03738nam a22004575i 4500001001800000003000900018005001700027007001500044008004100059020001800100024003500118050000900153072001600162072002300178072001500201245025100216250001800467264006900485300006600554336002600620337002600646338003600672347002400708490006100732505078200793520103801575650003202613650002902645650003202674650002902706700007402735700007602809700008202885700007402967710003403041773002603075776003603101776003603137830006103173856004603234978-3-031-74443-3DE-He21320251030114630.0cr nn 008mamaa241220s2024    sz |    s    |||| 0|eng d  a97830317444337 a10.1007/978-3-031-74443-32doi 4aQ342 7aUYQ2bicssc 7aCOM0040002bisacsh 7aUYQ2thema10aContributions Presented at The International Conference on Computing, Communication, Cybersecurity and AI, July 3–4, 2024, London, UKh[electronic resource] :bThe C3AI 2024 /cedited by Nitin Naik, Paul Jenkins, Shaligram Prajapat, Paul Grace.  a1st ed. 2024. 1aCham :bSpringer Nature Switzerland :bImprint: Springer,c2024.  aIX, 826 p. 335 illus., 280 illus. in color.bonline resource.  atextbtxt2rdacontent  acomputerbc2rdamedia  aonline resourcebcr2rdacarrier  atext filebPDF2rda1 aLecture Notes in Networks and Systems,x2367-3389 ;v8840 aSecurity model for IoT applications IoTSeMo -- DAN Deep Neural Network-based Application Mapping for Optimized Network-on-Chip Design -- Threat Modelling in Virtual Assistant Hub Devices -- Generate Unnoticeable Adversarial Examples on Audio Classification Models with Multi perspective Objectives -- Prior enhanced Semi supervised Federated Learning for IoT Intrusion Detection A Game Theory and Comparative Learning based Approach -- An empirical study on Insider Threats Towards Crime Prevention through Environmental Design CPTED A student case study -- Utilizing Machine Learning and Deep Learning Techniques for the Detection of Distributed Denial of Service DDoS Attacks -- Inspecting software architecture design styles to infer threat models and inform likely attacks.  aThis book offers an in-depth exploration of cutting-edge research across the interconnected fields of computing, communication, cybersecurity, and artificial intelligence. It serves as a comprehensive guide to the technologies shaping our digital world, providing both a profound understanding of these domains and practical strategies for addressing their challenges. The content is drawn from the International Conference on Computing, Communication, Cybersecurity and AI (C3AI 2024), held in London, UK, from July 3 to 4, 2024. The conference attracted 66 submissions from 17 countries, including the USA, UK, Canada, Brazil, India, China, Germany, and Spain. Of these, 47 high-calibre papers were rigorously selected through a meticulous review process, where each paper received three to four reviews to ensure quality and relevance. This book is an essential resource for readers seeking a thorough and timely review of the latest advancements and trends in computing, communication, cybersecurity, and artificial intelligence. 0aComputational intelligence. 0aArtificial intelligence.14aComputational Intelligence.24aArtificial Intelligence.1 aNaik, Nitin.eeditor.4edt4http://id.loc.gov/vocabulary/relators/edt1 aJenkins, Paul.eeditor.4edt4http://id.loc.gov/vocabulary/relators/edt1 aPrajapat, Shaligram.eeditor.4edt4http://id.loc.gov/vocabulary/relators/edt1 aGrace, Paul.eeditor.4edt4http://id.loc.gov/vocabulary/relators/edt2 aSpringerLink (Online service)0 tSpringer Nature eBook08iPrinted edition:z978303174442608iPrinted edition:z9783031744440 0aLecture Notes in Networks and Systems,x2367-3389 ;v88440uhttps://doi.org/10.1007/978-3-031-74443-3