This paper presents an approach to estimate the potency of obfuscation techniques. Our approach uses neural networks to accurately predict the value of complexity metrics – which are used to compute the potency – after an obfuscation transformation is applied to a code region. This work is the first step towards a decision support to optimally protect software applications.

Estimating Software Obfuscation Potency with Artificial Neural Networks / Canavese, Daniele; Regano, Leonardo; Basile, Cataldo; Viticchie', Alessio. - STAMPA. - 10547:(2017), pp. 193-202. ((Intervento presentato al convegno STM - 2017: 13th International Workshop on Security and Trust Management tenutosi a Oslo (NO) nel September 14–15, 2017 [10.1007/978-3-319-68063-7_13].

Estimating Software Obfuscation Potency with Artificial Neural Networks

CANAVESE, DANIELE;REGANO, LEONARDO;BASILE, CATALDO;VITICCHIE', ALESSIO
2017

Abstract

This paper presents an approach to estimate the potency of obfuscation techniques. Our approach uses neural networks to accurately predict the value of complexity metrics – which are used to compute the potency – after an obfuscation transformation is applied to a code region. This work is the first step towards a decision support to optimally protect software applications.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2680443
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