Assessing Two Dimensions of Interpersonal Trust: Other-Focused Trust and Propensity to Trust

One’s propensity to trust others and others’ trustworthiness are two important aspects of interpersonal trust. Both theory and research suggest that it is possible to distinguish between an individual’s propensity to trust (one’s “trustingness” or the extent to which one feels able to trust others) and their other-focused trust (the extent to which one feels that others are worthy of our trust). However, there is as yet no measure that distinguishes between these two components of trust. In three studies, we examined the psychometrics of a proposed two-dimensional measure of trust that encompasses propensity to trust and other-focused trust components. To test discriminant validity, we also administered measures of personality, personal self-esteem, social capital, propensity to like people, perceived social support, as well as general and personal beliefs in a just world. Factor analyses supported the proposed two-factor model for the new trust measure. Further analyses supported the difference between these measures.

Re-visiting traditional trust measurement: using artefactual field experiments to measure trust and predict micro-lending decisions

PurposeThe purpose of this work is to experimentally measure trust and study its relationship to group loan allocation within a community bank.Design/methodology/approachAn artefactual field experiment is run to capture a measure of trust that mimics aspects of trusting behavior in a community bank. The experimental design and empirical setting take into account risk and altruism, two known confounders of trust measures. Regression analysis is used to estimate the relationship between a novel measure of trust and the loan amount a borrower receives from their rural community bank.FindingsThe trust measure has a statistically significant, positive relationship with loan size. A one standard deviation increase in the trust measure corresponds to a 13.3 percent increase in the loan amount.Social implicationsResults of the study suggest that, for community banks, trust in a borrower plays a large role in screening applicants and therefore determining loan size. Several such banks have considered graduating to commercial credit. However, given the outsize role of trust in lending decisions, it is not clear if commercial lending models – which rely less on social capital – will work.Originality/valueA new trust game is developed that captures relationship-specific measures of directed trust that community bank members have towards each borrower. The trust measure is also context-specific as play in the game is analogous to how community bank members trust some borrowers (more than others) with larger loans. The emphasis on relationship- and context-specific trust measures is key to interpreting results from artefactual field experiments.

Privacy Based Preservation in Multi Cloud Environment Using Attribute Level Trusted Access Measure Technique

The Portent of data security in cloud setting is well studied. There are number of approaches has been discussed for the data security in multi cloud environments. The previous methods suffer to achieve higher performance in data security and privacy preservation. To improve the performance, an attribute level trusted access measure is presented. The method classifies the user data into several classes and for each class of attributes different access restriction has been enforced. The access between different cloud has been restricted based on the attribute level trusted access measure (ALTAM). The ALTAM measure for each request has been estimated based on the depth of privacy has been accessed by the request and the number of data values the user has access in the cloud and outside the cloud. Based on all these the method estimates the trust measure. According to the trust measure, the method restrict the access of data in multi cloud environments. The method produces efficient result in access restriction and privacy preservation.

A Biogeography-Based Optimization (BBO) With AOMDV for Mitigating Black Hole Attacks

The availability of smaller, cheaper and a lot more powerful mobile devices has made the Mobile Ad Hoc Networks (MANETs) emerge as a fast-growing research area. A Black Hole Attack can harm the mobile nodes by giving false replies to its source which can have the path that is the shortest to the destination without it checking the routing table. The primary aspect relaying the strategy of the trust route was the generation of a route by the selection of nodes that have high trust; thus, the nodes having the maximum trust measure with a better probability of routing success. One of the recently proposed metaheuristic that is applied successfully to various problems of optimization owing to its efficiency and simplicity is the Biogeography-based optimization (BBO). The BBO generally performs well for the problems of low-dimensional optimization but the performance keeps deteriorating rapidly for high-dimensional problems. In this work, proposed a BBO – Ad-hoc on Demand Multipath Distance Vector (AOMDV) method to mitigate black hole attack.

Multi Model Transmission Analysis Based Efficient Intrusion Detection System for Improved Performance

The problem of intrusion detection in network systems has been well studied. There exist numerous techniques in the mitigation of intrusion attacks, but they struggle to produce expected performance. To solve this issue, an efficient multi model analysis based approach is described in this article. The network systems faces various challenges like modification, distributed denial of service, spoofing, eavesdrop and so on. The proposed multi model approach monitors the network packets in different level by analyzing the payload, path, host and frequency of incoming packets. The method considers the frequency of packets, path being used, and frequency of transmission, host details and payload features. For each features, the method computes the trust measure which has been used to classify the packets. The method estimates cumulative multi mode trust weight towards any packet being received. According to the weight measures of different analysis, the attack has been identified. The proposed method improves the performance of intrusion detection and increases the accuracy.

A NOVEL USER PROFILE-BASED FUZZY APPROACH FOR EVALUATING TRUST IN SEMANTIC WEB

ABSTRACT: As a developed World Wide Web architecture, the Semantic Web collects traditional web contents with a formal and understandable semantic using a machine. The main purpose of the Semantic Web is to increase automation, web information processing, and improve interactions and collaboration among information systems. The subject of trust is one of the main challenges in the semantic web. Since different tools and individuals exist in the semantic web, a certain measure of trust in an entity cannot be used and a central system is responsible for data collection and estimating the reliability. In this study, a fuzzy system is used to evaluate the trust measure in the semantic web. For this purpose, the user profile data including a list of pages, user sessions, and visited pages in each session, and the time of page viewings are used as semantic parameters. After determining the general framework of trust in the semantic web, the effectiveness of the above mentioned semantic parameters on the trust measure is investigated and effective parameters are used for evaluation in the fuzzy system. The experiment results show that the proposed fuzzy method with a mean absolute error of 2.5% and an average precision of 97.5% could achieve the right value of trust in the semantic web. ABSTRAK: Sebagai senibina World Wide Web, Semantik Web mengumpul kandungan web tradisional bersama semantik formal dan mudah difahami menggunakan mesin. Tujuan utama Semantik Web adalah bagi meningkatkan automasi, pemprosesan maklumat web, dan meningkatkan interaksi dan kerjasama antara sistem maklumat. Kepercayaan adalah salah satu cabaran utama dalam web semantik. Disebabkan perbezaan alatan dan pelbagai individu wujud dalam web semantik, langkah tertentu sebagai entiti dipercayai tidak dapat digunakan dan sistem pusat adalah bertanggungjawab bagi pengumpulan data dan kebolehpercayaan anggaran. Dalam kajian ini, sistem rawak telah digunakan bagi menilai tahap kepercayaan dalam web semantik. Bagi tujuan ini, data profil pengguna termasuk senarai halaman, sesi pengguna, dan halaman yang dikunjungi dalam setiap sesi, dan masa paparan halaman telah digunakan sebagai parameter semantik. Selepas menentukan rangka umum kepercayaan dalam web semantik, keberkesanan parameter semantik yang dinyatakan di atas pada ukuran kepercayaan telah disiasat dan parameter yang berkesan telah digunakan bagi penilaian sistem rawak. Keputusan eksperimen menunjukkan bahawa kaedah rawak yang dicadangkan dengan ralat mutlak purata sebanyak 2.5% dan ketepatan purata sebanyak 97.5% dapat mencapai nilai kepercayaan yang benar dalam web semantik.