Kumar K. Attacks on Artificial Intelligence. The New Facets..Cyber Ecospace 2026

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Kumar K. Attacks on Artificial Intelligence. The New Facets..Cyber Ecospace 2026

Textbook in PDF format Cyber attacks, both on national infrastructures and private companies, have ramped up exponentially in recent years. Artificial Intelligence (AI) tools and algorithms can help detect and fend off cyber threats, but they can also be used by hackers in their cyber attacks. Defensive measures to address cyber attacks are not sufficient for Artificial Intelligence-based architectures, which present a new range of challenges. This new volume takes these concerns into consideration and examines recent developments and issues in attacks that target AI based systems and cyber infrastructures while also presenting research on using AI technologies to prevent attacks. Artificial Intelligence (AI) is one of the new state-of-the-art technologies and is an interdisciplinary concept that is observed in almost all the fields of technology and research development. In such context, “attacks on AI” is a newer threat to technology and automation. AI has received a lot of attention in all fields of technology with respect to its application and its hype in industrial revolution 4.0. As AI is evolving and improving on a wider scale, the need for securing the same is the necessity of the hour. With the state-of-the-art situation of AI, there are some limitations that developers overlook in algorithm design, which, however, attackers can use to their advantage. Cyberattacks can easily be deployed in via flaws in algorithm design, such as causing a misleading traffic signal for an autonomous vehicle. In such conditions, the face of cyber infrastructure needs to take a different path requiring comprehensive approaches for securing AI and surrounding cyber ecosystems. Attacking artificial-intelligence-based systems is the new weapon for attackers over untrusted inter–networks, so researchers need to focus more on understanding and analyzing the deep learning techniques and machine learning algorithms to address this neglected security facet of the problem. Attacks could be anticipated in the areas such as driverless/autonomous cars, UAVs such as drones, virtual agents, manipulated chat bots, robotic process automation, false emotion recognition, fake biometrics, disputed image recognition, etc. AI can be used to attack cyber-physical systems and individual sensitive information. Automatic AI attacks are deployed by attackers to steal and manipulate the data. Nonetheless, the focus of the book is on attacks on AI (the other way around) and how to operate incident response. National and international backbone systems are adopting AI in the modern technical world. Securing these systems is a continuous challenging scenario for the officials involved. Concepts associated to incident response, disaster recovery planning, and business continuity planning post-AI attacks are also part of this theme. Securing national and international cyber-physical systems toward AI attacks use cases in the field of driverless cars, automation in manufacturing, robotics and pattern recognition and is symbiotic with regard to vulnerability concerns. Artificial Intelligence works and builds algorithms that can be trained in such a way that the machines or electronic gadgets mimic the intelligence of the human brain and accomplish specific tasks like identifying patterns and performing specific operations based on a set of rules. There are many techniques based on artificial intelligence that have advanced considerably in the digital era, and their practical applications can be found in a variety of situations, from picture capturing, analyzing, and recognizing to facial identification for opening an account or doing financial transactions. While machines perform transactions by considering biometrical features, cyberattacks are prone, which are in turn handled by providing cybersecurity. In the field of AI-based strategies, cybersecurity can assist adversaries improve their attack methods and provide better cyber protection capabilities. Malicious actors, on the other hand, are aware of the new possibilities and will most likely try to exploit them. An Artificial Intelligence attack means the purposeful modification of an artificial intelligence system with the aim of causing a defect in the machine. The Chapter 1 provides an introduction to how Artificial Intelligence attacks are used for offensive and defensive purposes in the context of cybersecurity, the workings of different Artificial Intelligence models and applications of artificial intelligence, illustrates the various attacks that exist, including input attacks, poisoning attacks, and impacted systems, and presents the road to secure and trusted AI, along with a review of the work published in these areas. Preface Attacks Against Artificial Intelligence: An Overview Sridevi and Tukkappa K. Gundoor Offensive and Defensive Artificial Intelligence in Cyberspace Digital Forensics Analysis for Adversarial Attacks in AI‑based Systems Recent Developments of Artificial Intelligence Attacks and Challenges Kannadhasan, R. Nagarajan, K.Chandramohan, and R. Prabhu Security Viewpoint in Artificial Intelligence-Based Systems Secure Video Surveillance Systems for Person Reidentification Using Elliptic Curve Cryptography Forcasting Deployment of Web Forensics to Avert Misinformation Spread Using WEFA Tool Online Customers’ Purchase Intentions Classification Using Hybrid XGBoost Machine Learning Model and Its Security Concerns Process Mapping Military Aircraft Life Extension and Cyber Security Issues Application of AI and ML in Water Quality Monitoring System Implementation of Artificial Intelligence as a Protection Scheme for Cyber Security Cyberattacks and Employee Attrition Analysis for Business Continuity Planning: A Machine Learning Approach and an AI Application Internet of Things‑Based Ventilator: COVID‑19 and AI Security Perspective AI‑Secured Visitor Management System Cyber Warfare: A Modern Threat to a Nation’s Critical Infrastructure