Brian J. d'Auriol

Group-Based Trust Management Scheme for Clustered Wireless Sensor Networks

Traditional trust management schemes developed for wired and wireless ad hoc networks are not well suited for sensor networks due to their higher consumption of resources such as memory and power. In this work, we propose a new lightweight group-based trust management scheme (GTMS) for wireless sensor networks, which employs clustering. Our approach reduces the cost of trust evaluation. Also, theoretical as well as simulation results show that our scheme demands less memory, energy, and communication overheads as compared to the current state-of-the-art trust management schemes and it is more suitable for large-scale sensor networks. Furthermore, GTMS also enables us to detect and prevent malicious, selfish, and faulty nodes.

A novel feature selection method based on normalized mutual information

In this paper, a novel feature selection method based on the normalization of the well-known mutual information measurement is presented. Our method is derived from an existing approach, the max-relevance and min-redundancy (mRMR) approach. We, however, propose to normalize the mutual information used in the method so that the domination of the relevance or of the redundancy can be eliminated. We borrow some commonly used recognition models including Support Vector Machine (SVM), k-Nearest-Neighbor (kNN), and Linear Discriminant Analysis (LDA) to compare our algorithm with the original (mRMR) and a recently improved version of the mRMR, the Normalized Mutual Information Feature Selection (NMIFS) algorithm. To avoid data-specific statements, we conduct our classification experiments using various datasets from the UCI machine learning repository. The results confirm that our feature selection method is more robust than the others with regard to classification accuracy.

Achieving Network Level Privacy in Wireless Sensor Networks

Full network level privacy has often been categorized into four sub-categories: Identity, Route, Location and Data privacy. Achieving full network level privacy is a critical and challenging problem due to the constraints imposed by the sensor nodes (e.g., energy, memory and computation power), sensor networks (e.g., mobility and topology) and QoS issues (e.g., packet reach-ability and timeliness). In this paper, we proposed two new identity, route and location privacy algorithms and data privacy mechanism that addresses this problem. The proposed solutions provide additional trustworthiness and reliability at modest cost of memory and energy. Also, we proved that our proposed solutions provide protection against various privacy disclosure attacks, such as eavesdropping and hop-by-hop trace back attacks.

Mobility-Assisted Relocation for Self-Deployment in Wireless Sensor Networks

Sensor network deployment is very challenging due to the hostile and unpredictable nature of environments. The field coverage of wireless sensor networks (WSNs) can be enhanced and consequently network lifetime can be prolonged by optimizing the sensor deployment with a finite number of mobile sensors. In this paper, we introduce a comprehensive taxonomy for WSN self-deployment in which three sensor relocation algorithms are proposed to match the mobility degree of sensor nodes, particle swarm optimization based algorithm (PSOA), relay shift based algorithm (RSBA) and energy efficient fuzzy optimization algorithm (EFOA). PSOA regards the sensors in the network as a swarm, and reorganizes the sensors by the particle swarm optimization (PSO) algorithm, in the full sensor mobility case. RSBA and EFOA assume relatively limited sensor mobility, i.e., the movement distance is bounded by a threshold, to further reduce energy consumption. In the zero mobility case, static topology control or scheduling schemes can be used such as optimal cluster formation. Simulation results show that our approaches greatly improve the network coverage as well as energy efficiency compared with related works.

Optimal Routing in Sensor Networks for In-home Health Monitoring with Multi-factor Considerations

Recent technological advances in wireless sensor networking have opened up new opportunities in healthcare systems. Future medical systems are expected to benefit the most in such areas as in-home assistance, smart nursing homes, and clinical trial. However the network system including body sensor networks and environmental sensor networks are normally comprised of energy constrained nodes. Furthermore, communication interference between multi mode nodes in such a dynamic system is also a challenge. This limitation has led to the crucial need for energy and mobility aware protocols to produce an efficient network. In this paper, we propose an energy and mobility aware multipath routing scheme for sensor networks in a smart homecare application. The remaining battery capacity, distance to the gateway, mobility and queue size of candidate sensor nodes in the local communication range are taken into consideration for next hop relay node selection, and Analytical Hierarchy Process (AHP) is applied for decision making. Simulation results show that this scheme can extend the network lifetime and reduce the packet loss rate and link failure rate since the mobility and buffer capacity is considered.

