Paper Info
Title
Rise of the HaCRS: Augmenting Autonomous Cyber Reasoning Systems with Human Assistance.
Abstract
Software permeates every aspect of our world, from our homes to the infrastructure that provides mission-critical services. As the size and complexity of software systems increase, the number and sophistication of software security flaws increase as well. The analysis of these flaws began as a manual approach, but it soon became apparent that a manual approach alone cannot scale, and that tools were necessary to assist human experts in this task, resulting in a number of techniques and approaches that automated certain aspects of the vulnerability analysis process. Recently, DARPA carried out the Cyber Grand Challenge, a competition among autonomous vulnerability analysis systems designed to push the tool-assisted human-centered paradigm into the territory of complete automation, with the hope that, by removing the human factor, the analysis would be able to scale to new heights. However, when the autonomous systems were pitted against human experts it became clear that certain tasks, albeit simple, could not be carried out by an autonomous system, as they require an understanding of the logic of the application under analysis. Based on this observation, we propose a shift in the vulnerability analysis paradigm, from tool-assisted human-centered to human-assisted tool-centered. In this paradigm, the automated system orchestrates the vulnerability analysis process, and leverages humans (with different levels of expertise) to perform well-defined sub-tasks, whose results are integrated in the analysis. As a result, it is possible to scale the analysis to a larger number of programs, and, at the same time, optimize the use of expensive human resources. In this paper, we detail our design for a human-assisted automated vulnerability analysis system, describe its implementation atop an open-sourced autonomous vulnerability analysis system that participated in the Cyber Grand Challenge, and evaluate and discuss the significant improvements that non-expert human assistance can offer to automated analysis approaches.
Year
DOI
Venue
2017
10.1145/3133956.3134069
CCS
Keywords
DocType
Volume
Fuzzing, Human assistance, Cyber Reasoning Systems
Journal
abs/1708.02749
ISBN
Citations 
PageRank 
978-1-4503-4946-8
20
0.90
References 
Authors
15
7
Name
Order
Citations
PageRank
Yan Shoshitaishvili135826.98
Michael Weissbacher2583.75
Lukas Dresel3200.90
Christopher Salls41987.90
Ruoyu Wang528216.23
Christopher Kruegel68799516.05
Giovanni Vigna77121507.72