The traditional approach of providing network security has been to borrow tools from cryptography and authentication. However, we argue that the conventional view of security based on cryptography alone is not sufficient for the unique characteristics and novel misbehaviors encountered in sensor networks. Fundamental to this is the observation that cryptography cannot prevent malicious or non-malicious insertion of data from internal adversaries or faulty nodes. We believe that in general tools from different domains such as economics, statistics and data analysis will have to be combined with cryptography for the development of trustworthy sensor networks. Following this approach, we propose a reputation-based framework for sensor networks where nodes maintain reputation for other nodes and use it to evaluate their trustworthiness. The framework is modularized; we will analyze each building block in detail in this paper. We will show that this framework provides a scalable, diverse and a generalized approach for countering all types of misbehavior resulting from malicious and faulty nodes.

Reputation-Based Frameworks for High Integrity Sensor Networks

Trust and reputation models in wireless sensor networks (WSN) have been recently proposed by many researches as an innovative solution for guaranteeing an effective security mechanism. They play an important role in defending WSNs such as securing routing and data forwarding protocols, against insider attacks. However, despite of the advantages, reputation models face with several security issues, especially in the case of dishonest recommendation attacks, i.e. slandering, self-promoting and collusion where participants might give recommendations deviated from their real experience. In this paper we survey the current research related to dishonest recommendation attacks in WSNs. We have classified the schemes studied in two main categories: avoiding dishonest recommendations and dealing with dishonest recommendations. We provide an overview and a comparative study of these schemes and highlight the future research directions to address the drawbacks of existing protocols.

http://ieeexplore.ieee.org/iel7/7226732/7244951/07244964.pdf

Dishonest recommendation attacks in wireless sensor networks: A survey

Vampire attacks are considered to be the most vulnerable resource draining attack that is potential in disabling the connectivity of the network by draining mobile node’s energy at a faster rate. This vampire attack is generic as they exploit the characteristic features of the base protocol used for enabling communication in mobile ad hoc networks (MANETs). The core objective of this paper is an attempt to formulate an energy forecasting mechanism using grey theory that ensures reliable network connectivity that gets influenced through the vampire behaviour of mobile nodes under active communication. This Semi-Markov chain-based grey prediction-based mitigation (SMCGPM) is an enhanced Markov chain model that integrates the characteristic features of stochastic theory and grey theory for improving the efficacy in detecting a specific kind of vampire attack called as stretch attack. In this technique, the elucidated data from each mobile node are initially modeled based on Grey model. Then, the residual error is calculated between the forecasted and observed values of energy possessed by the mobile nodes based on their packet forwarding rates. SMCGPM has the capability of predicting the possible transition behaviour of mobile nodes through the estimated residual error derived from the Markov chain matrices. Simulation results confirm that SMCGPM is predominant than the baseline prediction schemes by facilitating an effective detection rate of 29% as they achieve correctness and accuracy in prediction through Semi-Markov chain stochastic properties inspired energy factor prediction.

Semi-Markov chain-based grey prediction-based mitigation scheme for vampire attacks in MANETs

Extending the lifetime of the wireless sensor networks (WSNs), where recharging sensors is not always possible, has been a major concern for researchers for the past decade. In this paper, we study the cooperation between nodes in wireless sensor networks in forwarding packets to others, and we propose a new collaboration technique which stimulates intermediate nodes to forward packets toward their destination. Some nodes show selfish behavior by denying the forwarding packets to other nodes in commercial networks in an effort to preserve their own energy. This paper applies a technique which is used to prolong the network lifetime, based on a node’s energy and trust value, and additionally incorporates fuzzy logic, which stimulates nodes to forward packets by rewarding cooperation. According to simulation results, the proposed approach surpasses the Nuglets (virtual currency) approach and the Reputation approach in network energy and thus prolongs the network lifetime. Additionally, our proposed approach demonstrates better results in the number of dropped packets, PDR and forwarded packets to neighboring nodes.

/pdf/an-efficient-billing-scheme-for-trusted-nodes-using-fuzzy-5g3hz72uep.pdf

An Efficient Billing Scheme for Trusted Nodes Using Fuzzy Logic in Wireless Sensor Networks

In Wireless Sensor Network (WSN), where nodes besides having its inbuilt capability of sensing, processing and communicating data, also possess some risks. These risks expose them to attacks and bring in many security challenges. Therefore, it is imperative to have a secure system where there is perfect confidentiality and correctness to the data being sent from one node to another. Cooperation among the nodes is needed so that they could confidently rely on other nodes and send the data faithfully. However, owing to certain hardware and software faults, nodes can behave fraudulently and send fraudulent information. Nevertheless, since the network is openly accessible, anybody can access the deployment area which breaches the security of WSN. Therefore, it is required to have correct and accurate secure model for WSN to protect the information and resources from attacks and misbehavior. Many researchers are engaged in developing innovative design paradigms to address such nodes by developing key management protocols , secure routing mechanisms and trust management systems. Key management protocols and secure routing cannot itself provide security to WSNs for various attacks. Trust management system can improve the security of WSN. The case study begins by explaining the security issues and challenges in WSN. It discusses the goals, threat models and attacks followed by the security measures that can be implemented in detection of attacks. Here, various types of trust and reputation models are also reviewed. The intent of this case study is to investigate the security related issues and challenges in wireless sensor networks and methodologies used to overcome them. Furthermore, the present case study provides details on how bio-inspired approaches in WSN prove a benefactor in many ways.

Case Study: A Review of Security Challenges, Attacks and Trust and Reputation Models in Wireless Sensor Networks

A Wireless Sensor Networks (Wsn) Is A Network Used For Computing, Sensing. There Are Various Resource Constrains In Wsn Like Energy, Computational Power, Memory, Design Challenges. The Problem In The Sensor Nodes That Nodes May Get Compromised. The Trust Management Schemes Consist Of Effective Tools To Identify Unexpected Behavior Of Sensor Nodes In The Network. Trust Has Been Effective And Provides Secure Mechanism For Managing Each Sensor Node In Network. In This Paper We Investigated Some Trust Techniques And Present The Effective Methodologies To Calculate The Trust Of A Sensor Node To Eliminate The Selfish Or Compromised Nodes In The Network.

A Survey on Detecting Selfish Nodes in Wireless Sensor Networks Using Different Trust Methodologies

For enhancing agricultural productivity, a zigbee based field sensor embedded device (FSED) that senses parameters like humidity, soil moisture and temperature has been proposed. The soil moisture conditions in the near future are predicted using prediction models based on Auto Regressive Moving Average (ARMA) technique and neural networks (NN). The predicted conditions aid the farmers in planning for the type of crop to be cultivated, amount of water and power supply required well ahead of time. The proposed FSED was tested in two different agricultural fields in Tamil Nadu, India.

Enhancing Agricultural Productivity Using Zigbee Based Low-Cost Field Sensor Embedded Device and Prediction Models

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A Survey on Detecting Selfish Nodes in Wireless Sensor Networks Using Different Trust Methodologies

Enhancing Agricultural Productivity Using Zigbee Based Low-Cost Field Sensor Embedded Device and Prediction Models