Analytical Study of Implementation Issues of Elliptical Curve Cryptography for Wireless Sensor networks

Wireless Sensor Networks (WSNs) are used in many applications in military, environmental, and health-related areas. These applications often include the monitoring of sensitive information such as enemy movement on the battlefield or the location of personnel in a building. Security is important in WSNs. However, WSNs suffer from many constraints, including low computation capability, small memory, limited energy resources, susceptibility to physical capture, and the use of insecure wireless communication channels. These constraints make security in WSNs a challenge. In this paper, we try to explore security issue in WSN. First, the constraints, security requirements and attacks with their corresponding countermeasures in WSNs are explained. Individual sensor nodes are subject to compromised security. An adversary can inject false reports into the networks via compromised nodes. Furthermore, an adversary can create a Gray hole by compromised nodes. If these two kinds of attacks occur simultaneously in a network, some of the existing methods fail to defend against those attacks. The Ad-hoc On Demand Distance (AODV) Vector scheme for detecting Gray-Hole attack and Statistical En-Route Filtering is used for detecting false report. For increasing security level, the Elliptic Curve Cryptography (ECC) algorithm is used. Simulations results obtain so far reduces energy consumption and also provide greater network security to some extent.

Wireless Sensor Networks (WSN) are becoming an increasingly popular technology for data collection. Since data is of significant importance in the current era, security of the data is essentially indispensable. Because the nodes deployed are usually on an unattended environment, security of the data communicated between the wireless sensor nodes is of utmost importance. A secure established connection between two nodes in a WSN promises a number of preventive measures against different threats but the main issue is to establish the secure connection between any two nodes in a wireless sensor network. With limited resources on a wireless sensor node in mind, this research focuses on establishing Symmetric-Pairwise keys between any two WSN nodes using Public-Key Cryptography (pkc) — which in this case is Elliptic Curve Cryptography.

In wireless sensor networks, data aggregation allows in-network processing, which leads to reduced packet transmissions and reduced redundancy, and thus is helpful to prolong the overall lifetime of wireless sensor networks. In current studies, Elliptic Curve ElGamal homomorphic encryption algorithm has been widely used to protect end-to-end data confidentiality. However, these works suffer from the expensive mapping function during decryption. If the aggregated results are huge, the base station has no way to gain the original data due to the hardness of the elliptic curve discrete logarithm problem. Therefore, these schemes are unsuitable for the large-scale WSNs. In this paper, we propose a secure energy-saving data aggregation scheme designed for the large-scale WSNs. We employ Okamoto-Uchiyama homomorphic encryption algorithm to protect end-to-end data confidentiality, use MAC to achieve in-network false data filtering, and utilize the homomorphic MAC algorithm to achieve end-to-end data integrity. Two popular IEEE 802.15.4-compliant wireless sensor network platforms, Tmote Sky and iMote 2 have been used to evaluate the efficiency and feasibility of our scheme. The results demonstrate that our scheme achieved better performance in reducing energy consumption. Moreover, system delay, especially decryption delay at the base station, has been reduced when compared to other state-of-art methods.

Cryptography is the field for mathematically transforming messages to protect their confidentiality from eavesdropping. It is an essential foundation for all secure protocols. This chapter is a concise review of cryptography used in wireless sensor networks (WSNs) beginning with background on symmetric key encryption and the Diffie–Hellman key agreement protocol for sharing secret keys. Asymmetric key encryption and its usefulness for digital signatures and digital certificates are described. Finally, the unique constraints on the use of cryptography in wireless sensor networks are reviewed. A short survey of the literature is presented, which mainly deal with evaluating ciphers (particularly elliptic curve cryptography), proposing new approaches for key management, and implementing identity-based cryptography.

In recent years, the number of super high-rise buildings is increasing due to the rapid development of economy and construction technology. It is important to evaluate the health condition of super high-rise buildings to make them operate safely. However, conventional structural health monitoring (SHM) system requires a great number of wires to connect the sensors, power sources, and the data acquisition equipment, which is an extremely difficult process to plan the layout of all wires. Hence, one of the usually used compromising approaches is to limit the number of sensors to reduce the usage of wires. Recently, wireless sensor networks and cloud platform have been widely used in SHM system for super high-rise buildings because of their convenient installation, low maintenance cost, and flexible deployment. This paper presents a comprehensive review of the existing SHM system for super high-rise buildings based on wireless sensor network and cloud platform, which usually consists of sensing network subsystem, data acquisition subsystem, data transmission subsystem, and condition evaluation subsystem. This paper also reviews the crucial techniques and typical examples of SHM system used for famous super high-rise buildings. In addition, the existing difficulties in wireless sensor network and cloud platform based SHM system for super high-rise buildings and the future research directions are discussed and summarized.

