Energy efficient chain based routing protocol for deterministic node deployment in wireless sensor networks

Wireless Sensor Network (WSN) consists of small sensor devices, which are connected wirelessly for sensing and delivering specific data to Base Station (BS). Routing protocols in WSN becomes an active area for both researchers and industrial, due to its responsibility for delivering data, extending network lifetime, reducing the delay and saving the node’s energy. According to hierarchical approach, chain base routing protocol is a promising type that can prolong the network lifetime and decrease the energy consumption. However, it is still suffering from long/single chain impacts such as delay, data redundancy, distance between the neighbors, chain head (CH) energy consumption and bottleneck. This research proposes a Deterministic Chain-Based Routing Protocol (DCBRP) for uniform nodes deployment, which consists of Backbone Construction Mechanism (BCM), Chain Heads Selection mechanism (CHS) and Next Hop Connection mechanism (NHC). BCM is responsible for chain construction by using multi chain concept, so it will divide the network to specific number of clusters depending on the number of columns. While, CHS is answerable on the number of chain heads and CH nodes selection based on their ability for data delivery. On the other hand, NHC is responsible for next hop connection in each row based on the energy and distance between the nodes to eliminate the weak nodes to be in the main chain. Network Simulator 3 (ns-3) is used to simulate DCBRP and it is evaluated with the closest routing protocols in the deterministic deployment in WSN, which are Chain-Cluster Mixed protocol (CCM) and Two Stage Chain based Protocol (TSCP). The results show that DCBRP outperforms CCM and TSCP in terms of end to end delay, CH energy consumption, overall energy consumption, network lifetime and energy*delay metrics. DCBRP or one of its mechanisms helps WSN applications by extending the sensor nodes lifetime and saving the energy for sensing purposes as long as possible

RAHIM: Robust Adaptive Approach Based on Hierarchical Monitoring Providing Trust Aggregation for Wireless Sensor Networks

In-network data aggregation has a great impact on the energy consumption in large-scale wireless sensor networks. However, the resource constraints and vulnerable deployment environments challenge the application of this technique in terms of security and efficiency. A compromised node may forge arbitrary aggregation value and mislead the base station into trusting a false reading. In this paper, we present RAHIM, a reactive defense to secure data aggregation scheme in cluster-based wireless sensor networks. The proposed scheme is based on a novel application of adaptive hierarchical level of monitoring providing accuracy of data aggregation result in lightweight manner, even if all aggregator nodes and a part of sensors are compromised in the network

Secure and Privacy-Preserving Data Aggregation Protocols for Wireless Sensor Networks

This chapter discusses the need of security and privacy protection mechanisms in aggregation protocols used in wireless sensor networks (WSN). It presents a comprehensive state of the art discussion on the various privacy protection mechanisms used in WSNs and particularly focuses on the CPDA protocols proposed by He et al. (INFOCOM 2007). It identifies a security vulnerability in the CPDA protocol and proposes a mechanism to plug that vulnerability. To demonstrate the need of security in aggregation process, the chapter further presents various threats in WSN aggregation mechanisms. A large number of existing protocols for secure aggregation in WSN are discussed briefly and a protocol is proposed for secure aggregation which can detect false data injected by malicious nodes in a WSN. The performance of the protocol is also presented. The chapter concludes while highlighting some future directions of research in secure data aggregation in WSNs.Comment: 32 pages, 7 figures, 3 table

Secure Data Aggregation Protocol with Byzantine Robustness for Wireless Sensor Networks

Sensor networks are dense wireless networks constituting of small and low-cost sensors that collect and disseminate sensory data. They have gained great attention in recent years due to their ability to offer economical and effective solutions in a variety of fields; and their profound suitability to address mission critical problems that are common in health, transportation, and military applications. “Sensor networks” is a technology that is seen to change the world, and as such their deployment is expected to see a rapid growth. Effective security strategy is essential for any sensor network in order to maintain trustful and reliable functionality, protect sensory information, and ensure network component authenticity. Security models and protocols that are typically used in other types of networks, such as wired networks, are not suitable for sensor networks due to their specific hardware specifications. This thesis highlights some of the research done so far in the area of security of wireless sensor networks and proposes a solution to detect Byzantine behaviour - a challenging security threat that many sensor networks face. The proposed solution’s use of cryptography is kept at a minimum to ensure maximum secure bandwidth. Under this solution, a sensor network continues to work normally until an attack is suspected. Once an attack is suspected, a cryptography scheme is enabled to authenticate suspected nodes and to allow the identification of potential external attacks. If an attack seems to persist after the cryptography scheme has been enabled, the same mechanism is used to identify and isolate potentially compromised nodes. The goal is to introduce a degree of intelligence into such networks and consequently improve reliability of data collection, accuracy of aggregated data, and prolong network lifetime

