Unattended Wireless Sensor Networks Research Articles

Data survivability in unattended wireless sensor networks with optimal clustering and hybrid encryption algorithm

Data survivability in unattended wireless sensor networks with optimal clustering and hybrid encryption algorithm

Data survivability in unattended wireless sensor networks with optimal clustering and hybrid encryption algorithm

Data survivability in unattended wireless sensor networks with optimal clustering and hybrid encryption algorithm

A secure model against mobile sink replication attacks in unattended sensor networks

Unattended wireless sensor networks (UWSNs), in which mobile sinks (MSs) are responsible for the data collection, and which are vulnerable to multiple attacks. For example, the adversaries can initiate MS replication attack after compromising a large number of sensor nodes (SNs). To resist such attacks, some scholars have proposed some schemes. In these schemes, it is assumed that MSs are equipped with tamper resistance hardware, so they are pre-distributed most of keys of a key pool for achieving authentication with SNs. However, in outdoor and even sensitive areas, tamper-resistant hardware is not always absolutely safe. Once MSs are compromised, networks become insecure. In this paper, we propose a secure model. The model contains three types of nodes, namely SNs, MSs, and a base station (BS). MSs are responsible for collecting the data encrypted by SNs and forwarding it to BS; BS is responsible for decrypting and analyzing the collected data. During the data collection process, an MS can collect an SN's data only after being authenticated by the SN using the pre-distribution key information. But it cannot decrypt the collected data. In this model, the adversaries can induce a new type of false data injection attack. In the attack, the replicated MSs impersonate uncompromised SNs to send false data to BS by using the compromised key information. If BS accepts a large amount of false data, it will make a wrong judgment. Analysis and simulation show that the proposed model has excellent resistance against MS replication attacks and false data injection attacks by setting appropriate parameter values.

Energy Aware Compressive Sensing Assisted Secure Data Survivability and Data Collection in Unattended Wireless Sensor Networks

Energy Aware Compressive Sensing Assisted Secure Data Survivability and Data Collection in Unattended Wireless Sensor Networks

Node Location Privacy Protection in Unattended Wireless Sensor Networks

Node location protection is critical to the wireless sensor networks (WSN), especially for unattended environment. However, due to most of the static deployment and the limitations in energy, storage, and communication capabilities of the sensors, WSNs are vulnerable to various location (and derivative) attacks. In this work, we study the node location privacy protection issue from both aspects of attacks and defenses. First, we present a new two-phase location attack for two important types of nodes (including base station and source node). It can locate a base station node within few amounts of local wireless transmission monitoring and then reversely trace the location of the source node. Different from existing methods, the proposed attack determines the node location based on the transmission direction, which can break through existing defenses. Then, to defend against such attacks, we design a pseudospiral-based routing protocol for WSN. We analyze the performance of parameters such as routing probability, maximum detectable angle, hop count, and number of loops based on PU SBRF, MoRF, and PLAUDIT methods. The theory analysis and confrontation experiment of attack and defense show that the proposed scheme can protect the location privacy of the target node with moderate communication and computation overhead.

NTRU-Like Random Congruential Public-Key Cryptosystem for Wireless Sensor Networks.

Wireless sensor networks (WSNs) are the core of the Internet of Things and require cryptographic protection. Cryptographic methods for WSN should be fast and consume low power as these networks rely on battery-powered devices and microcontrollers. NTRU, the fastest and secure public key cryptosystem, uses high degree, N, polynomials and is susceptible to the lattice basis reduction attack (LBRA). Congruential public key cryptosystem (CPKC), proposed by the NTRU authors, works on integers modulo q and is easily attackable by LBRA since it uses small numbers for the sake of the correct decryption. Herein, RCPKC, a random congruential public key cryptosystem working on degree polynomials modulo q, is proposed, such that the norm of a two-dimensional vector formed by its private key is greater than . RCPKC works as NTRU, and it is a secure version of insecure CPKC. RCPKC specifies a range from which the random numbers shall be selected, and it provides correct decryption for valid users and incorrect decryption for an attacker using LBRA by Gaussian lattice reduction. RCPKC asymmetric encryption padding (RAEP), similar to its NTRU analog, NAEP, is IND-CCA2 secure. Due to the use of big numbers instead of high degree polynomials, RCPKC is about 27 times faster in encryption and decryption than NTRU. Furthermore, RCPKC is more than three times faster than the most effective known NTRU variant, BQTRU. Compared to NTRU, RCPKC reduces energy consumption at least thirty times, which allows increasing the life-time of unattended WSNs more than thirty times.

