Implications of Artificial Intelligence for Cybersecurity
Implications of Artificial Intelligence for Cybersecurity

Author: National Academies of Sciences, Engineering, and Medicine

Publisher: National Academies Press

Published: 2020-01-27

Total Pages: 99

ISBN-13: 0309494508

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In recent years, interest and progress in the area of artificial intelligence (AI) and machine learning (ML) have boomed, with new applications vigorously pursued across many sectors. At the same time, the computing and communications technologies on which we have come to rely present serious security concerns: cyberattacks have escalated in number, frequency, and impact, drawing increased attention to the vulnerabilities of cyber systems and the need to increase their security. In the face of this changing landscape, there is significant concern and interest among policymakers, security practitioners, technologists, researchers, and the public about the potential implications of AI and ML for cybersecurity. The National Academies of Sciences, Engineering, and Medicine convened a workshop on March 12-13, 2019 to discuss and explore these concerns. This publication summarizes the presentations and discussions from the workshop.

Artificial Intelligence for Cyber Security: Methods, Issues and Possible Horizons or Opportunities
Artificial Intelligence for Cyber Security: Methods, Issues and Possible Horizons or Opportunities

Author: Sanjay Misra

Publisher: Springer Nature

Published: 2021-05-31

Total Pages: 467

ISBN-13: 3030722368

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This book provides stepwise discussion, exhaustive literature review, detailed analysis and discussion, rigorous experimentation results (using several analytics tools), and an application-oriented approach that can be demonstrated with respect to data analytics using artificial intelligence to make systems stronger (i.e., impossible to breach). We can see many serious cyber breaches on Government databases or public profiles at online social networking in the recent decade. Today artificial intelligence or machine learning is redefining every aspect of cyber security. From improving organizations’ ability to anticipate and thwart breaches, protecting the proliferating number of threat surfaces with Zero Trust Security frameworks to making passwords obsolete, AI and machine learning are essential to securing the perimeters of any business. The book is useful for researchers, academics, industry players, data engineers, data scientists, governmental organizations, and non-governmental organizations.

Hands-On Artificial Intelligence for Cybersecurity
Hands-On Artificial Intelligence for Cybersecurity

Author: Alessandro Parisi

Publisher: Packt Publishing Ltd

Published: 2019-08-02

Total Pages: 331

ISBN-13: 1789805171

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Build smart cybersecurity systems with the power of machine learning and deep learning to protect your corporate assets Key FeaturesIdentify and predict security threats using artificial intelligenceDevelop intelligent systems that can detect unusual and suspicious patterns and attacksLearn how to test the effectiveness of your AI cybersecurity algorithms and toolsBook Description Today's organizations spend billions of dollars globally on cybersecurity. Artificial intelligence has emerged as a great solution for building smarter and safer security systems that allow you to predict and detect suspicious network activity, such as phishing or unauthorized intrusions. This cybersecurity book presents and demonstrates popular and successful AI approaches and models that you can adapt to detect potential attacks and protect your corporate systems. You'll learn about the role of machine learning and neural networks, as well as deep learning in cybersecurity, and you'll also learn how you can infuse AI capabilities into building smart defensive mechanisms. As you advance, you'll be able to apply these strategies across a variety of applications, including spam filters, network intrusion detection, botnet detection, and secure authentication. By the end of this book, you'll be ready to develop intelligent systems that can detect unusual and suspicious patterns and attacks, thereby developing strong network security defenses using AI. What you will learnDetect email threats such as spamming and phishing using AICategorize APT, zero-days, and polymorphic malware samplesOvercome antivirus limits in threat detectionPredict network intrusions and detect anomalies with machine learningVerify the strength of biometric authentication procedures with deep learningEvaluate cybersecurity strategies and learn how you can improve themWho this book is for If you’re a cybersecurity professional or ethical hacker who wants to build intelligent systems using the power of machine learning and AI, you’ll find this book useful. Familiarity with cybersecurity concepts and knowledge of Python programming is essential to get the most out of this book.

