Reputation Aware Obfuscation for Mobile Opportunistic Networks

Abstract

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.

Wirelessly Powered Urban Crowd Sensing over Wearables: Trading Energy for Data

“…Today, resource constraints of wearables in terms of their energy (battery lifetime limitations), bandwidth (link capacity and data transmission latency), and computation (sensing and processing costs) constitute the major user adoption barriers. Further, wearables are person-centric in the sense that they collect and communicate information only about their specific wearer, which may raise privacy concerns that need to be addressed with e.g., adaptive obfuscation mechanisms [5]. Finally, small numbers of involved participants may compromise the efficiency of a crowd sensing service and thus scalable solutions are needed for incentivizing user involvement into data sharing.…”

Understanding Information Centric Layer of Adaptive Collaborative Caching Framework in Mobile Disconnection-Prone Networks

“…Mechanism Our distributed reputation aware mechanism built within information-centric layer of CafRepCache integrates four main features: centrality, credit-based feedback, reputation discounting and secondary response (as in line with [1,2,18]) to weigh the value of exchanged content popularities among ego network nodes in order to improve the collaborative caching decisions in highly mobile and disconnection-prone scenarios. Fig.…”

“…Assuming that take social metrics as the first reputation into account for every node, the aggregated content popularity of the content observed from all the neighbours of is now rewritten as: Then, we base on our previous work [1,3,18] to propose credit-based feedback algorithm in order to evaluate the accuracy and usefulness the content popularity value reported from a node in ego networks to a caching point.…”

“…In addition to using historical observations, we also use adaptive expiration timer, reputation discounting and secondary response [1,2,18] specifically tailored for our highly challenged environment in order to increase the accuracy and reliability of the reputation resolution. Each node holds N neighbour reputation records where N can be determined by the node's resource capacity.…”

Towards Better Understanding the Challenges of Reliable and Trust-Aware Critical Communications in the Aftermath of Disaster

“…To mitigate the impact of resource-related attacks by biased, selfish, and malicious nodes we propose a novel, distributed, decentralised, adaptive, collaborative, scalable framework for Trust-Aware Communications in Disaster -TACID. Our framework builds upon lessons learned from AdaptAnon [19] and OCOT-AA [20] and uses localised, predictive, real-time analytics derived from collaborative multidimensional multi-natured complex temporal graphs. TACID is a peer to peer, reputation and trust-aware approach for reliable and secure dissemination of sensitive resource-related communications amongst heterogeneous user groups in highly challenging, large-scale, distributed, delay and disconnection prone environments with hostile nodes present.…”