Packet dropping and modification are common attacks that can be launched by an adversary to disrupt communication in wireless multihop sensor networks. Many schemes have been proposed to mitigate or tolerate such attacks, but very few can effectively and efficiently identify the intruders. To address this problem, we propose a simple yet effective scheme, which can identify misbehaving forwarders that drop or modify packets. Extensive analysis and simulations have been conducted to verify the effectiveness and efficiency of the scheme.

When wireless sensors are deployed to monitor the working or life conditions of people, the data collected and processed by these sensors may reveal privacy of people. The actual content of sensory data should be concealed to preserve the privacy, but the data concealment feature may be abused by compromised sensors to modify or ill-process data without being caught. Hence, reconciling privacy preservation and intrusion detection, which apparently conflict with each other, is important. This paper studies this problem in the context of sensory data aggregation, a fundamental primitive for efficient operation of sensor networks. A scheme is proposed that can detect ill-performed aggregation without knowing the actual content of sensory data, and therefore allow sensory data to be kept concealed. The results show that, the actual content of raw and aggregated sensory data can be well concealed. Meanwhile, most of ill-performed aggregations can be detected; the ill-performed aggregations that can escape from being detected have only negligible impact on the final aggregation results.

Service-oriented architecture (SOA) provides a scalable and flexible framework for service composition. Service composition algorithms play an important role in selecting services from different providers to reach desirable QoS levels according to the performance requirements of composite services, and improve customer satisfaction. This paper proposes a novel QoS-based dynamic service composition technique for web services with Ant Colony Optimization (ACO) in an optimization approach. The novelty of this work lies with our multi-objective optimal-path selection modeling for QoS-based dynamic web service composition and a new version of ACO algorithm that is proposed to solve this multi-objective optimization problem. The experiments show that the new version of ACO algorithm is very efficient in solving such a problem.

We consider the problem of handling two-link failures in WDM mesh networks. Existing schemes either pre-reserve two backup paths for each demand or compute new backup paths for unprotected demands after the first link failure occurs. Both approaches require a large amount of backup capacity. In this paper, we propose a capacity efficient hybrid protection/restoration scheme for handling two-link failures. The protection component reserves backup capacity intelligently to ensure the majority of the affected demands can be restored using the pre-planned backup paths upon a two-link failure. For the rest of the affected demands, our restoration component dynamically finds new backup paths to quickly restore them. The capacity efficiency and protection/restoration capability of our hybrid scheme are demonstrated through numerical results.

The hybrid wireless-optical broadband-access network (WOBAN) is a promising architecture for access networks. Although the front-end wireless mesh networks in a WOBAN are self-healing, the back-end passive optical networks (PONs) do not have survivability due to their tree topology. We propose a cost-effective protection method for WOBAN that deals with network element failures in the optical part of WOBAN. We define the maximum protection with minimum cost (MPMC) problem and show that the problem can be converted to the minimum cost maximum flow (MCMF) problem. We also present an ILP model for the MCMF problem. Numerical results are reported for applying our algorithm to obtain the optimal solutions for different instances of the MPMC problem.

Packet dropping and modification are common attacks that can be launched by an adversary to disrupt communication in wireless multi-hop sensor networks. Many schemes have been proposed to mitigate the attacks but none can effectively and efficiently identify the intruders. To address the problem, we propose a simple yet effective scheme, which can identify misbehaving forwarders that drop or modify packets. Extensive analysis and simulations using ns2 simulator have been conducted and verified the effectiveness and efficiency of the scheme.

In WDM networks, it is important to maintain the survivability of communication sessions when link failure occurs due to the high bandwidth provided by a fiber link. Especially, link failures have more serious impact on multicast sessions than on unicast ones, making it more critical to protect multicast sessions. For this sake, researchers have proposed tree-based, path-based, and segment-based protection schemes, which however require long restoration time. In this paper, we propose a new solution based on p-cycles to address the problem. Specifically, we identify and address the challenges in applying p-cycles for multicast protection, and develop an intelligent p-cycle (IpC) scheme that forms p-cycles on-demand to protect dynamic multicast requests. Extensive simulations have been conducted to evaluate our IpC scheme, and the results show that it outperforms existing solutions.

Efficiency and security are two basic requirements for sensor network design. However, these requirements could be sharply contrary to each other in some scenarios. For example, in- network data aggregation can significantly reduce communication overhead and thus has been adopted widely as a means to improve network efficiency; however, the adoption of in-network data aggregation may prevent data from being encrypted since it is a prerequisite for aggregation that data be accessible during forwarding. We address this dilemma by proposing a family of secret perturbation-based schemes that can protect sensor data confidentiality without disrupting additive data aggregation. Extensive simulations are also conducted to evaluate the proposed schemes. The results show that our schemes provide confidentiality protection for both raw and aggregated data items with an overhead lower than that of existing related schemes.

Protecting privacy in sensor networks poses new challenges because of the potential incompatibilities between new privacy-preserving mechanisms and mechanisms already implemented in sensor networks (such as in-network data aggregation). To address this problem, we propose in this paper a set of new privacy-preservation data aggregation schemes. Different from past research, our solutions have the following features: supporting data aggregation for a variety of queries; providing privacy protection for both individual data and aggregate data; being resilient to any number of node collusion; being highly efficient.