000 | 03457nam a22005775i 4500 | ||
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001 | 978-981-19-8692-5 | ||
003 | DE-He213 | ||
005 | 20240423125406.0 | ||
007 | cr nn 008mamaa | ||
008 | 230310s2023 si | s |||| 0|eng d | ||
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024 | 7 |
_a10.1007/978-981-19-8692-5 _2doi |
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050 | 4 | _aQA76.9.A25 | |
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_aUR _2bicssc |
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_aUTN _2bicssc |
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_a005.8 _223 |
100 | 1 |
_aYu, Shui. _eauthor. _0(orcid) _10000-0003-4485-6743 _4aut _4http://id.loc.gov/vocabulary/relators/aut |
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245 | 1 | 0 |
_aSecurity and Privacy in Federated Learning _h[electronic resource] / _cby Shui Yu, Lei Cui. |
250 | _a1st ed. 2023. | ||
264 | 1 |
_aSingapore : _bSpringer Nature Singapore : _bImprint: Springer, _c2023. |
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300 |
_aXII, 133 p. 1 illus. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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347 |
_atext file _bPDF _2rda |
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490 | 1 |
_aDigital Privacy and Security, _x2731-9938 |
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505 | 0 | _aChapter 1. Introduction of Federated Learning -- Chapter 2. Inference Attacks and Counter Attacks in Federated Learning -- Chapter 3. Poisoning Attacks and Counter Attacks in Federated Learning -- Chapter 4. GAN Attacks and Counter Attacks in Federated Learning -- Chapter 5. Differential Privacy in Federated Learning -- Chapter 6. Secure Multi-Party Computation in Federated Learning -- Chapter 7. Secure Data Aggregation in Federated Learning -- Chapter 8. Anonymous Communication and Shuffle Model in Federated Learning -- Chapter 9. The Future Work. | |
520 | _aIn this book, the authors highlight the latest research findings on the security and privacy of federated learning systems. The main attacks and counterattacks in this booming field are presented to readers in connection with inference, poisoning, generative adversarial networks, differential privacy, secure multi-party computation, homomorphic encryption, and shuffle, respectively. The book offers an essential overview for researchers who are new to the field, while also equipping them to explore this “uncharted territory.” For each topic, the authors first present the key concepts, followed by the most important issues and solutions, with appropriate references for further reading. The book is self-contained, and all chapters can be read independently. It offers a valuable resource for master’s students, upper undergraduates, Ph.D. students, and practicing engineers alike. | ||
650 | 0 | _aData protection. | |
650 | 0 |
_aData protection _xLaw and legislation. |
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650 | 0 | _aArtificial intelligence. | |
650 | 1 | 4 | _aData and Information Security. |
650 | 2 | 4 | _aPrivacy. |
650 | 2 | 4 | _aArtificial Intelligence. |
700 | 1 |
_aCui, Lei. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut |
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710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer Nature eBook | |
776 | 0 | 8 |
_iPrinted edition: _z9789811986918 |
776 | 0 | 8 |
_iPrinted edition: _z9789811986932 |
776 | 0 | 8 |
_iPrinted edition: _z9789811986949 |
830 | 0 |
_aDigital Privacy and Security, _x2731-9938 |
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856 | 4 | 0 | _uhttps://doi.org/10.1007/978-981-19-8692-5 |
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912 | _aZDB-2-SXCS | ||
942 | _cSPRINGER | ||
999 |
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