
11075886 Paul et al. Jul 2021 B2
11165831 Higgins Nov 2021 B2
20010028631 Iwamura et al. Oct 2001 A1
20020116485 Black et al. Aug 2002 A1
20030004688 Gupta et al. Jan 2003 A1
20030161335 Fransdonk Aug 2003 A1
20030163684 Fransdonk Aug 2003 A1
20030165241 Fransdonk Sep 2003 A1
20040083362 Park et al. Apr 2004 A1
20040168050 Desrochers et al. Aug 2004 A1
20040268148 Karjala et al. Dec 2004 A1
20050050362 Peles Mar 2005 A1
20050111437 Maturi May 2005 A1
20050160269 Akimoto Jul 2005 A1
20060085862 Witt et al. Apr 2006 A1
20060259579 Beverly Nov 2006 A1
20070022284 Vishwanathan Jan 2007 A1
20070033408 Morten Feb 2007 A1
20070043940 Gustave et al. Feb 2007 A1
20070078929 Beverly Apr 2007 A1
20070156726 Levy Jul 2007 A1
20070169190 Kolton et al. Jul 2007 A1
20070179995 Prahlad et al. Aug 2007 A1
20080005782 Aziz Jan 2008 A1
20080031141 Lean et al. Feb 2008 A1
20080320297 Sabo et al. Dec 2008 A1
20090150521 Tripathi Jun 2009 A1
20090150527 Tripathi et al. Jun 2009 A1
20090150883 Tripathi et al. Jun 2009 A1
20090220080 Herne et al. Sep 2009 A1
20090222567 Tripathi et al. Sep 2009 A1
20090254990 McGee Oct 2009 A1
20100250769 Barreto et al. Sep 2010 A1
20110231659 Sinha Sep 2011 A1
20110286461 Ichino et al. Nov 2011 A1
20110289311 Roy-Chowdhury et al. Nov 2011 A1
20120082073 Andreasen et al. Apr 2012 A1
20120137289 Nolterieke et al. May 2012 A1
20120210318 Sanghvi Aug 2012 A1
20120236823 Kompella et al. Sep 2012 A1
20120304244 Xie et al. Nov 2012 A1
20130054761 Kempf et al. Feb 2013 A1
20130070777 Hutchison et al. Mar 2013 A1
20130117847 Friedman et al. May 2013 A1
20130204849 Chacko Aug 2013 A1
20130239119 Garg et al. Sep 2013 A1
20130265883 Henry et al. Oct 2013 A1
20130272136 Ali et al. Oct 2013 A1
20130301830 Bar-El et al. Nov 2013 A1
20130343191 Kim et al. Dec 2013 A1
20140010083 Hamdi et al. Jan 2014 A1
20140059200 Nguyen et al. Feb 2014 A1
20140082348 Chandrasekaran et al. Mar 2014 A1
20140115702 Li et al. Apr 2014 A1
20140189093 Du Toit et al. Jul 2014 A1
20140189861 Gupta et al. Jul 2014 A1
20140189961 He et al. Jul 2014 A1
20140226820 Chopra et al. Aug 2014 A1
20140351573 Martini Nov 2014 A1
20150026313 Chawla et al. Jan 2015 A1
20150039889 Andoni Feb 2015 A1
20150052345 Martini Feb 2015 A1
20150113132 Srinivas et al. Apr 2015 A1
20150113264 Wang et al. Apr 2015 A1
20150124622 Kovvali et al. May 2015 A1
20150172219 Johansson et al. Jun 2015 A1
20150264083 Prenger et al. Sep 2015 A1
20150281954 Warren Oct 2015 A1
20150288679 Ben-Nun et al. Oct 2015 A1
20150295780 Hsiao et al. Oct 2015 A1
20150319030 Nachum Nov 2015 A1
20150341212 Hsiao et al. Nov 2015 A1
20150379278 Thota et al. Dec 2015 A1
20160014016 Guichard et al. Jan 2016 A1
20160019232 Lambright Jan 2016 A1
20160080502 Yadav et al. Mar 2016 A1
20160105469 Galloway et al. Apr 2016 A1
20160105814 Hurst et al. Apr 2016 A1
20160119374 Williams et al. Apr 2016 A1
20160127517 Shcherbakov et al. May 2016 A1
20160142440 Qian et al. May 2016 A1
20160248685 Pignataro et al. Aug 2016 A1
20160277321 Johansson et al. Sep 2016 A1
20160277971 Hamdi et al. Sep 2016 A1
20160294784 Hopkins et al. Oct 2016 A1
20160344754 Rayapeta et al. Nov 2016 A1
20160373185 Wentzloff et al. Dec 2016 A1
