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A Secure Socially-Aware Content Retrieval Framework for Delay Tolerant Networks

Abstract

Delay Tolerant Networks (DTNs) are sparse mobile ad-hoc networks in which there is typically no complete path between the source and destination. Content retrieval is an important service in DTNs. It allows peer-to-peer data sharing and access among mobile users in areas that lack a fixed communication infrastructure such as rural areas, inter-vehicle communication, and military environments. There are many applications for content retrieval in DTNs. For example, mobile users can find interesting digital content such as music and images from other network peers for entertainment purposes. Vehicles can access live traffic information to avoid traffic delay. Soldiers with wireless devices can retrieve relevant information such as terrain descriptions, weather, and intelligence information from other nodes in a battlefield.

In this dissertation, we propose the design of a secure and scalable architecture for content retrieval in DTNs. Our design consists of five key components: (1) a distributed content discovery service, (2) a routing protocol for message delivery, (3) a buffer management policy to schedule and drop messages in resource-constrained environments, (4) a caching framework to enhance the performance of data access, and (5) a mechanism to detect malicious and selfish behaviors in the network. To cope with the unstable network topology due to the highly volatile movement of nodes in DTNs, we exploit the underlying stable social relationships among nodes for message routing, caching, and placement of the content-lookup service. Specifically, we rely on three key social concepts: social tie, centrality, and social level. Centrality is used to form the distributed content discovery service and the caching framework. Social level guides the forwarding of content requests to a content discovery service node. Once the content provider ID is discovered, social tie is exploited to deliver content requests to the content provider, and content data to the requester node. Furthermore, to reduce the transmission cost, we investigate and propose routing strategies for three dominant communication models in DTNs: unicast (a content is sent to a single node), multicast (a content is sent to multiple nodes), and anycast (a content is sent to any one member in a group of nodes).

We also address several security issues for content retrieval in DTNs. In the presence of malicious and selfish nodes, the content retrieval performance can be deteriorated significantly. To address this problem, we use Public Key Cryptography to secure social-tie records and content delivery records during a contact between two nodes. The unforgeable social-tie records prevent malicious nodes from falsifying the social-tie information, which corrupts the content lookup service placement and disrupts the social-tie routing protocol. The delivery records from which the packet forwarding ratio of a node is computed, helps detect selfish behavior. Furthermore, we propose a blacklist distribution scheme that allows nodes to filter out misbehaving nodes from their social contact graph, effectively preventing network traffic from flowing to misbehaving nodes.

Through extensive simulation studies using real-world mobility traces, we show that our content retrieval scheme can achieve a high content delivery ratio, low delay, and low transmission cost. In addition, our proposed misbehavior detection method can detect insider attacks efficiently with a high detection ratio and a low false positive rate, thus improving the content retrieval performance.

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