@inproceedings{d5533cb1b11c43868b38b94fe825ecbb,
title = "A market-based approach for detecting malware in the cloud via introspection",
abstract = "Traditional anti-virus (AV) solutions are known for their considerable consumption of resources, limiting their usefulness on the cloud. In contrast, cloud-based lightweight malware monitoring approaches consume fewer resources than a full malware scan would normally require, however, they are often prone to false alarms; limiting their effectiveness. In this paper, such a trade-off is addressed by proposing a prioritisation approach, consisting of two protection layers (i.e. lightweight and full malware scanning) to conduct a scalable and effective malware inspection of the cloud Virtual Machines (VMs). The novel contribution of this paper is a market-inspired mechanism that utilises lightweight scanners to prioritise the AV scanning process, by deciding which VM should be thoroughly scanned and when; it will trigger then a full malware scan on a pre-defined percentage of the most critical VMs. The conducted evaluation shows that the framework provides a cost-effective scanning method, while being able to confirm the infection status of the most critical set of VMs; thus maintaining a low rate of false alarms.",
author = "Nada Alruhaily and Carlos Mera-G{\'o}mez and Tom Chothia and Rami Bahsoon",
year = "2017",
doi = "10.1007/978-3-319-69035-3_52",
language = "English",
isbn = "978-3-319-69034-6",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "722--730",
editor = "Maximilien, {Michael } and Vallecillo, {Antonio } and Wang, {Jianmin } and Oriol, {Marc }",
booktitle = "Service-Oriented Computing - 15th International Conference, ICSOC 2017, Proceedings",
note = "15th International Conference on Service-Oriented Computing, ICSOC 2017 ; Conference date: 13-11-2017 Through 16-11-2017",
}