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.
| Original language | English (US) |
|---|---|
| Title of host publication | CCS 2017 - Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security |
| Publisher | Association for Computing Machinery |
| Pages | 347-362 |
| Number of pages | 16 |
| ISBN (Electronic) | 9781450349468 |
| DOIs | |
| State | Published - Oct 30 2017 |
| Event | 24th ACM SIGSAC Conference on Computer and Communications Security, CCS 2017 - Dallas, United States Duration: Oct 30 2017 → Nov 3 2017 |
Other
| Other | 24th ACM SIGSAC Conference on Computer and Communications Security, CCS 2017 |
|---|---|
| Country | United States |
| City | Dallas |
| Period | 10/30/17 → 11/3/17 |
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Keywords
- Cyber Reasoning Systems
- Fuzzing
- Human assistance
ASJC Scopus subject areas
- Software
- Computer Networks and Communications
Cite this
Rise of the HaCRS : Augmenting autonomous cyber reasoning systems with human assistance. / Shoshitaishvili, Yan; Weissbacher, Michael; Dresel, Lukas; Salls, Christopher; Wang, Ruoyu; Kruegel, Christopher; Vigna, Giovanni.
CCS 2017 - Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security. Association for Computing Machinery, 2017. p. 347-362.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Rise of the HaCRS
T2 - Augmenting autonomous cyber reasoning systems with human assistance
AU - Shoshitaishvili, Yan
AU - Weissbacher, Michael
AU - Dresel, Lukas
AU - Salls, Christopher
AU - Wang, Ruoyu
AU - Kruegel, Christopher
AU - Vigna, Giovanni
PY - 2017/10/30
Y1 - 2017/10/30
N2 - 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.
AB - 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.
KW - Cyber Reasoning Systems
KW - Fuzzing
KW - Human assistance
UR - http://www.scopus.com/inward/record.url?scp=85041432348&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85041432348&partnerID=8YFLogxK
U2 - 10.1145/3133956.3134105
DO - 10.1145/3133956.3134105
M3 - Conference contribution
AN - SCOPUS:85041432348
SP - 347
EP - 362
BT - CCS 2017 - Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security
PB - Association for Computing Machinery
ER -