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LDX: Causality Inference by Lightweight Dual Execution

Authors:

William Nick Sumner,

Brendan Saltaformaggio,

Dongyan XuAuthors Info & Claims

ASPLOS '16: Proceedings of the Twenty-First International Conference on Architectural Support for Programming Languages and Operating Systems

Pages 503 - 515

https://doi.org/10.1145/2872362.2872395

Published: 25 March 2016 Publication History

Abstract

Causality inference, such as dynamic taint anslysis, has many applications (e.g., information leak detection). It determines whether an event e is causally dependent on a preceding event c during execution. We develop a new causality inference engine LDX. Given an execution, it spawns a slave execution, in which it mutates c and observes whether any change is induced at e. To preclude non-determinism, LDX couples the executions by sharing syscall outcomes. To handle path differences induced by the perturbation, we develop a novel on-the-fly execution alignment scheme that maintains a counter to reflect the progress of execution. The scheme relies on program analysis and compiler transformation. LDX can effectively detect information leak and security attacks with an average overhead of 6.08% while running the master and the slave concurrently on separate CPUs, much lower than existing systems that require instruction level monitoring. Furthermore, it has much better accuracy in causality inference.

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Index Terms

LDX: Causality Inference by Lightweight Dual Execution
1. Security and privacy
  1. Systems security
    1. Information flow control
2. Software and its engineering
  1. Software notations and tools
    1. Compilers
      1. Runtime environments
      2. Source code generation

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ASPLOS '16: Proceedings of the Twenty-First International Conference on Architectural Support for Programming Languages and Operating Systems

March 2016

824 pages

ISBN:9781450340915

DOI:10.1145/2872362

General Chair:
Tom Conte
Georgia Tech, USA
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Program Chair:
Yuanyuan Zhou
University of California, San Diego, USA

ACM SIGARCH Computer Architecture News Volume 44, Issue 2
ASPLOS'16
May 2016
774 pages
ISSN:0163-5964
DOI:10.1145/2980024
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April 2016
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ISSN:0362-1340
EISSN:1558-1160
DOI:10.1145/2954679
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CHEN CWAN HZHAO X(2024)Log refusion: adversarial attacks against the integrity of application logs and defense methodsSCIENTIA SINICA Informationis10.1360/SSI-2024-004254:9(2157)Online publication date: 10-Sep-2024
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Sang AWang YYang LJia JZhou L(2024)Obfuscating Provenance-Based Forensic Investigations with Mapping System Meta-BehaviorProceedings of the 27th International Symposium on Research in Attacks, Intrusions and Defenses10.1145/3678890.3678916(248-262)Online publication date: 30-Sep-2024
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Zhang XLi KQi LLiu YWu PWang D(2024)An Apriori Knowledge-based Negative Sampling Method for APT Detection2024 5th International Conference on Computer Engineering and Application (ICCEA)10.1109/ICCEA62105.2024.10603935(1176-1182)Online publication date: 12-Apr-2024
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Liu ZChen KSullivan DArias ODutta RJin YGuo XKim T(2024)Microscope: Causality Inference Crossing the Hardware and Software Boundary from Hardware PerspectiveProceedings of the 29th Asia and South Pacific Design Automation Conference10.1109/ASP-DAC58780.2024.10473793(933-938)Online publication date: 22-Jan-2024
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Zhu TYu JXiong CCheng WYuan QYing JChen TZhang JLv MChen YWang TFan Y(2023)APTSHIELD: A Stable, Efficient and Real-Time APT Detection System for Linux HostsIEEE Transactions on Dependable and Secure Computing10.1109/TDSC.2023.324366720:6(5247-5264)Online publication date: Nov-2023
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Inam MChen YGoyal ALiu JMink JMichael NGaur SBates AHassan W(2023)SoK: History is a Vast Early Warning System: Auditing the Provenance of System Intrusions2023 IEEE Symposium on Security and Privacy (SP)10.1109/SP46215.2023.10179405(2620-2638)Online publication date: May-2023
https://doi.org/10.1109/SP46215.2023.10179405
Wang JWei JPang JZhang FLi S(2022)Security Enhancement Through Compiler-Assisted Software Diversity With Deep Reinforcement LearningInternational Journal of Digital Crime and Forensics10.4018/IJDCF.30287814:2(1-18)Online publication date: 17-Jun-2022
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徐志(2022)A Survey of Host-Based Advanced Persistent Threat Detection TechnologyComputer Science and Application10.12677/CSA.2022.12102412:01(233-251)Online publication date: 2022
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