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| dc.contributor.author | Maaroof, Bestan | |
| dc.date.accessioned | 2025-11-18T21:12:13Z | |
| dc.date.available | 2025-11-18T21:12:13Z | |
| dc.date.issued | 2025 | |
| dc.identifier | c579cdd2-a99e-4fa2-b67a-2e4a78914428 | |
| dc.identifier.uri | https://openlibrary-repo.ecampusontario.ca/jspui/handle/123456789/2446 | |
| dc.description.tableofcontents | Chapter 1: Introduction to Machine Learning Security and Challenges | en_US |
| dc.description.tableofcontents | Chapter 2: Threat Modelling | en_US |
| dc.description.tableofcontents | Chapter 3: Evasion Attack (Adversarial Examples) | en_US |
| dc.description.tableofcontents | Chapter 4: Poisoning Attack and Mitigations | en_US |
| dc.description.tableofcontents | Chapter 5: Backdoor Attacks | en_US |
| dc.description.tableofcontents | Chapter 6: Privacy Attack | en_US |
| dc.language.iso | eng | en_US |
| dc.publisher | Fanshawe College | en_US |
| dc.relation.isformatof | https://ecampusontario.pressbooks.pub/securemachinelearning/ | en_US |
| dc.rights | CC BY-NC-SA | https://creativecommons.org/licenses/by-nc-sa/4.0/ | en_US |
| dc.title | Winning the battle for secure ML | en_US |
| dc.type | Book | en_US |
| dcterms.accessRights | Open Access | en_US |
| dcterms.educationLevel | College | en_US |
| dcterms.educationLevel | University - Undergraduate | en_US |
| dc.identifier.slug | https://openlibrary.ecampusontario.ca/catalogue/item/?id=c579cdd2-a99e-4fa2-b67a-2e4a78914428 | |
| ecO-OER.Adopted | No | en_US |
| ecO-OER.AncillaryMaterial | No | en_US |
| ecO-OER.InstitutionalAffiliation | Fanshawe College | en_US |
| ecO-OER.ISNI | 0000 0001 0487 5961 | en_US |
| ecO-OER.Reviewed | No | en_US |
| ecO-OER.AccessibilityStatement | Yes | en_US |
| ecO-OER.AccessibilityURI | https://ecampusontario.pressbooks.pub/securemachinelearning/front-matter/about-this-book/ | |
| ecO-OER.CourseTitle | Fanshawe College, Machine Learning Security (INFO-6149) | en_US |
| lrmi.learningResourceType | Learning Resource - Textbook | en_US |
| ecO-OER.POD.compatible | No | en_US |
| dc.description.abstract | This book provides a comprehensive yet methodical understanding of securing today's AI systems. It covers vulnerabilities throughout the complete machine learning life cycle from data collection, to training, and deployment and inference, as well as presents practical methods for mitigating the most harmful threats. By integrating theoretical foundations, practical case studies, and recent research, the book covers essential topics including threat modelling, adversarial attacks, poisoning attacks, and privacy breaches. | en_US |
| dc.subject.other | Technology | en_US |
| ecO-OER.ItemType | Textbook | en_US |
| ecO-OER.ItemType | Learning Resource | en_US |
| ecO-OER.ItemType | Instructional Object | en_US |
| ecO-OER.MediaFormat | EPUB | en_US |
| ecO-OER.MediaFormat | en_US |
