Trust-based Secure Clustering Protocol In The Internet Of Things

Recently, Internet of Things (IOT) has been widely used to gather information,monitor and react to events from physical world for applications, such as militarysurveillance and smart grid. In those applications, there is a large amount of data thathas relationship with privacy and secrecy for groups and individuals. The security ishard to define in IOT, which is an open environment. In addition, the sensor node isoften deployed in harsh environment with brittle processing capability and limitedresource. Traditional data aggregation focuses on efficiency of data fusion instead of thetrust about node’s behavior. Furthermore, existing crypto and authentication schemesare too complex to prevent the inner attacks in IOT. Therefore How to protect securityof sensing data and the design of a safe clustering protocol become critical in IOT.The defects of current data aggregation schemes were analyzed in details asfollows. Periodic clustering is energy-consuming, and most of data aggregation schemesare not able to detect and resist security problems caused by internal malicious nodes. Inaddition, the node’s state could be impacted by remaining energy. Therefore, atrust-based secure clustering protocol (TBSCP) was proposed. TBSCP addresses trust ofnode’s behavior in data aggregation for IOT, which is used to detect and resist maliciousnodes with forged identities. Then cluster head was re-selected where old cluster was anattacker. Contributions of TBSCP are made as follows. Firstly, trust evaluation of node’sbehavior detection was caused by communications or periodically. By representing trustvalue as an unsigned integer, the storage can be reduced in trust evaluation. In addition,adopting cheat punishment in trust evaluation performs well in detecting maliciousnodes. Secondly, trust evaluation has ability to resist bad mouth attack with a revisedtrust combination method. Recommended trust was corrected by the discount, whichimproves the reliability of recommended trust with additional complexity. Thirdly,TBSCP detects inside attacks in process of data aggregation, and the re-clustering isdone in local region where cluster head was judged as malicious node. Simulationresults show TBSCP has ability to alleviate the effect of malicious nodes, better security,and trust evaluation is light-weight in term of communication and computation.