Different Attack and Defense Types for AI Cybersecurity
- Jing Zou,
- ,
- Meikang Qiu(corresponding author)
- Augusta University,
Related Event
Title
Event type
ConferenceDate
08/16/2024 - 08/18/2024Location
Abstract
Artificial Intelligence emerged as a field of study in the mid-20th century, driven by the ambition to develop machines capable of emulating human intelligence and reasoning. However, its rapid advancement has brought forth many cybersecurity challenges, encompassing data security, privacy preservation, and model resilience. Consequently, the field of AI necessitates tailored cybersecurity defense mechanisms and protective technologies to safeguard its integrity. In this paper, we delve into the realm of AI cybersecurity, exploring its prominent areas and delineating various attacks occurring across different phases of the Artificial Intelligence lifecycle. Furthermore, we elucidate defensive strategies against adversarial attacks, encompassing preprocessing techniques, adversarial training methodologies, and distillation methods.
Publication Information
Output type
Original language
English (US)Pages from-to (Number of pages)
Pages 179-192 (14 pages)Publication milestones
- Published - 2024
Publication status
Publisher
Springer Science and Business Media Deutschland GmbH, GermanyPublication series
- Publication series name: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print): 0302-9743
ISSN (Electronic): 1611-3349
Volume: 14886 LNAI
ISBN (Print)
9789819754977Publication IDs
- Scopus: 85200730279
Host publication title
Knowledge Science, Engineering and Management - 17th International Conference, KSEM 2024, ProceedingsHost publication editors
- Cungeng Cao
- Huajun Chen
- Liang Zhao
- Junaid Arshad
- Yonghao Wang
- Taufiq Asyhari
