Alexander Kott – författare

What if the true weak link of the Information Age force is not the hardware of machines, but the software of the human mind? And if so, could it be that the entire conceptual structure of the Information Revolution theorists, at least as it applies to military affairs, is built on sand, on the notorious fickleness of human cognition? These are the questions this book strives to examine. Looking at the command and control of information-rich warfare, the contributors explore its potential new processes, techniques, and organizational structures. As they do so, they find reasons for both optimism and concerns about the limitations of human cognition and supporting technologies in commanding battles in the Information Age.Since the beginning of the Information Revolution, the military in the United States and elsewhere has been analyzing and implementing the changes driven by the rapidly advancing information technologies. Among military theorists and practitioners, many focus on the Information Revolution's impact on matters of military equipment. Far fewer, however, seem to worry about the gray matter—the mind of the commander, the place where all the information power of the new age is supposed to converge and to yield its mighty dividends.Consider that it is the human mind, particularly the minds of military commanders and their staffs that remain the pinnacle and the ultimate consumer of the rapidly growing information flows. What if the true weak link of the Information Age force is not the hardware of machines, but the software of the human mind? And if so, could it be that the entire conceptual structure of the Information Revolution theorists, at least as it applies to military affairs, is built on sand, on the notorious fickleness of human cognition? These are the questions this book strives to examine. Looking at the command and control of information-rich warfare, the authors explore its potential new processes, techniques, and organizational structures. As they do so, they find reasons for both optimism and concerns about the limitations of human cognition and supporting technologies in commanding Information Age battles.

An essential guide to the modeling and design techniques for securing systems that utilize the Internet of ThingsModeling and Design of Secure Internet of Things offers a guide to the underlying foundations of modeling secure Internet of Things' (IoT) techniques. The contributors—noted experts on the topic—also include information on practical design issues that are relevant for application in the commercial and military domains. They also present several attack surfaces in IoT and secure solutions that need to be developed to reach their full potential.The book offers material on security analysis to help with in understanding and quantifying the impact of the new attack surfaces introduced by IoT deployments. The authors explore a wide range of themes including: modeling techniques to secure IoT, game theoretic models, cyber deception models, moving target defense models, adversarial machine learning models in military and commercial domains, and empirical validation of IoT platforms. This important book: Presents information on game-theory analysis of cyber deceptionIncludes cutting-edge research finding such as IoT in the battlefield, advanced persistent threats, and intelligent and rapid honeynet generationContains contributions from an international panel of expertsAddresses design issues in developing secure IoT including secure SDN-based network orchestration, networked device identity management, multi-domain battlefield settings, and smart citiesWritten for researchers and experts in computer science and engineering, Modeling and Design of Secure Internet of Things contains expert contributions to provide the most recent modeling and design techniques for securing systems that utilize Internet of Things.

Authoritative and highly comprehensive resource on the latest research and strategies to develop cyber resilience in any network system Autonomous Cyber Resilience presents key research contributions in the fields of cyber resilience, resilient machine learning, and game theory for network security. It introduces basic concepts on resilience assessment framework, human robot teaming, zero-trust cyber resilience, the Stackelberg network game, and adversarial machine learning. The book describes a comprehensive suite of solutions for a broad range of technical challenges in autonomous cyber resilience, examines network robustness, planning, learning, and self-adaptation in a dynamic and uncertain environment and provides a joint analysis of cyber resilience and machine learning resilience. The book gathers experts in this emerging area of research to share their latest contributions in federated learning, resilient deep neural networks, topological data analysis, and effective deployment of honeypots, with valuable insights on applying these new methods to address cyber autonomy, network intrusion detection, and NextG communication systems. Additional chapters summarize ongoing research topics in cyber security and point to open issues and future research challenges and opportunities for academia and industry. Autonomous Cyber Resilience includes information on: Hypergraphs as a tool to move beyond basic pairwise relations and interactions to accurately model higher order interactions between groups of agentsSettings where multiple, distributed, and collaborative bots involved in an attack can make the impact of vulnerabilities more severeThe Resilience Index, the percentage of Monte Carlo simulations where mission essential functions perform below the acceptable thresholdEigenvector centrality, a metric that takes into account not just the centrality (degree) of a node but also its powerProviding an extensive set of techniques to meet a diverse array of obstacles in the field, Autonomous Cyber Resilience is essential reading for researchers, students, and experts in the fields of computer science and engineering, along with industry and military professionals involved in projects related to cybersecurity.

Sociological theories of crime include: theories of strain blame crime on personal stressors; theories of social learning blame crime on its social rewards, and see crime more as an institution in conflict with other institutions rather than as in- vidual deviance; and theories of control look at crime as natural and rewarding, and explore the formation of institutions that control crime. Theorists of corruption generally agree that corruption is an expression of the Patron–Client relationship in which a person with access to resources trades resources with kin and members of the community in exchange for loyalty. Some approaches to modeling crime and corruption do not involve an explicit simulation: rule based systems; Bayesian networks; game theoretic approaches, often based on rational choice theory; and Neoclassical Econometrics, a rational choice-based approach. Simulation-based approaches take into account greater complexities of interacting parts of social phenomena. These include fuzzy cognitive maps and fuzzy rule sets that may incorporate feedback; and agent-based simulation, which can go a step farther by computing new social structures not previously identified in theory. The latter include cognitive agent models, in which agents learn how to perceive their en- ronment and act upon the perceptions of their individual experiences; and reactive agent simulation, which, while less capable than cognitive-agent simulation, is adequate for testing a policy’s effects with existing societal structures. For example, NNL is a cognitive agent model based on the REPAST Simphony toolkit.

