[Dmbu-l] A Game-Theoretic Approach for High-Assurance of Data Trustworthiness in Sensor Networks [Thursday 03/29 @ 12:00 pm in MCS 148]

Charalampos Mavroforakis cmav at bu.edu
Thu Mar 22 17:59:00 EDT 2012

Hello everyone.

Dr. Gabriel Ghinita will present the following on next week

*Title: *
*A Game-Theoretic Approach for High-Assurance of Data Trustworthiness in
Sensor Networks*

Dr. Gabriel Ghinita, University of Massachusetts, Boston,
Gabriel.Ghinita at umb.edu

*Abstract: *
Sensor networks are being increasingly deployed in many application domains
ranging from environment monitoring to supervising  critical
 infrastructure  systems  (e.g.,  the  power grid). Due to their ability
to continuously collect large amounts of data, sensor networks represent a
key component in decision making, enabling timely situation assessment and
However, sensors deployed in hostile environments may be subject to attacks
 by  adversaries  who  intend  to  inject  false  data  into the system. In
this context, data trustworthiness is an important concern, as false
readings may result in wrong decisions with serious consequences (e.g.,
large-scale power outages). To defend against this threat, it is important
to establish trust levels for sensor nodes and adjust node trustworthiness
scores to account for malicious interferences.
In this paper, we develop a game-theoretic defense strategy to protect
sensor nodes from attacks and to guarantee a high level of trustworthiness
for sensed data. We use a discrete time model, and we consider that there
is a limited attack budget that bounds the capability of the attacker in
each round. The defense strategy objective is to ensure that sufficient
sensor nodes are protected in each round such that the discrepancy between
the value accepted and the truthful sensed value is below a certain
threshold. We model  the attack-defense interaction as a Stackelberg game,
and we  derive  the  Nash  equilibrium  condition  that  is  sufficient  to
ensure that the sensed data are truthful within a nominal error bound.
We implement a prototype of the proposed strategy and we show through
extensive experiments that our solution provides an effective and efficient
way of protecting sensor networks from attacks.

Dr. Gabriel Ghinita is an Assistant Professor with the Department of
Computer Science, University of Massachusetts, Boston. His research
interests lie in the area of data security and privacy, with focus
on privacy-preserving transformation of microdata, private queries in
location based services and privacypreserving sharing of sensitive
datasets. Prior to joining University of Massachusetts, Dr. Ghinita was
a research associate with the Cyber Center at Purdue University, and a
member of the Center for Education and Research in Information Assurance
and Security (CERIAS). He also held visiting researcher appointments with
the National University of Singapore, Chinese University of Hong Kong and
Hong Kong University. Dr. Ghinita served as reviewer for top journals and
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