Identifying, characterizing, and controlling stealth worms in wireless networks through biological epidemiology

Kristopher  Hall; Randy  Marchany; Nathaniel Davis

2nd International ICST Workshop on Wireless Traffic Measurements and Modeling

Research Article

Identifying, characterizing, and controlling stealth worms in wireless networks through biological epidemiology

Cite: BibTeX Plain Text

@INPROCEEDINGS{10.1145/1234247.1234248,
    author={Kristopher  Hall and Randy  Marchany and Nathaniel Davis},
    title={Identifying, characterizing, and controlling stealth worms in wireless networks through biological epidemiology},
    proceedings={2nd International ICST Workshop on Wireless Traffic Measurements and Modeling},
    publisher={ACM},
    proceedings_a={WITMEMO},
    year={2006},
    month={8},
    keywords={},
    doi={10.1145/1234247.1234248}
}

Kristopher Hall
Randy Marchany
Nathaniel Davis
Year: 2006
Identifying, characterizing, and controlling stealth worms in wireless networks through biological epidemiology
WITMEMO
ACM
DOI: 10.1145/1234247.1234248

Kristopher Hall¹^,*, Randy Marchany²^,*, Nathaniel Davis³

1: Bradley Dept. of ECE, Virginia Tech, Blacksburg, Virginia
2: IT Security Lab, Virginia Tech, Blacksburg, Virginia
3: Dept. of ECE, Air Force Institute of Technology, Wright-Patterson AFB, OH

*Contact email: kjh@vt.edu, marchany@vt.edu

Abstract

This paper defines and evaluates a network security system, Rx, inspired by biological epidemiology that defends wireless networks against stealth worms. Rx applies concepts from epidemiology to identify and control worm behavior at the network level by aggregating and processing end-host anomaly reports. The system uses bio-mathematical modeling and demographic analysis to identify, characterize, forecast, and control network stealth worms early in the infection cycle. We present the design of Rx with simulation results that show the system increases by nearly an order of magnitude the survival rate of portable wireless devices under attack by a network stealth worm.

Published: 2006-08-05
Publisher: ACM

: http://dx.doi.org/10.1145/1234247.1234248