1 option
Security and Artificial Intelligence : A Crossdisciplinary Approach / edited by Lejla Batina, Thomas Bäck, Ileana Buhan, Stjepan Picek.
- Format:
- Book
- Series:
- Computer Science (SpringerNature-11645)
- Lecture notes in computer science 1611-3349 ; 13049
- Lecture Notes in Computer Science, 1611-3349 ; 13049
- Language:
- English
- Subjects (All):
- Data protection.
- Artificial intelligence.
- Computer networks.
- Social sciences-Data processing.
- Application software.
- Data and Information Security.
- Artificial Intelligence.
- Computer Communication Networks.
- Computer Application in Social and Behavioral Sciences.
- Computer and Information Systems Applications.
- Local Subjects:
- Data and Information Security.
- Artificial Intelligence.
- Computer Communication Networks.
- Computer Application in Social and Behavioral Sciences.
- Computer and Information Systems Applications.
- Physical Description:
- 1 online resource (X, 361 pages) : 43 illustrations, 28 illustrations in color.
- Edition:
- 1st ed. 2022.
- Contained In:
- Springer Nature eBook
- Place of Publication:
- Cham : Springer International Publishing : Imprint: Springer, 2022.
- System Details:
- text file PDF
- Summary:
- AI has become an emerging technology to assess security and privacy, with many challenges and potential solutions at the algorithm, architecture, and implementation levels. So far, research on AI and security has looked at subproblems in isolation but future solutions will require sharing of experience and best practice in these domains. The editors of this State-of-the-Art Survey invited a cross-disciplinary team of researchers to a Lorentz workshop in 2019 to improve collaboration in these areas. Some contributions were initiated at the event, others were developed since through further invitations, editing, and cross-reviewing. This contributed book contains 14 invited chapters that address side-channel attacks and fault injection, cryptographic primitives, adversarial machine learning, and intrusion detection. The chapters were evaluated based on their significance, technical quality, and relevance to the topics of security and AI, and each submission was reviewed in single-blind mode and revised. .
- Contents:
- AI for Cryptography
- Artificial Intelligence for the Design of Symmetric Cryptographic Primitives
- Traditional Machine Learning Methods for Side-Channel Analysis
- Deep Learning on Side-Channel Analysis
- Artificial Neural Networks and Fault Injection Attacks
- Physically Unclonable Functions and AI: Two Decades of Marriage
- AI for Authentication and Privacy
- Privacy-Preserving Machine Learning using Cryptography
- Machine Learning Meets Data Modification: the Potential of Pre-processing for Privacy Enhancement
- AI for Biometric Authentication Systems
- Machine Learning and Deep Learning for Hardware Fingerprinting. - AI for Intrusion Detection
- Intelligent Malware Defenses
- Open-World Network Intrusion Detection
- Security of AI
- Adversarial Machine Learning
- Deep Learning Backdoors. - On Implementation-level Security of Edge-based Machine Learning Models.
- Other Format:
- Printed edition:
- ISBN:
- 978-3-030-98795-4
- 9783030987954
- Access Restriction:
- Restricted for use by site license.
The Penn Libraries is committed to describing library materials using current, accurate, and responsible language. If you discover outdated or inaccurate language, please fill out this feedback form to report it and suggest alternative language.