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A Cognitive Approach to Improving Binary Reverse Engineering with Immersive Virtual Reality

Dennis G. Brown, Julian Bauer, Luke Wittbrodt, Samuel Mulder

TL;DR

This work addresses the cognitive challenges of binary reverse engineering by leveraging immersive virtual reality to apply embodied and external cognition. It follows a cognitive systems engineering approach, combining a basic cognitive task analysis with VR testbed design to identify VR affordances that support sensemaking in RE. The authors implement a CogBRE MVP featuring interactive graphs and slates and integrate tools via Oxide and Nexus to enable VR-based analysis of binary programs. Early practitioner feedback indicates improved exploratory capabilities and spatial organization in VR, guiding planned formal effectiveness studies to quantify impact on task performance and cognitive load.

Abstract

Through its affordances, immersive virtual reality (VR) offers a means to apply embodied and external cognition from the physical realm to solving analytical problems that are typically only conceptual. We present an example of executing a structured analysis following the tenets of cognitive systems engineering to derive immersive affordances applicable to a difficult analytical problem, in our case, reverse engineering (RE) binary programs. We conducted a basic cognitive task analysis of the problem to reveal features of its cognitive model and their associated fundamental cognitive phenomena, and then we mapped those concepts to immersive affordances associated with those concepts. We implemented a subset of those affordances in a VR system facilitating discovery of features of a binary program. Feedback from RE practitioners drove the initial development of the system and we are preparing for a formal effectiveness study to inform the direction of future research.

A Cognitive Approach to Improving Binary Reverse Engineering with Immersive Virtual Reality

TL;DR

This work addresses the cognitive challenges of binary reverse engineering by leveraging immersive virtual reality to apply embodied and external cognition. It follows a cognitive systems engineering approach, combining a basic cognitive task analysis with VR testbed design to identify VR affordances that support sensemaking in RE. The authors implement a CogBRE MVP featuring interactive graphs and slates and integrate tools via Oxide and Nexus to enable VR-based analysis of binary programs. Early practitioner feedback indicates improved exploratory capabilities and spatial organization in VR, guiding planned formal effectiveness studies to quantify impact on task performance and cognitive load.

Abstract

Through its affordances, immersive virtual reality (VR) offers a means to apply embodied and external cognition from the physical realm to solving analytical problems that are typically only conceptual. We present an example of executing a structured analysis following the tenets of cognitive systems engineering to derive immersive affordances applicable to a difficult analytical problem, in our case, reverse engineering (RE) binary programs. We conducted a basic cognitive task analysis of the problem to reveal features of its cognitive model and their associated fundamental cognitive phenomena, and then we mapped those concepts to immersive affordances associated with those concepts. We implemented a subset of those affordances in a VR system facilitating discovery of features of a binary program. Feedback from RE practitioners drove the initial development of the system and we are preparing for a formal effectiveness study to inform the direction of future research.
Paper Structure (9 sections, 4 figures)

This paper contains 9 sections, 4 figures.

Table of Contents

  1. Introduction
  2. Tracing Cognition to Affordances in VR
  3. Cognitive Models of Binary RE
  4. Cognitive Theory Applied to Binary RE
  5. Synthesis: Identifying Related Affordances in VR
  6. System Design and Implementation
  7. Initial Feedback
  8. User Study Design
  9. Conclusion and Future Work

Figures (4)

  • Figure 1: Exploring data recovered from a typical small binary program in our VR system: function call graph (upper left) and the disassembly, decompilation, and control flow graph for a selected function (left to right under function call graph).
  • Figure 2: Primary themes for analysis with most closely-related elements; highlighted area indicates highest-priority affordances in VR.
  • Figure 3: CogBRE MVP Feature Implementation.
  • Figure 4: CogBRE System Architecture.