The present disclosure relates generally to logic locking, and more specifically, to exemplary embodiments of an exemplary system, method and computer-accessible medium for stripped-functionality logic locking.
The increasing cost of integrated circuit (“IC”) manufacturing has forced many companies to go fabless over the years. With the outsourcing of IC fabrication in a globalized/distributed design flow including multiple (e.g., potentially untrusted) entities, the semiconductor industry is facing a number of challenging security threats. This fragility in the face of poor state-of-the-art intellectual property (“IP”) protection has resulted in hardware security vulnerabilities such as IP piracy, overbuilding, reverse engineering, and hardware Trojans. (See, e.g., References 9, 13, 19, 20, 37, 39, 45 and 47-49).
To address these issues most effectively at the hardware level (see, e.g., Reference 32), a number of hardware design-for-trust (“DfTr”) procedures such as IC metering (see, e.g., References 1, 22 and 23), watermarking (see, e.g., References 17, 18, 21 and 31), IC camouflaging (see, e.g., References 3, 4, 27, 28, 35, 46, 51, 56 and 62), split manufacturing (see, e.g., References 14 and 16), and logic locking (see, e.g., References 34, 36, 38, 40, 41, 52, 53, 55, 61 and 63) have been proposed. Logic locking, in particular, has received significant interest from the research community, as it can protect against a potential attacker located anywhere in the IC supply chain, whereas other DfTr procedures, such as camouflaging or split manufacturing, can protect only against a limited set of malicious entities as shown in Table 1 below. Mentor Graphics, a major CAD tool provider, has announced the launch of TrustChain, a framework to support logic locking and camouflaging. (See, e.g., References 26 and 42).
Logic locking inserts additional logic into a circuit, locking the original design with a secret key. For example, as shown in the diagram of
Traditional logic locking procedures choose key gate locations based on various gate selection procedures, such as random logic locking (“RLL”) (see, e.g., Reference 38), fault analysis-based logic locking (“FLL”) (see, e.g., References 5 and 36), and strong interference-based logic locking (“SLL”). (See, e.g., References 34 and 59). Over the years, many key-recovery attacks have been mounted that exploit the vulnerabilities of logic locking procedures. (See, e.g., References 33, 34, 44, 54 and 60). A summary of these attacks is presented in Table 2 below.
A powerful attack that broke many previous logic locking procedures is a Boolean satisfiability (“SAT”)-based key-pruning attack, referred to as SAT attack. The attack is based on the notion of incorrect key elimination using distinguishing input patterns (“DIPs”). (See, e.g., Reference 44). DIPs are computed using a miter circuit constructed using two copies of the locked netlist; the two circuits share the primary inputs but have different key inputs. A DIP is found when the two copies of the locked netlist differ in their outputs. A functional IC with the secret key loaded in its memory is used as an oracle to identify the incorrect keys in an iterative fashion. The computational complexity of the attack is expressed in terms of the number of DIPs generated by the SAT attack. (See, e.g., Reference 44). The latest research on logic locking has focused on defending against the SAT attack. (See, e.g., References 52, 55 and 57).
Two SAT attack resilient logic locking procedures are SARLock (see, e.g., schematic diagram shown in
SARLock can be intertwined with one of the gate selection-based logic locking procedures, such as RLL, FLL, or SLL, providing multiple layers of defense. (See, e.g., Reference 55). A variant of the SAT attack, referred to as AppSAT (see, e.g., Reference 40), was recently provided to show that a multi-layered defense comprising a point function and a SAT attack vulnerable logic locking procedure can be reduced to a single-layer defense comprising the point function alone (e.g., from SARLock+FLL to SARLock). The Double-DIP attack achieves the same objective using more powerful 2-DIPs, for example, DIPs that can eliminate at least two incorrect keys in a single iteration. (See, e.g., Reference 41).
Despite their SAT attack resilience, both SARLock (see, e.g., Reference 55) and Anti-SAT (see, e.g., Reference 52) exhibit security vulnerabilities, as they leave the original circuit implementation (e.g., the IP-to-be protected), as is. SARLock is also vulnerable to removal attack. Given a protected/locked netlist, an attacker can identify the comparator/mask blocks and the flip signal that directly feeds the output by tracing the transitive-fanout of key-inputs, and remove these blocks, retrieving the original circuit (e.g., the proprietary IP). Anti-SAT can also be vulnerable to signal probability skew (“SPS”) attack. (See, e.g., Reference 57). Given a protected netlist, an attacker can identify the flip signal since it is at the output of the gate whose inputs exhibit the maximum bias towards opposite values. The attacker can then retrieve the original design by re-synthesizing the locked netlist with a constraint value 0 (1) on the flip signal. Even upon additional obfuscation using additional XOR/XNOR and multiplexer key gates (see, e.g., Reference 52), the Anti-SAT block can be isolated using the AppSAT guided removal (“AGR”) attack. (See, e.g., Reference 58). In addition, both SARLock and Anti-SAT are also vulnerable to the Bypass attack. (See, e.g., Reference 53). The Bypass attack generally finds a DIP that causes an incorrect output for a wrong key and bypass circuitry is added around the Anti-SAT/SARLock block to fix the output for this DIP. This fix recovers the original design for both SARLock and Anti-SAT since the incorrect key-driven design fails for only one input pattern.
