Imperial College London


Faculty of EngineeringDepartment of Computing

Professor of Computer Systems



+44 (0)20 7594 8375j.mccann Website




258ACE ExtensionSouth Kensington Campus






BibTex format

author = {Tomic, I and Chen, PY and Breza, MJ and McCann, JA},
publisher = {ACM},
title = {Antilizer: run time self-healing security for wireless sensor networks},
url = {},

RIS format (EndNote, RefMan)

AB - Wireless Sensor Network (WSN) applications range from domesticInternet of Things systems like temperature monitoring of homesto the monitoring and control of large-scale critical infrastructures.The greatest risk with the use of WSNs in critical infrastructure istheir vulnerability to malicious network level attacks. Their radiocommunication network can be disrupted, causing them to lose ordelay data which will compromise system functionality. This paperpresents Antilizer, a lightweight, fully-distributed solution to enableWSNs to detect and recover from common network level attackscenarios. In Antilizer each sensor node builds a self-referencedtrust model of its neighbourhood using network overhearing. Thenode uses the trust model to autonomously adapt its communica-tion decisions. In the case of a network attack, a node can makeneighbour collaboration routing decisions to avoid affected regionsof the network. Mobile agents further bound the damage caused byattacks. These agents enable a simple notification scheme whichpropagates collaborative decisions from the nodes to the base sta-tion. A filtering mechanism at the base station further validatesthe authenticity of the information shared by mobile agents. Weevaluate Antilizer in simulation against several routing attacks. Ourresults show that Antilizer reduces data loss down to 1% (4% onaverage), with operational overheads of less than 1% and providesfast network-wide convergence.
AU - Tomic,I
AU - Chen,PY
AU - Breza,MJ
AU - McCann,JA
TI - Antilizer: run time self-healing security for wireless sensor networks
UR -
ER -