By Topic

Overcoming Adversaries in Sensor Networks: A Survey of Theoretical Models and Algorithmic Approaches for Tolerating Malicious Interference

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Young, M. ; David R. Cheriton Sch. of Comput. Sci., Univ. of Waterloo, Waterloo, ON, Canada ; Boutaba, R.

Interference is an unavoidable property of the wireless communication medium and, in sensor networks, such interference is exacerbated due to the energy-starved nature of the network devices themselves. In the presence of antagonistic interference, reliable communication in sensor networks becomes an extremely challenging problem that, in recent years, has attracted significant attention from the research community. This survey presents the current state of affairs in the formulation of theoretical models for adversarial interference in sensor networks and the different algorithmic remedies developed by the research community. There is a particular focus on jamming adversaries and Byzantine faults as these capture a wide range of benign faults as well as malicious attacks. The models in the literature are examined and contrasted with the aim of discerning the underlying assumptions that dictate analytical bounds with regards to feasibility and a number of performance metrics such as communication complexity, latency, and energy efficiency. Limitations are also highlighted with a focus on how various results impact real world applications and, conversely, how the current sensor network technology informs newer models. Finally, directions for future research are discussed.

Published in:

Communications Surveys & Tutorials, IEEE  (Volume:13 ,  Issue: 4 )