Download or read book The Unforeseen Threat of AI on Security written by Emmanuel Joseph and published by Independently Published. This book was released on 2023-09-26 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In a rapidly evolving digital landscape, the convergence of artificial intelligence (AI) and security presents both unprecedented opportunities and unforeseen challenges. "The Unforeseen Threat of AI on Security" delves deep into the complex and dynamic relationship between AI and cybersecurity, offering a comprehensive exploration of the critical issues that define this technological frontier. As AI continues to reshape the world, it simultaneously empowers cyber adversaries with unprecedented capabilities. This book navigates through the shadowy world of AI-driven threats, unveiling the dark side of machine learning, autonomous cyberattacks, and state-sponsored espionage. Through real-world case studies, it reveals the tangible consequences of AI infiltrating the security realm, from crippling ransomware attacks to sophisticated deepfake-driven scams. Amidst these challenges, "The Unforeseen Threat of AI on Security" also illuminates the defensive power of AI. It explores cutting-edge AI security technologies, from predictive threat intelligence to autonomous incident response, showcasing how AI is becoming a vital ally in the fight against evolving cyber threats. Furthermore, it dissects the evolving dynamics of human-machine collaboration in security, highlighting the pivotal role that humans play alongside AI in safeguarding digital ecosystems. Ethical considerations are woven throughout the narrative, as the book addresses the profound ethical dilemmas posed by AI in security, from privacy and bias to transparency and accountability. It delves into the evolving governance and policy frameworks that govern AI security practices, emphasizing the need for responsible and lawful AI deployment. Looking ahead, "The Unforeseen Threat of AI on Security" anticipates future trends in AI security, offering insights into AI-generated malware, quantum computing's impact on encryption, deepfake attacks, and the evolving role of AI in national security. This book is a must-read for cybersecurity professionals, policymakers, technologists, and anyone interested in the transformative power of AI in both shaping and safeguarding our digital future. It serves as a vital guide for navigating the intricate landscape of AI and security, where innovation and defense intersect, and where the unforeseen threats of AI are met with resilience, vigilance, and ethical responsibility.

Download or read book Hands On Artificial Intelligence for Cybersecurity written by Alessandro Parisi and published by Packt Publishing Ltd. This book was released on 2019-08-02 with total page 331 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book AI in Cybersecurity written by Leslie F. Sikos and published by Springer. This book was released on 2018-09-17 with total page 215 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a collection of state-of-the-art AI approaches to cybersecurity and cyberthreat intelligence, offering strategic defense mechanisms for malware, addressing cybercrime, and assessing vulnerabilities to yield proactive rather than reactive countermeasures. The current variety and scope of cybersecurity threats far exceed the capabilities of even the most skilled security professionals. In addition, analyzing yesterday’s security incidents no longer enables experts to predict and prevent tomorrow’s attacks, which necessitates approaches that go far beyond identifying known threats. Nevertheless, there are promising avenues: complex behavior matching can isolate threats based on the actions taken, while machine learning can help detect anomalies, prevent malware infections, discover signs of illicit activities, and protect assets from hackers. In turn, knowledge representation enables automated reasoning over network data, helping achieve cybersituational awareness. Bringing together contributions by high-caliber experts, this book suggests new research directions in this critical and rapidly growing field.

Download or read book AI Enabled Threat Detection and Security Analysis for Industrial IoT written by Hadis Karimipour and published by Springer Nature. This book was released on 2021-08-03 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: This contributed volume provides the state-of-the-art development on security and privacy for cyber-physical systems (CPS) and industrial Internet of Things (IIoT). More specifically, this book discusses the security challenges in CPS and IIoT systems as well as how Artificial Intelligence (AI) and Machine Learning (ML) can be used to address these challenges. Furthermore, this book proposes various defence strategies, including intelligent cyber-attack and anomaly detection algorithms for different IIoT applications. Each chapter corresponds to an important snapshot including an overview of the opportunities and challenges of realizing the AI in IIoT environments, issues related to data security, privacy and application of blockchain technology in the IIoT environment. This book also examines more advanced and specific topics in AI-based solutions developed for efficient anomaly detection in IIoT environments. Different AI/ML techniques including deep representation learning, Snapshot Ensemble Deep Neural Network (SEDNN), federated learning and multi-stage learning are discussed and analysed as well. Researchers and professionals working in computer security with an emphasis on the scientific foundations and engineering techniques for securing IIoT systems and their underlying computing and communicating systems will find this book useful as a reference. The content of this book will be particularly useful for advanced-level students studying computer science, computer technology, cyber security, and information systems. It also applies to advanced-level students studying electrical engineering and system engineering, who would benefit from the case studies.

