METrust: A mutual evaluation-based trust model for P2P networks

Abstract

It is necessary to construct an effective trust model to build trust relationship between peers in peer-to-peer (P2P) network and enhance the security and reliability of P2P systems. The current trust models only focus on the consumers evaluation to a transaction, which may be abused by malicious peers to exaggerate or slander the provider deliberately. In this paper, we propose a novel trust model based on mutual evaluation, called METrust, to suppress the peers malicious behavior, such as dishonest evaluation and strategic attack. METrust considers the factors including mutual evaluation, similarity risk, time window, incentive, and punishment mechanism. The trust value is composed of the direct trust value and the recommendation trust value. In order to inhibit dishonest evaluation, both participants should give evaluation information based on peers own experiences about the transaction while computing the direct trust value. In view of this, the mutual evaluation consistency factor and its time decay function are proposed. Besides, to reduce the risk of computing the recommendation trust based on the recommendations of friend peers, the similarity risk is introduced to measure the uncertainty of the similarity computing, while similarity is used to measure credibility. The experimental results show that METrust is effective, and it has advantages in the inhibition of the various malicious behaviors.

A Human Factor Approach to Threat Modeling

“…It supplies the foundation of our theoretical model known as STRIDE-HF (Spoofing, Tampering, Repudiation, Information Disclosure, Denial of Service, and Elevation of privilege -Human Factor). STRIDE has also been used to address many concerns within cybersecurity (e.g., [8,24,28,36]) as well as variations such as STRIDE-per-element and STRIDE-per-interaction [41]. Moreover, Khan et al [24] differentiate the two variations by describing STRIDE-per-element as a more complex method because it analyzes the behavior and operations of each system component; and STRIDE-per-interaction as a more simpler method to perform because it provides protection strategies sufficient enough to protect a system.…”

A Compact Trust Computation and Management Approach for Defending against Derailed Attacks for Wireless Sensor Networks and Its Applications

“…After choosing the shortest path, the data can be transmitted from S 1 to D 1 . The route construction can be obtained by providing a link between the pair of next neighbors, if it satisfies the following constraints: , and the third is distance based link Equations (7), (8) and (12) decide whether the node is valid and it can have a link or not. The values of the conditional parameters cannot have a constant value all the time and they can have a threshold value for computing its validity.…”

“…Then again, recuperation reports from different nodes can permit nodes to rejoin the system [6]- [9]. There exist trust administration plots that address the proposed assault in different types of systems, for example, Traditional Networks [10], Cognitive Radio Networks [11], Peer-to-Peer Networks [12], Ad-hoc Networks [13], and Wireless Sensor Networks [14] [15]. Be that as it may be, no trust administration plan can separate between interim blunders and on-off assaults.…”

Trust Management in a Friend-to-Friend Network

“…Direct trust is trust between two peers that directly exchange information while direct reputation is based on previous experience. In recommended trust, the two peers never exchange information directly but they establish trust relationship based on the recommendation from other peers (Cheng et al, 2012). In the theoretics of trust; trust-like values are of different types, each of which can be represented formally.…”