An Information-Theoretical View of Network-Aware Malware Attacks
Zesheng Chen, Chuanyi Ji

TL;DR
This paper uses information theory to analyze how non-uniform vulnerable-host distributions influence malware spread and explores the challenges in defending against network-aware malware exploiting these vulnerabilities.
Contribution
It introduces a non-uniformity factor based on Renyi entropy to quantify vulnerability distribution and links it to malware propagation speed and defense challenges.
Findings
Non-uniform vulnerable-host distributions are consistently observed.
The non-uniformity factor correlates with malware spreading speed.
Defending against network-aware malware is significantly more challenging.
Abstract
This work investigates three aspects: (a) a network vulnerability as the non-uniform vulnerable-host distribution, (b) threats, i.e., intelligent malwares that exploit such a vulnerability, and (c) defense, i.e., challenges for fighting the threats. We first study five large data sets and observe consistent clustered vulnerable-host distributions. We then present a new metric, referred to as the non-uniformity factor, which quantifies the unevenness of a vulnerable-host distribution. This metric is essentially the Renyi information entropy and better characterizes the non-uniformity of a distribution than the Shannon entropy. Next, we analyze the propagation speed of network-aware malwares in view of information theory. In particular, we draw a relationship between Renyi entropies and randomized epidemic malware-scanning algorithms. We find that the infection rates of malware-scanning…
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Taxonomy
TopicsNetwork Security and Intrusion Detection · Advanced Malware Detection Techniques · Spam and Phishing Detection