Security protocols suite for machine-to-machine systems

Nowadays, the great diffusion of advanced devices, such as smart-phones, has shown that there is a growing trend to rely on new technologies to generate and/or support progress; the society is clearly ready to trust on next-generation communication systems to face today’s concerns on economic and social fields. The reason for this sociological change is represented by the fact that the technologies have been open to all users, even if the latter do not necessarily have a specific knowledge in this field, and therefore the introduction of new user-friendly applications has now appeared as a business opportunity and a key factor to increase the general cohesion among all citizens. Within the actors of this technological evolution, wireless machine-to-machine (M2M) networks are becoming of great importance. These wireless networks are made up of interconnected low-power devices that are able to provide a great variety of services with little or even no user intervention. Examples of these services can be fleet management, fire detection, utilities consumption (water and energy distribution, etc.) or patients monitoring. However, since any arising technology goes together with its security threats, which have to be faced, further studies are necessary to secure wireless M2M technology. In this context, main threats are those related to attacks to the services availability and to the privacy of both the subscribers’ and the services providers’ data. Taking into account the often limited resources of the M2M devices at the hardware level, ensuring the availability and privacy requirements in the range of M2M applications while minimizing the waste of valuable resources is even more challenging. Based on the above facts, this Ph. D. thesis is aimed at providing efficient security solutions for wireless M2M networks that effectively reduce energy consumption of the network while not affecting the overall security services of the system. With this goal, we first propose a coherent taxonomy of M2M network that allows us to identify which security topics deserve special attention and which entities or specific services are particularly threatened. Second, we define an efficient, secure-data aggregation scheme that is able to increase the network lifetime by optimizing the energy consumption of the devices. Third, we propose a novel physical authenticator or frame checker that minimizes the communication costs in wireless channels and that successfully faces exhaustion attacks. Fourth, we study specific aspects of typical key management schemes to provide a novel protocol which ensures the distribution of secret keys for all the cryptographic methods used in this system. Fifth, we describe the collaboration with the WAVE2M community in order to define a proper frame format actually able to support the necessary security services, including the ones that we have already proposed; WAVE2M was funded to promote the global use of an emerging wireless communication technology for ultra-low and long-range services. And finally sixth, we provide with an accurate analysis of privacy solutions that actually fit M2M-networks services’ requirements. All the analyses along this thesis are corroborated by simulations that confirm significant improvements in terms of efficiency while supporting the necessary security requirements for M2M networks

Robust data protection and high efficiency for IoTs streams in the cloud

Remotely generated streaming of the Internet of Things (IoTs) data has become a vital category upon which many applications rely. Smart meters collect readings for household activities such as power and gas consumption every second - the readings are transmitted wirelessly through various channels and public hops to the operation centres. Due to the unusually large streams sizes, the operation centres are using cloud servers where various entities process the data on a real-time basis for billing and power management. It is possible that smart pipe projects (where oil pipes are continuously monitored using sensors) and collected streams are sent to the public cloud for real-time flawed detection. There are many other similar applications that can render the world a convenient place which result in climate change mitigation and transportation improvement to name a few. Despite the obvious advantages of these applications, some unique challenges arise posing some questions regarding a suitable balance between guaranteeing the streams security, such as privacy, authenticity and integrity, while not hindering the direct operations on those streams, while also handling data management issues, such as the volume of protected streams during transmission and storage. These challenges become more complicated when the streams reside on third-party cloud servers. In this thesis, a few novel techniques are introduced to address these problems. We begin by protecting the privacy and authenticity of transmitted readings without disrupting the direct operations. We propose two steganography techniques that rely on different mathematical security models. The results look promising - security: only the approved party who has the required security tokens can retrieve the hidden secret, and distortion effect with the difference between the original and protected readings that are almost at zero. This means the streams can be used in their protected form at intermediate hops or third party servers. We then improved the integrity of the transmitted protected streams which are prone to intentional or unintentional noise - we proposed a secure error detection and correction based stenographic technique. This allows legitimate recipients to (1) detect and recover any noise loss from the hidden sensitive information without privacy disclosure, and (2) remedy the received protected readings by using the corrected version of the secret hidden data. It is evident from the experiments that our technique has robust recovery capabilities (i.e. Root Mean Square (RMS) <0.01%, Bit Error Rate (BER) = 0 and PRD < 1%). To solve the issue of huge transmitted protected streams, two compression algorithms for lossless IoTs readings are introduced to ensure the volume of protected readings at intermediate hops is reduced without revealing the hidden secrets. The first uses Gaussian approximation function to represent IoTs streams in a few parameters regardless of the roughness in the signal. The second reduces the randomness of the IoTs streams into a smaller finite field by splitting to enhance repetition and avoiding the floating operations round errors issues. Under the same conditions, our both techniques were superior to existing models mathematically (i.e. the entropy was halved) and empirically (i.e. achieved ratio was 3.8:1 to 4.5:1). We were driven by the question ‘Can the size of multi-incoming compressed protected streams be re-reduced on the cloud without decompression?’ to overcome the issue of vast quantities of compressed and protected IoTs streams on the cloud. A novel lossless size reduction algorithm was introduced to prove the possibility of reducing the size of already compressed IoTs protected readings. This is successfully achieved by employing similarity measurements to classify the compressed streams into subsets in order to reduce the effect of uncorrelated compressed streams. The values of every subset was treated independently for further reduction. Both mathematical and empirical experiments proved the possibility of enhancing the entropy (i.e. almost reduced by 50%) and the resultant size reduction (i.e. up to 2:1)

Security in Distributed, Grid, Mobile, and Pervasive Computing

This book addresses the increasing demand to guarantee privacy, integrity, and availability of resources in networks and distributed systems. It first reviews security issues and challenges in content distribution networks, describes key agreement protocols based on the Diffie-Hellman key exchange and key management protocols for complex distributed systems like the Internet, and discusses securing design patterns for distributed systems. The next section focuses on security in mobile computing and wireless networks. After a section on grid computing security, the book presents an overview of security solutions for pervasive healthcare systems and surveys wireless sensor network security