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342
How to Go Beyond the BlackBox Simulation Barrier
 In 42nd FOCS
, 2001
"... The simulation paradigm is central to cryptography. A simulator is an algorithm that tries to simulate the interaction of the adversary with an honest party, without knowing the private input of this honest party. Almost all known simulators use the adversary’s algorithm as a blackbox. We present t ..."
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Cited by 227 (13 self)
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The simulation paradigm is central to cryptography. A simulator is an algorithm that tries to simulate the interaction of the adversary with an honest party, without knowing the private input of this honest party. Almost all known simulators use the adversary’s algorithm as a blackbox. We present the first constructions of nonblackbox simulators. Using these new nonblackbox techniques we obtain several results that were previously proven to be impossible to obtain using blackbox simulators. Specifically, assuming the existence of collision resistent hash functions, we construct a new zeroknowledge argument system for NP that satisfies the following properties: 1. This system has a constant number of rounds with negligible soundness error. 2. It remains zero knowledge even when composed concurrently n times, where n is the security parameter. Simultaneously obtaining 1 and 2 has been recently proven to be impossible to achieve using blackbox simulators. 3. It is an ArthurMerlin (public coins) protocol. Simultaneously obtaining 1 and 3 was known to be impossible to achieve with a blackbox simulator. 4. It has a simulator that runs in strict polynomial time, rather than in expected polynomial time. All previously known constantround, negligibleerror zeroknowledge arguments utilized expected polynomialtime simulators.
NonInteractive Verifiable Computing: Outsourcing Computation to Untrusted Workers
, 2009
"... Verifiable Computation enables a computationally weak client to “outsource ” the computation of a function F on various inputs x1,...,xk to one or more workers. The workers return the result of the function evaluation, e.g., yi = F(xi), as well as a proof that the computation of F was carried out co ..."
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Cited by 219 (13 self)
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Verifiable Computation enables a computationally weak client to “outsource ” the computation of a function F on various inputs x1,...,xk to one or more workers. The workers return the result of the function evaluation, e.g., yi = F(xi), as well as a proof that the computation of F was carried out correctly on the given value xi. The verification of the proof should require substantially less computational effort than computing F(xi) from scratch. We present a protocol that allows the worker to return a computationallysound, noninteractive proof that can be verified in O(m) time, where m is the bitlength of the output of F. The protocol requires a onetime preprocessing stage by the client which takes O(C) time, where C is the smallest Boolean circuit computing F. Our scheme also provides input and output privacy for the client, meaning that the workers do not learn any information about the xi or yi values. 1
Candidate indistinguishability obfuscation and functional encryption for all circuits
 In FOCS
, 2013
"... In this work, we study indistinguishability obfuscation and functional encryption for general circuits: Indistinguishability obfuscation requires that given any two equivalent circuits C0 and C1 of similar size, the obfuscations of C0 and C1 should be computationally indistinguishable. In functional ..."
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Cited by 170 (37 self)
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In this work, we study indistinguishability obfuscation and functional encryption for general circuits: Indistinguishability obfuscation requires that given any two equivalent circuits C0 and C1 of similar size, the obfuscations of C0 and C1 should be computationally indistinguishable. In functional encryption, ciphertexts encrypt inputs x and keys are issued for circuits C. Using the key SKC to decrypt a ciphertext CTx = Enc(x), yields the value C(x) but does not reveal anything else about x. Furthermore, no collusion of secret key holders should be able to learn anything more than the union of what they can each learn individually. We give constructions for indistinguishability obfuscation and functional encryption that supports all polynomialsize circuits. We accomplish this goal in three steps: • We describe a candidate construction for indistinguishability obfuscation for NC 1 circuits. The security of this construction is based on a new algebraic hardness assumption. The candidate and assumption use a simplified variant of multilinear maps, which we call Multilinear Jigsaw Puzzles. • We show how to use indistinguishability obfuscation for NC 1 together with Fully Homomorphic Encryption (with decryption in NC 1) to achieve indistinguishability obfuscation for all circuits.
Static Analysis of Executables to Detect Malicious Patterns
 In Proceedings of the 12th USENIX Security Symposium
, 2003
"... Malicious code detection is a crucial component of any defense mechanism. In this paper, we present a unique viewpoint on malicious code detection. We regard malicious code detection as an obfuscationdeobfuscation game between malicious code writers and researchers working on malicious code detecti ..."
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Cited by 149 (0 self)
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Malicious code detection is a crucial component of any defense mechanism. In this paper, we present a unique viewpoint on malicious code detection. We regard malicious code detection as an obfuscationdeobfuscation game between malicious code writers and researchers working on malicious code detection. Malicious code writers attempt to obfuscate the malicious code to subvert the malicious code detectors, such as antivirus software. We tested the resilience of three commercial virus scanners against codeobfuscation attacks. The results were surprising: the three commercial virus scanners could be subverted by very simple obfuscation transformations! We present an architecture for detecting malicious patterns in executables that is resilient to common obfuscation transformations. Experimental results demonstrate the efficacy of our prototype tool, SAFE (a static analyzer for executables). 1
Private Circuits: Securing Hardware against Probing Attacks
 In Proceedings of CRYPTO 2003
, 2003
"... Abstract. Can you guarantee secrecy even if an adversary can eavesdrop on your brain? We consider the problem of protecting privacy in circuits, when faced with an adversary that can access a bounded number of wires in the circuit. This question is motivated by side channel attacks, which allow an a ..."