In this paper, we propose an enhanced window-based mutual opposite form (EW-MOF) for scalar multiplication with ECC in WSNs. The proposed EW-MOF combines MOF with an enhanced window method that can reduce not only pre-computation time and memory usage, but also average key generation time that includes pre-computation time in each sensor node. Our analysis has shown that the proposed EW-MOF requires a smaller number of essential pre-computed points than the one's complement. Therefore, it is very suitable for WSNs. Simulation results show that the proposed EW-MOF is 24.69% faster than the one's complement method, which is the best method available, in the average key generation time of ECC that includes pre-computation time under different field sizes. In summary, the proposed EW-MOF is more feasible than the one's complement for wireless sensor networks in terms of key generation time and power saving.

In the recent years, wireless sensor networks have attracted a lot of attention due to their broad application areas. In many application scenarios, hundreds or thousands of sensor nodes may be deployed in the physical environment. To design, implement, manage and maintain such large-scale networks efficiently is a major challenge which requires an integrated middleware development approach. In this paper, we focus on the development of a simulation platform specifically designed to support the development of sensor network middleware services. This novel platform is designed in a modular manner to facilitate the rapid integration and testing of different middleware algorithms and services. We present the simulator's software architecture and its operation. A case study to illustrate the usage of our simulation platform is also presented. The simulation platform shows potentials to support the research and development of middleware servicesfor wireless sensor networks.

Wireless Sensor Networks (WSNs), comprising of tiny nodes with limited energy, computational and communication resources, are being widely used in various application areas ranging from pollution and weather monitoring to military. Even though every application may not require data to be exchanged in a secure manner, few WSN applications may have certain security requirements. The data is encrypted by a sender and sent over the wireless links and the same is decrypted at the receiver. To meet this purpose, symmetric key cryptographic (SKC) algorithms may be used. Such SKC primitives require keys to be made available before carrying out the data transfer between the nodes. Alternately, Public Key Cryptographic techniques, such as RSA algorithm can be considered. Even though, RSA is a popular algorithm providing good security level, it is computationally intensive involving large key sizes. The RSA can not be used in WSNs, as the nodes have limited resources. Presently, it is infeasible to implement the RSA algorithm using any of the WSN nodes commercially available. Elliptic curve cryptography (ECC), another public key cryptographic (PKC) algorithm providing same level of security with smaller key size requirements, can be used as an alternative in order to provide security in WSN applications. ECC encryption and decryption use domain parameters, which includes the Generator point to be published. In most of the outdoor WSN applications, the deployment of the nodes is random and the nodes could be captured and an attacker could launch man-in-middle (MIM) attack, and break the public key thereby leading to security breach in the network. A technique to overcome such an attack is proposed in this work and the same is compared with two other similar approaches.

Integration of wireless sensor network into cloud computing is a growing paradigm that supports a massive amount of applications in cloud computing, optimization of resources required in the machines. This integration requires the optimization of resources to efficiently complete the different tasks in the devices at cloud platform. This optimization can be done using load scheduling algorithms. These algorithms reduce overload and achieve higher throughput by maximizing the machine utilization concerning cost stabilization. There are lots of methods like First Come First Serve, Min-Min, Particle Swarm Optimization (PSO) for optimizing the load but we use Particle Swarm Optimization as it obtains the motivation from the social behavior of the flock of birds and analyses various approaches for load scheduling. In this paper, we propose the load scheduling algorithm based on PSO in wireless sensor networks for cloud computing to minimize total transfer time and cost stabilization. The proposed method is compared with the existing approaches used for load scheduling in Cloudlets. It is clear from the simulation results that the proposed method is more efficient because it minimizes the transfer time and cost than the conventional algorithms thereby making a system for cost stable.

Among the classes of wireless personal area networks, a wireless sensor network typically refers to a versatile and densely distributed sensing platform that enables the support of a wide variety of application domains. Among the various technical challenges addressed by more than one decade of research in wireless sensor networks, security across wireless links is by far one of the most critical ones and relates to the need of guaranteeing reliability and trustiness of the collected data. This article deals with the cryptographic aspects involved in securing wireless sensor networks, in terms of confidentiality and authentication. In particular, moving from some results previously achieved in our research activity, this article extends a cryptography scheme in order to better comply with the security requirements that arise from real-world wireless sensor network installations. The proposed scheme, called topology-authenticated key scheme 2, takes advantage of hybrid cryptography to provide security in the presence of resource-constrained sensor nodes using topology-authenticated keys to provide increased robustness to the scheme itself. The proposed extensions provide full practical support to star-topology wireless sensor networks and the article presents also some experimental results obtained by implementing the scheme on two different wireless sensor network platforms available for protocol stacks compliant with the IEEE 802.15.4 standard.

Research of the past years has led to numerous novel developments and approaches for wireless sensor networks (WSNs). However, most previous work has focused on either mathematical analysis or theoretical algorithms with extensive simulation results. In this paper, in order to realistically understand the complexity of WSNs, a ZigBee/IEEE 802.15.4 platform has been designed and implemented. Based on an IEEE 802.15.4 radio and ZigBee protocol stack, the developed ITRI ZBnode is an autonomous wireless communication and computing platform aimed at fast prototyping and research in WSNs. The platform attempts to provide a low data rate, low power, and low cost wireless networking on the device-level communication. Finally, examples of tree and mesh network formation are provided to demonstrate practicability of the developed ZBnode platform.

