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On the Statistical Detection of Adversarial Instances over Encrypted Data. / Sheikhalishahi, Mina; Nateghizad, Majid; Martinelli, Fabio; Erkin, Zekeriya; Loog, Marco.

Security and Trust Management - 15th International Workshop, STM 2019, Proceedings. ed. / Sjouke Mauw; Mauro Conti. Springer, 2019. p. 71-88 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11738 LNCS).

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

Harvard

Sheikhalishahi, M, Nateghizad, M, Martinelli, F, Erkin, Z & Loog, M 2019, On the Statistical Detection of Adversarial Instances over Encrypted Data. in S Mauw & M Conti (eds), Security and Trust Management - 15th International Workshop, STM 2019, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11738 LNCS, Springer, pp. 71-88, 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, Luxembourg, Luxembourg, 26/09/19. https://doi.org/10.1007/978-3-030-31511-5_5

APA

Sheikhalishahi, M., Nateghizad, M., Martinelli, F., Erkin, Z., & Loog, M. (2019). On the Statistical Detection of Adversarial Instances over Encrypted Data. In S. Mauw, & M. Conti (Eds.), Security and Trust Management - 15th International Workshop, STM 2019, Proceedings (pp. 71-88). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11738 LNCS). Springer. https://doi.org/10.1007/978-3-030-31511-5_5

Vancouver

Sheikhalishahi M, Nateghizad M, Martinelli F, Erkin Z, Loog M. On the Statistical Detection of Adversarial Instances over Encrypted Data. In Mauw S, Conti M, editors, Security and Trust Management - 15th International Workshop, STM 2019, Proceedings. Springer. 2019. p. 71-88. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-030-31511-5_5

Author

Sheikhalishahi, Mina ; Nateghizad, Majid ; Martinelli, Fabio ; Erkin, Zekeriya ; Loog, Marco. / On the Statistical Detection of Adversarial Instances over Encrypted Data. Security and Trust Management - 15th International Workshop, STM 2019, Proceedings. editor / Sjouke Mauw ; Mauro Conti. Springer, 2019. pp. 71-88 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

BibTeX

@inproceedings{696ab9aad01e4b27a18466730a42638b,
title = "On the Statistical Detection of Adversarial Instances over Encrypted Data",
abstract = "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.",
keywords = "Adversarial machine learning, Homomorphic encryption, Privacy",
author = "Mina Sheikhalishahi and Majid Nateghizad and Fabio Martinelli and Zekeriya Erkin and Marco Loog",
year = "2019",
doi = "10.1007/978-3-030-31511-5_5",
language = "English",
isbn = "9783030315108",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer",
pages = "71--88",
editor = "Sjouke Mauw and Mauro Conti",
booktitle = "Security and Trust Management - 15th International Workshop, STM 2019, Proceedings",

}

RIS

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

SN - 9783030315108

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

ER -

ID: 67416055