A layer-crossing multi-factor and dynamic security model over a moving target defence

2021 ◽  
Vol 16 (1/2) ◽  
pp. 150
Author(s):  
Zhanwei Cui ◽  
Jianping Zeng ◽  
Chengrong Wu
Keyword(s):  
Moving Target ◽  
Security Model ◽  
Dynamic Security

Trust Extended Dynamic Security Model and Its Application in Network

2006 ◽  
pp. 404-415 ◽  
Author(s):  
Xiaofei Zhang ◽  
Fang Xu ◽  
Yi Liu ◽  
Xing Zhang ◽  
Changxiang Shen
Keyword(s):  
Security Model ◽  
Dynamic Security ◽  
Extended Dynamic

Dynamic Security Metrics for Software-Defined Network-based Moving Target Defense

2020 ◽  
Vol 170 ◽  
pp. 102805
Author(s):  
Dilli P. Sharma ◽  
Simon Yusuf Enoch ◽  
Jin-Hee Cho ◽  
Terrence J. Moore ◽  
Frederica F. Nelson ◽  
...  
Keyword(s):  
Moving Target ◽  
Software Defined Network ◽  
Security Metrics ◽  
Moving Target Defense ◽  
Dynamic Security

Design and Application of a Network Security Model

2013 ◽  
Vol 347-350 ◽  
pp. 2773-2776
Author(s):  
Shi Ping Xu ◽  
Yu Han Zhang ◽  
Ying Zhou ◽  
Yong Qiang Bai ◽  
Hai Peng Fu
Keyword(s):  
Network Security ◽  
Risk Analysis ◽  
Security Model ◽  
Dynamic Security ◽  
Defense In Depth ◽  
Design And Application

This paper analyzes the deficiency of P2DR security model, and proposes a kind of new active dynamic security model AD-RPPDRRM, in which risk analysis, management and recovery are imported. On the basis of this model, basic technologies used to implement the defense in depth system are discussed. At last, a defense in-depth system of a typical network is given.

scholarly journals Dynamic security metrics for measuring the effectiveness of moving target defense techniques

2018 ◽  
Vol 79 ◽  
pp. 33-52 ◽  
Author(s):  
Jin B. Hong ◽  
Simon Yusuf Enoch ◽  
Dong Seong Kim ◽  
Armstrong Nhlabatsi ◽  
Noora Fetais ◽  
...  
Keyword(s):  
Moving Target ◽  
Security Metrics ◽  
Moving Target Defense ◽  
Dynamic Security

A Survey of Security Models Using Effective Moving Target Defenses

2018 ◽  
Vol 12 (3) ◽  
pp. 123-140
Author(s):  
B S Kiruthika Devi ◽  
T. Subbulakshmi ◽  
KV Mahesh Babu
Keyword(s):  
Formal Method ◽  
Cyber Attacks ◽  
Networked Systems ◽  
Moving Target ◽  
Security Model ◽  
Attack Tree ◽  
Attack Graph ◽  
Representation Model ◽  
Security Models ◽  
Attack Surface

This article describes how nowadays, attackers are targeting valuable assets and infrastructures in networked systems causing an impact on enterprises and individuals. By implementing moving target defenses helps to prevent cyber-attacks by changing the attack surface. Some security models like Attack Graph (A.G) and Attack Tree (A.T) provide a formal method to access and compare the effectiveness of them. So, in this article, the authors incorporate moving target defenses in a security model, using a Hierarchical Attack Representation Model (HARM), to compare and access the effectiveness of the security. In addition, the authors are also taking important measures (IMs) for implementing MTD techniques to enhance the scalability of the network. Finally, they compare the scalability of an attack graph and HARM models by implementing MTD techniques to find the effectiveness of security in network.

Proactive Defense for Internet-of-things: Moving Target Defense With Cyberdeception

2022 ◽  
Vol 22 (1) ◽  
pp. 1-31
Author(s):  
Mengmeng Ge ◽  
Jin-Hee Cho ◽  
Dongseong Kim ◽  
Gaurav Dixit ◽  
Ing-Ray Chen
Keyword(s):  
Internet Of Things ◽  
Network Topology ◽  
Optimal Parameter ◽  
Service Availability ◽  
Moving Target ◽  
Security Model ◽  
Moving Target Defense ◽  
Intrusion Prevention ◽  
Attack Path ◽  
Iot Devices

Resource constrained Internet-of-Things (IoT) devices are highly likely to be compromised by attackers, because strong security protections may not be suitable to be deployed. This requires an alternative approach to protect vulnerable components in IoT networks. In this article, we propose an integrated defense technique to achieve intrusion prevention by leveraging cyberdeception (i.e., a decoy system) and moving target defense (i.e., network topology shuffling). We evaluate the effectiveness and efficiency of our proposed technique analytically based on a graphical security model in a software-defined networking (SDN)-based IoT network. We develop four strategies (i.e., fixed/random and adaptive/hybrid) to address “when” to perform network topology shuffling and three strategies (i.e., genetic algorithm/decoy attack path-based optimization/random) to address “how” to perform network topology shuffling on a decoy-populated IoT network, and we analyze which strategy can best achieve a system goal, such as prolonging the system lifetime, maximizing deception effectiveness, maximizing service availability, or minimizing defense cost. We demonstrated that a software-defined IoT network running our intrusion prevention technique at the optimal parameter setting prolongs system lifetime, increases attack complexity of compromising critical nodes, and maintains superior service availability compared with a counterpart IoT network without running our intrusion prevention technique. Further, when given a single goal or a multi-objective goal (e.g., maximizing the system lifetime and service availability while minimizing the defense cost) as input, the best combination of “when” and “how” strategies is identified for executing our proposed technique under which the specified goal can be best achieved.

Where's That Wascally Wilber? The Challenges of Hitting a Moving Target

PsycCRITIQUES ◽  
2007 ◽  
Vol 52 (13) ◽  
Author(s):  
Douglas A. MacDonald
Keyword(s):  
Moving Target
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