001441943 000__ 03880cam\a2200565Ii\4500
001441943 001__ 1441943
001441943 003__ OCoLC
001441943 005__ 20230309003350.0
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001441943 008__ 220413s2021\\\\si\a\\\\ob\\\\000\0\eng\d
001441943 019__ $$a1309133235$$a1309867516$$a1309959418$$a1310332353
001441943 020__ $$a9789811661860$$q(electronic bk.)
001441943 020__ $$a9811661863$$q(electronic bk.)
001441943 020__ $$z9811661855$$q(print)
001441943 020__ $$z9789811661853$$q(print)
001441943 0247_ $$a10.1007/978-981-16-6186-0$$2doi
001441943 035__ $$aSP(OCoLC)1310677358
001441943 040__ $$aGW5XE$$beng$$erda$$epn$$cGW5XE$$dEBLCP$$dYDX$$dOCLCO$$dOCLCF$$dOCLCQ
001441943 049__ $$aISEA
001441943 050_4 $$aQA76.9.A25
001441943 08204 $$a005.8$$223
001441943 24500 $$aDeep learning for security and privacy preservation in IoT /$$cAaisha Makkar, Neeraj Kumar, editors.
001441943 264_1 $$aSingapore :$$bSpringer,$$c2021.
001441943 300__ $$a1 online resource (1 volume) :$$billustrations (black and white, and color).
001441943 336__ $$atext$$btxt$$2rdacontent
001441943 337__ $$acomputer$$bc$$2rdamedia
001441943 338__ $$aonline resource$$bcr$$2rdacarrier
001441943 4901_ $$aSignals and communication technology
001441943 504__ $$aIncludes bibliographical references.
001441943 5050_ $$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.
001441943 506__ $$aAccess limited to authorized users.
001441943 520__ $$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.
001441943 588__ $$aDescription based on print version record.
001441943 650_0 $$aComputer networks$$xSecurity measures.
001441943 650_0 $$aInternet of things$$xSecurity measures.
001441943 650_0 $$aDeep learning (Machine learning)
001441943 650_6 $$aRéseaux d'ordinateurs$$xSécurité$$xMesures.
001441943 650_6 $$aInternet des objets$$xSécurité$$xMesures.
001441943 655_0 $$aElectronic books.
001441943 7001_ $$aMakkar, Aaisha,$$eeditor.
001441943 7001_ $$aKumar, Neeraj$$c(Computer scientist),$$eeditor.
001441943 77608 $$iPrint version:$$aMAKKAR, AAISHA. KUMAR, NEERAJ.$$tDEEP LEARNING FOR SECURITY AND PRIVACY PRESERVATION IN IOT.$$d[Place of publication not identified] : SPRINGER VERLAG, SINGAPOR, 2022$$z9811661855$$w(OCoLC)1264139321
001441943 830_0 $$aSignals and communication technology.
001441943 852__ $$bebk
001441943 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-981-16-6186-0$$zOnline Access$$91397441.1
001441943 909CO $$ooai:library.usi.edu:1441943$$pGLOBAL_SET
001441943 980__ $$aBIB
001441943 980__ $$aEBOOK
001441943 982__ $$aEbook
001441943 983__ $$aOnline
001441943 994__ $$a92$$bISE