Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/142012
Title: ROPSentry : runtime defense against ROP attacks using hardware performance counters
Authors: Das, Sanjeev
Chen, Bihuan
Chandramohan, Mahintham
Liu, Yang
Zhang, Wei
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2018
Source: Das, S., Chen, B., Chandramohan, M., Liu, Y., & Zhang, W. (2018). ROPSentry : runtime defense against ROP attacks using hardware performance counters. Computers and Security, 73, 374-388. doi:10.1016/j.cose.2017.11.011
Journal: Computers and Security
Abstract: Return-Oriented Programming (ROP) is one of the most common techniques to exploit software vulnerabilities. However, existing defense techniques can be defeated by attackers, or suffer from high performance overhead. In this paper, we propose a defense framework, named ROPSentry, to detect ROP attacks at runtime. It is built on the observation that ROP exploits usually trigger different hardware events than normal programs generated by compilers. Hence, we leverage hardware performance counters to track such hardware events and analyze behavioral patterns of ROP attacks. ROPSentry has two approaches. The ROP-only defense approach detects ROP attacks via capturing the patterns of ROP exploits, where we propose to sample the hardware performance counters at mispredicted return events instead of at every microinstruction for a low performance overhead. To further reduce performance overhead, we propose a self-adaptive defense approach to dynamically switch between low and high sampling rates. It detects the patterns of spraying attacks (i.e., one common ROP payload delivery technique) at a low sampling rate, and then switches to a high sampling rate for detecting the patterns of ROP exploits. Our evaluation on 11 real-world ROP exploits, 50 synthetically generated ROP exploits and 1000 benign websites has shown that, the ROP-only and self-adaptive approaches are effective in detecting ROP attacks with low performance overhead (11% and 1% respectively) as well as low false positive; and they significantly outperform the state-of-the-art techniques in terms of performance overhead without losing the detection accuracy.
URI: https://hdl.handle.net/10356/142012
ISSN: 0167-4048
DOI: 10.1016/j.cose.2017.11.011
Rights: © 2017 Elsevier Ltd. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:EEE Journal Articles

SCOPUSTM   
Citations 20

4
Updated on Mar 10, 2021

PublonsTM
Citations 20

4
Updated on Mar 9, 2021

Page view(s)

88
Updated on Jan 19, 2022

Google ScholarTM

Check

Altmetric


Plumx

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.