Advances In Malware And Data Driven Network Security
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Advances in Malware and Data-Driven Network Security
Every day approximately three-hundred thousand to four-hundred thousand new malware are registered, many of them being adware and variants of previously known malware. Anti-virus companies and researchers cannot deal with such a deluge of malware – to analyze and build patches. The only way to scale the efforts is to build algorithms to enable machines to analyze malware and classify and cluster them to such a level of granularity that it will enable humans (or machines) to gain critical insights about them and build solutions that are specific enough to detect and thwart existing malware and generic-enough to thwart future variants. Advances in Malware and Data-Driven Network Security comprehensively covers data-driven malware security with an emphasis on using statistical, machine learning, and AI as well as the current trends in ML/statistical approaches to detecting, clustering, and classification of cyber-threats. Providing information on advances in malware and data-driven network security as well as future research directions, it is ideal for graduate students, academicians, faculty members, scientists, software developers, security analysts, computer engineers, programmers, IT specialists, and researchers who are seeking to learn and carry out research in the area of malware and data-driven network security.
Handbook of Research on Cyber Law, Data Protection, and Privacy
The advancement of information and communication technology has led to a multi-dimensional impact in the areas of law, regulation, and governance. Many countries have declared data protection a fundamental right and established reforms of data protection law aimed at modernizing the global regulatory framework. Due to these advancements in policy, the legal domain has to face many challenges at a rapid pace making it essential to study and discuss policies and laws that regulate and monitor these activities and anticipate new laws that should be implemented in order to protect users. The Handbook of Research on Cyber Law, Data Protection, and Privacy focuses acutely on the complex relationships of technology and law both in terms of substantive legal responses to legal, social, and ethical issues arising in connection with growing public engagement with technology and the procedural impacts and transformative potential of technology on traditional and emerging forms of dispute resolution. Covering a range of topics such as artificial intelligence, data protection, and social media, this major reference work is ideal for government officials, policymakers, industry professionals, academicians, scholars, researchers, practitioners, instructors, and students.
Methods, Implementation, and Application of Cyber Security Intelligence and Analytics
Cyber security is a key focus in the modern world as more private information is stored and saved online. In order to ensure vital information is protected from various cyber threats, it is essential to develop a thorough understanding of technologies that can address cyber security challenges. Artificial intelligence has been recognized as an important technology that can be employed successfully in the cyber security sector. Due to this, further study on the potential uses of artificial intelligence is required. Methods, Implementation, and Application of Cyber Security Intelligence and Analytics discusses critical artificial intelligence technologies that are utilized in cyber security and considers various cyber security issues and their optimal solutions supported by artificial intelligence. Covering a range of topics such as malware, smart grid, data breachers, and machine learning, this major reference work is ideal for security analysts, cyber security specialists, data analysts, security professionals, computer scientists, government officials, researchers, scholars, academicians, practitioners, instructors, and students.