Constructing An Ethical Hacking Knowledge Base For Threat Awareness And Prevention
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Constructing an Ethical Hacking Knowledge Base for Threat Awareness and Prevention
Author: Dhavale, Sunita Vikrant
language: en
Publisher: IGI Global
Release Date: 2018-12-14
In recent decades there has been incredible growth in the use of various internet applications by individuals and organizations who store sensitive information online on different servers. This greater reliance of organizations and individuals on internet technologies and applications increases the threat space and poses several challenges for implementing and maintaining cybersecurity practices. Constructing an Ethical Hacking Knowledge Base for Threat Awareness and Prevention provides innovative insights into how an ethical hacking knowledge base can be used for testing and improving the network and system security posture of an organization. It is critical for each individual and institute to learn hacking tools and techniques that are used by dangerous hackers in tandem with forming a team of ethical hacking professionals to test their systems effectively. Highlighting topics including cyber operations, server security, and network statistics, this publication is designed for technical experts, students, academicians, government officials, and industry professionals.
Confluence of AI, Machine, and Deep Learning in Cyber Forensics
Developing a knowledge model helps to formalize the difficult task of analyzing crime incidents in addition to preserving and presenting the digital evidence for legal processing. The use of data analytics techniques to collect evidence assists forensic investigators in following the standard set of forensic procedures, techniques, and methods used for evidence collection and extraction. Varieties of data sources and information can be uniquely identified, physically isolated from the crime scene, protected, stored, and transmitted for investigation using AI techniques. With such large volumes of forensic data being processed, different deep learning techniques may be employed. Confluence of AI, Machine, and Deep Learning in Cyber Forensics contains cutting-edge research on the latest AI techniques being used to design and build solutions that address prevailing issues in cyber forensics and that will support efficient and effective investigations. This book seeks to understand the value of the deep learning algorithm to handle evidence data as well as the usage of neural networks to analyze investigation data. Other themes that are explored include machine learning algorithms that allow machines to interact with the evidence, deep learning algorithms that can handle evidence acquisition and preservation, and techniques in both fields that allow for the analysis of huge amounts of data collected during a forensic investigation. This book is ideally intended for forensics experts, forensic investigators, cyber forensic practitioners, researchers, academicians, and students interested in cyber forensics, computer science and engineering, information technology, and electronics and communication.
Handbook of Research on Trends and Issues in Crime Prevention, Rehabilitation, and Victim Support
A complex and vulnerable contemporary society continually poses new challenges in terms of social conflict, and as crime advances, so must strategies for prevention and rehabilitation. Many facets of crime prevention and rehabilitation of offenders are public activities closely linked to other aspects of the political and social life of a region. The Handbook of Research on Trends and Issues in Crime Prevention, Rehabilitation, and Victim Support is a scholarly publication that examines existing knowledge on crime dynamics and the implementation of crime victims’ rights. Highlighting a wide array of topics such as cyberbullying, predatory crimes, and psychological violence, this book is ideal for criminologists, forensic psychologists, psychiatrists, victim advocates, law enforcement, criminal profilers, crime analysts, therapists, rehabilitation specialists, psychologists, correctional facilities, wardens, government officials, policymakers, academicians, researchers, and students.