000 | 03673nam a22005775i 4500 | ||
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001 | 978-981-16-6186-0 | ||
003 | DE-He213 | ||
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008 | 220403s2021 si | s |||| 0|eng d | ||
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_a9789811661860 _9978-981-16-6186-0 |
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024 | 7 |
_a10.1007/978-981-16-6186-0 _2doi |
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_aUR _2bicssc |
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_a005.8 _223 |
245 | 1 | 0 |
_aDeep Learning for Security and Privacy Preservation in IoT _h[electronic resource] / _cedited by Aaisha Makkar, Neeraj Kumar. |
250 | _a1st ed. 2021. | ||
264 | 1 |
_aSingapore : _bSpringer Nature Singapore : _bImprint: Springer, _c2021. |
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300 |
_aXII, 179 p. 58 illus., 44 illus. in color. _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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_atext file _bPDF _2rda |
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490 | 1 |
_aSignals and Communication Technology, _x1860-4870 |
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505 | 0 | _aMetamorphosis of Industrial IoT using Deep Leaning -- Deep Learning Models and their Architectures for Computer Vision Applications: A Review -- IoT Data Security with Machine Learning Blockchain: Risks and Countermeasures -- A Review on Cyber Crimes on the Internet of Things -- Deep learning framework for anomaly detection in IoT enabled systems -- Anomaly Detection using Unsupervised Machine Learning Algorithms -- Game Theory Based Privacy Preserving Approach for Collaborative Deep Learning in IoT -- Deep Learning based security preservation of IoT: An industrial machine health monitoring scenario -- Deep learning Models: An Understandable Interpretable Approaches. | |
520 | _aThis book addresses the issues with privacy and security in Internet of things (IoT) networks which are susceptible to cyber-attacks and proposes deep learning-based approaches using artificial neural networks models to achieve a safer and more secured IoT environment. Due to the inadequacy of existing solutions to cover the entire IoT network security spectrum, the book utilizes artificial neural network models, which are used to classify, recognize, and model complex data including images, voice, and text, to enhance the level of security and privacy of IoT. This is applied to several IoT applications which include wireless sensor networks (WSN), meter reading transmission in smart grid, vehicular ad hoc networks (VANET), industrial IoT and connected networks. The book serves as a reference for researchers, academics, and network engineers who want to develop enhanced security and privacy features in the design of IoT systems. | ||
650 | 0 | _aData protection. | |
650 | 0 | _aInternet of things. | |
650 | 0 | _aArtificial intelligence. | |
650 | 1 | 4 | _aData and Information Security. |
650 | 2 | 4 | _aInternet of Things. |
650 | 2 | 4 | _aArtificial Intelligence. |
700 | 1 |
_aMakkar, Aaisha. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt |
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700 | 1 |
_aKumar, Neeraj. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt |
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710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer Nature eBook | |
776 | 0 | 8 |
_iPrinted edition: _z9789811661853 |
776 | 0 | 8 |
_iPrinted edition: _z9789811661877 |
776 | 0 | 8 |
_iPrinted edition: _z9789811661884 |
830 | 0 |
_aSignals and Communication Technology, _x1860-4870 |
|
856 | 4 | 0 | _uhttps://doi.org/10.1007/978-981-16-6186-0 |
912 | _aZDB-2-SCS | ||
912 | _aZDB-2-SXCS | ||
942 | _cSPRINGER | ||
999 |
_c178800 _d178800 |