Download or read book Artificial Intelligence for Security written by Tuomo Sipola and published by Springer Nature. This book was released on with total page 373 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Practical AI for Cybersecurity written by Ravi Das and published by CRC Press. This book was released on 2021-02-26 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: The world of cybersecurity and the landscape that it possesses is changing on a dynamic basis. It seems like that hardly one threat vector is launched, new variants of it are already on the way. IT Security teams in businesses and corporations are struggling daily to fight off any cyberthreats that they are experiencing. On top of this, they are also asked by their CIO or CISO to model what future Cyberattacks could potentially look like, and ways as to how the lines of defenses can be further enhanced. IT Security teams are overburdened and are struggling to find ways in order to keep up with what they are being asked to do. Trying to model the cyberthreat landscape is a very laborious process, because it takes a lot of time to analyze datasets from many intelligence feeds. What can be done to accomplish this Herculean task? The answer lies in Artificial Intelligence (AI). With AI, an IT Security team can model what the future Cyberthreat landscape could potentially look like in just a matter of minutes. As a result, this gives valuable time for them not only to fight off the threats that they are facing, but to also come up with solutions for the variants that will come out later. Practical AI for Cybersecurity explores the ways and methods as to how AI can be used in cybersecurity, with an emphasis upon its subcomponents of machine learning, computer vision, and neural networks. The book shows how AI can be used to help automate the routine and ordinary tasks that are encountered by both penetration testing and threat hunting teams. The result is that security professionals can spend more time finding and discovering unknown vulnerabilities and weaknesses that their systems are facing, as well as be able to come up with solid recommendations as to how the systems can be patched up quickly.

Download or read book Artificial Intelligence for Security written by Archie Addo and published by Business Expert Press. This book was released on 2020-03-13 with total page 125 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence (AI) for security management explores terminologies of security and how AI can be applied to automate security processes. Additionally, the text provides detailed explanations and recommendations for how implement procedures. Practical examples and real-time use cases are evaluated and suggest appropriate algorithms based on the author’s experiences. Threat and associated securities from the data, process, people, things (e.g., Internet of things), systems, and actions were used to develop security knowledge base, which will help readers to build their own knowledge base. This book will help the readers to start their AI journey on security and how data can be applied to drive business actions to build secure environment.