SARLock can be re-architected into TTLock (see, e.g., Reference 61) to gain resilience against removal attacks. TTLock makes changes to the original design to corrupt the output in the absence of the secret key. As SARLock is based on a one-point function, its re-architected version TTLock ends up protecting one input pattern. Thus, the modified netlist and the original netlist differ in their outputs for one input pattern only. Previous work has described this SAT and removal attack resilient architecture but provides neither a CAD framework to effect the design changes, nor a formal analysis proving resilience against various attacks. (See, e.g., Reference 61). Furthermore, protection of a single input pattern can lead to a rigid scheme where the designer lacks the control to hide an arbitrary amount of IP-critical logic in arbitrary parts of his/her design. Protection of a single input pattern, and thus low and uncontrollable corruptibility, can also lead to the recovery of an approximate netlist through attacks, such as AppSAT (see, e.g., Reference 40) and Double-DIP (see, e.g., Reference 41), which SARLock is vulnerable to as well.
Thus, it may be beneficial to provide an exemplary system, method, and computer-accessible medium for stripped-functionality logic locking which can overcome at least some of the deficiencies described herein above.
An exemplary system, method and computer-accessible medium for modifying a design of an integrated circuit(s) (ICs), can include, for example, modifying a logic gate(s) in the design for a protected input pattern(s), where the protected input pattern(s) is an input pattern for which the modified design produces a different output than an original design, and providing a restoration unit(s) into the design, where the restoration unit(s) can be configured to (i) produce an error-free output(s) when a correct secret key can be applied to the restoration unit(s), and (ii) produce an erroneous output(s) when an incorrect key can be applied to the restoration unit(s). A behavior of the design(s) can deviate from the original design for only a pre-determined constant number of incorrect keys based on an input pattern(s). A determination can be made as to whether the design and the restoration unit produce an erroneous output(s) with respect an original design for only a pre-determined constant number of incorrect keys based on an input pattern(s).
In some exemplary embodiments of the present disclosure, the restoration unit(s) can include a Hamming Distance checker(s) configured to check a Hamming Distance between the protected input pattern(s) and a key(s). The Hamming Distance checker(s) can be used to protect input patterns that can be of a pre-determined Hamming Distance away from a correct key(s). The correct key(s) can be stored in a tamper-proof memory.
In certain exemplary embodiments of the present disclosure, the restoration unit(s) can include a tamper-proof content-addressable look-up table. The tamper-proof content-addressable look-up table(s) can be used to protect input patterns that can be included in a plurality of input cubes stored in the tamper-proof content-addressable look-up table. The input cubes can be determined based on set of protected inputs patterns using of (i) a cube compression procedure, or (ii) a cube bit selection procedure. Each of the input cubes can have a specified number of bits. Each of the input cubes can be or include a secret key loaded on to the integrated circuit(s). The input cubes can be associated with a flip vector(s). The flip vector(s) can include information regarding which outputs of the integrated circuit(s) can be flipped based on each of the input cubes.
In some exemplary embodiments of the present disclosure, The flip vector(s) can be stored in the tamper-proof content-addressable look-up table. The input cubes can be compressed prior to being stored in the tamper-proof content-addressable look-up table. The input cubes can be compressed, for example, by merging compatible input cubes. The at least one restoration unit(s) can include a plurality of XOR gates and an adder(s). The logic gate(s) can be modified based on a security-aware synthesis procedure which can be configured to reduce a design metric(s) while ensuring that k−log2c is greater than a target security level, and where k is a key size and c is a number of cubes. The design metric(s) can include (i) a power, (ii) an area, or (iii) a delay.
These and other objects, features and advantages of the exemplary embodiments of the present disclosure will become apparent upon reading the following detailed description of the exemplary embodiments of the present disclosure, when taken in conjunction with the appended claims.
Further objects, features and advantages of the present disclosure will become apparent from the following detailed description taken in conjunction with the accompanying Figures showing illustrative embodiments of the present disclosure, in which:
Throughout the drawings, the same reference numerals and characters, unless otherwise stated, are used to denote like features, elements, components, or portions of the illustrated embodiments. Moreover, while the present disclosure will now be described in detail with reference to the figures, it is done so in connection with the illustrative embodiments and is not limited by the particular embodiments illustrated in the figures and the appended claims.
While hiding any part of the design IP from its hardware implementation can be sufficient to render general applications resilient to reverse engineers (e.g., removal attacks), there can be applications where a designer can want to specify the specific parts of the IP to hide.
Examples include processors with to-be-protected address spaces, for which access can be granted only to restricted entities (see, e.g., Reference 8); network-on-chip (“NoC”) routers, where certain IP address ranges can carry particular semantics (see, e.g., Reference 12); intrusion detection systems that rely on pattern matching (see, e.g., Reference 24); and digital signal processing applications, such as comb filters (see, e.g., Reference 10), which accentuate/attenuate frequencies at regular intervals.
Building on previous architecture (see, e.g., Reference 61), the exemplary procedure can strip at least part of the design functionality from its hardware implementation. The exemplary design implemented in hardware can therefore no longer be the same as the original design, as the former can be missing the stripped functionality. An exemplary procedure can be used that can arbitrarily specify this stripped functionality as Stripped-Functionality Logic Locking (“SFLL”). The hardware implementation can have an intentionally controllable built-in error. This error can be canceled by a restore unit only upon the application of the secret key of the logic locking.
The stripped functionality can be captured efficiently in terms of input cubes for which the hardware-implemented design and the original one can produce different outputs. These inputs cubes can be referred to as protected cubes. They can be stored in bits rather than hardcoded in logic gates. SARLock (see, e.g., Reference 55) and Anti-SAT (see, e.g., Reference 52) protect zero cubes, as they implement the design IP as is in hardware. Protected cubes can also be conceived as conditions to manifest the built-in error; a reverse-engineer applying the removal attack can obtain a netlist with this error with respect to the original design.