20170048328 Korotaev et al. Feb 2017 A1
20170070531 Huston, III et al. Mar 2017 A1
20170237640 Stocker Aug 2017 A1
20170237719 Schwartz et al. Aug 2017 A1
20170289104 Shankar Oct 2017 A1
20170302554 Chandrasekaran et al. Oct 2017 A1
20170339022 Hegde et al. Nov 2017 A1
20170364794 Mahkonen et al. Dec 2017 A1
20180006923 Gao et al. Jan 2018 A1
20180091421 Ma et al. Mar 2018 A1
20180091427 Kumar et al. Mar 2018 A1
20180097787 Murthy et al. Apr 2018 A1
20180097788 Murthy Apr 2018 A1
20180097840 Murthy Apr 2018 A1
20180124025 Lam et al. May 2018 A1
20180176036 Butcher et al. Jun 2018 A1
20180176192 Davis et al. Jun 2018 A1
20180198838 Murgia et al. Jul 2018 A1
20180234322 Cohn et al. Aug 2018 A1
20180241699 Raney Aug 2018 A1
20180254990 Ramaiah et al. Sep 2018 A1
20180278419 Higgins et al. Sep 2018 A1
20180331912 Edmison et al. Nov 2018 A1
20180332078 Kumar et al. Nov 2018 A1
20180351970 Majumder et al. Dec 2018 A1
20180367422 Raney et al. Dec 2018 A1
20180375644 Karagiannis et al. Dec 2018 A1
20190028376 Ganapathy et al. Jan 2019 A1
20190058714 Joshi et al. Feb 2019 A1
20190068561 Caragea Feb 2019 A1
20190068564 Putatunda et al. Feb 2019 A1
20190104437 Bartfai-Walcott et al. Apr 2019 A1
20190116111 Izard et al. Apr 2019 A1
20190166049 Bakshi May 2019 A1
20190205151 Suzuki Jul 2019 A1
20190205244 Smith Jul 2019 A1
20190260794 Woodford et al. Aug 2019 A1
20190303385 Ching et al. Oct 2019 A1
20190349403 Anderson et al. Nov 2019 A1
20190373052 Pollitt et al. Dec 2019 A1
20200036610 Indiresan et al. Jan 2020 A1
20200053064 Oprisan et al. Feb 2020 A1
20200067700 Bergeron Feb 2020 A1
20200076773 Monat et al. Mar 2020 A1
20200104052 Vijayan et al. Apr 2020 A1
20200137021 Janakiraman Apr 2020 A1
20200137115 Janakiraman et al. Apr 2020 A1
20210111975 Raney Apr 2021 A1
20210119982 Oprisan et al. Apr 2021 A1
20210160275 Anderson et al. May 2021 A1
20210194779 Punj et al. Jun 2021 A1
Foreign Referenced Citations (3)
Number Date Country
2777226 Aug 2019 EP
3528430 Aug 2019 EP
2016176070 Nov 2016 WO
Non-Patent Literature Citations (65)
Entry
Non-Final Office Action for U.S. Appl. No. 16/781,542 (dated Feb. 24, 2021).
Hardegen et al., “Flow-based Throughput Prediction using Deep Learning and Real-World Network Traffic,” 15th International Conference on Network and Service Management (CNSM), pp. 1-9 (2019).
“The ABCs of Network Visibility,” Ixia, pp. 1-57 (2017).
Eisen et al., “goProbe: A Scalable Distributed Network Monitoring Solution,” IEEE Xplore, pp. 1-10 (2015).
Lee et al., “Public Review for Towards Scalable Internet Traffic Measurement and Analysis with Hadoop,” ACM SIGCOMM Computer Communication Review, vol. 43, No. 1, pp. 1-9 (Jan. 2013).
Zou et al., “An Enhanced Netflow Data Collection System,” 2012 Second International Conference on Instrumentation & Measurement, Computer, Communication and Control, pp. 508-511 (2012).
Applicant-Initiated Interview Summary for U.S. Appl. No. 16/103,598 (dated Oct. 22, 2020).
Notice of Allowance and Fee(s) Due for U.S. Appl. No. 16/103,598 (dated Oct. 16, 2020).
Notice of Allowance and Fee(s) Due and Examiner-Initiated Interview Summary for U.S. Appl. No. 16/113,360 (dated Oct. 15, 2020).
