Paper Info
Title
Poster: Towards Automated Quantitative Analysis and Forecasting of Vulnerability Discoveries in Debian GNU/Linux
Abstract
Quantitative analysis and forecasting of software vulnerability discoveries is important for patching cost and time estimation, and as input to security metrics and risk assessment methodologies. However, as of now, quantitative studies (a) require considerable manual effort, (b) make use of noisy datasets, and (c) are especially challenging to reproduce. In this poster abstract we describe our ongoing work towards quantitative analysis of vulnerabilities in Debian GNU/Linux packages. We focus on the challenges of making the process as automated and reproducible as possible, while collecting good-quality data necessary for the analysis. We then state a number of interesting hypotheses that can be investigated, and present preliminary results.
Year
DOI
Venue
2019
10.1145/3319535.3363285
Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications Security
Keywords
Field
DocType
dataset, open-source software, software security, vulnerabilities
Data science,Computer security,Computer science,Vulnerability
Conference
ISBN
Citations 
PageRank 
978-1-4503-6747-9
0
0.34
References 
Authors
0
4
Name
Order
Citations
PageRank
Nikolaos D. Alexopoulos142.44
Rolf Egert294.19
Tim Grube3197.54
Max Mühlhäuser41652252.87