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EnglishThis 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 |
File in questo prodotto:
| File | Descrizione | Tipologia | Licenza | |
|---|---|---|---|---|
| 10.1007_978-3-319-68063-7_13.pdf | Articolo principale | 2. Post-print / Author's Accepted Manuscript | Non Pubblico - Accesso privato/ristretto | Administrator Richiedi una copia |
http://hdl.handle.net/11583/2680443
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