THE SOCIAL CAPITAL FOUNDATIONS OF TRUST IN GLOBAL AGRI-FOOD SYSTEM TRANSACTIONS

The concept of social capital is defined as a third process (along with individual incentives and authority relationships) for assuring transaction cost efficiency. Social capital is especially relevant to international transactions because cultural differences, large distances, and limited international institutional scope lessen the effectiveness of incentives and authority relationships while social capital can be built within the context of specific international transactions. Methods for building social capital in international settings are explored. A research agenda is articulated as well as a list of managerial implications for using social capital in an international context.Agribusiness,

Reputation aware obfuscation for mobile opportunistic networks

© 2013 IEEE. Current anonymity techniques for mobile opportunistic networks typically use obfuscation algorithms to hide node's identity behind other nodes. These algorithms are not well suited to sparse and disconnection prone networks with large number of malicious nodes and new opportunistic, adaptive. So, new, opportunistic, adaptive fully localized mechanisms are needed for improving user anonymity. This paper proposes reputation aware localized adaptive obfuscation for mobile opportunistic networks that comprises of two complementary techniques: opportunistic collaborative testing of nodes' obfuscation behaviour (OCOT) and multidimensional adaptive anonymisation (AA). OCOT-AA is driven by both explicit and implicit reputation building, complex graph connectivity analytics and obfuscation history analyses. We show that OCOT-AA is very efficient in terms of achieving high levels of node identity obfuscation and managing low delays for answering queries between sources and destinations while enabling fast detection and avoidance of malicious nodes typically within the fraction of time within the experiment duration. We perform extensive experiments to compare OCOT-AA with several other competitive and benchmark protocols and show that it outperforms them across a range of metrics over a one month real-life GPS trace. To demonstrate our proposal more clearly, we propose new metrics that include best effort biggest length and diversity of the obfuscation paths, the actual percentage of truly anonymised sources' IDs at the destinations and communication quality of service between source and destination

A collaborative trust management scheme for emergency communication using delay tolerant networks

Delay Tolerant Network (DTN) comprises of nodes with small and limited resources including power and memory capacity. We propose the use of DTN as an alternate means of communication for the dissemination of emergency information in a post-disaster evacuation operation. We investigate the performance of DTN in providing emergency communication support services under packet dropping attacks. We consider internally motivated attacks where the nodes that are part of the emergency rescue team are compromised with malicious behaviours thereby dropping packets to disrupt the message dissemination during the evacuation operation. A way to mitigating malicious behaviour and improve network performance of DTN is to use incentives in exchanging information between nodes. Unlike existing schemes, we consider the Basic Watchdog Detection System which detects and acts against misbehaving nodes to reduce their overall impact on the network performance. We design a Collaborative Trust Management Scheme (CTMS) which is based on the Bayesian detection watchdog approach to detect selfish and malicious behaviour in DTN nodes. We have evaluated our proposed CTMS through extensive simulations and compared our results with the other existing schemes. Our evaluations show that the use of adequate collaborative strategies between well behaved nodes could improve the performance of Watchdog schemes taking into account the delivery ratio, routing cost and the message delay from the source node to the destination node

ReFIoV: a novel reputation framework for information-centric vehicular applications

In this article, a novel reputation framework for information-centric vehicular applications leveraging on machine learning and the artificial immune system (AIS), also known as ReFIoV, is proposed. Specifically, Bayesian learning and classification allow each node to learn as newly observed data of the behavior of other nodes become available and hence classify these nodes, meanwhile, the K-Means clustering algorithm allows to integrate recommendations from other nodes even if they behave in an unpredictable manner. AIS is used to enhance misbehavior detection. The proposed ReFIoV can be implemented in a distributed manner as each node decides with whom to interact. It provides incentives for nodes to cache and forward others’ mobile data as well as achieves robustness against false accusations and praise. The performance evaluation shows that ReFIoV outperforms state-of-the-art reputation systems for the metrics considered. That is, it presents a very low number of misbehaving nodes incorrectly classified in comparison to another reputation scheme. The proposed AIS mechanism presents a low overhead. The incorporation of recommendations enabled the framework to reduce even further detection time

A collaborative trust management scheme for emergency communication using delay tolerant networks

Delay Tolerant Network (DTN) comprises of nodes with small and limited resources including power and memory capacity. We propose the use of DTN as an alternate means of communication for the dissemination of emergency information in a post-disaster evacuation operation. We investigate the performance of DTN in providing emergency communication support services under packet dropping attacks. We consider internally motivated attacks where the nodes that are part of the emergency rescue team are compromised with malicious behaviours thereby dropping packets to disrupt the message dissemination during the evacuation operation. A way to mitigating malicious behaviour and improve network performance of DTN is to use incentives in exchanging information between nodes. Unlike existing schemes, we consider the Basic Watchdog Detection System which detects and acts against misbehaving nodes to reduce their overall impact on the network performance. We design a Collaborative Trust Management Scheme (CTMS) which is based on the Bayesian detection watchdog approach to detect selfish and malicious behaviour in DTN nodes. We have evaluated our proposed CTMS through extensive simulations and compared our results with the other existing schemes. Our evaluations show that the use of adequate collaborative strategies between well behaved nodes could improve the performance of Watchdog schemes taking into account the delivery ratio, routing cost and the message delay from the source node to the destination node

REPSYS: A robust and distributed incentive scheme for collaborative caching and dissemination in content-centric cellular-based vehicular delay-tolerant networks

In this article, a robust and distributed incentive scheme for collaborative caching and dissemination in content-centric cellular-based vehicular delay-tolerant networks (REPSYS) is proposed. REPSYS is robust because despite taking into account first- and second-hand information, it is resilient against false accusations and praise, and distributed, as the decision to interact with another node depends entirely on each node. The performance evaluation shows that REPSYS is capable, while evaluating each node's participation in the network, of correctly classifying nodes in most cases. In addition, it reveals that there are trade-offs in REPSYS, for example, to reduce detection time of nodes that neither cache nor disseminate other nodes' data, one may sacrifice the system's resilience against false accusations and praise, or even, by penalizing nodes that do not disseminate data, one may temporarily isolate nodes that could contribute to data dissemination

Cohesive subgroup formation: Enabling and constraining effects of social capital in strategic technology alliance networks

formation, subgroup, social capital

Emergency warning messages dissemination in vehicular social networks: A trust based scheme

To ensure users' safety on the road, a plethora of dissemination schemes for Emergency Warning Messages (EWMs) have been proposed in vehicular networks. However, the issue of false alarms triggered by malicious users still poses serious challenges, such as disruption of vehicular traffic especially on highways leading to precarious effects. This paper proposes a novel Trust based Dissemination Scheme (TDS) for EWMs in Vehicular Social Networks (VSNs) to solve the aforementioned issue. To ensure the authenticity of EWMs, we exploit the user-post credibility network for identifying true and false alarms. Moreover, we develop a reputation mechanism by calculating a trust-score for each node based on its social-utility, behavior, and contribution in the network. We utilize the hybrid architecture of VSNs by employing social-groups based dissemination in Vehicle-to-Infrastructure (V2I) mode, whereas nodes' friendship-network in Vehicle-to-Vehicle (V2V) mode. We analyze the proposed scheme for accuracy by extensive simulations under varying malicious nodes ratio in the network. Furthermore, we compare the efficiency of TDS with state-of-the-art dissemination schemes in VSNs for delivery ratio, transmission delay, number of transmissions, and hop-count. The experimental results validate the significant efficacy of TDS in accuracy and aforementioned network parameters. © 2019 Elsevier Inc