For exemplary applications that utilize hiding any part of the functionality, it can be sufficient to protect an arbitrary set of cubes. For applications that can be specific about the part of the functionality to hide, the exemplary SFLL framework can facilitate the designer to strip functionality based on IP-critical cubes that he/she can specify and provide as input to the framework.
A set can be defined as S, and its elements can be denoted as s∈S. sS can be written to denote that s has been sampled uniformly randomly from the set S. cktlock, cktactv, and cktrec can be used to denote a logic-locked, an activated, and a reconstructed circuit, respectively. For a circuit ckt, the set of all possible inputs and outputs can be denoted as I and O respectively. can be used to denote a probabilistic polynomial time (“PPT”) adversary following an attack strategy .
A combinational circuit ckt can be a netlist that can implement a Boolean function F:I→O, where I={0,1}n and O={0,1}m with n inputs and in outputs. A logic locking procedure can be viewed as a triplet of procedures, (Gen, Lock, Activate), where:
For example, the attacker has access to an oracle, denoted, ckt(⋅), which can be a copy of a working chip with the secret key loaded onto its memory. The attacker can query the oracle with a set of input patterns and observe the corresponding outputs. Apart from this, the attacker can also have the reverse-engineered netlist cktlock, which can be locked using a logic locking procedure . It can be assumed that the attacker also knows the corresponding elements between the original and the locked netlist; in other words, he can identify the location of the protection unit. The attack success for an adversary can imply recovering a circuit such that:
∀i∈I, cktrec(i)=F(i),:cktlock→cktrec (1)
SAT attack, a representative and effective oracle-guided attack that iteratively prunes the key space, can query the oracle cktlock(⋅) with an input pattern d, called a distinguishing input pattern, to eliminate a set of incorrect keys in each iteration. The attack can terminate after querying the oracle with a set of DIPs, and outputting a single key z′. The attacker can reconstruct a circuit cktrec where cktrec←Activatez′(cktlock) such that Eq. (1) can be satisfied.
A logic locking procedure can be called λ-secure against a PPT adversary , making a polynomial number of queries q(λ) to the oracle, if he/she cannot reconstruct cktrec with probability greater than
A logic locking procedure resilient to the SAT attack can also be expected to thwart other variant key-space pruning attacks.
Sensitization attack, which can be another oracle-guided attack, can determine individual key bits by generating and applying patterns that sensitize them to the outputs. Two key bits can be considered pairwise-secure if the sensitization of one key bit cannot be done without controlling the other key bit and vice versa. (See, e.g., Reference 34). SLL can maximize key bits that can all be pairwise-secure. For example, key bits converging at a dominating gate can all be pairwise-secure if there can be no input assignment to block any one of them before they reach the dominating gate. A logic locking procedure can be λ-secure against a sensitization attack if λ key bits can all be pairwise secure.
A removal attack can operate on a locked netlist and can attempt to isolate and remove the protection logic. The attack can be a transformation T: cktlock→cktrec|∀i∈I, cktrec=F(i), irrespective of the key value. Note that for a removal attack cktrec(p)≠F(p), ∀p∈P, where P can denote the set of protected patterns. A logic locking procedure can be λ-resilient against a removal attack, where λ can denote the cardinality of the set of protected input patterns P.
SFLL-HDh can be used for general applications that can benefit from stripping an arbitrary part of the design functionality. It can also be shown that SFLL-HDh can be a logic locking platform that can provide controllable resilience against all known attacks. In SFLL-HDh, all the protected input cubes can be of the same Hamming Distance h from the secret key; though the set of protected cubes can be restricted, a large number of cubes can be protected through a simple, scalable, and cost-effective hardware.
SFLL-HDh can be used for the special case of h=0; there may only be one protected input cube, and it can be the same as the secret key. Thus, SFLL-HD0 can be functionally the same as TTLock. (See, e.g., Reference 61). SFLL-HD0 can modify a design to invert its output for one selected (e.g., protected) input pattern; this inversion can be the manifestation of the built-in error. The functionality stripping can be effected via logic gate insertions/replacements; the security-aware synthesis module in SFLL-flex can also be used to strip functionality based on a set of protected input cubes. SFLL-HD0 can invert the erroneous output only upon the application of the correct key to the restore unit, thereby, cancelling out the built-in error and recovering the correct output. Moreover, SFLL-HD0 can introduce one additional error into the design along with the inverted output for each incorrect key. Here, the secret key can include the protected input cube selected by the designer.
SFLL-HD0 can have the following exemplary properties:
As shown in the schematic diagram of
Various exemplary circuits can be used to illustrate the architecture of SFLL-HD0 as shown in the schematic diagram of
n inputs and k key bits can be assumed, where k≤n. SFLL-HD0 can deliver the same security properties as TTLock. (See, e.g., Reference 61). To establish the security properties of SFLL-SFLL-HD0, an exemplary procedure was developed. SFLL-HD0 resilience against SAT attack can be achieved by ensuring that the attack encounters its worst-case scenario. In each iteration, a DIP can eliminate exactly one incorrect key, necessitating a number of iterations that can be exponential in the key-size. In the example shown in the schematic diagram of
First, the input cubes can be classified into two sets, the set of protected cubes P and set of unprotected cubes {circumflex over (P)}. Now, as SFLL-HD0 only contains one protected input cube, P can be a singleton set. Thus, |P|=1 and |{circumflex over (P)}|=2k−1. For example, an attacker can recover the secret key and the original functionality of the design if she can find a protected input cube in P. However, for a PPT attacker making only a polynomial number of queries q (k) to the oracle, the probability of finding this cube can be, for example:
Note, without loss of generality, the sampling can be considered as without replacement as the SAT attack does not repeat any DIP. Thus, SFLL-HD0 can be k-secure against SAT attack.
