Fenye Bao

Dynamic Trust Management for Delay Tolerant Networks and Its Application to Secure Routing

Delay tolerant networks (DTNs) are characterized by high end-to-end latency, frequent disconnection, and opportunistic communication over unreliable wireless links. In this paper, we design and validate a dynamic trust management protocol for secure routing optimization in DTN environments in the presence of well-behaved, selfish and malicious nodes. We develop a novel model-based methodology for the analysis of our trust protocol and validate it via extensive simulation. Moreover, we address dynamic trust management, i.e., determining and applying the best operational settings at runtime in response to dynamically changing network conditions to minimize trust bias and to maximize the routing application performance. We perform a comparative analysis of our proposed routing protocol against Bayesian trust-based and non-trust based (PROPHET and epidemic) routing protocols. The results demonstrate that our protocol is able to deal with selfish behaviors and is resilient against trust-related attacks. Furthermore, our trust-based routing protocol can effectively trade off message overhead and message delay for a significant gain in delivery ratio. Our trust-based routing protocol operating under identified best settings outperforms Bayesian trust-based routing and PROPHET, and approaches the ideal performance of epidemic routing in delivery ratio and message delay without incurring high message or protocol maintenance overhead.

Dynamic trust management for internet of things applications

We propose a dynamic trust management protocol for Internet of Things (IoT) systems to deal with misbehaving nodes whose status or behavior may change dynamically. We consider an IoT system being deployed in a smart community where each node autonomously performs trust evaluation. We provide a formal treatment of the convergence, accuracy, and resilience properties of our dynamic trust management protocol and validate these desirable properties through simulation. We demonstrate the effectiveness of our dynamic trust management protocol with a trust-based service composition application in IoT environments. Our results indicate that trust-based service composition significantly outperforms non-trust-based service composition and approaches the maximum achievable performance based on ground truth status. Furthermore, our dynamic trust management protocol is capable of adaptively adjusting the best trust parameter setting in response to dynamically changing environments to maximize application performance.

Trust Management for SOA-Based IoT and Its Application to Service Composition

A future Internet of Things (IoT) system will connect the physical world into cyberspace everywhere and everything via billions of smart objects. On the one hand, IoT devices are physically connected via communication networks. The service oriented architecture (SOA) can provide interoperability among heterogeneous IoT devices in physical networks. On the other hand, IoT devices are virtually connected via social networks. In this paper we propose adaptive and scalable trust management to support service composition applications in SOA-based IoT systems. We develop a technique based on distributed collaborative filtering to select feedback using similarity rating of friendship, social contact, and community of interest relationships as the filter. Further we develop a novel adaptive filtering technique to determine the best way to combine direct trust and indirect trust dynamically to minimize convergence time and trust estimation bias in the presence of malicious nodes performing opportunistic service and collusion attacks. For scalability, we consider a design by which a capacity-limited node only keeps trust information of a subset of nodes of interest and performs minimum computation to update trust. We demonstrate the effectiveness of our proposed trust management through service composition application scenarios with a comparative performance analysis against EigenTrust and PeerTrust.

Trust Management for Encounter-Based Routing in Delay Tolerant Networks

We propose and analyze a class of trust management protocols for encounter-based routing in delay tolerant networks (DTNs). The underlying idea is to incorporate trust evaluation in the routing protocol, considering not only quality-of-service (QoS) trust properties (connectivity) but also social trust properties (honesty and unselfishness) to evaluate other nodes encountered. Two versions of trust management protocols are considered: an equal-weight QoS and social trust management protocol (called trust-based routing) and a QoS only trust management protocol (called connectivity-based routing). By utilizing a stochastic Petri net model describing a DTN behavior, we analyze the performance characteristics of these two routing protocols in terms of message delivery ratio, latency, and message overhead. We also perform a comparative performance analysis with epidemic routing for a DTN consisting of heterogeneous mobile nodes with vastly different social and networking behaviors. The results indicate that trust-based routing approaches the ideal performance of epidemic routing in delivery ratio, while connectivity-based routing approaches the ideal performance in message delay of epidemic routing, especially as the percentage of selfish and malicious nodes present in the DTN system increases. By properly selecting weights associated with QoS and social trust metrics for trust evaluation, our trust management protocols can approximate the ideal performance obtainable by epidemic routing in delivery ratio and message delay without incurring high message overhead.

Scalable, adaptive and survivable trust management for community of interest based Internet of Things systems

An Internet of Things (IoT) system connects a large amount of tags, sensors, and mobile devices to facilitate information sharing, enabling a variety of attractive applications. It challenges the design and evaluation of IoT systems to meet the scalability, compatibility, extendibility, dynamic adaptability and resiliency requirements. In this paper, we design and evaluate a scalable, adaptive and survivable trust management protocol in dynamic IoT environments. Recognizing that entities in an IoT system are connected through social networks of entity owners, we consider a community of interest (CoI) based social IoT where nodes form into communities of interest. Given inter-CoI vs. intra-CoI social connections among entity owners as input, we identify best trust protocol settings for achieving convergence, accuracy, dynamic adaptability and resiliency properties in the presence of dynamically changing conditions and malicious nodes performing trust-related attacks. For scalability, we consider a design by which a node only keeps trust information of a subset of nodes meeting its interest and performs minimum computation to update trust. We validate our design by extensive simulation considering both limited and ideal (unlimited) storage space. The results demonstrate that our trust management protocol using limited storage space achieves a similar performance level compared with the one under ideal storage space, and a newly joining node can quickly build up trust towards other nodes with desirable accuracy and convergence behavior.