Machine Learning and Security
Machine Learning and Security

Author: Clarence Chio

Publisher: "O'Reilly Media, Inc."

Published: 2018-01-26

Total Pages: 394

ISBN-13: 1491979852

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Can machine learning techniques solve our computer security problems and finally put an end to the cat-and-mouse game between attackers and defenders? Or is this hope merely hype? Now you can dive into the science and answer this question for yourself. With this practical guide, you’ll explore ways to apply machine learning to security issues such as intrusion detection, malware classification, and network analysis. Machine learning and security specialists Clarence Chio and David Freeman provide a framework for discussing the marriage of these two fields, as well as a toolkit of machine-learning algorithms that you can apply to an array of security problems. This book is ideal for security engineers and data scientists alike. Learn how machine learning has contributed to the success of modern spam filters Quickly detect anomalies, including breaches, fraud, and impending system failure Conduct malware analysis by extracting useful information from computer binaries Uncover attackers within the network by finding patterns inside datasets Examine how attackers exploit consumer-facing websites and app functionality Translate your machine learning algorithms from the lab to production Understand the threat attackers pose to machine learning solutions

Generative AI and Implications for Ethics, Security, and Data Management
Generative AI and Implications for Ethics, Security, and Data Management

Author: Gomathi Sankar, Jeganathan

Publisher: IGI Global

Published: 2024-08-21

Total Pages: 468

ISBN-13:

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As generative AI rapidly advances with the field of artificial intelligence, its presence poses significant ethical, security, and data management challenges. While this technology encourages innovation across various industries, ethical concerns regarding the potential misuse of AI-generated content for misinformation or manipulation may arise. The risks of AI-generated deepfakes and cyberattacks demand more research into effective security tactics. The supervision of datasets required to train generative AI models raises questions about privacy, consent, and responsible data management. As generative AI evolves, further research into the complex issues regarding its potential is required to safeguard ethical values and security of people’s data. Generative AI and Implications for Ethics, Security, and Data Management explores the implications of generative AI across various industries who may use the tool for improved organizational development. The security and data management benefits of generative AI are outlined, while examining the topic within the lens of ethical and social impacts. This book covers topics such as cybersecurity, digital technology, and cloud storage, and is a useful resource for computer engineers, IT professionals, technicians, sociologists, healthcare workers, researchers, scientists, and academicians.

Artificial Intelligence and Cybersecurity
Artificial Intelligence and Cybersecurity

Author: Ishaani Priyadarshini

Publisher: CRC Press

Published: 2022-02-04

Total Pages: 222

ISBN-13: 1000530639

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Artificial intelligence and cybersecurity are two emerging fields that have made phenomenal contributions toward technological advancement. As cyber-attacks increase, there is a need to identify threats and thwart attacks. This book incorporates recent developments that artificial intelligence brings to the cybersecurity world. Artificial Intelligence and Cybersecurity: Advances and Innovations provides advanced system implementation for Smart Cities using artificial intelligence. It addresses the complete functional framework workflow and explores basic and high-level concepts. The book is based on the latest technologies covering major challenges, issues and advances, and discusses intelligent data management and automated systems. This edited book provides a premier interdisciplinary platform for researchers, practitioners and educators. It presents and discusses the most recent innovations, trends and concerns as well as practical challenges and solutions adopted in the fields of artificial intelligence and cybersecurity.

