Zhiyou Tian (Xidian University), Cong Sun (Xidian University), Dongrui Zeng (Palo Alto Networks), Gang Tan (Pennsylvania State University)

Dynamic taint analysis (DTA) has been widely used in security applications, including exploit detection, data provenance, fuzzing improvement, and information flow control. Meanwhile, the usability of DTA is argued on its high runtime overhead, causing a slowdown of more than one magnitude on large binaries. Various approaches have used preliminary static analysis and introduced parallelization or higher-granularity abstractions to raise the scalability of DTA. In this paper, we present a dynamic taint analysis framework podft that defines and enforces different fast paths to improve the efficiency of DBI-based dynamic taint analysis. podft uses a value-set analysis (VSA) to differentiate the instructions that must not be tainted from those potentially tainted. Combining the VSA-based analysis results with proper library function abstractions, we develop taint tracking policies for fast and slow paths and implement the tracking policy enforcement as a Pin-based taint tracker. The experimental results show that podft is more efficient than the state-of-the-art fast path-based DTA approach and competitive with the static binary rewriting approach. podft has a high potential to integrate basic block-level deep neural networks to simplify fast path enforcement and raise tracking efficiency.

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The “Beatrix” Resurrections: Robust Backdoor Detection via Gram Matrices

Wanlun Ma (Swinburne University of Technology), Derui Wang (CSIRO’s Data61), Ruoxi Sun (The University of Adelaide & CSIRO's Data61), Minhui Xue (CSIRO's Data61), Sheng Wen (Swinburne University of Technology), Yang Xiang (Digital Research & Innovation Capability Platform, Swinburne University of Technology)

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An Exploratory study of Malicious Link Posting on Social...

Muhammad Hassan, Mahnoor Jameel, Masooda Bashir (University of Illinois at Urbana Champaign)

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Md Hasan Shahriar, Wenjing Lou, Y. Thomas Hou (Virginia Polytechnic Institute and State University)

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Private Certifier Intersection

Bishakh Chandra Ghosh (Indian Institute of Technology Kharagpur), Sikhar Patranabis (IBM Research - India), Dhinakaran Vinayagamurthy (IBM Research - India), Venkatraman Ramakrishna (IBM Research - India), Krishnasuri Narayanam (IBM Research - India), Sandip Chakraborty (Indian Institute of Technology Kharagpur)

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