SFLL-HD0 is k-Secure Against a Sensitization Attack.
In SFLL-SFLL-HD0, all the k bits of the key can converge within the comparator inside the restore unit to produce the restore signal. Therefore, sensitizing any key bit through the restore signal to the output can utilize controlling all the other key bits. All k bits can therefore be pairwise-secure. SFLL-HD0 can be k-secure against sensitization attack.
Since the restore signal can be highly skewed towards zero, it can be easily identified by a signal probability skew (“SPS”) attack. However, any removal attack would recover only the FSC, without leaking any information about the original design. As the FSC produces an erroneous response for the protected input cube, the design can be resilient against removal attack.
SFLL-HD0 is 2n-k-Resilient Against Removal Attack.
Suppose the attacker recovers a circuit cktrec by identifying and removing the restoration logic. Now, cktrec can produce an incorrect output for the set of protected input cubes, denoted as P. However, it is known that each cube can contain 2n-k input patterns. Thus, if Γ can denote the set of all input patterns contained in P, then, for example:
Thus, SFLL-HD0 can be 2n-k-resilient against a removal attack.
SFLL-HDh can be generalized for arbitrary values of h, and can protect all input cubes that can be of Hamming distance of h from the secret key. The number of protected input cubes can be
Exemplary Construction of SFLL-HDh.
With a HD of h, an input-size of n, and key-size of k, SFLL-HDh can invert the FSC output Yfs for
input cubes, which can contain 2n-k
patterns. The restore unit, which can include k XOR gates and an adder to compute the Hamming distance, can rectify all these errors for the correct key, while it can introduce a different but possibly overlapping, set of errors for any incorrect key.
Exemplary Security analysis of SFLL-HDh.
n inputs and k key hits, k≤n can be assumed. Thus, for example, the following can be assumed.
As shown above, h can be adjusted to trade resilience to one attack for resilience to another. Values of h closer to either 0 or k can deliver higher resilience to SAT and other key-pruning attacks, whereas resilience to the removal attack can be maximized by setting h=k/2.
In contrast to SFLL-HDh, SFLL-flexc×k can facilitate the user to specify, and thus protect the IP-critical input patterns; the restore unit can store the protected input patterns in a compact form, for example, in the form of c input cubes, each with k specified bits. In this context, the input cubes can be conceived as the secret keys to be loaded onto the chip for the restore unit to recover the stripped functionality. Thus, terms “protected input cubes” and “secret keys” can be used interchangeably for SFLL-flexc×k. The SFLL-flexc×k framework is shown in the flow diagram shown in
For example, as illustrated in the flow diagram of
In a design with multiple outputs, not every output needs protection; only the IP-critical part of the design has to be protected to control the cost of logic locking, which can be at the discretion of the designer. SFLL-flexc×k can facilitate the outputs to be selectively flipped, and restored, for the protected input cubes; a flip vector associated with each protected input cube can hold information regarding which outputs can be flipped for the protected input cube.
The restore unit of SFLL-flexc×k can include a tamper-proof look-up table (“LUT”) and XOR gates (see, e.g., Reference 50). The LUT can store c k-bit input cubes along with the corresponding f-bit flip vectors (e.g., for protecting f out of m outputs) that can dictate the functionality stripped from the circuit. When the input matches an entry in the LUT, the associated flip vector can be retrieved from the table and XORed with the outputs to restore the original functionality.
The cost of SFLL-flexc×k can be proportional to the size of the LUT, in addition to fXOR gates inserted at the outputs of the FSC. The cost of the LUT can be denoted as c×(k+f), where f can be a designer-defined parameter. Cost minimization can utilize the minimization of c and k. Additionally, functionality stripping can be used to reduce implementation cost. Thus, the net cost of SFLL-flexc×k can be this savings subtracted from the LUT cost.
Exemplary Optimization framework for SFLL-flexc×k
Given a desired security level s and a set of input cubes, or input patterns, Cinit to be protected, both provided by the designer for a netlist N, the exemplary stripped-functionality logic locking where implemented at minimal cost: Costsf+c×k, where Costsf, which can be minimized, can be the implementation cost of the functionality-stripped netlist Nsf, and c×k can be the implementation cost of the LUT. This can be an optimization problem that can be formulated as, for example:
minimize Costsf+c×k such that k−log2 c≥s
where k−log2c can be the security level attained against SAT attacks.
This optimization problem can be broken down into two smaller processes. In the first exemplary process, the input cubes, or input patterns, can be compressed to minimize the LUT cost=c×k, producing the resulting keys in the process, while honoring the security constraint. In the second exemplary process, the logic of the protected outputs can be re-synthesized based on the keys obtained from the first process with the goal of minimizing Costsf. Such a sequential approach where the output of the first process can be fed into the second process can fail to deliver the overall optimum solution.
In this exemplary process, the objective can be to reduce the LUT cost c×k, the major component of overall implementation cost, thus, reducing the exemplary optimization objective to for example:
minimize c×k such that k−log2c≥s
There can be a couple of exemplary strategies that can be followed to solve this optimization problem. In one exemplary strategy, keys can be created that can flip at least one output for every pattern in every cube in Cinit. The problem then can be finding minimum cubes that collectively cover each cube in Cinit; this can be the classical problem of minimum-cube cover in 2-level logic optimization (see, e.g., Reference 30), and an exemplary synthesis tool can be utilized to solve this problem.
