TY - GEN
T1 - On the Statistical Detection of Adversarial Instances over Encrypted Data
AU - Sheikhalishahi, Mina
AU - Nateghizad, Majid
AU - Martinelli, Fabio
AU - Erkin, Zekeriya
AU - Loog, Marco
PY - 2019
Y1 - 2019
N2 - Adversarial instances are malicious inputs designed to fool machine learning models. In particular, motivated and sophisticated attackers intentionally design adversarial instances to evade classifiers which have been trained to detect security violation, such as malware detection. While the existing approaches provide effective solutions in detecting and defending adversarial samples, they fail to detect them when they are encrypted. In this study, a novel framework is proposed which employs statistical test to detect adversarial instances, when data under analysis are encrypted. An experimental evaluation of our approach shows its practical feasibility in terms of computation cost.
AB - Adversarial instances are malicious inputs designed to fool machine learning models. In particular, motivated and sophisticated attackers intentionally design adversarial instances to evade classifiers which have been trained to detect security violation, such as malware detection. While the existing approaches provide effective solutions in detecting and defending adversarial samples, they fail to detect them when they are encrypted. In this study, a novel framework is proposed which employs statistical test to detect adversarial instances, when data under analysis are encrypted. An experimental evaluation of our approach shows its practical feasibility in terms of computation cost.
KW - Adversarial machine learning
KW - Homomorphic encryption
KW - Privacy
UR - http://www.scopus.com/inward/record.url?scp=85075597788&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-31511-5_5
DO - 10.1007/978-3-030-31511-5_5
M3 - Conference contribution
AN - SCOPUS:85075597788
SN - 9783030315108
VL - 11738
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 71
EP - 88
BT - Security and Trust Management - 15th International Workshop, STM 2019, Proceedings
A2 - Mauw, Sjouke
A2 - Conti, Mauro
PB - Springer
T2 - 15th International Workshop on Security and Trust Management, STM 2019 held in conjunction with the 24th European Symposium on Research in Computer Security, ESORICS 2019
Y2 - 26 September 2019 through 27 September 2019
ER -