Network Level Privacy for Wireless Sensor Networks

Full network level privacy spectrum comprises of identity, route, location and data privacy. Existing privacy schemes of wireless sensor networks only provide partial network level privacy. Providing full network level privacy is a critical and challenging problem due to the constraints imposed by the sensor nodes, sensor networks and QoS issues. In this paper, we propose full network level privacy solution that addresses this problem. This solution comprises of Identity, Route and Location (IRL) privacy algorithm and data privacy mechanism, that collectively provides protection against privacy disclosure attacks such as eavesdropping and hop-by-hop trace back attacks.

Energy-aware routing for wireless sensor networks by AHP

Wireless sensor networks (WSNs) are comprised of energy constrained nodes. This limitation has led to the crucial need for energy-aware protocols to produce an efficient network. In this paper, we propose an energy aware geographical multipath routing scheme for WSNs. The distance to the destination location, remaining battery capacity, and queue size of candidate sensor nodes in the local communication range are taken into consideration for next hop relay node selection, and Analytical Hierarchy Process (AHP) is applied for decision making. Simulation results show that this scheme can extend the network lifetime longer than the original geographical routing scheme which only considers distance to the destination location. Moreover, the proposed scheme can reduce the packet loss rate and link failure rate since the buffer capacity is considered.

Trusting Anomaly and Intrusion Claims for Cooperative Distributed Intrusion Detection Schemes of Wireless Sensor Networks

Any unidentified malicious nodes in the network could send faulty anomaly and intrusion claims about the legitimate nodes to the other nodes. Verifying the validity of such claims is a critical and challenging issue that is not considered in existing cooperative-based distributed anomaly and intrusion detection schemes of wireless sensor networks. In this paper, we propose a validation algorithm that addresses this problem. This algorithm utilizes the concept of intrusion-aware reliability that helps to provide adequate reliability at the modest communication cost.

Intrusion-Aware Alert Validation Algorithm for Cooperative Distributed Intrusion Detection Schemes of Wireless Sensor Networks

Existing anomaly and intrusion detection schemes of wireless sensor networks have mainly focused on the detection of intrusions. Once the intrusion is detected, an alerts or claims will be generated. However, any unidentified malicious nodes in the network could send faulty anomaly and intrusion claims about the legitimate nodes to the other nodes. Verifying the validity of such claims is a critical and challenging issue that is not considered in the existing cooperative-based distributed anomaly and intrusion detection schemes of wireless sensor networks. In this paper, we propose a validation algorithm that addresses this problem. This algorithm utilizes the concept of intrusion-aware reliability that helps to provide adequate reliability at a modest communication cost. In this paper, we also provide a security resiliency analysis of the proposed intrusion-aware alert validation algorithm.

The election algorithm for semantically meaningful location-awareness

The technology of multimedia content adaptation based upon the location of a target device can become the long expected killer application of ubiquitous computing. Easy to develop, lightweight, and robust location estimation is the core component of this technology. Until now, location estimation technology remains restricted to highly sophisticated hardware and networking infrastructure where semantics of the location information are defined and controlled by service providers. We aim to lower the technical and infrastructure barriers to allow general users to define and develop the semantically meaningful location systems. This paper presents a simple location estimation method to build radio beacon based location systems in the indoor environments. It employs an realtime learning approach which requires zero prior knowledge. The salient features of our method are low memory requirements and simple computations which make it desirable for location-aware multimedia systems functioning in distributed client-server settings as well as privacy sensitive applications residing on stand alone devices.