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“Comparing Approaches to Interactive Lifelog Search at the Lifelog Search Challenge (LSC2018)”,
ITE Transactions on Media Technology and Applications, vol. 7, pp. 46-59, 2019.
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“Digital Investigation of PDF Files: Unveiling Traces of Embedded Malware”,
IEEE Security and Privacy: Special Issue on Digital Forensics, vol. 17, no. 1, pp. 63-71, 2019.
(838.95 KB) M. Scalas, Maiorca, D., Mercaldo, F., Visaggio, C. Aaron, Martinelli, F., and Giacinto, G.,
“On the Effectiveness of System API-Related Information for Android Ransomware Detection”,
Computers and Security, vol. 86, pp. 162-182, 2019.
(706.92 KB) L. Demetrio, Biggio, B., Lagorio, G., Roli, F., and Armando, A.,
“Explaining Vulnerabilities of Deep Learning to Adversarial Malware Binaries”, in
3rd Italian Conference on Cyber Security, ITASEC 2019, Pisa, Italy, 2019, vol. 2315.
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“PowerDrive: Accurate De-Obfuscation and Analysis of PowerShell Malware”,
16th Conference on Detection of Intrusions and Malware & Vulnerability Assessment (DIMVA). Springer, Gothenburg, Sweden, pp. 240-259, 2019.
(352.39 KB) A. Demontis, Melis, M., Pintor, M., Jagielski, M., Biggio, B., Oprea, A., Nita-Rotaru, C., and Roli, F.,
“Why Do Adversarial Attacks Transfer? Explaining Transferability of Evasion and Poisoning Attacks”, in
28th Usenix Security Symposium, Santa Clara, California, USA, 2019, vol. 28th {USENIX} Security Symposium ({USENIX} Security 19), p. 321--338.
(1.09 MB) A. Demontis, Melis, M., Biggio, B., Maiorca, D., Arp, D., Rieck, K., Corona, I., Giacinto, G., and Roli, F.,
“Yes, Machine Learning Can Be More Secure! A Case Study on Android Malware Detection”,
IEEE Trans. Dependable and Secure Computing, vol. 16, no. 4, pp. 711-724, 2019.
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