In another exemplary strategy, keys can be created that can flip at least one output for at least one input pattern in every cube in Cinit. In this case, the problem can be to find minimum cubes that, this time, collectively intersect each cube in Cinit. To solve this problem, a heuristic approach, as described in Procedure 1 below, can be utilized. The first step of the exemplary procedure can be cube compression where compatible cubes can be merged to reduce c. To achieve the beneficial security level, s=k−log2c, all the k bits in a cube may not need to be considered, reducing k. The second step of the exemplary procedure can be to eliminate, or turn into x's, the bits that can be conflicting among the cubes, while adhering to security level s. This second step can further reduce c, as certain cubes can become compatible for merging.
Consider c17 ISCAS benchmark circuit shown in the schematic diagram of
If the designer explicitly specifies which output can be flipped for each cube, then the flip vectors can already be determined. Such a rigid scheme does not offer any opportunity for optimization; the selected output functions can be flipped for the corresponding input patterns included in the protected input cubes. An exemplary logic synthesis tool can be used for this purpose. On the other hand, if the designer chooses not to specify the flip vectors, a security-aware synthesis process can leverage this flexibility to minimize implementation cost of the functionality-stripped design Nsf without compromising security. The exemplary process can also produce the flip vectors, denoted by V, as described in Procedure 2 below.
Procedure 2 starts with the original netlist N and a set of cubes C. Initially, a random solution Nsf with the associated cost costsf can be generated by initializing the flip vector V with a random value. From this random solution, simulated annealing can start optimization by selecting a neighboring solution at each iteration. A new solution Nnew can be generated by changing a random bit in the flip vector V. which can lead to the inclusion/exclusion of the corresponding cube for a particular output. The solution Nnew can be accepted if it yields cost savings, for example, costnew<costsf. An inferior solution can be accepted with a probability
This can be a key feature of simulated annealing for exploring a larger search space without getting stuck at a local optimum.
The application of security-aware synthesis to the c17 circuit shown in
An attacker, following a SAT-based or a random guess attack model, must typically identify all input patterns of the protected input cubes in SFLL-flexc×k to be able to recover the correct functionality of the original design from the on-chip implementation; in contrast to SFLL-HDh, the protected input cubes can be arbitrary in SFLL-flexc×k, and one cube may not infer another. This can utilize the retrieval of the content of the entire LUT that can represent the stripped functionality. Nevertheless, the security strength of SFLL can be assessed conservatively; attack success can be defined by the attacker's ability to retrieve any input pattern that belongs to one of the protected input cubes. The following exemplary procedure establishes the resilience of SFLL-flexc×k against SAT attack.
SFLL-flexc×k is (k−└log2c┐)-secure against SAT attack.
SFLL-flexc×k is k-secure against sensitization attack.
SFLL-flexc×k is c·2n-k-resilient against removal attack.
The number and the size of the protected input cubes, denoted by c and k respectively, can describe the trade-off between resilience to oracle-guided and removal attacks.
The exemplary experiments were executed on a 28-core Intel Xeon processors running at 2 GHz with 128 GB of RAM. The combinational part of the sequential benchmark circuits from the ISCAS'89 (see, e.g., Reference 7) and ITC'99 (see, e.g., Reference 11) suites in the exemplary experiments were locked. Table 3 below shows the statistics for the circuits; the largest circuit b18 has greater than about 100K gates. The area, power, and delay (“APD”) overhead for SFLL-HD and SFLL-flex versions were obtained using Synopsys Design Compiler along with Global Foundries 65 nm LPe library. The exemplary results of security analysis are shown where different variants of the SAT attack were launched on various versions of SFLL-HD and SELL-flex. In particular, the SAT attack (see, e.g., Reference 44) and the AppSAT (see, e.g., Reference 40) were launched against the exemplary procedures. Each attack experiment was repeated ten times to improve the statistical significance; average results of the ten runs were reported.
Exemplary Security Analysis.
The resilience of SFLL-HDh can be described by the key-size k and h, which together can describe the number of protected input cubes (hk). In SFLL-HD experiments, the largest logic cone in each circuit can be protected. The number of DIPs utilized for the SAT attack to succeed on SFLL-HDh circuits, and the corresponding execution time are shown in
The execution time of the SAT attack can be proportional to the number of DIPs, although there can be a slight variation of 3× to 4× across the benchmark circuits; the execution time can grow exponentially in k.
Exemplary Impact of Hamming Distance h.
SFLL-HDh can be (k−└log2(hk)┐)-secure. Thus, an increase in h can lead to a significant change in the security level and the expected number of DIPs utilized for the SAT attack. For example, the average number of DIPs for the circuit s38584 for h={0,1,2} and k=14 can be 15K, 10K, and 5K, respectively, as shown in
Exemplary APD Overhead.
The APD overhead can be obtained using Synopsys DC Compiler using Global Foundries 65 nm LPe library (see, e.g., Reference 43) and is shown in the graphs of
Exemplary Scalability.
The SFLL-HDh procedure can operate on the RT-level circuit.
Exemplary Security Analysis.
To validate the security of the exemplary SFLL-flex, the SAT attack (see, e.g., Reference 44) and AppSAT (see, e.g., Reference 40) attack were launched on circuits locked using SFLL-flex for c={1,2,3} and k={11,12,13,14}. The results shown in the graphs of
Exemplary Cube Compression.
The savings for the cube compression procedure are shown in Table 4 below. In the exemplary experiments, test cubes were generated for randomly selected cinit stuck-at faults by using an Atalanta test pattern generation tool (see, e.g., Reference 25), and these test cubes were treated as the designer-provided input cubes Cinit. The compression ratio R were computed as the ratio of the initial number of key bits to be stored cinit×kinit to that of compressed key bits cfinal×kfinal; kinit equals the number of inputs n. The results are presented for two different security levels s=64 and 128 and for two different numbers of initial cubes c=32 and 64. On average, a compression level of 400× can be achieved while still maintaining the desired security level. These compression levels directly translate to a reduction in implementation cost for the restore unit. It can be noted that a lower security level (s=64) facilitates a higher compression level.
