Heaven

Marcus Botacin, Marco Zanata Alves, Daniela Oliveira,André Grégio

Expert Systems with Applications: An International Journal(2022)

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摘要
Antiviruses (AVs) are computing-intensive applications that rely on constant monitoring of OS events and on applying pattern matching procedures on binaries to detect malware. In this paper, we introduce HEAVEN, a framework for Intel x86/x86-64 and MS Windows that combines hardware and software to improve AVs performance. HEAVEN workflow consists of a hardware-assisted signature matching process as its first step (triage), which is fast, and only invokes the software-based AV when the software is suspicious, i.e., with an unknown hardware signature for malignity. We implement a PoC for HEAVEN by instrumenting Intel’s x86/x86-64 branch predictor, which allows for the generation of malware signatures based on branch pattern history. To validate our PoC, we evaluate HEAVEN with a dataset composed of 10,000 malware and 1,000 benign software samples from different categories and accomplished malware detection rates of 100% (no false-positives). The detection occurred before the execution of 10% of the samples’ code. HEAVEN is designed to be memory efficient: it identified unique 32-bit signatures for each sample at the storage cost of only 35KB of SRAM. HEAVEN is also designed with processing efficiency in mind: its hardware extensions present negligible performance overhead and reduces the average workload of the chosen software AV counterpart (ClamWin)—10% for CPU usage, 5.61% for memory throughput, 16.22% for disk writes, and 20.22% for disk reads. With HEAVEN, we may decrease the number of CPU cycles used for malware scanning by 87.5%, which is a promising result regarding the feasibility of our proposal: the combination of hardware-/software-based AVs for practical and effective malware detection that flags suspicious software while posing negligible performance overhead. • Real-time AntiViruses (AVs) become performance-prohibitive if purely implemented in software. • A Hardware–Software collaborative AV might fully mitigate the overhead of real-time AV monitoring. • Branch patterns might be used as fingerprint of known malicious code execution. • The Branch Prediction Unit (BPU) might be instrumented to fingerprint applications without much redesign. • Hardware-assisted Avs can support software updates to not break current AV’s operation modes.
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关键词
Malware,Antivirus,Signatures,Branch prediction,Performance
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