A genetic epidemiology approach to cyber-security

DSpace/Manakin Repository

A genetic epidemiology approach to cyber-security

Citable link to this page

 

 
Title: A genetic epidemiology approach to cyber-security
Author: Gil, Santiago; Kott, Alexander; Barabási, Albert-László

Note: Order does not necessarily reflect citation order of authors.

Citation: Gil, Santiago, Alexander Kott, and Albert-László Barabási. 2014. “A genetic epidemiology approach to cyber-security.” Scientific Reports 4 (1): 5659. doi:10.1038/srep05659. http://dx.doi.org/10.1038/srep05659.
Full Text & Related Files:
Abstract: While much attention has been paid to the vulnerability of computer networks to node and link failure, there is limited systematic understanding of the factors that determine the likelihood that a node (computer) is compromised. We therefore collect threat log data in a university network to study the patterns of threat activity for individual hosts. We relate this information to the properties of each host as observed through network-wide scans, establishing associations between the network services a host is running and the kinds of threats to which it is susceptible. We propose a methodology to associate services to threats inspired by the tools used in genetics to identify statistical associations between mutations and diseases. The proposed approach allows us to determine probabilities of infection directly from observation, offering an automated high-throughput strategy to develop comprehensive metrics for cyber-security.
Published Version: doi:10.1038/srep05659
Other Sources: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4100021/pdf/
Terms of Use: This article is made available under the terms and conditions applicable to Other Posted Material, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#LAA
Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:12717524
Downloads of this work:

Show full Dublin Core record

This item appears in the following Collection(s)

 
 

Search DASH


Advanced Search
 
 

Submitters