THE NEXT FRONTIER IN CYBERSECURITY Integrating AI, ML, and Generative AI for Advanced Protection PDF Download
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Author: Dr Sivaraju Kuraku
Publisher: JEC PUBLICATION
ISBN: 9361759825
Category : Architecture
Languages : en
Pages : 175
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Book Description
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Author: Dr Sivaraju Kuraku
Publisher: JEC PUBLICATION
ISBN: 9361759825
Category : Architecture
Languages : en
Pages : 175
Get Book Here
Book Description
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Author: Raj Badhwar
Publisher: Springer Nature
ISBN: 3030753549
Category : Computers
Languages : en
Pages : 398
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Book Description
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.
Author: Keshav Kaushik
Publisher: Springer Nature
ISBN: 9819712491
Category :
Languages : en
Pages : 473
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Book Description
Author: John Sotiropoulos
Publisher:
ISBN: 9781835087985
Category : Computers
Languages : en
Pages : 0
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Book Description
Understand how adversarial attacks work against predictive and generative AI, and learn how to safeguard AI and LLM projects with practical examples leveraging OWASP, MITRE, and NIST Key Features: - Understand the connection between AI and security by learning about adversarial AI attacks - Discover the latest security challenges in adversarial AI by examining GenAI, deepfakes, and LLMs - Implement secure-by-design methods and threat modeling, using standards and MLSecOps to safeguard AI systems - Purchase of the print or Kindle book includes a free PDF eBook Book Description: Adversarial attacks trick AI systems with malicious data, creating new security risks by exploiting how AI learns. This challenges cybersecurity as it forces us to defend against a whole new kind of threat. This book demystifies adversarial attacks and equips cybersecurity professionals with the skills to secure AI technologies, moving beyond research hype or business-as-usual strategies. The strategy-based book is a comprehensive guide to AI security, presenting a structured approach with practical examples to identify and counter adversarial attacks. This book goes beyond a random selection of threats and consolidates recent research and industry standards, incorporating taxonomies from MITRE, NIST, and OWASP. Next, a dedicated section introduces a secure-by-design AI strategy with threat modeling to demonstrate risk-based defenses and strategies, focusing on integrating MLSecOps and LLMOps into security systems. To gain deeper insights, you'll cover examples of incorporating CI, MLOps, and security controls, including open-access LLMs and ML SBOMs. Based on the classic NIST pillars, the book provides a blueprint for maturing enterprise AI security, discussing the role of AI security in safety and ethics as part of Trustworthy AI. By the end of this book, you'll be able to develop, deploy, and secure AI systems effectively. What You Will Learn: - Understand poisoning, evasion, and privacy attacks and how to mitigate them - Discover how GANs can be used for attacks and deepfakes - Explore how LLMs change security, prompt injections, and data exposure - Master techniques to poison LLMs with RAG, embeddings, and fine-tuning - Explore supply-chain threats and the challenges of open-access LLMs - Implement MLSecOps with CIs, MLOps, and SBOMs Who this book is for: This book tackles AI security from both angles - offense and defense. AI builders (developers and engineers) will learn how to create secure systems, while cybersecurity professionals, such as security architects, analysts, engineers, ethical hackers, penetration testers, and incident responders will discover methods to combat threats and mitigate risks posed by attackers. The book also provides a secure-by-design approach for leaders to build AI with security in mind. To get the most out of this book, you'll need a basic understanding of security, ML concepts, and Python. Table of Contents - Getting Started with AI - Building Our Adversarial Playground - Security and Adversarial AI - Poisoning Attacks - Model Tampering with Trojan Horses and Model Reprogramming - Supply Chain Attacks and Adversarial AI - Evasion Attacks against Deployed AI - Privacy Attacks - Stealing Models - Privacy Attacks - Stealing Data - Privacy-Preserving AI - Generative AI - A New Frontier - Weaponizing GANs for Deepfakes and Adversarial Attacks - LLM Foundations for Adversarial AI - Adversarial Attacks with Prompts - Poisoning Attacks and LLMs - Advanced Generative AI Scenarios - Secure by Design and Trustworthy AI - AI Security with MLSecOps - Maturing AI Security
Author: Marwan Omar
Publisher: Engineering Science Reference
ISBN:
Category : Computers
Languages : en
Pages : 0
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Book Description
In the rapidly evolving digital landscape, the importance of cybersecurity has never been more critical. With the increasing sophistication of cyber threats, traditional security measures often fall short in providing adequate protection. Cyber artificial intelligence (AI) offers advanced capabilities to detect, prevent, and respond to attacks in real time. As cyber threats continue to grow in complexity and frequency, the integration of AI into cybersecurity frameworks is not just advantageous but essential for maintaining robust and resilient defenses. Redefining Security With Cyber AI delves into the profound transformation of security paradigms brought about by the advent of AI. This book explores the intricate dance between the ever-expanding frontiers of digital technology and the AI-driven mechanisms that aim to safeguard them. Covering topics such as artificial neural networks, intrusion detection, and large language models, this book is an excellent resource for cybersecurity professionals, AI and machine learning researchers, IT executives and managers, policy makers and regulators, postgraduate students and educators, academicians, and more.