Exemplary Security-Aware Synthesis.
The API) overhead can be reported separately for (i) for the “optimal-cost” FSC (e.g., without the restore unit) and (ii) the overall circuit (e.g., with the restore unit comprising the LUT and the surrounding combinational logic). The APD overhead is shown in graphs of
The combined execution time for cube compression and security-aware synthesis is shown in a graph of
While the SAT attack terminates only upon retrieving the correct key, the AppSAT (see, e.g., Reference 40) and Double-DIP (see, e.g., Reference 41) attacks can (e.g., counter-intuitively) terminate earlier, returning an incorrect key value, which can result in an approximate netlist. (See, e.g., Reference 40). The termination criteria for AppSAT can be described by an error rate specified by the attacker, whereas, Double-DIP can terminate when it can no longer find DIPs that eliminate at least two incorrect keys.
Exemplary Double-DIP.
Each of the 2-DIPs employed by the Double-DIP attack can eliminate at least two incorrect keys. Since no such 2-DIPs exist for SFLL-HD0 and SFLL-flex1×k, the attack can terminate immediately, recovering an approximate netlist. For larger h and c values, each input pattern can be a 2-DIP, leading to scalability issues for the Double-DIP attack. As shown in a graph of
Exemplary AppSAT.
In the first set of exemplary AppSAT experiments, various AppSAT parameters were used (see, e.g., Reference 40), for example, 50 random queries to the oracle were employed at every 12th iteration of the attack. It was observed that estimating the error rate using such a small number of patterns can be misleading and can result in premature termination of the AppSAT attack, even for circuits with high corruptibility. Table 5 below shows that the “default” AppSAT attack terminates erroneously for all of the SFLL, circuits, failing to retrieve the correct netlist.
For more realistic corruptibility estimates, the exemplary experiments were repeated on s38417 SFLL-HD circuit with 32 key bits. 1000 random queries were applied after every 12 iterations.
both AppSAT 1610 and the SAT attack 1605 fail to succeed within the time limit of 48 hours. Note that due to the inclusion of the random queries, and additional clauses in the SAT formula, the execution time of AppSAT 1610 can be occasionally higher than that of the SAT attack 1605.
For SFLL-flexc×k, however, s can decrease only logarithmically with c(s=k−[log2c]). As an example, for c=128 cubes, the security levels attained can be 121, irrespective of the circuit. The number of protected patterns can increase linearly with c. For example, for the circuit b20, the number of protected patterns increases from 2384 for c=1 to 2391 for c=128.
Both variants of the exemplary SELL can facilitate the protection of a large number of input patterns. While SFLL-HD can facilitate the designer to choose only the secret key value and the Hamming distance h, SFLL-flex can facilitate him/her to specify the complete set of input cubes to be protected.
With the objective of deploying SFLL for IoT applications, the details of silicon implementation of SFLL on an in-house designed microcontroller using ARM Cortex-M0 microprocessor are discussed below. (See, e.g., Reference 2). For accurate comparisons, both the baseline and the SFLL-locked microcontroller were fabricated. Cortex-M0 belongs to the family of Cortex-M 32-bit RISC processor series from ARM, suitable for a variety of low-cost microcontrollers. The microcontroller includes ARM Ai IB-Lite as its BUS, UART interface, and 64 KB of SRAM.
The baseline ARM Cortex-M0 was locked using 128-bit SFLL-HD0 along with 128-bit FLL. (See, e.g., Reference 36). FLL can be a procedure used to achieve high output corruptibility, while the exemplary SFLL can ensure security against any SAT-based attack. In the exemplary implementation, the program counter (“PC”) was locked to safeguard against unauthorized execution. This ensures that an attacker with an incorrect key would end up with an incorrect execution due to the corrupted PC. The secret key can be stored in a tamper-proof memory, such as one-time programmable fuse ROM. However, in the exemplary implementation, the 256-bit key for the locked processor can be stored in a write-only configuration register. The locked processor can be activated by loading the secret key onto the configuration register through UART.
Exemplary Chip Design/Fabrication Flow.
Synopsys VCS was used for simulation, Synopsys Design Compiler was used for RTL synthesis, Synopsis IC Compiler was used for back-end implementation, Synopsys Prime Time was used for static timing analysis, Synopsys Formality was used for logical equivalence checking, PrimeRail was used for IR drop analysis, and Cadence PVS was used for physical verification. The baseline and the locked versions with the maximum frequency of 100 MHz were fabricated using Global Foundries 65 nm LPe process. A microscopic view of the bare dies for the baseline and the locked versions are shown in exemplary images of
Other implementation parameters, such as RAM size, combinational/sequential area, or wirelength can demonstrate that the two versions of the processor can be quite similar. The most significant difference can be in the combinational area, which can be about 15.2%. This increase in area for the locked processor can be attributed to the key gates introduced by FLL, and the restore unit introduced by SFLL. The additional routing resources utilized for the additional logic translate into a wirelength overhead of 7.6%
The exemplary locked processor can protect against all oracle-guided attacks. The sensitization attack (see, e.g., Reference 34) can terminate in a few minutes but without returning the correct key. When the SAT attack (see, e.g., Reference 44) can be launched on the locked processor, the attack does not terminate within the specified time limit of 48 hours. Since compound logic locking (e.g., SFLL+FLL) was implemented on the processor, the AppSAT attack (see, e.g., Reference 40) would be able to reduce the compound logic locking problem to SFLL alone; indeed the AppSAT attack on the locked processor terminates after 46 hours, but fails to identify the SFLL key.