Towards trusted and energy-efficient data collection in unattended wireless sensor networks

The Internet of Things (IoT), including wireless sensors, is one of the highly anticipated contributors to big data; therefore, avoiding misleading or forged data gathering in cases of sensitive and critical data through secure communication is vital. Wireless sensor networks are relatively simple, scalable networks with many applications in research. They can provide many benefits, including ad hoc distribution, lower costs, and higher flexibility. In a scenario where time is of the essence and dedicated base stations cannot be established, mobile sinks must be used to gather data. IoT systems are based on a collective organization in which devices collaborate to provide better and more accurate decisions. It is important to ensure that the information being shared is legitimate to avoid any significant degradation in system performance because of false or inaccurate information. Building trust—the “assurance” between two devices that the information being shared can be used with confidence that it is accurate—will create a trustworthy, secure system in which all devices are identified and no information is accepted from any unauthorized device. The key contribution of this work is a new, dynamic, trust-based clustering mechanism by which nodes can securely connect to one another and begin transmitting data to a sink while it is available. To demonstrate the utility of this mechanism, we examine two possible attacks on a trust-based network and present a heuristic solution for minimizing the negative effects of such attacks in an energy-efficient way. Our results show improved network performance through reduction of the number of cycles required to isolate or mitigate the effect of malicious nodes in the network, thus reducing the energy consumption in the network with a concomitant increase in its lifespan. Our cluster methodology also has the effect of spreading energy consumption among nodes, thereby reducing early fall-off of nodes and network holes.

A Smart Cryptographic measure for Data Survivability in Unattended Wireless Sensor Networks

An Unattended Wireless Sensor Network (UWSN) wherein a sporadically visiting sink tries to collect data absorbed by the motes. This setup is most suitable in hostile environments where the collected valuable data becomes the target for a mobile adversary. Unattended sensors cannot instantly transmit collected data to some safe external entity. Though there is an intermittent visit by the sink, a powerful mobile adversary can easily compromise the valuable data collected by sensor nodes between the intervals. Therefore, the data needs to be preserved to be handed over to the sink in its next visit. This property of unattended WSN is called as Data Survivability. We propose a symmetric key cryptosystem that tackles sensor collected data erasure, modification, or disclosure as a support for data survivability in UWSNs. The proposed model has been designed using Linear Feedback Shift Registers (LFSRs) embodied with less power dissipation mechanism that operates on mask method. This is critical to any application running in unattended environments. We have compared our design with other standard works and have substantially proved the trustworthiness. Our work has been assessed using NIST test suite and found reliable.

An Efficient Authentication Scheme Based on Deployment Knowledge Against Mobile Sink Replication Attack in UWSNs

Unattended wireless sensor networks (UWSNs) are vulnerable to mobile sink (MS) replication attack. In this attack, using the compromised key information, an attacker can collect data from networks by impersonating sinks. To resist such an attack, some schemes have been proposed. To improve the resilience of MS replication attack of these schemes, we can integrate them with schemes based on deployment knowledge. However, there are the following defects: 1) the probability of mutual authentication between a MS and a sensor node is less than 1 and 2) during the authentication phase, the energy consumption of sensor nodes increases significantly as the deployment area expands. In this paper, we construct 3-D backward key chains based on deployment knowledge and propose a new authentication scheme based on these. As compared with these existing related schemes, the detailed theory analysis and simulation results indicate that the scheme can ensure that a MS can be authenticated by sensor nodes, and can improve the resilience of networks’ MS replication attack with low energy consumption.

