Risk-based Attack Surface Approximation: Poster
Title | Risk-based Attack Surface Approximation: Poster |
Publication Type | Conference Paper |
Year of Publication | 2016 |
Authors | Theisen, Christopher, Williams, Laurie |
Conference Name | Proceedings of the Symposium and Bootcamp on the Science of Security |
Publisher | ACM |
Conference Location | New York, NY, USA |
ISBN Number | 978-1-4503-4277-3 |
Keywords | attack surface, Big Data, big data security, big data security metrics, crash dumps, Metrics, pubcrawl, security, Stack traces |
Abstract | Proactive security review and test efforts are a necessary component of the software development lifecycle. Since resource limitations often preclude reviewing, testing and fortifying the entire code base, prioritizing what code to review/test can improve a team's ability to find and remove more vulnerabilities that are reachable by an attacker. One way that professionals perform this prioritization is the identification of the attack surface of software systems. However, identifying the attack surface of a software system is non-trivial. The goal of this poster is to present the concept of a risk-based attack surface approximation based on crash dump stack traces for the prioritization of security code rework efforts. For this poster, we will present results from previous efforts in the attack surface approximation space, including studies on its effectiveness in approximating security relevant code for Windows and Firefox. We will also discuss future research directions for attack surface approximation, including discovery of additional metrics from stack traces and determining how many stack traces are required for a good approximation. |
URL | http://doi.acm.org/10.1145/2898375.2898388 |
DOI | 10.1145/2898375.2898388 |
Citation Key | theisen_risk-based_2016 |