Author: Aaron Cordova
Publisher: "O'Reilly Media, Inc."
ISBN: 1491946938
Category : Computers
Languages : en
Pages : 552
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Book Description
Get up to speed on Apache Accumulo, the flexible, high-performance key/value store created by the National Security Agency (NSA) and based on Google’s BigTable data storage system. Written by former NSA team members, this comprehensive tutorial and reference covers Accumulo architecture, application development, table design, and cell-level security. With clear information on system administration, performance tuning, and best practices, this book is ideal for developers seeking to write Accumulo applications, administrators charged with installing and maintaining Accumulo, and other professionals interested in what Accumulo has to offer. You will find everything you need to use this system fully. Get a high-level introduction to Accumulo’s architecture and data model Take a rapid tour through single- and multiple-node installations, data ingest, and query Learn how to write Accumulo applications for several use cases, based on examples Dive into Accumulo internals, including information not available in the documentation Get detailed information for installing, administering, tuning, and measuring performance Learn best practices based on successful implementations in the field Find answers to common questions that every new Accumulo user asks
Author: Söhnke M. Bartram
Publisher: CFA Institute Research Foundation
ISBN: 195292703X
Category : Business & Economics
Languages : en
Pages : 95
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Book Description
Artificial intelligence (AI) has grown in presence in asset management and has revolutionized the sector in many ways. It has improved portfolio management, trading, and risk management practices by increasing efficiency, accuracy, and compliance. In particular, AI techniques help construct portfolios based on more accurate risk and return forecasts and more complex constraints. Trading algorithms use AI to devise novel trading signals and execute trades with lower transaction costs. AI also improves risk modeling and forecasting by generating insights from new data sources. Finally, robo-advisors owe a large part of their success to AI techniques. Yet the use of AI can also create new risks and challenges, such as those resulting from model opacity, complexity, and reliance on data integrity.
Author: Introbooks
Publisher:
ISBN:
Category :
Languages : en
Pages : 50
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Book Description
In these highly competitive times and with so many technological advancements, it is impossible for any industry to remain isolated and untouched by innovations. In this era of digital economy, the banking sector cannot exist and operate without the various digital tools offered by the ever new innovations happening in the field of Artificial Intelligence (AI) and its sub-set technologies. New technologies have enabled incredible progression in the finance industry. Artificial Intelligence (AI) and Machine Learning (ML) have provided the investors and customers with more innovative tools, new types of financial products and a new potential for growth.According to Cathy Bessant (the Chief Operations and Technology Officer, Bank of America), AI is not just a technology discussion. It is also a discussion about data and how it is used and protected. She says, "In a world focused on using AI in new ways, we're focused on using it wisely and responsibly."
Author: World Intellectual Property Organization
Publisher: WIPO
ISBN: 9280530070
Category : Law
Languages : en
Pages : 156
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Book Description
The first report in a new flagship series, WIPO Technology Trends, aims to shed light on the trends in innovation in artificial intelligence since the field first developed in the 1950s.
Author: National Science and Technology Council
Publisher: Createspace Independent Publishing Platform
ISBN: 9781539773153
Category :
Languages : en
Pages : 48
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Book Description
Artificial intelligence (AI) is a transformative technology that holds promise for tremendous societal and economic benefit. AI has the potential to revolutionize how we live, work, learn, discover, and communicate. AI research can further our national priorities, including increased economic prosperity, improved educational opportunities and quality of life, and enhanced national and homeland security. Because of these potential benefits, the U.S. government has invested in AI research for many years. Yet, as with any significant technology in which the Federal government has interest, there are not only tremendous opportunities but also a number of considerations that must be taken into account in guiding the overall direction of Federally-funded R&D in AI. On May 3, 2016, the Administration announced the formation of a new NSTC Subcommittee on Machine Learning and Artificial intelligence, to help coordinate Federal activity in AI.1 This Subcommittee, on June 15, 2016, directed the Subcommittee on Networking and Information Technology Research and Development (NITRD) to create a National Artificial Intelligence Research and Development Strategic Plan. A NITRD Task Force on Artificial Intelligence was then formed to define the Federal strategic priorities for AI R&D, with particular attention on areas that industry is unlikely to address. This National Artificial Intelligence R&D Strategic Plan establishes a set of objectives for Federally-funded AI research, both research occurring within the government as well as Federally-funded research occurring outside of government, such as in academia. The ultimate goal of this research is to produce new AI knowledge and technologies that provide a range of positive benefits to society, while minimizing the negative impacts.