The exemplary code below that performs one addition operation to explain the impact of logic locking (e.g., hardware-level protection) on processor operations (e.g., software execution) can be used.
This C code can be compiled for the ARM Cortex-M0 using ARM IAR Embedded Workbench and the corresponding binary images can be loaded onto the SRAM via the UART interface. The activated processor (e.g., that has the secret key loaded on the chip) executes the code correctly as shown in an exemplary diagram of
Table 7 below shows an exemplary comparison of SFLL-HD and SFLL-flex with other logic locking procedures. Existing SAT attack resilient procedures such as SARLock and Anti-SAT can be vulnerable to removal attacks. The exemplary SFLL thwarts all known attacks on logic locking. Further, it facilitates a designer to cost-effectively explore the trade-off between resilience to SAT and removal attacks.
While SFLL-HD can be suitable for generic applications where the main requirement can be to protect a large number of input patterns with minimal overhead, SELL-flex can facilitate a designer to protect specific input cubes. The capability to specify IP-critical cubes to protect, even a small number of them, can be very beneficial for applications such as microprocessors with IP-critical controllers, digital signal processing applications with IP-critical coefficients, etc. The flexibility required in SFLL-flex necessitates a slightly more expensive restore unit mainly due to the LUT, compared to SFLL-HD, which has a generic, simple, and scalable restore unit. In either case, the security-aware synthesis framework can facilitate the designer to attain the desired security level.
These attacks mainly target compound (e.g., multi-layered) logic locking procedures. AppSAT and Double-DIP can be approximate attacks as they only reduce a compound logic locking procedure (e.g. SARLock+SLL) to a SAT attack resilient procedure (e.g. SARLock). The Bypass attack, however, can be an exact attack; the attack, if successful, returns a netlist functionally equivalent to the oracle (e.g., functional IC).
These attacks can rely on the classification of compound logic locking key bits into two classes: key bits for RLL/SLL etc. that introduce high corruptibility and key bits for SARLock/Anti-SAT etc. that induce low corruptibility at the outputs. These attacks can quickly determine the correct values for the high corruptibility key bits. The AppSAT and Double-DIP attacks can then assign a random value for the low corruptibility key bits, whereas, the Bypass attack can introduce additional logic to fix the occasional corruption at the outputs. These attacks may not be effective against the exemplary SFLL as all the key bits in SFLL can incur uniform corruptibility and it may not be feasible to partition the key search space into low/high corruptibility regions.
There can be two primary differences between the AppSAT and the SAT attack. First, AppSAT can be constructed by augmenting the SAT attack with random queries to the oracle at regular intervals. AppSAT includes, e.g., 50 random queries every 12 iterations of the attack. (See, e.g., Reference 40). Second, AppSAT can terminate much earlier than the SAT attack, for example, when the error rate, or Hamming distance at the outputs, can be below a certain threshold
While the AppSAT attack can quickly recover an approximate netlist for low-corruptibility SFLL circuits (e.g., with low h or c), it behaves similarly to the SAT attack for high-corruptibility SFLL circuits since the early termination condition may not be satisfied. Thus, SFLL resilience against AppSAT can be similar to that against the SAT attack.
The 50 queries as per the default AppSAT settings can be sufficient to separate the key bits into two classes in case of compound locking procedures. However, no such classes of key bits exist in SFLL where the corruptibility can be uniform for all the key values. When the attack was launched on SFLL circuits with varying corruptibility values (e.g., represented using h), the attack terminated erroneously even for high corruptibility circuits. The error can be better estimated with 1000 random queries. The attack then quickly extracts the approximate netlist for the smaller values of h. For the larger h values, the attack performance can be similar to that of the SAT attack.
Exemplary Double-DIP.
Compared to the SAT attack, the Double-DIP attack uses a larger miter circuit comprising four copies of the locked netlist. (See, e.g., Reference 41). The 2-DIPs computed by the attack eliminate at least two incorrect keys per DIP. The attack terminates when no more 2-DIPs can be found, implying that only DIPs that can eliminate at most one incorrect key remain in the search space. The attack returns an approximate netlist. While the attack can break compound logic locking procedures, it may not be scalable, especially if the locked circuit has multiple correct keys.
Except for SFLL-HD0 or SFLL-flex1×k (e.g., where there may be no 2 DIPs), the Double-DIP attack, when launched on SFLL circuits, can run into scalability issues as it can compute an exponential number of DIPs before it terminates. Rarely, when the attack is fortuitous and selects one of the protected patterns as a DIP (e.g., the protected pattern can be a 2-DIP), it can eliminate most of the incorrect keys in a single iteration of the attack. In such cases, the attack returns the exact netlist, similar to the basic SAT attack, but this can be highly unlikely for large enough key sizes.
Exemplary Bypass. The Bypass attack generally selects two random key values as constraints for the two locked netlists in the miter circuit. (See, e.g., Reference 53). The attack then computes all the DIPs that result in differing outputs for the two key values. For the traditional low corruptibility locking procedures such as SARLock, only a few DIPs can be extracted. The attacker then determines the correct key values for those DIPs from the output of functional IC. One of the two key values can be designated as the secret key and an additional bypass circuit can be added around the locked netlist to fix the output for the selected DIPs.
In SFLL, a protected input pattern produces the same incorrect output for most of the incorrect key values. Occasionally, the output can be correctly restored even for incorrect key values, as shown in
A microscopic view of the bare dies of the baseline and locked versions are shown in
Further, a scanning electron microscope (“SEM”) image of the locked version is shown in
n inputs and k key bits can be assumed, where k<n.
