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  1. Proceedings of the 2015 Workshop on Automated Decision Making for Active Cyber Defense (SafeConfig '15)
  2. Estimating Risk Boundaries for Persistent and Stealthy Cyber-Attacks
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Integrated Adaptive Cyber Defense: Integration Spiral Results
Action Recommendation for Cyber Resilience
Using Probability Densities to Evolve more Secure Software Configurations
Automated Decision Making for Active Cyber Defense: Panel Discussion
Cyber Resilience-by-Construction: Modeling, Measuring & Verifying
Policy Specialization to Support Domain Isolation
Estimating Risk Boundaries for Persistent and Stealthy Cyber-Attacks
FlowMon: Detecting Malicious Switches in Software-Defined Networks
Who Touched My Mission: Towards Probabilistic Mission Impact Assessment
A Security Enforcement Framework for Virtual Machine Migration Auction
Behavior-dependent Routing: Responding to Anomalies with Automated Low-cost Measures

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Estimating Risk Boundaries for Persistent and Stealthy Cyber-Attacks

Content Provider ACM Digital Library
Author Awan, Malik Shahzad Rana, Omer F. Burnap, Peter
Abstract Increasingly mature, stealthy and dynamic techniques and attack vectors used by cyber criminals have made network infrastructure more vulnerable to security breaches. Moreover, cyber-attacks involving advanced evasion techniques often bypass security controls, and even if detected at a later time could still remain in the system for a long time without any monitorable trace. Such types of cyber-attacks are costing billions of dollars to the organizations across the globe. This dynamic and complex threat landscape demands a network administrator to understand the nature, patterns and risks of cyber-attacks targeting the network infrastructure so that appropriate measures could be introduced. In this paper we propose: (i) a framework to formally characterize the features of such advanced persistent threats, (ii) propose a security metric to calculate risk based on characteristics of such threats, and (iii) estimate risk boundaries for persistent and stealthy cyber-attacks. We validate and analyze the application of our proposed risk framework using real-world traffic logs acquired from an Intrusion Detection/Prevention System.
Starting Page 15
Ending Page 20
Page Count 6
File Format PDF
ISBN 9781450338219
DOI 10.1145/2809826.2809830
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2015-10-12
Publisher Place New York
Access Restriction Subscribed
Subject Keyword Taxonomy Classification Cyberattacks Malware
Content Type Text
Resource Type Article
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