Machine learning for cyber agents: attack and defence
The cyber world has been both enhanced and endangered by AI. On the one hand, the performance of many existing security services has been improved, and new tools created. On the other, it entails new cyber threats both through evolved attacking capacities and through its own imperfections and vulner...
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| Main Authors: | , |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Cham, Switzerland
Springer
[2022]
|
| Series: | Advanced sciences and technologies for security applications
|
| Subjects: | |
| Summary: | The cyber world has been both enhanced and endangered by AI. On the one hand, the performance of many existing security services has been improved, and new tools created. On the other, it entails new cyber threats both through evolved attacking capacities and through its own imperfections and vulnerabilities. Moreover, quantum computers are further pushing the boundaries of what is possible, by making machine learning cyber agents faster and smarter.With the abundance of often-confusing information and lack of trust in the diverse applications of AI-based technologies, it is essential to have a book that can explain, from a cyber security standpoint, why and at what stage the emerging, powerful technology of machine learning can and should be mistrusted, and how to benefit from it while avoiding potentially disastrous consequences. In addition, this book sheds light on another highly sensitive area – the application of machine learning for offensive purposes, an aspect that is widely misunderstood, under-represented in the academic literature and requires immediate expert attention |
| Item Description: | 1. Introduction.- 2. Understanding Machine Learning.- 3. Defence.- 4. Attack.- 5. Feasibility and Misconceptions.- 6. International resonance.- 7. Prospects.- 8. Conclusion. |
| Physical Description: | xv, 227 Seiten Illustrationen 379 grams |
| ISBN: | 9783030915872 |
Staff View
MARC
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| 500 | |a 1. Introduction.- 2. Understanding Machine Learning.- 3. Defence.- 4. Attack.- 5. Feasibility and Misconceptions.- 6. International resonance.- 7. Prospects.- 8. Conclusion. | ||
| 520 | |a The cyber world has been both enhanced and endangered by AI. On the one hand, the performance of many existing security services has been improved, and new tools created. On the other, it entails new cyber threats both through evolved attacking capacities and through its own imperfections and vulnerabilities. Moreover, quantum computers are further pushing the boundaries of what is possible, by making machine learning cyber agents faster and smarter.With the abundance of often-confusing information and lack of trust in the diverse applications of AI-based technologies, it is essential to have a book that can explain, from a cyber security standpoint, why and at what stage the emerging, powerful technology of machine learning can and should be mistrusted, and how to benefit from it while avoiding potentially disastrous consequences. In addition, this book sheds light on another highly sensitive area – the application of machine learning for offensive purposes, an aspect that is widely misunderstood, under-represented in the academic literature and requires immediate expert attention | ||
| 650 | 4 | |a Data protection | |
| 650 | 4 | |a Computer networks—Security measures | |
| 650 | 4 | |a Security systems | |
| 650 | 4 | |a Machine learning | |
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| id | DE-604.BV048851506 |
| illustrated | Illustrated |
| index_date | 2024-07-03T21:40:18Z |
| indexdate | 2024-07-10T09:47:49Z |
| institution | BVB |
| isbn | 9783030915872 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-034116770 |
| oclc_num | 1376413631 |
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| owner | DE-29T |
| owner_facet | DE-29T |
| physical | xv, 227 Seiten Illustrationen 379 grams |
| publishDate | 2022 |
| publishDateSearch | 2022 |
| publishDateSort | 2022 |
| publisher | Springer |
| record_format | marc |
| series2 | Advanced sciences and technologies for security applications |
| spelling | Abaimov, Stanislav 1989- Verfasser (DE-588)117973985X aut Machine learning for cyber agents attack and defence Stanislav Abaimov, Maurizio Martellini Cham, Switzerland Springer [2022] xv, 227 Seiten Illustrationen 379 grams txt rdacontent n rdamedia nc rdacarrier Advanced sciences and technologies for security applications 1. Introduction.- 2. Understanding Machine Learning.- 3. Defence.- 4. Attack.- 5. Feasibility and Misconceptions.- 6. International resonance.- 7. Prospects.- 8. Conclusion. The cyber world has been both enhanced and endangered by AI. On the one hand, the performance of many existing security services has been improved, and new tools created. On the other, it entails new cyber threats both through evolved attacking capacities and through its own imperfections and vulnerabilities. Moreover, quantum computers are further pushing the boundaries of what is possible, by making machine learning cyber agents faster and smarter.With the abundance of often-confusing information and lack of trust in the diverse applications of AI-based technologies, it is essential to have a book that can explain, from a cyber security standpoint, why and at what stage the emerging, powerful technology of machine learning can and should be mistrusted, and how to benefit from it while avoiding potentially disastrous consequences. In addition, this book sheds light on another highly sensitive area – the application of machine learning for offensive purposes, an aspect that is widely misunderstood, under-represented in the academic literature and requires immediate expert attention Data protection Computer networks—Security measures Security systems Machine learning Hardcover, Softcover / Informatik, EDV/Informatik Martellini, Maurizio 1953- Verfasser (DE-588)1179739744 aut Erscheint auch als Online-Ausgabe 978-3-030-91585-8 |
| spellingShingle | Abaimov, Stanislav 1989- Martellini, Maurizio 1953- Machine learning for cyber agents attack and defence Data protection Computer networks—Security measures Security systems Machine learning |
| title | Machine learning for cyber agents attack and defence |
| title_auth | Machine learning for cyber agents attack and defence |
| title_exact_search | Machine learning for cyber agents attack and defence |
| title_exact_search_txtP | Machine learning for cyber agents attack and defence |
| title_full | Machine learning for cyber agents attack and defence Stanislav Abaimov, Maurizio Martellini |
| title_fullStr | Machine learning for cyber agents attack and defence Stanislav Abaimov, Maurizio Martellini |
| title_full_unstemmed | Machine learning for cyber agents attack and defence Stanislav Abaimov, Maurizio Martellini |
| title_short | Machine learning for cyber agents |
| title_sort | machine learning for cyber agents attack and defence |
| title_sub | attack and defence |
| topic | Data protection Computer networks—Security measures Security systems Machine learning |
| topic_facet | Data protection Computer networks—Security measures Security systems Machine learning |
| work_keys_str_mv | AT abaimovstanislav machinelearningforcyberagentsattackanddefence AT martellinimaurizio machinelearningforcyberagentsattackanddefence |