The CISO’s Next Frontier
The CISO’s Next Frontier

Author: Raj Badhwar

Publisher: Springer Nature

Published: 2021-08-05

Total Pages: 398

ISBN-13: 3030753549

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This book provides an advanced understanding of cyber threats as well as the risks companies are facing. It includes a detailed analysis of many technologies and approaches important to decreasing, mitigating or remediating those threats and risks. Cyber security technologies discussed in this book are futuristic and current. Advanced security topics such as secure remote work, data security, network security, application and device security, cloud security, and cyber risk and privacy are presented in this book. At the end of every chapter, an evaluation of the topic from a CISO’s perspective is provided. This book also addresses quantum computing, artificial intelligence and machine learning for cyber security The opening chapters describe the power and danger of quantum computing, proposing two solutions for protection from probable quantum computer attacks: the tactical enhancement of existing algorithms to make them quantum-resistant, and the strategic implementation of quantum-safe algorithms and cryptosystems. The following chapters make the case for using supervised and unsupervised AI/ML to develop predictive, prescriptive, cognitive and auto-reactive threat detection, mitigation, and remediation capabilities against advanced attacks perpetrated by sophisticated threat actors, APT and polymorphic/metamorphic malware. CISOs must be concerned about current on-going sophisticated cyber-attacks, and can address them with advanced security measures. The latter half of this book discusses some current sophisticated cyber-attacks and available protective measures enabled by the advancement of cybersecurity capabilities in various IT domains. Chapters 6-10 discuss secure remote work; chapters 11-17, advanced data security paradigms; chapters 18-28, Network Security; chapters 29-35, application and device security; chapters 36-39, Cloud security; and chapters 40-46 organizational cyber risk measurement and event probability. Security and IT engineers, administrators and developers, CIOs, CTOs, CISOs, and CFOs will want to purchase this book. Risk personnel, CROs, IT and Security Auditors as well as security researchers and journalists will also find this useful.

Designing Secure Software
Designing Secure Software

Author: Loren Kohnfelder

Publisher: No Starch Press

Published: 2021-12-21

Total Pages: 330

ISBN-13: 1718501935

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What every software professional should know about security. Designing Secure Software consolidates Loren Kohnfelder’s more than twenty years of experience into a concise, elegant guide to improving the security of technology products. Written for a wide range of software professionals, it emphasizes building security into software design early and involving the entire team in the process. The book begins with a discussion of core concepts like trust, threats, mitigation, secure design patterns, and cryptography. The second part, perhaps this book’s most unique and important contribution to the field, covers the process of designing and reviewing a software design with security considerations in mind. The final section details the most common coding flaws that create vulnerabilities, making copious use of code snippets written in C and Python to illustrate implementation vulnerabilities. You’ll learn how to: • Identify important assets, the attack surface, and the trust boundaries in a system • Evaluate the effectiveness of various threat mitigation candidates • Work with well-known secure coding patterns and libraries • Understand and prevent vulnerabilities like XSS and CSRF, memory flaws, and more • Use security testing to proactively identify vulnerabilities introduced into code • Review a software design for security flaws effectively and without judgment Kohnfelder’s career, spanning decades at Microsoft and Google, introduced numerous software security initiatives, including the co-creation of the STRIDE threat modeling framework used widely today. This book is a modern, pragmatic consolidation of his best practices, insights, and ideas about the future of software.

Trustworthy AI
Trustworthy AI

Author: Beena Ammanath

Publisher: John Wiley & Sons

Published: 2022-03-15

Total Pages: 230

ISBN-13: 1119867959

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An essential resource on artificial intelligence ethics for business leaders In Trustworthy AI, award-winning executive Beena Ammanath offers a practical approach for enterprise leaders to manage business risk in a world where AI is everywhere by understanding the qualities of trustworthy AI and the essential considerations for its ethical use within the organization and in the marketplace. The author draws from her extensive experience across different industries and sectors in data, analytics and AI, the latest research and case studies, and the pressing questions and concerns business leaders have about the ethics of AI. Filled with deep insights and actionable steps for enabling trust across the entire AI lifecycle, the book presents: In-depth investigations of the key characteristics of trustworthy AI, including transparency, fairness, reliability, privacy, safety, robustness, and more A close look at the potential pitfalls, challenges, and stakeholder concerns that impact trust in AI application Best practices, mechanisms, and governance considerations for embedding AI ethics in business processes and decision making Written to inform executives, managers, and other business leaders, Trustworthy AI breaks new ground as an essential resource for all organizations using AI.