With hardware support and software optimization, Public Key Cryptography (PKC) has been announced feasible on micro sensors recently [1][2][22][23]. A number of experiments proved that the Elliptic Curve Cryptography (ECC) is more suitable for resource constraint motes compared with RSA [2][3]. But even ECC based protocols still cost too much energy. In this paper, we propose C4W, an identity-based public key infrastructure specially designed for wireless sensor networks (WSNs), in which all nodes can generate others' ECC public keys directly from their identities. Without certificates, no energy will be consumed for certificates communication and verification, which makes C4W especially energy efficient. C4W uses a protocol without certificates to realize mutual authentication and key agreement. Compared with a simplified SSL (SSSL) protocol using an abbreviated certificate, C4W consumes lower than 35% energy, and the communication consumption of C4W is only 28.5% of that consumed by SSSL. Furthermore, the energy analysis of C4W illuminates that the expensive public key computational cost is almost neglectable compared with the heavy communication consumption in a large-scale WSNs, which gives the asymmetric key management in WSNs a bright future.

A wireless sensor network (WSN) is a collection of sensor nodes which can monitor the physical activities and attributes of a whole spectrum of objects and environments. The purpose of collecting this data and processing it in a meaningful manner requires that it adds significant value to the end user. WSN are deployed ever more frequently and applications vary from providing an early alert system on the activity of a volcano, to controlling the movements of livestock so that farming output can be maximized using virtual fencing. There are many challenges facing wireless sensor networks, with one being found in the uniqueness of each application, and challenges arise when WSN developers try to adequately test such applications when they are deployed with varying numbers of nodes, in all ranges of environmental conditions. To implement such systems in hardware involves a huge financial investment and from a development perspective prevents the developer from changing hardware platforms or communications protocols throughout the testing phase without incurring further financial hardship. Due to this fact, tools which can accurately simulate the behavior and performance of real world WSN applications are in high demand and a crucial aspect in the continued growth of WSN in the Internet of Things (IoT). This paper presents a cloud based system which makes various simulation platforms available to multiple users who wish to test WSN routing protocols or the hardware constraints of the various WSN platforms. This simulation testbed is hosted on a Dell PowerEdge R720 server in the communications laboratory in the University of Limerick and it is made available to users through the use of a virtual machine. This offers users access to many of the popular WSN simulation environments with vast computing resources and storage but at far reduced costs for protocol simulation.

The Wireless Sensor Networks (WSNs) are characterized by their widespread deployment due to low cost, but the WSNs are vulnerable to various types of attacks. To defend against the attacks, an effective security solution is required. However, the limits of these networks’ battery-based energy to the sensor are the most critical impediments to selecting cryptographic techniques. Consequently, finding a suitable algorithm that achieves the least energy consumption in data encryption and decryption and providing a highly protected system for data remains the fundamental problem. In this research, the main objective is to obtain data security during transmission by proposing a robust and low-power encryption algorithm, in addition, to examining security algorithms such as ECC and MD5 based on previous studies. In this research, the Energy Saving and Securing Data algorithm (ESSD) algorithm is introduced, which provides the Message Digest 5 (MD5) computation simplicity by modifying the Elliptic Curve Cryptography (ECC) under the primary condition of power consumption. These three algorithms, ECC, MD5, and ESSD, are applied to Low Energy Adaptive Clustering Hierarchy (LEACH) and Threshold-sensitive Energy Efficient Sensor Network Protocol (TEEN) hierarchical routing algorithms which are considered the most widely used in WSNs. The results of security methods under the LEACH protocol show that all nodes are dead at 456, 496, and 496, respectively, to ECC, MD5, and ESSD. The results of security methods under the TEEN protocol show that the test ends at 3743, 4815, and 4889, respectively, to ECC, MD5, and ESSD. Based on these results, the ESSD outperforms better in terms of increased security and less power consumption. In addition, it is advantageous when applied to TEEN protocol.

The Internet of Things (IoT) is envisioned as a paradigm shift, with a plethora of applications, on the premise of well-established enabling technologies; prominently Wireless Sensor Networks (WSNs) and RFIDs. The former has evolved to improve energy efficiency and resilient operation, yet true scalability has only been recently probed and quite sparsely advanced. Moreover, the traditional approach, whereby most WSN platforms are tailored for a single-application, imposes significant rigidity in re-utilizing platforms for new applications, and limitations on re-using previously deployed ones. In remedy, we present a novel paradigm in WSNs to efficiently utilize network resources, and extend it to a platform for multiple applications to cross-utilize resources over multiple WSNs. We present the approach in three phases; the first calibers resources in the network and their usability. Then applications are represented as finite sets of functional requirements. Finally, we present an optimization approach to find an optimal mapping between applications and resources. This paradigm presents a leap in scalability, not only in a WSN but across multiple ones, dynamically accommodating varying resources being introduced and removed; in addition to utilizing transient resources in their vicinity. To this end, we present an architecture to efficiently adopt WSNs in IoT with changing demands and scale. Our approach is further explained and demonstrated via a detailed use case depicting the premise of IoT applications.