Contributions Presented at The International Conference on Computing, Communication, Cybersecurity and AI, July 3–4, 2024, London, UK : The C3AI 2024 / edited by Nitin Naik, Paul Jenkins, Shaligram Prajapat, Paul Grace.

Format:

Book

Author/Creator:

Naik, Nitin.

Contributor:

Jenkins, Paul.

Prajapat, Shaligram.

Grace, Paul.

Series:

Lecture Notes in Networks and Systems, 2367-3389 ; 884

Language:

English

Subjects (All):

Computational intelligence.

Artificial intelligence.

Computational Intelligence.

Artificial Intelligence.

Local Subjects:

Computational Intelligence.

Artificial Intelligence.

Physical Description:

1 online resource (826 pages)

Edition:

1st ed. 2024.

Place of Publication:

Cham : Springer Nature Switzerland : Imprint: Springer, 2024.

Summary:

This 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.

Contents:

Security 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.

Notes:

Description based on publisher supplied metadata and other sources.

ISBN:

9783031744433

3031744438

OCLC:

1482268517