Sociological theories of crime include: theories of strain blame crime on personal stressors; theories of social learning blame crime on its social rewards, and see crime more as an institution in conflict with other institutions rather than as in- vidual deviance; and theories of control look at crime as natural and rewarding, and explore the formation of institutions that control crime. Theorists of corruption generally agree that corruption is an expression of the Patron–Client relationship in which a person with access to resources trades resources with kin and members of the community in exchange for loyalty. Some approaches to modeling crime and corruption do not involve an explicit simulation: rule based systems; Bayesian networks; game theoretic approaches, often based on rational choice theory; and Neoclassical Econometrics, a rational choice-based approach. Simulation-based approaches take into account greater complexities of interacting parts of social phenomena. These include fuzzy cognitive maps and fuzzy rule sets that may incorporate feedback; and agent-based simulation, which can go a step farther by computing new social structures not previously identified in theory. The latter include cognitive agent models, in which agents learn how to perceive their en- ronment and act upon the perceptions of their individual experiences; and reactive agent simulation, which, while less capable than cognitive-agent simulation, is adequate for testing a policy’s effects with existing societal structures. For example, NNL is a cognitive agent model based on the REPAST Simphony toolkit.

The rising tide of threats, from financial cybercrime to asymmetric military conflicts, demands greater sophistication in tools and techniques of law enforcement, commercial and domestic security professionals, and terrorism prevention. Concentrating on computational solutions to determine or anticipate an adversary's intent, Adversarial Reasoning: Computational Approaches to Reading the Opponent's Mind discusses the technologies for opponent strategy prediction, plan recognition, deception discovery and planning, and strategy formulation that not only applies to security issues but also to game industry and business transactions.Addressing a broad range of practical problems, including military planning and command, military and foreign intelligence, antiterrorism, network security, as well as simulation and training systems, this reference presents an overview of each problem and then explores various approaches and applications to understand the minds and negate the actions of your opponents. The techniques discussed originate from a variety of disciplines such as stochastic processes, artificial intelligence planning, cognitive modeling, robotics and agent theory, robust control, game theory, and machine learning, among others. The beginning chapters outline the key concepts related to discovering the opponent's intent and plans while the later chapters journey into mathematical methods for counterdeception. The final chapters employ a range of techniques, including reinforcement learning within a stochastic dynamic games context to devise strategies that combat opponents.By answering specific questions on how to create practical applications that require elements of adversarial reasoning while also exploring theoretical developments, Adversarial Reasoning: Computational Approaches to Reading the Opponent's Mind is beneficial for practitioners as well as researchers.

This book introduces fundamental concepts of cyber resilience, drawing expertise from academia, industry, and government.

This book offers a structured overview and a comprehensive guide to the emerging field of Autonomous Intelligent Cyber Defense Agents (AICA).

This book offers a structured overview and a comprehensive guide to the emerging field of Autonomous Intelligent Cyber Defense Agents (AICA).

Resilience, unlike the concept of security (which is often and incorrectly conflated with resilience) refers to the system's ability to recover or regenerate its performance after an unexpected impact produces a degradation in its performance.

This book explores cybersecurity research and development efforts, including ideas that deal with the growing challenge of how computing engineering can merge with neuroscience. The contributing authors, who are renowned leaders in this field, thoroughly examine new technologies that will automate security procedures and perform autonomous functions with decision making capabilities. To maximize reader insight into the range of professions dealing with increased cybersecurity issues, this book presents work performed by government, industry, and academic research institutions working at the frontier of cybersecurity and network sciences. Cybersecurity Systems for Human Cognition Augmentation is designed as a reference for practitioners or government employees working in cybersecurity. Advanced-level students or researchers focused on computer engineering or neuroscience will also find this book a useful resource.

This book is the first publication to give a comprehensive, structured treatment to the important topic of situational awareness in cyber defense. It presents the subject in a logical, consistent, continuous discourse, covering key topics such as formation of cyber situational awareness, visualization and human factors, automated learning and inference, use of ontologies and metrics, predicting and assessing impact of cyber attacks, and achieving resilience of cyber and physical mission. Chapters include case studies, recent research results and practical insights described specifically for this book. Situational awareness is exceptionally prominent in the field of cyber defense. It involves science, technology and practice of perception, comprehension and projection of events and entities in cyber space. Chapters discuss the difficulties of achieving cyber situational awareness – along with approaches to overcoming the difficulties - in the relatively young field of cyber defense where key phenomena are so unlike the more conventional physical world. Cyber Defense and Situational Awareness is designed as a reference for practitioners of cyber security and developers of technology solutions for cyber defenders. Advanced-level students and researchers focused on security of computer networks will also find this book a valuable resource.

This book provides a comprehensive overview of the fundamental security of Industrial Control Systems (ICSs), including Supervisory Control and Data Acquisition (SCADA) systems and touching on cyber-physical systems in general.

This book explores cybersecurity research and development efforts, including ideas that deal with the growing challenge of how computing engineering can merge with neuroscience. The contributing authors, who are renowned leaders in this field, thoroughly examine new technologies that will automate security procedures and perform autonomous functions with decision making capabilities. To maximize reader insight into the range of professions dealing with increased cybersecurity issues, this book presents work performed by government, industry, and academic research institutions working at the frontier of cybersecurity and network sciences. Cybersecurity Systems for Human Cognition Augmentation is designed as a reference for practitioners or government employees working in cybersecurity. Advanced-level students or researchers focused on computer engineering or neuroscience will also find this book a useful resource.

It presents the subject in a logical, consistent, continuous discourse, covering key topics such as formation of cyber situational awareness, visualization and human factors, automated learning and inference, use of ontologies and metrics, predicting and assessing impact of cyber attacks, and achieving resilience of cyber and physical mission.