Download or read book Implications of Artificial Intelligence for Cybersecurity written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2020-01-27 with total page 99 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book AI and Cyber Attacks The Growing Threat of AI Enhanced Hacking written by AQEEL AHMED and published by AQEEL AHMED. This book was released on 2023-06-01 with total page 100 pages. Available in PDF, EPUB and Kindle. Book excerpt: AI and Cyber Attacks: The Growing Threat of AI-Enhanced Hacking Introduction Artificial intelligence (AI) has transformed many industries, including cybersecurity. Rapid breakthroughs in artificial intelligence technology have created both opportunities and difficulties in the field of cybersecurity. While AI has enormous potential to improve security defenses and fight against cyber threats, it also poses major hazards when misused. Because of the confluence of AI and cyberattacks, a new breed of threats known as AI-enhanced hacking has emerged, which mixes AI algorithms and tactics with malicious intent. AI-enhanced hacking refers to hostile actors' use of AI and machine learning (ML) tools to increase the effectiveness, sophistication, and scope of cyberattacks. AI algorithms are being used by hackers to automate processes, boost attack success rates, elude detection, and circumvent security restrictions. Cybercriminals can substantially increase the effect and speed of their attacks by leveraging the capabilities of AI. For hackers, one of the most important benefits of AI is the capacity to launch more sophisticated and targeted attacks. AI systems can find vulnerabilities, build specialized attack methods, and adapt to changing protection mechanisms by analyzing massive volumes of data. Because of this sophistication, traditional security systems are finding it increasingly difficult to identify and resist AI-enhanced threats. AI algorithms can be used by hackers to undertake extensive reconnaissance, uncover system weaknesses, and launch precise and well-coordinated attacks. As a result, attack sophistication has increased, posing substantial problems for cybersecurity professionals. Furthermore, artificial intelligence enables hackers to automate many stages of an attack, from reconnaissance to exploitation and even post-exploitation activities. This automation enables attackers to undertake large-scale attacks, targeting several systems at the same time and improving their chances of success. Automated attacks present a big challenge to cybersecurity specialists, who must devise equally sophisticated protection systems to counter them. Hackers can save time and resources by automating their attacks while increasing their impact. Another significant benefit of AI for hackers is its ability to circumvent standard security measures and avoid discovery. In real-time, AI algorithms can evaluate trends, learn from previous attacks, and change defensive methods. Because of this adaptive behavior, attackers might go unnoticed for long periods of time, making it difficult for security analysts to identify and respond to threats quickly. AI-powered assaults can imitate legitimate user behavior, making it difficult to discern between legitimate and malicious activity. Hackers can extend their access to networks and collect critical information without alerting security measures by escaping detection. Another troubling element of AI-enhanced hacking is the weaponization of AI. As AI technology becomes more widely available, thieves can use them to develop stronger hacking tools. AI algorithms can be trained to generate convincing phishing emails, deepfake movies, and even replicate human behavior in order to circumvent multi-factor authentication systems. The weaponization of AI increases the potency of attacks and poses major hazards to individuals, organizations, and even governments. In the cybersecurity landscape, the potential for AI-powered assaults to deceive and manipulate users is becoming a significant worry. The growing threat of AI-enhanced hacking has necessitated the implementation of preventative measures to limit the hazards. To confront the shifting threat landscape, organizations and cybersecurity experts must adjust their protection measures. Advanced protection systems that use AI and machine learning can assist detect and respond to AI-enhanced threats more quickly, lessening the effect of possible breaches. AI-powered security systems can improve threat detection and response capabilities by monitoring network traffic, evaluating patterns, and recognizing anomalies in real-time. Collaboration between human expertise and AI technologies is also critical. AI can help cybersecurity professionals handle and analyze massive amounts of data, detect trends, and provide insights. Human specialists contribute critical thinking skills, contextual knowledge, and the capacity to make sound decisions in difficult situations. Organizations can develop a more effective security posture by combining human intuition and knowledge with AI's computational capabilities. In the development and deployment of Certainly! Ethical considerations are critical. There are various other factors to consider when it comes to AI and cyber-attacks, in addition to the ones described above. One critical issue is the continued need for AI-powered cybersecurity tool research and development. As AI-enhanced hacking techniques evolve, cybersecurity experts must stay on the cutting edge of technology. Continued research and development efforts can result in the development of creative technologies capable of detecting, preventing, and responding to AI-driven cyber-attacks. Collaboration and information sharing among cybersecurity specialists and companies are also critical. The cybersecurity community can collectively improve its ability to prevent AI-enhanced hacking by sharing knowledge, insights, and best practices. Collaborative initiatives such as information sharing platforms, industry conferences, and public-private partnerships can help to facilitate information flow and develop a collective defense against cyber threats. Furthermore, incorporating AI into threat intelligence can boost the ability to anticipate and respond to cyber-attacks dramatically. To identify prospective risks and deliver actionable