Reputation-Based Cooperative Detection Model of Selfish Nodes in Cluster-Based QoS-OLSR Protocol

Dai

Human Centered Computing

et al. 2016

Abstract. Localization is one of the most important technologies in wireless sensor networks. Range-based localization methods are widely used in many applications. However, traditional RSS-based methods cannot work well in scenarios with unreliable anchors. A reputation scheme based distributed location verification model called UNDA is proposed to solve the unreliable node recognizing issue in such scenarios. UNDA combines direct reputation and third-party reputation to recognize unreliable anchor. Furthermore, a credibilityupdating scheme is presented to make the third-party reputation more accuracy. Extensive simulation experiments indicate that the location verification algorithm has relatively high accuracy as well as low communication overhead, and the convergence of UNDA is rapid. The UNDA can be a used as an underlayer for traditional RSS-based localization algorithms to realize reliable localization.

Section: Reputation Modelmentioning

confidence: 99%

A Node Localization Verification Model for WSN

Dai

Human Centered Computing

et al. 2016

“…In this simple approach, we do not consider the case where certain nodes will deliberately announce that they are farther away from the sink in order to delay the process or try to launch attacks. This kind of malicious behaviour is studied in [38], where the authors propose a solution based on the reputation of nodes. This kind of solutions could be applied to our protocols and are part of our future works.…”

Section: Attack Detection Perspectivementioning

confidence: 99%

Evaluation of Secure Multi-Hop Node Authentication and Key Establishment Mechanisms for Wireless Sensor Networks

Mansour

Chalhoub

Lafourcade

2014

JSAN

Designing secure authentication mechanisms in wireless sensor networks in order to associate a node to a secure network is not an easy task due to the limitations of this type of networks. In this paper, we propose different multi-hop node authentication protocols for wireless sensor networks. For each protocol, we provide a formal proof to verify the security of our proposals using Scyther, which is an automatic cryptographic protocols verification tool. We also provide implementation results in terms of execution time consumption obtained by real measurements on TelosB motes. These protocols offer different security mechanisms depending on the design of the protocol itself. Moreover, we evaluate the overhead of protection of each solution by studying the effect on execution time overhead of each protocol. Finally, we propose a mechanism to detect possible attack based on our evaluation results.

“…RCMs have been widely studied in various fields of distributed networks to support secure and trustworthy communications and collaborations among participants [4][5][6][7][8][9][10][11][12].…”

Section: Related Workmentioning

confidence: 99%

“…As a key scheme for managing trust, the reputation computation model (RCM) has been introduced as an effective approach to characterize and quantify nodes' behaviors for MWNs. Although a number of RCMs and reputation-based trust functions for MWNs have been proposed in the literature, all existing RCMs were based on the direct observation of layer-specifics to evaluate the node reputation, thus ignoring many key factors of reputation in other layers [4][5][6][7][8][9][10][11][12] such as node forwarding behaviors at the network layer, channel collisions at the MAC layer, channel quality measures at the physical layer and node access behaviors at the application layer. Moreover, they did not take into account the bad mouthing attack where attackers provide dishonest recommendations to frame up good parties and/or boost trust values of malicious peers.…”

Section: Introductionmentioning

confidence: 99%

CRM: A New Dynamic Cross-Layer Reputation Computation Model in Wireless Networks

Lin¹,

Hu²,

Ma³

et al. 2014

The Computer Journal

Multi-hop wireless networks (MWNs) have been widely accepted as an indispensable component of next-generation communication systems due to their broad applications and easy deployment without relying on any infrastructure. Although showing huge benefits, MWNs face many security problems, especially the internal multi-layer security threats being one of the most challenging issues. Since most security mechanisms require the cooperation of nodes, characterizing and learning actions of neighboring nodes and the evolution of these actions over time is vital to construct an efficient and robust solution for security-sensitive applications such as social networking, mobile banking, and teleconferencing. In this paper, we propose a new dynamic cross-layer reputation computation model named CRM to dynamically characterize and quantify actions of nodes. CRM couples uncertainty based conventional layered reputation computation model with cross-layer design and multi-level security technology to identify malicious nodes and preserve security against internal multi-layer threats. Simulation results and performance analyses demonstrate that CRM can provide rapid and accurate malicious node identification and management, and implement the security preservation against the internal multi-layer and bad mouthing attacks more effectively and efficiently than existing models.