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Author: Sachin Shetty
Publisher: Springer
ISBN: 3319310321
Category : Computers
Languages : en
Pages : 92
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Book Description
This book provides an overview of Moving Target Defense (MTD) and the importance of developing novel MTD schemes to protect distributed systems. It presents MTD-based research efforts to protect cloud data centers, along with network and security risk-aware approaches to place Virtual Machines (VM) in cloud data centers. These approaches include MTD-based network diversity models that enable an evaluation of the robustness of cloud data centers against potential zero-day attacks. Since these models can be used as a security metric the authors include different network configurations and policies, consider the similarity and dissimilarity of network resources, and account for minimum impact to maximum impact attacks. Also offered is a framework for determining the cost of MTD-based VM migration on cloud data centers. Designed for researchers and practitioners, Moving Target Defense for Distributed Systems enables readers to understand the potential of MTD capabilities. It enables defenders to change system or network behaviors, policies, and configurations automatically to keep potential attack surfaces protected. Advanced level students in computer science, especially those interested in networks and security, will benefit from this book.
Author: Sachin Shetty
Publisher: Springer
ISBN: 3319310321
Category : Computers
Languages : en
Pages : 92
Get Book Here
Book Description
This book provides an overview of Moving Target Defense (MTD) and the importance of developing novel MTD schemes to protect distributed systems. It presents MTD-based research efforts to protect cloud data centers, along with network and security risk-aware approaches to place Virtual Machines (VM) in cloud data centers. These approaches include MTD-based network diversity models that enable an evaluation of the robustness of cloud data centers against potential zero-day attacks. Since these models can be used as a security metric the authors include different network configurations and policies, consider the similarity and dissimilarity of network resources, and account for minimum impact to maximum impact attacks. Also offered is a framework for determining the cost of MTD-based VM migration on cloud data centers. Designed for researchers and practitioners, Moving Target Defense for Distributed Systems enables readers to understand the potential of MTD capabilities. It enables defenders to change system or network behaviors, policies, and configurations automatically to keep potential attack surfaces protected. Advanced level students in computer science, especially those interested in networks and security, will benefit from this book.
Author: Todd Perez
Publisher: Createspace Independent Publishing Platform
ISBN: 9781984966063
Category :
Languages : en
Pages : 82
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Book Description
Designed for researchers and practitioners, Moving Target Defense for Distributed Systems enables readers to understand the potential of MTD capabilities. It enables defenders to change system or network behaviors, policies, and configurations automatically to keep potential attack surfaces protected. Advanced level students in computer science, especially those interested in networks and security, will benefit from this book.Since these models can be used as a security metric the authors include different network configurations and policies, consider the similarity and dissimilarity of network resources, and account for minimum impact to maximum impact attacks. Also offered is a framework for determining the cost of MTD-based VM migration on cloud data centers.
Author: Carl Aguilar
Publisher: Createspace Independent Publishing Platform
ISBN: 9781984360212
Category :
Languages : en
Pages : 82
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Book Description
Moving Target Defense for Distributed Systems presents MTD-based research efforts to protect cloud data centers, along with network and security risk-aware approaches to place Virtual Machines (VM) in cloud data centers. These approaches include MTD-based network diversity models that enable an evaluation of the robustness of cloud data centers against potential zero-day attacks. Since these models can be used as a security metric the authors include different network configurations and policies, consider the similarity and dissimilarity of network resources, and account for minimum impact to maximum impact attacks. Also offered is a framework for determining the cost of MTD-based VM migration on cloud data centers.
Author: Sushil Jajodia
Publisher: Springer Science & Business Media
ISBN: 1461409772
Category : Computers
Languages : en
Pages : 196
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Book Description
Moving Target Defense: Creating Asymmetric Uncertainty for Cyber Threats was developed by a group of leading researchers. It describes the fundamental challenges facing the research community and identifies new promising solution paths. Moving Target Defense which is motivated by the asymmetric costs borne by cyber defenders takes an advantage afforded to attackers and reverses it to advantage defenders. Moving Target Defense is enabled by technical trends in recent years, including virtualization and workload migration on commodity systems, widespread and redundant network connectivity, instruction set and address space layout randomization, just-in-time compilers, among other techniques. However, many challenging research problems remain to be solved, such as the security of virtualization infrastructures, secure and resilient techniques to move systems within a virtualized environment, automatic diversification techniques, automated ways to dynamically change and manage the configurations of systems and networks, quantification of security improvement, potential degradation and more. Moving Target Defense: Creating Asymmetric Uncertainty for Cyber Threats is designed for advanced -level students and researchers focused on computer science, and as a secondary text book or reference. Professionals working in this field will also find this book valuable.
