scispace - formally typeset
W

Wade Trappe

Researcher at Rutgers University

Publications -  295
Citations -  16889

Wade Trappe is an academic researcher from Rutgers University. The author has contributed to research in topics: Wireless network & Communication channel. The author has an hindex of 59, co-authored 284 publications receiving 15655 citations. Previous affiliations of Wade Trappe include University of Texas at Austin & Bell Labs.

Papers
More filters
Proceedings ArticleDOI

The feasibility of launching and detecting jamming attacks in wireless networks

TL;DR: This paper proposes four different jamming attack models that can be used by an adversary to disable the operation of a wireless network, and evaluates their effectiveness in terms of how each method affects the ability of a Wireless node to send and receive packets.
Proceedings ArticleDOI

Radio-telepathy: extracting a secret key from an unauthenticated wireless channel

TL;DR: This paper presents a protocol that allows two users to establish a common cryptographic key by exploiting special properties of the wireless channel: the underlying channel response between any two parties is unique and decorrelates rapidly in space.
Journal ArticleDOI

Jamming sensor networks: attack and defense strategies

TL;DR: In this paper, the authors survey different jamming attacks that may be employed against a sensor network and highlight the challenges associated with detecting jamming, and propose two different but complementary approaches.
Proceedings ArticleDOI

Enhancing Source-Location Privacy in Sensor Network Routing

TL;DR: This paper provides a formal model for the source-location privacy problem in sensor networks and examines the privacy characteristics of different sensor routing protocols, and devised new techniques to enhance source- location privacy that augment these routing protocols.
Proceedings ArticleDOI

Robust statistical methods for securing wireless localization in sensor networks

TL;DR: This paper develops robust statistical methods to make localization attack-tolerant, and proposes an adaptive least squares and least median squares position estimator that has the computational advantages of least squares in the absence of attacks and is capable of switching to a robust mode when being attacked.