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Malware detection is a crucial aspect of software security. Current malware detectors work by checking for signatures , which attempt to capture the syntactic characteristics of the machine-level byte sequence of the malware. This reliance on a syntactic approach makes current detectors vulnerable to code obfuscations, increasingly used by malware writers, that alter the syntactic properties of the malware byte sequence without significantly affecting their execution behavior. This paper takes the position that the key to malware identification lies in their semantics. It proposes a semantics-based framework for reasoning about malware detectors and proving properties such as soundness and completeness of these detectors. Our approach uses a trace semantics to characterize the behavior of malware as well as that of the program being checked for infection, and uses abstract interpretation to “hide” irrelevant aspects of these behaviors. As a concrete application of our approach, we show that (1) standard signature matching detection schemes are generally sound but not complete, (2) the semantics-aware malware detector proposed by Christodorescu et al. is complete with respect to a number of common obfuscations used by malware writers and (3) the malware detection scheme proposed by Kinder et al. and based on standard model-checking techniques is sound in general and complete on some, but not all, obfuscations handled by the semantics-aware malware detector.

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Remote trusting aims at verifying the "healthy" execution of a program running on an untrusted client that communicates with a trusted server via network connection. After giving a formal definition of the remote trusting problem and a test to determine whether an attack against a given remote trusting scheme is successful or not, we propose a protection against malicious modification of the client code, based on the replication of a portion of the client on the server. To minimize the size of the code that is replicated, we propose to use barrier slicing. We show the feasibility of our approach on a case study. Our results indicate that a barrier slice is significantly smaller than the corresponding backward slice while providing the same level of protection.

Abstract. We present AIOCJ, a framework for programming distributed adaptive applications. Applications are programmed using AIOC, a choreographic language suited for expressing patterns of interaction from a global point of view. AIOC allows the programmer to specify which parts of the application can be adapted. Adaptation takes place at runtime by means of rules, which can change during the execution to tackle possibly unforeseen adaptation needs. AIOCJ relies on a solid theory that ensures applications to be deadlock-free by construction also after adaptation. We describe the architecture of AIOCJ, the design of the AIOC language, and an empirical validation of the framework.

In recent years code obfuscation has attracted research interest as a promising technique for protecting secret properties of programs. The basic idea of code obfuscation is to transform programs in order to hide their sensitive information while preserving their functionality. One of the major drawbacks of code obfuscation is the lack of a rigorous theoretical framework that makes it difficult to formally analyze and certify the effectiveness of obfuscating techniques. We face this problem by providing a formal framework for code obfuscation based on abstract interpretation and program semantics. In particular, we show that what is hidden and what is preserved by an obfuscating transformation can be expressed as abstract interpretations of program semantics. Being able to specify what is masked and what is preserved by an obfuscation allows us to understand its potency, namely the amount of obscurity that the transformation adds to programs. In the proposed framework, obfuscation and attackers are modeled as approximations of program semantics and the lattice of abstract interpretations provides a formal tool for comparing obfuscations with respect to their potency. In particular, we prove that our framework provides an adequate setting to measure not only the potency of an obfuscation but also its resilience, i.e., the difficulty of undoing the obfuscation. We consider code obfuscation by opaque predicate insertion and we show how the degree of abstraction needed to disclose different opaque predicates allows us to compare their potency and resilience.

Malware detection is a crucial aspect of software security. Current malware detectors work by checking for "signatures," which attempt to capture (syntactic) characteristics of the machine-level byte sequence of the malware. This reliance on a syntactic approach makes such detectors vulnerable to code obfuscations, increasingly used by malware writers, that alter syntactic properties of the malware byte sequence without significantly affecting their execution behavior.This paper takes the position that the key to malware identification lies in their semantics. It proposes a semantics-based framework for reasoning about malware detectors and proving properties such as soundness and completeness of these detectors. Our approach uses a trace semantics to characterize the behaviors of malware as well as the program being checked for infection, and uses abstract interpretation to "hide" irrelevant aspects of these behaviors. As a concrete application of our approach, we show that the semantics-aware malware detector proposed by Christodorescu et al. is complete with respect to a number of common obfuscations used by malware writers.