A Long-Lasting Microliter-Scale Microbial Biobattery Using Solid-State Ionics

We report a microliter-scale bacteria-powered biobattery providing a long-term operational capability for potentially powering unattended wireless sensor networks. In a 20μL-chamber, the biobattery contained a horizontally arranged anode/salt-bridge/cathode configuration with solid-state agar electrolytes. A slow release of bacterial nutrients from a synthetic solid anolyte enabled a continuous current generation (> 6μA/cm2) over 8 days while a liquid-based anolyte was completely depleted within 4 hours. Given that wireless sensors require an ultra-low power intermittently, our micro-biobattery can be practically used for more than a month without human intervention. Agar-based catholyte and salt bridge further enhanced the device lifespan and ensured its practical feasibility as a power source for wireless sensors. The device was sealed with a gas-permeable polydimethylsiloxane (PDMS) membrane to facilitate gas exchange to the bacteria and cathodic reactions, even ideally allowing for replenishing bacterial nutrients from environments for self-sustainable energy harvesting. Our device used Shewanella oneidensis MR-1 to produce a maximum power density of 4μW/cm2 and current density 45μA/cm2 after 96 hours (day 4), which will be enough power for small-power applications.

Additively homomorphic encryption and fragmentation scheme for data aggregation inside unattended wireless sensor networks

Data fragmentation and dispersion is recognized as a way of providing confidentiality and availability of data stored inside unattended wireless sensor networks. This paper introduces an additively homomorphic encryption and fragmentation scheme (AHEF). AHEF replaces additively homomorphic secret sharing used in state-of-the-art techniques with additively homomorphic fragmentation. This change has a significant impact on the volume of data stored inside the sensors which in turn supports lower transmission costs. Both, storage and transmission costs are reduced by a factor of at least 2. Moreover, by reducing the number of required computations, AHEF allows sensors to save energy.

Trade‐off between self‐healing and energy consumption in mobile unattended WSNs

This study investigates the performance analysis of mobile unattended wireless sensor networks (UWSNs) during the self-healing process under informed movement inside a cluster of healed and sick sensors. Introducing mobility within a cluster can increase the chance that a sick sensor has healthy neighbours and this will aid the sick sensor to be healed faster and better. However, sensor mobility is considered as one of the most energy consuming factors in UWSNs. This study proposes a new self-healing scheme based on a single flow controlled mobility within a cluster to make a trade-off between self-healing and energy consumption in mobile UWSNs. The obtained results show that using the proposed scheme, UWSNs can exploit controlled sensor mobility to enhance network capability in terms of self-healing and reduce the communication-related energy consumption. In addition, the proposed scheme with single flow controlled mobility does not disturb the number of neighbours per sensor and the network coverage.

Epidemic data survivability in Unattended Wireless Sensor Networks: New models and results

Unattended Wireless Sensor Networks (UWSNs), characterized by the intermittent presence of the sink, are exposed to attacks aiming at tampering with the sensors and the data they store. In order to prevent an adversary from erasing any sensed data before the sink collects them, it is common practice to rely on data replication. However, identifying the most suitable replication rate is challenging: data should be redundant enough to avoid data loss, but not so much as to pose an excessive burden on the limited resources of the sensors. As noted before in the literature, this problem is similar to finding the minimum infection rate that makes a disease endemic in a population. Yet, unlike previous attempts to leverage on this parallelism, we argue that model and system parameters must be carefully bound according to conservative and realistic assumptions on the behavior of the network, further taking into account possible statistical fluctuations. In this paper, we therefore refine the connection between the Susceptible, Infected, Susceptible (SIS) epidemic model and the survivability of sensed data in UWSNs. In particular, based on probabilistic data replication and deletion rates, we identify proper conditions to guarantee that sensed information become endemic. In both the full visibility model (i.e. unlimited transmission range) and the geometric one (i.e. limited transmission range), the proposed approach achieves: (i) data survivability, (ii) optimal usage of sensors resources, and (iii) fast collecting time. Building on advanced probabilistic tools, we provide theoretically sound results, that are further supported by an extensive experimental campaign performed on synthetically generated networks. Obtained results show the quality of our model and viability of the proposed solution.

