An energy-efficient and scalable slot-based privacy homomorphic encryption scheme for WSN-integrated networks

YesWith the advent of Wireless Sensor Networks (WSN) and its immense popularity in a wide range of applications, security has been a major concern for these resource-constraint systems. Alongside security, WSNs are currently being integrated with existing technologies such as the Internet, satellite, Wi-Max, Wi-Fi, etc. in order to transmit data over long distances and hand-over network load to more powerful devices. With the focus currently being on the integration of WSNs with existing technologies, security becomes a major concern. The main security requirement for WSN-integrated networks is providing end-to-end security along with the implementation of in-processing techniques of data aggregation. This can be achieved with the implementation of Homomorphic encryption schemes which prove to be computationally inexpensive since they have considerable overheads. This paper addresses the ID-issue of the commonly used Castelluccia Mykletun Tsudik (CMT) [12] homomorphic scheme by proposing an ID slotting mechanism which carries information pertaining to the security keys responsible for the encryption of individual sensor data. The proposed scheme proves to be 93.5% lighter in terms of induced overheads and 11.86% more energy efficient along with providing efficient WSN scalability compared to the existing scheme. The paper provides analytical results comparing the proposed scheme with the existing scheme thus justifying that the modification to the existing scheme can prove highly efficient for resource-constrained WSNs

Energy-efficient privacy homomorphic encryption scheme for multi-sensor data in WSNs

YesThe recent advancements in wireless sensor hardware ensures sensing multiple sensor data such as temperature, pressure, humidity, etc. using a single hardware unit, thus defining it as multi-sensor data communication in wireless sensor networks (WSNs). The in-processing technique of data aggregation is crucial in energy-efficient WSNs; however, with the requirement of end-to-end data confidentiality it may prove to be a challenge. End-to-end data confidentiality along with data aggregation is possible with the implementation of a special type of encryption scheme called privacy homomorphic (PH) encryption schemes. This paper proposes an optimized PH encryption scheme for WSN integrated networks handling multi-sensor data. The proposed scheme ensures light-weight payloads, significant energy and bandwidth consumption along with lower latencies. The performance analysis of the proposed scheme is presented in this paper with respect to the existing scheme. The working principle of the multi-sensor data framework is also presented in this paper along with the appropriate packet structures and process. It can be concluded that the scheme proves to decrease the payload size by 56.86% and spend an average energy of 8-18 mJ at the aggregator node for sensor nodes varying from 10-50 thereby ensuring scalability of the WSN unlike the existing scheme

Framework for integrated oil pipeline monitoring and incident mitigation systems

Wireless Sensor Nodes (motes) have witnessed rapid development in the last two decades. Though the design considerations for Wireless Sensor Networks (WSNs) have been widely discussed in the literature, limited investigation has been done for their application in pipeline surveillance. Given the increasing number of pipeline incidents across the globe, there is an urgent need for innovative and effective solutions for deterring the incessant pipeline incidents and attacks. WSN pose as a suitable candidate for such solutions, since they can be used to measure, detect and provide actionable information on pipeline physical characteristics such as temperature, pressure, video, oil and gas motion and environmental parameters. This paper presents specifications of motes for pipeline surveillance based on integrated systems architecture. The proposed architecture utilizes a Multi-Agent System (MAS) for the realization of an Integrated Oil Pipeline Monitoring and Incident Mitigation System (IOPMIMS) that can effectively monitor and provide actionable information for pipelines. The requirements and components of motes, different threats to pipelines and ways of detecting such threats presented in this paper will enable better deployment of pipeline surveillance systems for incident mitigation. It was identified that the shortcomings of the existing wireless sensor nodes as regards their application to pipeline surveillance are not effective for surveillance systems. The resulting specifications provide a framework for designing a cost-effective system, cognizant of the design considerations for wireless sensor motes used in pipeline surveillance

Machine Learning in Wireless Sensor Networks: Algorithms, Strategies, and Applications

Wireless sensor networks monitor dynamic environments that change rapidly over time. This dynamic behavior is either caused by external factors or initiated by the system designers themselves. To adapt to such conditions, sensor networks often adopt machine learning techniques to eliminate the need for unnecessary redesign. Machine learning also inspires many practical solutions that maximize resource utilization and prolong the lifespan of the network. In this paper, we present an extensive literature review over the period 2002-2013 of machine learning methods that were used to address common issues in wireless sensor networks (WSNs). The advantages and disadvantages of each proposed algorithm are evaluated against the corresponding problem. We also provide a comparative guide to aid WSN designers in developing suitable machine learning solutions for their specific application challenges.Comment: Accepted for publication in IEEE Communications Surveys and Tutorial

A Review of the Enviro-Net Project

Ecosystems monitoring is essential to properly understand their development and the effects of events, both climatological and anthropological in nature. The amount of data used in these assessments is increasing at very high rates. This is due to increasing availability of sensing systems and the development of new techniques to analyze sensor data. The Enviro-Net Project encompasses several of such sensor system deployments across five countries in the Americas. These deployments use a few different ground-based sensor systems, installed at different heights monitoring the conditions in tropical dry forests over long periods of time. This paper presents our experience in deploying and maintaining these systems, retrieving and pre-processing the data, and describes the Web portal developed to help with data management, visualization and analysis.Comment: v2: 29 pages, 5 figures, reflects changes addressing reviewers' comments v1: 38 pages, 8 figure

n-Tier Modelling of Robust Key management for Secure Data Aggregation in Wireless Sensor Network

Security problems in Wireless Sensor Network (WSN) have been researched from more than a decade. There are various security approaches being evolving towards resisting various forms of attack using different methodologies. After reviewing the existing security approaches, it can be concluded that such security approaches are highly attack-specific and doesnt address various associated issues in WSN. It is essential for security approach to be computationally lightweight. Therefore, this paper presents a novel analytical modelling that is based on n-tier approach with a target to generate an optimized secret key that could ensure higher degree of security during the process of data aggregation in WSN. The study outcome shows that proposed system is computationally lightweight with good performance on reduced delay and reduced energy consumption. It also exhibits enhanced response time and good data delivery performance to balance the need of security and data forwarding performance in WSN