Paper Info
Title
Leaps: Learning-Based Proactive Security Auditing For Clouds
Abstract
Cloud security auditing assures the transparency and accountability of a cloud provider to its tenants. However, the high operational complexity implied by the multi-tenancy and self-service nature, coupled with the sheer size of a cloud, imply that security auditing in the cloud can become quite expensive and non-scalable. Therefore, a proactive auditing approach, which starts the auditing ahead of critical events, has recently been proposed as a promising solution for delivering practical response time. However, a key limitation of such approaches is their reliance on manual efforts to extract the dependency relationships among events, which greatly restricts their practicality and adoptability. In this paper, we propose a fully automated approach, namely LeaPS, leveraging learning-based techniques to extract dependency models from runtime events in order to facilitate the proactive security auditing of cloud operations. We integrate LeaPS to OpenStack, a popular cloud platform, and perform extensive experiments in both simulated and real cloud environments that show a practical response time (e.g., 6 ms to audit a cloud of 100,000 VMs) and a significant improvement (e.g., about 50% faster) over existing proactive approaches.
Year
DOI
Venue
2017
10.1007/978-3-319-66399-9_15
COMPUTER SECURITY - ESORICS 2017, PT II
Keywords
Field
DocType
Proactive auditing, Security auditing, Cloud security, OpenStack
Transparency (graphic),Audit,Computer science,Computer security,Response time,Cloud provider,Accountability,LEAPS,Cloud computing security,Cloud computing
Conference
Volume
ISSN
Citations 
10493
0302-9743
3
PageRank 
References 
Authors
0.38
19
7
Name
Order
Citations
PageRank
Suryadipta Majumdar1265.26
Yosr Jarraya217314.52
Momen Oqaily362.15
Amir Alimohammadifar471.49
Makan Pourzandi521628.31
Lingyu Wang61440121.43
Mourad Debbabi71467144.47