Non-Final Office Action for U.S. Appl. No. 16/781,542 (dated Sep. 25, 2020).
Non-Final Office Action for U.S. Appl. No. 15/980,699 (dated Sep. 22, 2020).
Notice of Allowance and Fee(s) Due for U.S. Appl. No. 15/608,369 (dated Aug. 19, 2020).
Advisory Action and AFCP 2.0 Decision for U.S. Appl. No. 15/608,369 (dated Jul. 1, 2020).
Advisory Action and AFCP 2.0 Decision for U.S. Appl. No. 15/980,699 (dated Jun. 30, 2020).
Non-Final Office Action for U.S. Appl. No. 16/113,360 (dated May 19, 2020).
Non-Final Office Action for U.S. Appl. No. 16/103,598 (dated May 11, 2020).
Final Office Action for U.S. Appl. No. 15/608,369 (dated Apr. 22, 2020).
Final Office Action for U.S. Appl. No. 15/980,699 (dated Apr. 20, 2020).
Commonly-Assigned, co-pending U.S. Appl. No. 16/781,542 for “Methods, Systems, and Computer Readable Media for Processing Network Flow Metadata at a Network Packet Broker,” (Unpublished, filed Feb. 4, 2020).
Stankovic, “How to solve duplicated NetFlow caused by multiple exporters,” https://www.netvizura.com/blog/how-to-solve-duplicated-netflow-caused-by-multiple-exporters, pp. 1-4 (Accessed Jan. 15, 2020).
“Jumbo Frame,” Wikipedia, https://en.wikipedia.org/wiki/Jumbo_frame, pp. 1-4 (Jan. 15, 2020).
“How is the MTU is 65535 in UDP but ethernet does not allow frame size more that 1500 bytes,” ServerFault, TCPIP, pp. 1-9 (Accessed Jan. 15, 2020).
“Network Monitoring Step 2: The Next-Generation of Packet Brokers,” MantisNet, pp. 1-6 (2020).
“CPacket cVu 2440NG/3240NG,” https://www.cpacket.com/resources/cvu-3240-2440-datasheet/, pp. 1-4 (Accessed Jan. 15, 2020).
“What are Microservices,” An Introduction to Microservices, https://opensource.com/resources/what-are-microservices, pp. 1-8 (Accessed Jan. 15, 2020).
“IPv6,” Wikipedia, https://en.wikipedia.org/wiki/IPv6, pp. 1-15 (Jan. 8, 2020).
Paul, Santanu, “Network Visibility Component with Netflow Jumbo Frame Support,” The IP.com Journal, pp. 1-8 (Aug. 2019).
Paul, Santanu, “Methods and Systems for Session-Aware Collection of Netflow Statistics,” The IP.com Journal, pp. 1-5 (Jul. 2019).
Pandey, Shardendu; Johansson, Stefan Jan, “Network Packet Broker with Flow Segmentation Capability,” The IP.com Journal, pp. 1-6 (Jul. 2019).
Paul, Santanu,“Network Packet Broker with Flow Segmentation Capability,” The IP.com Journal, pp. 1-6 (Aug. 2019).
Paul, Santanu, “Custom Key Performance Indicator (KPI) Network Visibility System,” The IP.com Journal, pp. 1-4 (Jul. 2019).
Paul, Santanu, “Self-Healing Network Visibility System,” The IP.com Journal, pp. 1-5 (Jun. 2019).
“About NetFlow,” Watchguard Technologies, Inc., pp. 1-3 (2019).
Non-Final Office Action for U.S. Appl. No. 15/980,699 (dated Dec. 9, 2019).
“Multiprotocol Label Switching,” Wikipedia, https://en.wikipedia.org/wiki/multiprotocol_label_switching, pp. 1-7 (Dec. 6, 2019).
“Netflow,” Wikipedia, https://en.wikipedia.org/wiki/NetFlow, pp. 1-9 (Dec. 3, 2019).
Non-Final Office Action for U.S. Appl. No. 15/608,369 (dated Oct. 31, 2019).
“NetFlow Collector,” Kentipedia, Kentik, pp. 1-4 (Sep. 17, 2019).
Advisory Action for U.S. Appl. No. 15/608,369 (dated Sep. 13, 2019).
Nubeva, “Nubeva TLS Decrypt Out-of-Band Decrypted Visibility for the Cloud,” www.nubeva.com/decryption, pp. 1-8 (Sep. 2019).
