This paper deals with metamorphic viruses. More precisely, it examines the use of advanced code obfuscation techniques with respect to metamorphic viruses. Our objective is to evaluate the difficulty of a reliable static detection of viruses that use such obfuscation techniques. Here we extend Spinellis' result (IEEE Trans. Inform. Theory, 49(1), [280][281][282][283][284] 2003) on the detection complexity of bounded-length polymorphic viruses to metamorphic viruses. In particular, we prove that reliable static detection of a particular category of metamorphic viruses is an N P-complete problem. Then we empirically illustrate our result by constructing a practical obfuscator which could be used by metamorphic viruses in the future to evade detection.
In this paper, we propose an original black-box approach concerning antivirus products evaluation. Contrary to classical tests focusing on detection rates concerning a specific malware sample, we use a generic metamorphic engine to observe the detection products behaviors. We believe that this point of view presents a double interest: First, it offers an original way of evaluating current antivirus products focusing on the observed detection technique. More precisely, the use of metamorphic malware guarantees the difficulty of static signature based detection techniques to focus only on heuristic and behavioral detection approaches. Second, by pointing out current detection capabilities, we practically evaluate the danger that complex metamorphic malware could represent. To achieve this goal, we start with the description of a generic metamorphic engine acting in two steps: obfuscation and modeling. Then, we apply this engine to a real mass-mailing worm and propose the resulting metamorphic malware samples to current antivirus products. The observed results lead to a classification of detection techniques in two main categories: the first one, relying on static detection techniques, presents low detection rates obtained by heuristic analysis. The second one, composed of behavioral detection programs, mainly focuses on elementary suspicious actions. In all cases, no product was able to detect a global malware behavior. Consequently, we consider J.-M. Borello (B) CELAR,
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