InforLorV4, Hal, Corpus, bibRecord, 001212

Behavior Analysis of Malware by Rewriting-based Abstraction - Extended Version

Identifieur interne : 001212 ( Hal/Corpus ); précédent : 001211; suivant : 001213

Behavior Analysis of Malware by Rewriting-based Abstraction - Extended Version

Auteurs : Philippe Beaucamps ; Isabelle Gnaedig ; Jean-Yves Marion

Source :

RBID : Hal:inria-00594396

English descriptors

mix :
- behavior abstraction, behavioral analysis, information leak, malware detection, model checking, static analysis, temporal logic, term rewriting.

Abstract

We propose a formal approach for the detection of high-level program behaviors. These behaviors, defined as combinations of patterns in a signature, are detected by model-checking on abstracted forms of program traces. Our approach works on unbounded sets of traces, which makes our technique useful not only for dynamic analysis, considering one trace at a time, but also for static analysis, considering a set of traces inferred from a control flow graph. Our technique uses a rewriting-based abstraction mechanism, producing a high-level representation of the program behavior, independent of the program implementation. It allows us to handle similar behaviors in a generic way and thus to be robust with respect to variants. Successfully applied to malware detection, our approach allows us in particular to model and detect information leak.

Url:

https://hal.inria.fr/inria-00594396

Links to Exploration step

Hal:inria-00594396

Le document en format XML

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<front><div type="abstract" xml:lang="en">We propose a formal approach for the detection of high-level program behaviors. These behaviors, defined as combinations of patterns in a signature, are detected by model-checking on abstracted forms of program traces. Our approach works on unbounded sets of traces, which makes our technique useful not only for dynamic analysis, considering one trace at a time, but also for static analysis, considering a set of traces inferred from a control flow graph. Our technique uses a rewriting-based abstraction mechanism, producing a high-level representation of the program behavior, independent of the program implementation. It allows us to handle similar behaviors in a generic way and thus to be robust with respect to variants. Successfully applied to malware detection, our approach allows us in particular to model and detect information leak.</div>
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<abstract xml:lang="en">We propose a formal approach for the detection of high-level program behaviors. These behaviors, defined as combinations of patterns in a signature, are detected by model-checking on abstracted forms of program traces. Our approach works on unbounded sets of traces, which makes our technique useful not only for dynamic analysis, considering one trace at a time, but also for static analysis, considering a set of traces inferred from a control flow graph. Our technique uses a rewriting-based abstraction mechanism, producing a high-level representation of the program behavior, independent of the program implementation. It allows us to handle similar behaviors in a generic way and thus to be robust with respect to variants. Successfully applied to malware detection, our approach allows us in particular to model and detect information leak.</abstract>
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Behavior Analysis of Malware by Rewriting-based Abstraction - Extended Version

Behavior Analysis of Malware by Rewriting-based Abstraction - Extended Version

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