Nubeva, “What is Symmetric Key Intercep Architecture?” https://www.nubeva.com/blog/what-is-symmetric-key-intercept-architecture, pp. 1-4 (Aug. 8, 2019).
Final Office Action for U.S. Appl. No. 15/608,369 (dated Jun. 27, 2019).
Notice of Allowance and Fee(s) Due for U.S. Appl. No. 15/826,787 (dated Apr. 25, 2019).
Petryschuk, “NetFlow Basics: An Introduction to Monitoring Network Traffic,” Auvik, https://www.auvik.com/, pp. 1-8 (Mar. 19, 2019).
Non-Final Office Action for U.S. Appl. No. 15/608,369 (dated Mar. 7, 2019).
“Automatic versus Manual NetFlow Deduplication,” Noction, https://www.noction.com/blog/automatic-manual-netflow-deduplication, pp. 1-7 (Feb. 1, 2019).
Paul, Santanu, “Network Visibility System with Integrated Netflow Over Syslog Reporting Capability” The IP.com Journal, pp. 1-7 (Jan. 28, 2019).
Non-Final Office Action for U.S. Appl. No. 15/826,787 (dated Jan. 3, 2019).
Leskiw, “Understanding Syslog: Servers, Messages & Security,” https://www.networkmanagementsoftware.com/what-s-syslog/, pp. 1-7 (Oct. 2018).
Commonly-Assigned, co-pending U.S. Appl. No. 16/113,360 for “Monitoring Encrypted Network Traffic Flows in a Virtual Environment Using Dynamic Session Key Acquisition Techniques,” (Unpublished, filed Aug. 27, 2018).
McGillicuddy, “Next-Generation Network Packet Brokers: Defining the Future of Network Visibility Fabrics,” Enterprise Management Associates (EMA) Research, Niagara Networks, pp. 1-27 (Aug. 2018).
Commonly-Assigned, co-pending U.S. Appl. No. 16/103,598 for “Methods, Systems, And Computer Readable Media For Implementing Bandwidth Limitations On Specific Application Traffic At A Proxy Element,” (Unpublished, filed Aug. 14, 2018).
Evans, David, “Network Packet Broker with Dynamic Filter Rules,” The IP.com Journal, pp. 1-8 (Jun. 2018).
Schulist et al., “Linux Socket Filtering aka Berkeley Packet Filter (BPF),” Wayback Machine, https://www.kernel.org/doc/Documentation/networking/filter.txt, pp. 1-25 (Jun. 8, 2018).
Commonly-Assigned, co-pending U.S. Appl. No. 15/980,699 for “Methods, Systems, and Computer Readable Media for Monitoring Encrypted Network Traffic Flows,” (Unpublished, filed May 15, 2018).
“Principles of Chaos Engineering,” https://principlesofchaos.org/?lang=ENcontent, pp. 1-3 (May 2018).
Notice of Allowance and Fee(s) Due for U.S. Appl. No. 15/980,699 (dated Feb. 8, 2021).
Commonly-Assigned, co-pending U.S. Appl. No. 17/111,445 for “Methods, Systems, and Computer Readable Media for Implementing Bandwidth Limitations on Specific Application Traffic at a Proxy Element,” (Unpublished, filed Dec. 3, 2020).
Non-Final Office Action for U.S. Appl. No. 17/111,445 (dated Jul. 14, 2022).
“Network Monitoring Step 2: The Next-Generation of Packet Brokers,” Mantisnet, pp. 1-5 (2021).
Notice of Allowance and Examiner Initiated Interview Summary for U.S. Appl. No. 16/781,542 (dated Aug. 2, 2021).
Petryschuk, “NetFlow Basics: An Introduction to Monitoring Network Traffic,” Auvik, pp. 1-14 (Mar. 19, 2019).
McGillicuddy, “Next-Generation Network Packet Brokers: Defining the Future of Network Visibility Fabrics,” Niagara Networks, pp. 1-27 (Aug. 2018).
Flanders, “Sending NetFlow Over Syslog,” https://sflanders.net/2013/11/04/sending-netflow-syslog/, pp. 1-4 (Nov. 4, 2013).
He et al., “Data Deduplication Techniques,” 2010 International Conference on Future Information Technology and Management Engineering, pp. 1-4 (2010).
Related Publications (1)
Number Date Country
20210083857 A1 Mar 2021 US
Provisional Applications (1)
Number Date Country
62550558 Aug 2017 US
Continuations (1)
Number Date Country
Parent 16113360 Aug 2018 US
Child 17105411 US