Trustworthiness Of Sensor Nodes Research Articles

A blockchain-based trust management method for Internet of Things

In Internet of things (IoT), one of the main concepts is wireless sensor networks where there are a large of resource-constrained sensor nodes. With the wide application of Internet of things (IoT), these resource-constrained sensor nodes have to suffer from more security threats. One of possible solutions is to establish a trustworthy IoT environment where the interactions are based on the trustworthiness of sensor nodes. More and more scholars focus on studying trust management and trust evaluation in IoT, but there is few research in ensuring that the feedbacks used in the trust evaluating process is trustworthy. Furthermore, a resource-constrained IoT node does not have enough memory to satisfy the usage of trust computation and maintenance. To solve the problem, this paper proposes a blockchain-based trust management mechanism (BBTM), where the trustworthiness of sensor nodes will be evaluated by the mobile edge nodes. BBTM can create smart contracts for trust computation and verify the computation process. We analyze BBTM performance in terms of trust accuracy, convergence, and resiliency against attacks. In addition, we also compare BBTM with other methods. Experimental results demonstrate the effectiveness of the proposed method.

An Energy-Efficient Key Management Scheme using Trust Model for Wireless Sensor Network

<p>In wireless sensor networks (WSNs), secret shared keys must be established with the neighboring nodes in order to achieve secure communication. The challenge issues for secured communication in WSN are the Key management. Location Dependent Key (LDK) management is a suitable scheme when compared to other location based key management schemes because of lesser memory space requirement and lesser number of keys to be stored on each sensor node. However, the LDK is affected by communication interference problem which is solved by the key is distributed based on trust model. The distributed key updates and revocation processes are effectively resist inside attackers. An energy-efficient Key Management with Trust Model (KM-TM) for WSNs is proposed to achieve the secured communication and the nodes are resisting from the attackers. The performances of proposed KM-TM for WSNs are evaluated in terms of trustworthiness of sensor nodes and security breaches more effectively. </p>

Agent based trusted neighbor identification in Wireless Sensor Networks

Wireless Sensor Networks (WSNs) have been extensively used in various applications such as environmental monitor- ing, industrial monitoring, agriculture, green house monitoring, structural monitoring, passive localization, tracking and battle- field surveillance. Sensor nodes in these applications are required to sense and process the physical conditions like temperature, pressure, humidity, rainfall, fog, etc. and route the data to a predefined base station or a sink node. In most of these applications, sensor nodes are deployed in public domain and they are prone to be attacked by many types of attacks where in the data con- fidentiality, integrity and authentication are compromised. Some times, it is difficult to correctly locate the compromised data unless we use autonomous third party that uses intelligent software techniques to safeguard our data and correctly means route it to destined party. In this paper, we propose a Trust based Neighbor Identification in Wireless Sensor Networks (TNIWSN) using agents to identify trustworthy nodes in a network. The trusted neighbor identification is necessary for routing the data through trustworthy neighbors and avoid untrusted neighbors that are compromised by various threats. The proposed scheme operates in following phases. (1) Defining safeguard agency that consists of one static agent known as Safeguard Manager Agent (SMA) and one mobile agent known as Trusted Neighbor Agent (TNA) and a knowledge base. (2) Safeguard agency identifies trustworthy neighbor nodes using static and mobile agents by means of trust model that comprise of the probability model and Message Authentication Code (MAC) model. The probability model identifies trusted neighbors based upon the probabilities of trustworthiness of wireless channel and the trustworthiness of sensor node. MAC model encrypts the message using the two keys k 1a ndk2 are generated with k-ERF (Error Resilient Function) key generation process to ensure the trustworthiness of neighbors identified by the probability model. (3) MACs are dynamically computed by agents (either on sender node or on neighbor node) by generating keys with the help of k-ERF. (4) Agents effectively identify possible security threats on wireless channel and node. Simulation analysis shows that TNIWSN outperforms Neighbor based Malicious Node Detection (NMND) in Wireless Sensor Networks in terms of average success ratio and memory overhead.