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].
Titolo: | Estimating Software Obfuscation Potency with Artificial Neural Networks | |
Autori: | ||
Data di pubblicazione: | 2017 | |
Serie: | ||
Abstract: | This paper presents an approach to estimate the potency of obfuscation techniques. Our approach u...ses 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. | |
ISBN: | 978-3-319-68062-0 978-3-319-68063-7 | |
Appare nelle tipologie: | 4.1 Contributo in Atti di convegno |
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http://hdl.handle.net/11583/2680443