Trust management for the internet of things and its application to service composition

The Internet of Things (IoT) integrates a large amount of everyday life devices from heterogeneous network environments, bringing a great challenge into security and reliability management. Recognizing that the smart objects in IoT are most likely human-carried or human-operated devices, we propose a scalable trust management protocol for IoT, with the emphasis on social relationships. We consider multiple trust properties including honesty, cooperativeness, and community-interest to account for social interaction. Each node performs trust evaluation towards a limited set of devices of its interest only. The trust management protocol is event-driven upon the occurrence of a social encounter or interaction event, and trust is aggregated using both direct observations and indirect recommendations. We analyze the effect of trust parameters on trust assessment accuracy and trust convergence time. Our results show that there exists a trade-off between trust assessment accuracy vs. trust convergence time in the presence of false recommendations attacks performed by malicious nodes. We demonstrate the effectiveness of the proposed trust management protocol with a trust-based service composition application. Our results indicate that trust-based service composition significantly outperforms non-trust-based (random) service composition and its performance approaches the maximum achievable performance with global knowledge.

CROWDSAFE: crowd sourcing of crime incidents and safe routing on mobile devices

Crowd sourcing is based on a simple but powerful concept: Virtually anyone has the potential to plug in valuable information. The concept revolves around large groups of people or community handling tasks that have traditionally been associated with a specialist or small group of experts. With the advent of the smart devices, many mobile applications are already tapping into crowd sourcing to report community issues and traffic problems, but more can be done. While most of these applications work well for the average user, it neglects the information needs of particular user communities. We present CROWDSAFE, a novel convergence of Internet crowd sourcing and portable smart devices to enable real time, location based crime incident searching and reporting. It is targeted to users who are interested in crime information. The system leverages crowd sourced data to provide novel features such as a Safety Router and value added crime analytics. We demonstrate the system by using crime data in the metropolitan Washington DC area to show the effectiveness of our approach. Also highlighted is its ability to facilitate greater collaboration between citizens and civic authorities. Such collaboration shall foster greater innovation to turn crime data analysis into smarter and safe decisions for the public.

Trust management in mobile ad hoc networks for bias minimization and application performance maximization

Abstract Trust management for mobile ad hoc networks (MANETs) has emerged as an active research area as evidenced by the proliferation of trust/reputation protocols to support mobile group based applications in recent years. In this paper we address the performance issue of trust management protocol design for MANETs in two important areas: trust bias minimization and application performance maximization. By means of a novel model-based approach to model the ground truth status of mobile nodes in MANETs as the basis for design validation, we identify and validate the best trust protocol settings under which trust bias is minimized and application performance is maximized. We demonstrate the effectiveness of our approach with an integrated social and quality-of-service (QoS) trust protocol (called SQTrust) with which we identify the best trust aggregation setting under which trust bias is minimized despite the presence of malicious nodes performing slandering attacks. Furthermore, using a mission-oriented mobile group utilizing SQTrust, we identity the best trust formation protocol setting under which the application performance in terms of the system reliability of the mission-oriented mobile group is maximized.

Integrated Social and QoS Trust-Based Routing in Delay Tolerant Networks

We propose and analyze a class of integrated social and quality of service (QoS) trust-based routing protocols in mobile ad-hoc delay tolerant networks. The underlying idea is to incorporate trust evaluation in the routing protocol, considering not only QoS trust properties but also social trust properties to evaluate other nodes encountered. We prove that our protocol is resilient against bad-mouthing, good-mouthing and whitewashing attacks performed by malicious nodes. By utilizing a stochastic Petri net model describing a delay tolerant network consisting of heterogeneous mobile nodes with vastly different social and networking behaviors, we analyze the performance characteristics of trust-based routing protocols in terms of message delivery ratio, message delay, and message overhead against connectivity-based, epidemic and PROPHET routing protocols. The results indicate that our trust-based routing protocols outperform PROPHET and can approach the ideal performance obtainable by epidemic routing in delivery ratio and message delay, without incurring high message overhead. Further, integrated social and QoS trust-based protocols can effectively trade off message delay for a significant gain in message delivery ratio and message overhead over traditional connectivity-based routing protocols.

Hierarchical trust management for wireless sensor networks and its application to trust-based routing

In this work, we propose a highly scalable cluster-based hierarchical trust management protocol for wireless sensor networks to effectively deal with selfish or malicious nodes. Unlike prior work, we consider multidimensional trust attributes derived from communication and social networks to evaluate the overall trust of a sensor node. Our peer-to-peer trust evaluation method leverages the cluster-based hierarchical structure for efficient communications. We develop a probability model using stochastic Petri net techniques to analyze the performance of the proposed trust management protocol. We validate the protocol design by comparing subjective trust generated as a result of protocol execution against objective trust obtained from actual node status. We apply our hierarchical trust management protocol to trust-based geographical routing as an application. Our results demonstrate that trust-based geographic routing under identified design settings can approach the ideal performance level achievable by flooding-based routing in message delivery ratio and message delay without incurring substantial message overhead. Furthermore, it can significantly outperform traditional geographic routing protocols that do not use trust concept in selecting forwarding nodes in message delivery ratio over a wide range of design parameter settings.