insight, AI systems can scan enormous amounts of data, including previous attack patterns, new threats, and indicators of compromise. Organizations can proactively discover vulnerabilities, prioritize mitigation efforts, and improve incident response capabilities by employing AI in threat intelligence. End-user education and awareness are also critical in limiting the hazards of AI-enhanced hacking. Individuals must be educated on the risks posed by AI-driven cyber-attacks, such as phishing schemes, social engineering, and malware. Promoting cyber hygiene measures such as using strong passwords, being skeptical of questionable emails or links, and keeping software up to date can reduce the likelihood of falling victim to AI-powered assaults dramatically. Furthermore, legal frameworks and standards to control the development and deployment of AI technologies should be established. Governments and regulatory agencies can play an important role in establishing rules, verifying compliance, and encouraging the ethical use of AI in cybersecurity. These policies can address issues such as data privacy, algorithmic transparency, accountability, and ethical considerations, increasing trust in AI-powered cybersecurity solutions in the long run. AI has made important advances in a variety of fields, including cybersecurity. It does, however, introduce additional obstacles and threats, particularly in the form of AI-enhanced hacking. Organizations must adjust their protection methods and employ AI technology to identify, prevent, and respond to AI-driven assaults as they become more complex. Collaboration, continuing research, education, regulatory frameworks, and a team approach are critical in limiting risks and reaping the benefits of AI in cybersecurity. We can traverse the growing landscape of AI and cyber-attacks with confidence and resilience by remaining watchful, proactive, and always inventing. Artificial intelligence (AI) has surely altered various industries, including cybersecurity. The introduction of AI has created an enormous opportunity to strengthen security defenses against emerging threats. Organizations may improve their ability to detect and respond to threats in real time by leveraging the power of AI. However, the same qualities that make AI such a powerful asset in cybersecurity also offer major hazards when misused. Because of the convergence of AI and cyberattacks, a new species of risks known as AI-enhanced hacking has emerged, posing unprecedented challenges to the security landscape. AI-enhanced hacking refers to hostile actors' use of AI and machine learning techniques to increase the effectiveness, sophistication, and size of cyber-attacks. AI algorithms are being used by hackers to automate processes, boost attack success rates, elude detection, and circumvent security restrictions. This fusion of AI and hacking methodologies has significant ramifications for cybersecurity experts and companies. The implications of AI-enhanced hacking are wide-ranging and frightening. For starters, AI enables hackers to conduct more sophisticated attacks. AI systems can find vulnerabilities, build specialized attack methods, and adapt to changing protection mechanisms by analyzing massive volumes of data. Because of this sophistication, traditional security systems are finding it increasingly difficult to identify and resist AI-enhanced assaults successfully. Furthermore, AI enables unparalleled scale of automated attacks. AI algorithms can be used by hackers to automate many stages of an attack, from reconnaissance to exploitation and even post-exploitation. Because of this automation, attackers can target several systems at the same time, boosting their chances of success. The ability to launch automated attacks presents a big challenge for cybersecurity professionals, who must create similarly advanced protection measures to properly counter them. Another major problem is AI's ability to avoid discovery. AI algorithms are being used by hackers to detect trends, learn from previous attacks, and change defensive methods in real-time. Because of this adaptive behavior, attackers might go unnoticed for long periods of time, making it difficult for security analysts to identify and respond to threats quickly. Furthermore, the weaponization of AI increases the effectiveness of strikes while posing significant hazards. As AI technology becomes more widely available, thieves can use them to develop stronger hacking tools. AI algorithms can be trained to generate convincing phishing emails, deepfake movies, and even replicate human behavior in order to circumvent multi-factor authentication systems. The ability to weaponize AI raises the effect and possible harm caused by hacks dramatically. Several efforts can be made to reduce the hazards posed by AI-enhanced hacking. First and foremost, enterprises must invest in modern defense mechanisms that employ AI and machine learning. Organizations may monitor network traffic, analyze patterns, and detect anomalies in real time by using AI-powered security solutions. This proactive approach can assist in detecting and responding to attacks more quickly, limiting the effect of possible breaches. Furthermore, human-AI collaboration is critical in preventing AI-enhanced hacking. While AI is powerful, human expertise is also necessary. To increase threat intelligence and response, organizations should encourage collaboration between cybersecurity specialists and AI systems. A more effective defense posture can be built by combining human intuition and contextual knowledge with AI's computational skills. In tackling the issue of AI-enhanced hacking, ethical considerations and responsible use of AI are critical. Governments, organizations, and technology suppliers should collaborate to develop guidelines for the ethical use of AI in cybersecurity. Transparency, accountability, and privacy should be prioritized in AI development and deployment. As AI evolves at a rapid pace, continuous monitoring and training of AI systems is critical. To remain abreast of new assault strategies, regular assessments and upgrades are required. Organizations should also invest in employee training programs to educate users about the potential threats of AI-enhanced hacking, as well as how to spot and respond to them.

