Can Migration-Based Dynamic Platform Technique Work Effectively: A Quantitative Analysis Perspective

被引:0
作者
Zhu, Weiqiao [1 ]
Yang, Yang [1 ]
Zhang, Yipin [2 ]
Chang, Xiaolin [2 ]
机构
[1] China Acad Railway Sci Co Ltd, Inst Comp Technol, Beijing 100081, Peoples R China
[2] Beijing Jiaotong Univ, Sch Cyberspace Sci & Technol, Beijing 100044, Peoples R China
关键词
Migration-based dynamic platform technique; moving target defense; security effectiveness; semi-Markov process; MOVING TARGET DEFENSE;
D O I
10.1109/ACCESS.2024.3457763
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Migration-based Dynamic Platform (MdyPlat) is a type of Moving Target Defense (MTD) techniques to protect the task executed on the platform. MdyPlat actively hinders sophisticated attacks through randomly and dynamically setting up a platform for executing the task. This paper aims to investigate how MdyPlat-related factors make quantitative impact on the capability of MdyPlat technique. We develop a semi-Markov model for describing the system dynamics and then derive metric calculation formulas for investigation. Compared to the existing analytical-modeling-based evaluation methods, our modeling approach can work even the times of all MdyPlat-related events follow any type of distribution. The comparison between simulation and numerical results validates the approximate accuracy of the model and formulas. Numerical experiment results uncover that 1) MdyPlat technique can effectively enhance the task security, particularly under high attack intensity; 2) The security risk of the executed task varies in different task-execution scenarios, which are denoted by the number of platforms and the probability distribution of the times of MDP-related events; and 3) Different cumulative distribution function of event time under the same mean value leads to different analysis result of the task security.
引用
收藏
页码:138319 / 138328
页数:10
相关论文
共 30 条
[11]   RL and Fingerprinting to Select Moving Target Defense Mechanisms for Zero-Day Attacks in IoT [J].
Huertas Celdran, Alberto ;
Sanchez Sanchez, Pedro Miguel ;
von der Assen, Jan ;
Schenk, Timo ;
Bovet, Gerome ;
Martinez Perez, Gregorio ;
Stiller, Burkhard .
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, 2024, 19 :5520-5529
[12]   Enhancing cloud security: harnessing bayesian game theory for a dynamic defense mechanism [J].
Kandoussi, El Mehdi ;
Houmairi, Adam ;
El Mir, Iman ;
Bellafkih, Mostafa .
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS, 2024, 27 (09) :12509-12526
[13]   A Moving Target Defense Control Framework for Cyber-Physical Systems [J].
Kanellopoulos, Aris ;
Vamvoudakis, Kyriakos G. .
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2020, 65 (03) :1029-1043
[14]   Time-Based Moving Target Defense Using Bayesian Attack Graph Analysis [J].
Kim, Hyejin ;
Hwang, Euiseok ;
Kim, Dongseong ;
Cho, Jin-Hee ;
Moore, Terrence J. ;
Nelson, Frederica F. ;
Lim, Hyuk .
IEEE ACCESS, 2023, 11 :40511-40524
[15]  
Li H., 2022, P DEC GAM THEOR SEC, P107
[16]   Security Modeling and Analysis of Moving Target Defense in Software Defined Networks [J].
Mendonca, Julio ;
Kim, Minjune ;
Graczyk, Rafal ;
Volp, Marcus ;
Kim, Dan Dongseong .
2022 IEEE 27TH PACIFIC RIM INTERNATIONAL SYMPOSIUM ON DEPENDABLE COMPUTING (PRDC), 2022, :141-151
[17]   Proactive defense mechanism: Enhancing IoT security through diversity-based moving target defense and cyber deception [J].
Rehman, Zubaida ;
Gondal, Iqbal ;
Ge, Mengmeng ;
Dong, Hai ;
Gregory, Mark ;
Tari, Zahir .
COMPUTERS & SECURITY, 2024, 139
[18]   Event-Based Moving Target Defense in Cloud Computing With VM Migration: A Performance Modeling Approach [J].
Santos, Lucas ;
Brito, Carlos ;
Fe, Iure ;
Carvalho, Juliana ;
Torquato, Matheus ;
Choi, Eunmi ;
Min, Dugki ;
Lee, Jae-Woo ;
Nguyen, Tuan Anh ;
Silva, Francisco Airton .
IEEE ACCESS, 2024, 12 :165539-165554
[19]   A Survey of Moving Target Defenses for Network Security [J].
Sengupta, Sailik ;
Chowdhary, Ankur ;
Sabur, Abdulhakim ;
Alshamrani, Adel ;
Huang, Dijiang ;
Kambhampati, Subbarao .
IEEE COMMUNICATIONS SURVEYS AND TUTORIALS, 2020, 22 (03) :1909-1941
[20]   D3GF: A Study on Optimal Defense Performance Evaluation of Drone-Type Moving Target Defense Through Game Theory [J].
Seo, Sang ;
Moon, Heaeun ;
Lee, Sunho ;
Kim, Donghyeon ;
Lee, Jaeyeon ;
Kim, Byeongjin ;
Lee, Woojin ;
Kim, Dohoon .
IEEE ACCESS, 2023, 11 :59575-59598