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Cited by 128 (7 self)
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Abstract. Can you guarantee secrecy even if an adversary can eavesdrop on your brain? We consider the problem of protecting privacy in circuits, when faced with an adversary that can access a bounded number of wires in the circuit. This question is motivated by side channel attacks, which allow an adversary to gain partial access to the inner workings of hardware. Recent work has shown that side channel attacks pose a serious threat to cryptosystems implemented in embedded devices. In this paper, we develop theoretical foundations for security against side channels. In particular, we propose several efficient techniques for building private circuits resisting this type of attacks. We initiate a systematic study of the complexity of such private circuits, and in contrast to most prior work in this area provide a formal threat model and give proofs of security for our constructions.
Implementing an Untrusted Operating System on Trusted Hardware
 In Proceedings of the 19th ACM Symposium on Operating Systems Principles
, 2003
"... Recently, there has been considerable interest in providing "trusted computing platforms" using hardware  TCPA and Palladium being the most publicly visible examples. In this paper we discuss our experience with building such a platform using a traditional timesharing operating system ..."
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Cited by 89 (0 self)
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Recently, there has been considerable interest in providing "trusted computing platforms" using hardware  TCPA and Palladium being the most publicly visible examples. In this paper we discuss our experience with building such a platform using a traditional timesharing operating system executing on XOM  a processor architecture that provides copy protection and tamperresistance functions. In XOM, only the processor is trusted; main memory and the operating system are not trusted.
On Obfuscating Point Functions
, 2005
"... We study the problem of obfuscation in the context of point functions (also known as delta functions). ..."
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Cited by 74 (2 self)
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We study the problem of obfuscation in the context of point functions (also known as delta functions).
Limits of Static Analysis for Malware Detection
"... Malicious code is an increasingly important problem that threatens the security of computer systems. The traditional line of defense against malware is composed of malware detectors such as virus and spyware scanners. Unfortunately, both researchers and malware authors have demonstrated that these s ..."
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Cited by 71 (9 self)
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Malicious code is an increasingly important problem that threatens the security of computer systems. The traditional line of defense against malware is composed of malware detectors such as virus and spyware scanners. Unfortunately, both researchers and malware authors have demonstrated that these scanners, which use pattern matching to identify malware, can be easily evaded by simple code transformations. To address this shortcoming, more powerful malware detectors have been proposed. These tools rely on semantic signatures and employ static analysis techniques such as model checking and theorem proving to perform detection. While it has been shown that these systems are highly effective in identifying current malware, it is less clear how successful they would be against adversaries that take into account the novel detection mechanisms. The goal of this paper is to explore the limits of static analysis for the detection of malicious code. To this end, we present a binary obfuscation scheme that relies on the idea of opaque constants, which are primitives that allow us to load a constant into a register such that an analysis tool cannot determine its value. Based on opaque constants, we build obfuscation transformations that obscure program control flow, disguise access to local and global variables, and interrupt tracking of values held in processor registers. Using our proposed obfuscation approach, we were able to show that advanced semanticsbased malware detectors can be evaded. Moreover, our opaque constant primitive can be applied in a way such that is provably hard to analyze for any static code analyzer. This demonstrates that static analysis techniques alone might no longer be sufficient to identify malware. 1
Functional Signatures and Pseudorandom Functions
, 2013
"... In this paper, we introduce functional digital signatures and pseudorandom functions. In a functional signature scheme, in addition to a master signing key that can be used to sign any message, there are signing keys for a function f, which allow one to sign any message in the range of f. We show ap ..."
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Cited by 69 (7 self)
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In this paper, we introduce functional digital signatures and pseudorandom functions. In a functional signature scheme, in addition to a master signing key that can be used to sign any message, there are signing keys for a function f, which allow one to sign any message in the range of f. We show applications of functional signatures to construct succinct noninteractive arguments and delegation schemes. We give several general constructions for this primitive based on different computational hardness assumptions, and describe the tradeoffs between them in terms of the assumptions they require and the size of the signatures. In a functional pseudorandom function, in addition to a master secret key that can be used to evaluate the pseudorandom function F on any point in the domain, there are additional secret keys for a function f, which allow one to evaluate F on any y for which there exists an x such that f(x) = y. This implies the ability to delegate keys per function f for computing a pseudorandom function F on points y for which f(y) = 1. We define and provide a sample construction of a functional pseudorandom function family for the prefixfixing function family. 1