TY - GEN
T1 - Benchmarking Label Dynamics of VirusTotal Engines
AU - Zhu, Shuofei
AU - Zhang, Ziyi
AU - Yang, Limin
AU - Song, Linhai
AU - Wang, Gang
N1 - Funding Information:
This research was supported in part by a Seed Grant award from the Institute for Computational and Data Sciences at the Pennsylvania State University.
Publisher Copyright:
© 2020 Owner/Author.
PY - 2020/10/30
Y1 - 2020/10/30
N2 - VirusTotal is the largest online anti-malware scanning service. It is widely used by security researchers for labeling malware data or serving as a comparison baseline. However, several important challenges of using VirusTotal are left unaddressed (e.g., whether VirusTotal labels are already stable, when VirusTotal labels can be trusted), severely harming the correctness of research projects depending on VirusTotal. In this paper, we present VTSet, which contains daily VirusTotal labels on more than 14,000 files over one year. VTSet can be used to build and evaluate various tools to tackle the existing challenges and facilitate the usage of VirusTotal. Besides the data, VTSet also provides a demonstration tool to display many measurement results and a query tool to ease the access of its data. A video demonstration of VTSet is located at the following link: https://youtu.be/aSVaUGHxFi4.
AB - VirusTotal is the largest online anti-malware scanning service. It is widely used by security researchers for labeling malware data or serving as a comparison baseline. However, several important challenges of using VirusTotal are left unaddressed (e.g., whether VirusTotal labels are already stable, when VirusTotal labels can be trusted), severely harming the correctness of research projects depending on VirusTotal. In this paper, we present VTSet, which contains daily VirusTotal labels on more than 14,000 files over one year. VTSet can be used to build and evaluate various tools to tackle the existing challenges and facilitate the usage of VirusTotal. Besides the data, VTSet also provides a demonstration tool to display many measurement results and a query tool to ease the access of its data. A video demonstration of VTSet is located at the following link: https://youtu.be/aSVaUGHxFi4.
KW - dataset
KW - malware detection
UR - http://www.scopus.com/inward/record.url?scp=85096176279&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85096176279&partnerID=8YFLogxK
U2 - 10.1145/3372297.3420013
DO - 10.1145/3372297.3420013
M3 - Conference contribution
AN - SCOPUS:85096176279
T3 - Proceedings of the ACM Conference on Computer and Communications Security
SP - 2081
EP - 2083
BT - CCS 2020 - Proceedings of the 2020 ACM SIGSAC Conference on Computer and Communications Security
PB - Association for Computing Machinery
T2 - 27th ACM SIGSAC Conference on Computer and Communications Security, CCS 2020
Y2 - 9 November 2020 through 13 November 2020
ER -