TY - GEN
T1 - Attacks on ML Systems
T2 - 18th International Conference on Information Systems Security, ICISS 2022
AU - Zou, Qingtian
AU - Zhang, Lan
AU - Singhal, Anoop
AU - Sun, Xiaoyan
AU - Liu, Peng
N1 - Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2022
Y1 - 2022
N2 - The past several years have witnessed rapidly increasing use of machine learning (ML) systems in multiple industry sectors. Since security analysis is one of the most essential parts of the real-world ML system protection practice, there is an urgent need to conduct systematic security analysis of ML systems. However, it is widely recognized that the existing security analysis approaches and techniques, which were developed to analyze enterprise (software) systems and networks, are no longer very suitable for analyzing ML systems. In this paper, we seek to present a vision on how to address two unique ML security analysis challenges through ML-system-specific security analysis. This paper intends to take the initial step to bridge the gap between the existing computer security analysis approaches and an ‘ideal’ ML system security analysis approach.
AB - The past several years have witnessed rapidly increasing use of machine learning (ML) systems in multiple industry sectors. Since security analysis is one of the most essential parts of the real-world ML system protection practice, there is an urgent need to conduct systematic security analysis of ML systems. However, it is widely recognized that the existing security analysis approaches and techniques, which were developed to analyze enterprise (software) systems and networks, are no longer very suitable for analyzing ML systems. In this paper, we seek to present a vision on how to address two unique ML security analysis challenges through ML-system-specific security analysis. This paper intends to take the initial step to bridge the gap between the existing computer security analysis approaches and an ‘ideal’ ML system security analysis approach.
UR - http://www.scopus.com/inward/record.url?scp=85145258152&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85145258152&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-23690-7_7
DO - 10.1007/978-3-031-23690-7_7
M3 - Conference contribution
AN - SCOPUS:85145258152
SN - 9783031236891
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 119
EP - 138
BT - Information Systems Security - 18th International Conference, ICISS 2022, Proceedings
A2 - Badarla, Venkata Ramana
A2 - Nepal, Surya
A2 - Shyamasundar, Rudrapatna K.
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 16 December 2022 through 20 December 2022
ER -