Author: Sushil Jajodia
Publisher: Springer Science & Business Media
ISBN: 1461454166
Category : Computers
Languages : en
Pages : 210
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Book Description
Our cyber defenses are static and are governed by lengthy processes, e.g., for testing and security patch deployment. Adversaries could plan their attacks carefully over time and launch attacks at cyber speeds at any given moment. We need a new class of defensive strategies that would force adversaries to continually engage in reconnaissance and re-planning of their cyber operations. One such strategy is to present adversaries with a moving target where the attack surface of a system keeps changing. Moving Target Defense II: Application of Game Theory and Adversarial Modeling includes contributions from world experts in the cyber security field. In the first volume of MTD, we presented MTD approaches based on software transformations, and MTD approaches based on network and software stack configurations. In this second volume of MTD, a group of leading researchers describe game theoretic, cyber maneuver, and software transformation approaches for constructing and analyzing MTD systems. Designed as a professional book for practitioners and researchers working in the cyber security field, advanced -level students and researchers focused on computer science will also find this book valuable as a secondary text book or reference.
Author: Charles A. Kamhoua
Publisher: John Wiley & Sons
ISBN: 1119593360
Category : Technology & Engineering
Languages : en
Pages : 704
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Book Description
An essential guide to the modeling and design techniques for securing systems that utilize the Internet of Things Modeling 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 deception Includes cutting-edge research finding such as IoT in the battlefield, advanced persistent threats, and intelligent and rapid honeynet generation Contains contributions from an international panel of experts Addresses design issues in developing secure IoT including secure SDN-based network orchestration, networked device identity management, multi-domain battlefield settings, and smart cities Written 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.
Author: Rui Zhuang
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
The static nature of cyber systems gives attackers a valuable and asymmetric advantage - time. To eliminate this asymmetric advantage, a new approach, called Moving Target Defense (MTD) has emerged as a potential solution. MTD system seeks to proactively change system configurations to invalidate the knowledge learned by the attacker and force them to spend more effort locating and re-locating vulnerabilities. While it sounds promising, the approach is so new that there is no standard definition of what an MTD is, what is meant by diversification and randomization, or what metrics to define the effectiveness of such systems. Moreover, the changing nature of MTD violates two basic assumptions about the conventional attack surface notion. One is that the attack surface remains unchanged during an attack and the second is that it is always reachable. Therefore, a new attack surface definition is needed. To address these issues, I propose that a theoretical framework for MTD be defined. The framework should clarify the most basic questions such as what an MTD system is and its properties such as adaptation, diversification and randomization. The framework should reveal what is meant by gaining and losing knowledge, and what are different attack types. To reason over the interactions between attacker and MTD system, the framework should define key concepts such as attack surface, adaptation surface and engagement surface. Based on that, this framework should allow MTD system designers to decide how to use existing configuration choices and functionality diversification to increase security. It should allow them to analyze the effectiveness of adapting various combinations of different configuration aspects to thwart different types of attacks. To support analysis, the frame- work should include an analytical model that can be used by designers to determine how different parameter settings will impact system security.
Author: Bo Liu
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
Moving target defense (MTD) in the power system is a promising defense strategy to detect false data injection (FDI) attacks against state estimation by using distributed flexible AC transmission system (D-FACTS) devices. Optimal planning and operation are two essential stages in the MTD application. MTD planning determines the optimal allocation of D-FACTS devices, while MTD operation decides the optimal D-FACTS setpoints under different load conditions in real-time. However, most MTD works focus on studying the MTD operation methods and neglect MTD planning. It is generally assumed that all lines are equipped with D-FACTS devices, which is the most expensive MTD planning solution. This dissertation separates MTD planning and MTD operation as two independent problems by distinguishing their roles in attack detection effectiveness, MTD application costs, and MTD hiddenness. The contributions of this work are three-fold as follows. Firstly, this dissertation proves that MTD planning can determine the MTD detection effectiveness, regardless of D-FACTS device setpoints in MTD operation. This work designs max-rank MTD planning algorithms by using the minimum number of D-FACTS devices to ensure MTD detection effectiveness and minimize the MTD planning cost. It is proved that any MTDs under proposed planning algorithms have the maximum rank of its composite matrix, a widely used metric of the MTD detection effectiveness. In addition, this work further points out the maximum rank of the composite matrix is not strictly equivalent to maximal MTD detection effectiveness. Three types of unprotected buses in MTD are identified, and attack detecting probability (ADP) is introduced as a novel metric for measuring the detection effectiveness of MTD planning. It is proved that the rank of the composite matrix merely represents the lower bound of ADP, while the number of unprotected buses determines the upper bound of ADP. Then, a novel graph-theory-based planning algorithm is proposed to achieve maximal MTD detection effectiveness. Secondly, this dissertation highlights that MTD operation ought to focus on reducing the MTD operation cost. This work proposes an AC optimal power flow (ACOPF) model considering D-FACTS devices as an MTD operation model, in which the reactance of D-FACTS equipped lines are introduced as decision variables to minimize system losses and generation costs. The proposed model can be used by system operators to achieve economic and cybersecure system operations. In addition, this dissertation rigorously derives the gradient and Hessian matrices of the objective function and constraints with respect to line reactance, which are further used to build an interior-point solver of the proposed ACOPF model. Finally, this dissertation designs the optimal planning and operation of D-FACTS devices for hidden MTD (HMTD), which is a superior MTD method stealthy to sophisticated attackers. A depth-first-search-based MTD planning algorithm is proposed to guarantee the MTD hiddenness while maximizing the rank of its composite matrix and covering all necessary buses. Additionally, this work proposes DC- and AC-HMTD operation models to determine the setpoints of D-FACTS devices. The optimization-based DC-HMTD model outperforms the existing HMTD operation in terms of CPU time and detection effectiveness. The ACOPF-based HMTD operation model ensures the hiddenness and minimizes the generation cost to utilize the economic benefits of D-FACTS devices. Comparative numerical results on multiple systems show the efficacy of the proposed planning and operation approaches in achieving high detecting effectiveness and MTD hiddenness.
