Wajih Ul Hassan (University of Illinois Urbana-Champaign), Mohammad A. Noureddine (University of Illinois Urbana-Champaign), Pubali Datta (University of Illinois Urbana-Champaign), Adam Bates (University of Illinois Urbana-Champaign)

Recent advances in causality analysis have enabled investigators to trace multi-stage attacks using whole- system provenance graphs. Based on system-layer audit logs (e.g., syscalls), these approaches omit vital sources of application context (e.g., email addresses, HTTP response codes) that can found in higher layers of the system. Although this information is often essential to understanding attack behaviors, incorporating this evidence into causal analysis engines is difficult due to the semantic gap that exists between system layers.

To address this shortcoming, we propose the notion of universal provenance, which encodes all forensically-relevant causal dependencies regardless of their layer of origin. To transparently realize this vision on commodity systems, we present ωLOG (“Omega Log”), a provenance tracking mechanism that bridges the semantic gap between system and application logging contexts. ωLOG analyzes program binaries to identify and model application-layer logging behaviors, enabling application events to be accurately reconciled with system-layer accesses. ωLOG then intercepts applications’ runtime logging activities and grafts those events onto the system-layer provenance graph, allowing investigators to reason more precisely about the nature of attacks. We demonstrate that ωLOG is widely-applicable to existing software projects and can transparently facilitate execution partitioning of dependency graphs without any training or developer intervention. Evaluation on real-world attack scenarios shows that universal provenance graphs are concise and rich with semantic information as compared to the state-of-the-art, with 12% average runtime overhead.

View More Papers

Practical Traffic Analysis Attacks on Secure Messaging Applications

Alireza Bahramali (University of Massachusetts Amherst), Amir Houmansadr (University of Massachusetts Amherst), Ramin Soltani (University of Massachusetts Amherst), Dennis Goeckel (University of Massachusetts Amherst), Don Towsley (University of Massachusetts Amherst)

Read More

PhantomCache: Obfuscating Cache Conflicts with Localized Randomization

Qinhan Tan (Zhejiang University), Zhihua Zeng (Zhejiang University), Kai Bu (Zhejiang University), Kui Ren (Zhejiang University)

Read More

Automated Discovery of Cross-Plane Event-Based Vulnerabilities in Software-Defined Networking

Benjamin E. Ujcich (University of Illinois at Urbana-Champaign), Samuel Jero (MIT Lincoln Laboratory), Richard Skowyra (MIT Lincoln Laboratory), Steven R. Gomez (MIT Lincoln Laboratory), Adam Bates (University of Illinois at Urbana-Champaign), William H. Sanders (University of Illinois at Urbana-Champaign), Hamed Okhravi (MIT Lincoln Laboratory)

Read More

ABSynthe: Automatic Blackbox Side-channel Synthesis on Commodity Microarchitectures

Ben Gras (Vrije Universiteit Amsterdam, Intel Corporation), Cristiano Giuffrida (Vrije Universiteit Amsterdam), Michael Kurth (Vrije Universiteit Amsterdam), Herbert Bos (Vrije Universiteit Amsterdam), Kaveh Razavi (Vrije Universiteit Amsterdam)

Read More