Download or read book Artificial Intelligence and Global Security written by Yvonne R. Masakowski and published by Emerald Group Publishing. This book was released on 2020-07-15 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence and Global Security: Future Trends, Threats and Considerations brings a much-needed perspective on the impact of the integration of Artificial Intelligence (AI) technologies in military affairs. Experts forecast that AI will shape future military operations in ways that will revolutionize warfare.

Download or read book AI Driven Cybersecurity andThreat Intelligence written by Iqbal H. Sarker and published by Springer Nature. This book was released on with total page 207 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Research Anthology on Artificial Intelligence Applications in Security written by Management Association, Information Resources and published by IGI Global. This book was released on 2020-11-27 with total page 2253 pages. Available in PDF, EPUB and Kindle. Book excerpt: As industries are rapidly being digitalized and information is being more heavily stored and transmitted online, the security of information has become a top priority in securing the use of online networks as a safe and effective platform. With the vast and diverse potential of artificial intelligence (AI) applications, it has become easier than ever to identify cyber vulnerabilities, potential threats, and the identification of solutions to these unique problems. The latest tools and technologies for AI applications have untapped potential that conventional systems and human security systems cannot meet, leading AI to be a frontrunner in the fight against malware, cyber-attacks, and various security issues. However, even with the tremendous progress AI has made within the sphere of security, it’s important to understand the impacts, implications, and critical issues and challenges of AI applications along with the many benefits and emerging trends in this essential field of security-based research. Research Anthology on Artificial Intelligence Applications in Security seeks to address the fundamental advancements and technologies being used in AI applications for the security of digital data and information. The included chapters cover a wide range of topics related to AI in security stemming from the development and design of these applications, the latest tools and technologies, as well as the utilization of AI and what challenges and impacts have been discovered along the way. This resource work is a critical exploration of the latest research on security and an overview of how AI has impacted the field and will continue to advance as an essential tool for security, safety, and privacy online. This book is ideally intended for cyber security analysts, computer engineers, IT specialists, practitioners, stakeholders, researchers, academicians, and students interested in AI applications in the realm of security research.

Download or read book Artificial Intelligence for Cyber Security Methods Issues and Possible Horizons or Opportunities written by Sanjay Misra and published by Springer Nature. This book was released on 2021-05-31 with total page 467 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Machine Learning for Cyber Agents written by Stanislav Abaimov and published by Springer Nature. This book was released on 2022-01-27 with total page 235 pages. Available in PDF, EPUB and Kindle. Book excerpt: The cyber world has been both enhanced and endangered by AI. On the one hand, the performance of many existing security services has been improved, and new tools created. On the other, it entails new cyber threats both through evolved attacking capacities and through its own imperfections and vulnerabilities. Moreover, quantum computers are further pushing the boundaries of what is possible, by making machine learning cyber agents faster and smarter. With the abundance of often-confusing information and lack of trust in the diverse applications of AI-based technologies, it is essential to have a book that can explain, from a cyber security standpoint, why and at what stage the emerging, powerful technology of machine learning can and should be mistrusted, and how to benefit from it while avoiding potentially disastrous consequences. In addition, this book sheds light on another highly sensitive area – the application of machine learning for offensive purposes, an aspect that is widely misunderstood, under-represented in the academic literature and requires immediate expert attention.

Download or read book Adversarial AI Attacks Mitigations and Defense Strategies written by John Sotiropoulos and published by Packt Publishing Ltd. This book was released on 2024-07-26 with total page 586 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 DescriptionAdversarial 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.

Download or read book Adversary Aware Learning Techniques and Trends in Cybersecurity written by Prithviraj Dasgupta and published by Springer Nature. This book was released on 2021-01-22 with total page 229 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is intended to give researchers and practitioners in the cross-cutting fields of artificial intelligence, machine learning (AI/ML) and cyber security up-to-date and in-depth knowledge of recent techniques for improving the vulnerabilities of AI/ML systems against attacks from malicious adversaries. The ten chapters in this book, written by eminent researchers in AI/ML and cyber-security, span diverse, yet inter-related topics including game playing AI and game theory as defenses against attacks on AI/ML systems, methods for effectively addressing vulnerabilities of AI/ML operating in large, distributed environments like Internet of Things (IoT) with diverse data modalities, and, techniques to enable AI/ML systems to intelligently interact with humans that could be malicious adversaries and/or benign teammates. Readers of this book will be equipped with definitive information on recent developments suitable for countering adversarial threats in AI/ML systems towards making them operate in a safe, reliable and seamless manner.

Download or read book Powering the Digital Economy Opportunities and Risks of Artificial Intelligence in Finance written by El Bachir Boukherouaa and published by International Monetary Fund. This book was released on 2021-10-22 with total page 35 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper discusses the impact of the rapid adoption of artificial intelligence (AI) and machine learning (ML) in the financial sector. It highlights the benefits these technologies bring in terms of financial deepening and efficiency, while raising concerns about its potential in widening the digital divide between advanced and developing economies. The paper advances the discussion on the impact of this technology by distilling and categorizing the unique risks that it could pose to the integrity and stability of the financial system, policy challenges, and potential regulatory approaches. The evolving nature of this technology and its application in finance means that the full extent of its strengths and weaknesses is yet to be fully understood. Given the risk of unexpected pitfalls, countries will need to strengthen prudential oversight.