Author: Adrian R. Chavez
Publisher:
ISBN: 9780355763836
Category :
Languages : en
Pages :
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Book Description
Critical infrastructure systems continue to foster predictable communication patterns and static configurations over extended periods of time. The static nature of these systems eases the process of gathering reconnaissance information that can be used to design, develop, and launch attacks by adversaries. In this research effort, the early phases of an attack vector will be disrupted by randomizing application port numbers, IP addresses, and communication paths dynamically through the use of overlay networks within Industrial Control Systems (ICS). These protective measures convert static systems into "moving targets," adding an additional layer of defense. Moving Target Defense (MTD) is an active area of research that periodically changes the attack surface of a system to create uncertainty and increase the workload for an adversary. To assess the effectiveness of MTD strategies within an ICS environment, performance metrics have been captured to quantify the impacts introduced to the operational network and to the adversary. Our MTD strategies are implemented using Software Defined Networking (SDN) to provide a scalable and transparent solution to the end devices within the network. We show that our MTD techniques are feasible within an ICS environment and that they can improve the resiliency of ICS systems. Our MTD strategies meet the real-time constraints of ICS systems and incur latency impacts of less than 50~ms and in most cases, well under 20 ms. Resiliency is improved by introducing crash tolerant and Byzantine fault tolerant algorithms to detect and prevent attacks against the SDN controller. We also evaluate the success rates of individual adversaries, distributed adversaries, and those attempting side-channel attacks to learn the frequencies at which the MTD techniques reconfigure the system. We demonstrate the effectiveness of our approaches in simulated, virtualized, and representative ICS environments.
Author: Charles A. Kamhoua
Publisher: John Wiley & Sons
ISBN: 1119723949
Category : Technology & Engineering
Languages : en
Pages : 546
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Book Description
GAME THEORY AND MACHINE LEARNING FOR CYBER SECURITY Move beyond the foundations of machine learning and game theory in cyber security to the latest research in this cutting-edge field In Game Theory and Machine Learning for Cyber Security, a team of expert security researchers delivers a collection of central research contributions from both machine learning and game theory applicable to cybersecurity. The distinguished editors have included resources that address open research questions in game theory and machine learning applied to cyber security systems and examine the strengths and limitations of current game theoretic models for cyber security. Readers will explore the vulnerabilities of traditional machine learning algorithms and how they can be mitigated in an adversarial machine learning approach. The book offers a comprehensive suite of solutions to a broad range of technical issues in applying game theory and machine learning to solve cyber security challenges. Beginning with an introduction to foundational concepts in game theory, machine learning, cyber security, and cyber deception, the editors provide readers with resources that discuss the latest in hypergames, behavioral game theory, adversarial machine learning, generative adversarial networks, and multi-agent reinforcement learning. Readers will also enjoy: A thorough introduction to game theory for cyber deception, including scalable algorithms for identifying stealthy attackers in a game theoretic framework, honeypot allocation over attack graphs, and behavioral games for cyber deception An exploration of game theory for cyber security, including actionable game-theoretic adversarial intervention detection against advanced persistent threats Practical discussions of adversarial machine learning for cyber security, including adversarial machine learning in 5G security and machine learning-driven fault injection in cyber-physical systems In-depth examinations of generative models for cyber security Perfect for researchers, students, and experts in the fields of computer science and engineering, Game Theory and Machine Learning for Cyber Security is also an indispensable resource for industry professionals, military personnel, researchers, faculty, and students with an interest in cyber security.