B.1 SFLL-HDh
For SFLL-HDh,
Thus, for a PPT attacker oblivious to the protected input cubes, making only only polynomial number of queries q(k), the success probability can be given by Eq. 2,
Thus, from the above, SFLL-HDh can be
secure against the SAT attack can be achieved.
SFLL-HDh is k-Secure Against Sensitization Attack.
Similar to SFLL-SFLL-HD0, all the k bits of SFLL-HDh converge within the comparator inside the restore unit to produce the restore signal. Therefore, sensitizing any key bit through the restore signal to the output utilizes controlling all the other key bits. All k bits can be therefore pairwise-secure. SFLL-HDh can be k-secure against sensitization attack.
As the restore signal can be skewed towards 0, it can be identified by a signal probability skew (“SPS”) attack. The attacker can then be able to recover the FSC, denoted as cktrec which produces erroneous output for the set of protect input patterns Γ. Similar to the above, from Eq. 3, the following can be achieved,
Thus, from the above, SFLL-HDh can be 2n-k·
resilient against a removal attack can be achieved.
SFLL-Flexc×k is (k−└log2c┐)-Secure Against SAT Attack.
For SFLL-flexc×k, the cardinality of the set of protected cubes P can be |P|=c. Thus, from Eq. 2, the success probability of a PPT adversary making a polynomial number of queries q(k) can be given by, for example:
Thus, from the above, SFLL-HDc×k can be (k−└log2c┐)-secure against the SAT attack can be achieved.
SFLL-Flexc×k is k-Secure Against Sensitization Attack
All the k bits of SELL-flexc×k converge within the comparator inside the LUT to produce the signal that asserts the XOR vector operation between the flip vector and the outputs. Therefore, sensitizing any key bit through the LUT to any of the outputs utilizes controlling all the other key bits. All k bits can therefore be pairwise-secure. SFLL-flexc×k can be k-secure against sensitization attack.
SFLL-Flexc×k is c·2n-k-Resilient Against Removal Attack
Even if the LUT along with its surrounding logic can be identified by a reverse-engineer, he/she can only recover the FSC denoted as cktrec. However, cktrec produces incorrect output for the protected input patterns Γ. Thus, for example:
Thus, from the above, SFLL-HDc×k can be c·2n-k-resilient against a removal attack can be achieved.
An exemplary stripped-functionality logic locking can be used, which can include a low-cost, secure, and scalable logic locking procedure that can thwart most or all known and anticipated attacks. The resilience of any logic locking procedure can be quantified against a given attack in terms of the number and the size of the protected input cubes. Based on this finding, CAD framework was developed that can facilitate the designer to strip functionality from the hardware implementation of the design based on a set of input cubes to be protected; a security-aware synthesis process can also be used that can strip functionality with the objective of minimizing the cost of implementation. By adjusting the number and the size of the protected cubes, the designer can explore the trade-off between resilience to different attacks. The stripped functionality can be hidden from untrusted entities, such as the foundry and the end-user (e.g., potential reverse-engineer). Only the secret key, for example, the protected cubes, can successfully recover the stripped functionality through an on-chip restore operation.
Another flexibility that the exemplary framework offers can be that for general applications, it facilitates the designer to protect any number of a restricted set of cubes, leading to a simple and scalable architecture. It also supports specialized applications that utilized IP-critical input cubes to be protected. The designer can thus choose the solution that best fits the security needs of his/her application.
Upon implementing the exemplary logic locking procedure on large-sized benchmarks (e.g., greater than about 100K gates) and launching all known attacks on them, it was confirmed that the exemplary procedure can be secure and cost-efficient. For further validation, the exemplary logic locking procedure was applied on an industry-strength microprocessor design that was then implement in silicon; the data obtained from the fabricated chips also confirm the practicality, security, and scalability of the exemplary procedure. The exemplary procedure can be seamlessly integrated into the IC design flow to thwart IP piracy, reverse engineering, and overbuilding attacks.
As shown in
Further, the exemplary processing arrangement 2305 can be provided with or include an input/output ports 2335, which can include, for example a wired network, a wireless network, the internet, an intranet, a data collection probe, a sensor, etc. As shown in
The foregoing merely illustrates the principles of the disclosure. Various modifications and alterations to the described embodiments will be apparent to those skilled in the art in view of the teachings herein. It will thus be appreciated that those skilled in the art will be able to devise numerous systems, arrangements, and procedures which, although not explicitly shown or described herein, embody the principles of the disclosure and can be thus within the spirit and scope of the disclosure. Various different exemplary embodiments can be used together with one another, as well as interchangeably therewith, as should be understood by those having ordinary skill in the art. In addition, certain terms used in the present disclosure, including the specification, drawings and claims thereof, can be used synonymously in certain instances, including, but not limited to, for example, data and information. It should be understood that, while these words, and/or other words that can be synonymous to one another, can be used synonymously herein, that there can be instances when such words can be intended to not be used synonymously. Further, to the extent that the prior art knowledge has not been explicitly incorporated by reference herein above, it is explicitly incorporated herein in its entirety. All publications referenced are incorporated herein by reference in their entireties.
The following references are hereby incorporated by reference in their entireties:
This application relates to and claims priority from U.S. Patent Application No. 62/576,988, filed on Oct. 25, 2017, the entire disclosure of which is incorporated herein by reference.
This invention was made with government support under Grant Nos. 1319841 and 1652842, awarded by the National Science Foundation. The government has certain rights in the invention.
Number | Date | Country | |
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62576988 | Oct 2017 | US |