Defense Against Advanced Persistent Threats: Optimal Network Security Hardening Using Multi-stage Maze Network Game

2020 ◽  
Author(s):  
Hangsheng Zhang ◽  
Haitao Liu ◽  
Jie Liang ◽  
Ting Li ◽  
Liru Geng ◽  
...  
Keyword(s):  
Network Security ◽  
Advanced Persistent Threats ◽  
Multi Stage ◽  
Security Hardening ◽  
Optimal Network ◽  
Network Game

A Generation Method of Network Security Hardening Strategy Based on Attack Graphs

2015 ◽  
Vol 12 (1) ◽  
pp. 45-61 ◽  
Author(s):  
Chao Zhao ◽  
Huiqiang Wang ◽  
Junyu Lin ◽  
Hongwu Lv ◽  
Yushu Zhang
Keyword(s):  
Network Security ◽  
Heuristic Algorithm ◽  
Scoring System ◽  
Time Complexity ◽  
Path Length ◽  
Low Cost ◽  
Attack Graphs ◽  
Running Time ◽  
Security Hardening ◽  
The Common

Analyzing attack graphs can provide network security hardening strategies for administrators. Concerning the problems of high time complexity and costly hardening strategies in previous methods, a method for generating low cost network security hardening strategies is proposed based on attack graphs. The authors' method assesses risks of attack paths according to path length and the common vulnerability scoring system, limits search scope with a threshold to reduce the time complexity, and lowers cost of hardening strategies by using a heuristic algorithm. The experimental results show that the authors' method has good scalability, and significantly reduces cost of network security hardening strategies with reasonable running time.

Network Security Situation Awareness Based on Phishing Detection

2014 ◽  
Vol 644-650 ◽  
pp. 2784-2787
Author(s):  
Jian Yi Zhang ◽  
Cheng Gen Song ◽  
Xin Jin
Keyword(s):  
Machine Learning ◽  
Network Security ◽  
Situation Awareness ◽  
High Accuracy ◽  
Statistical Machine Learning ◽  
Advanced Persistent Threats ◽  
Learning Classifier ◽  
Phishing Detection

In this paper, we introduce a statistical machine learning classifier and a LSH page similarity detector as the network security situation awareness mechanism to detect the spear phishing that has been widely used in the Advanced Persistent Threats. Then, a number of comprehensive experiments show that our proposed method achieves high accuracy over a balanced dataset. The accuracy is no less than 92% while the recall is more than 97%.

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