Convex-Hull-Based Boundary Detection in Unattended Wireless Sensor Networks

Perimeter protection aims at identifying intrusions across the temporary base established by army in critical regions. Convex-hull algorithm is used to determine the boundary nodes among a set of nodes in the network. To study the effectiveness of such algorithm, we opted three variations, such as distributed approach, centralized, and mobile approach, suitable for wireless sensor networks for boundary detection. The convex-hull approaches are simulated with different node density, and the performance is measured in terms of energy consumption, boundary detection time, and accuracy. Results from the simulations highlight that the convex-hull approach is effective under densely deployed nodes in an environment. The different approaches of convex-hull algorithm are found to be suitable under different sensor network application scenarios.

Independent Neighbour Set based Clustering Algorithm for Routing in Wireless Sensor Networks

Efficient energy consumption of sensor devices is a prominent problem in battery constrained, unattended wireless sensor networks (WSNs) and it directly influence on WSN lifetime. Designing energy-aware routing protocol can significantly reduce energy consumption in WSNs. Grouping of sensor nodes into clusters is a proficient routing technique for reducing the energy depletion of the nodes in the WSN. In this work, a novel multi-branch tree based clustering approach is proposed to extend the lifetime of the WSNs. A number of branches and selection of cluster heads are performed based on the independent neighbour set properties of nodes. For this, a maximum of five branches constructed by the algorithm and these branches are grown to different direction using the nature of INS. In this approach, inter-cluster communication distance is drastically minimized and evenly distributed the energy consumption of nodes over the network. The performance of the proposed algorithm is compared with the traditional existing methods in terms of cluster structure, nodes energy distribution and network lifetime through the extensive simulations.

Robust data authentication for unattended wireless sensor networks

This paper presents a robust data authentication scheme for protecting data integrity and availability in unattended wireless sensor networks. Such networks are vulnerable to several types of attacks. In particular, attackers can compromise a subset of nodes and use these nodes to transmit modified data or to prevent genuine data from being verified. The presented scheme combines security against data modification and denial of service attacks with traffic and storage efficiency. This is achieved by involving all sensor nodes in the network in the authentication process, implementing cooperative authentication with multiple authenticators, and using dual storage. Detailed analysis and extensive simulation tests show that our scheme achieves better performance compared to related schemes published in the literature in terms of traffic, storage, security against DoS attacks, and security against data replacement attacks.

Erratum to: MRL-SCSO: Multi-agent Reinforcement Learning-Based Self-Configuration and Self-Optimization Protocol for Unattended Wireless Sensor Networks

Resource-constrained nodes in unattended wireless sensor network (UWSN) operate in a hostile environment with less human intervention. Achieving the optimal quality of service (QoS) in terms of packet delivery ratio, delay, energy, and throughput is crucial. In this paper, we propose a topology control and data dissemination protocol that uses multi-agent reinforcement learning (MRL) and energy-aware convex-hull algorithm, for effective self-configuration and self-optimization (SCSO) in UWSN, called MRL-SCSO. MRL-SCSO maintains a reliable topology in which the effective active neighbor nodes are selected using MRL. The network boundary is determined using convex-hull algorithm to maintain the connectivity and coverage of the network. The boundary nodes transmit data under high traffic load conditions. The performance of MRL-SCSO is evaluated for various nodes count and under different load conditions by using the Contiki’s Cooja simulator. The results showed that MRL-SCSO stabilizes the performance and improves QoS.

MRL-SCSO: Multi-agent Reinforcement Learning-Based Self-Configuration and Self-Optimization Protocol for Unattended Wireless Sensor Networks

MRL-SCSO: Multi-agent Reinforcement Learning-Based Self-Configuration and Self-Optimization Protocol for Unattended Wireless Sensor Networks

Survey on state scheduling-based topology control in unattended wireless sensor networks

Wireless sensor networks comprise nodes with limited power supply. The dense deployment of nodes on a terrain for monitoring the environment causes contention in wireless channels that leads to interference and high energy consumption. The topology of the network changes frequently because of failure of nodes, addition of new nodes, and channel fading. Topology control is an important technique for reducing energy consumption, interference, and maintaining connectivity in the network. This paper provides a survey on state scheduling-based topology control techniques for unattended wireless sensor networks. Topology control algorithms for both flat and hierarchical networks are discussed. The algorithms are further categorized according to the key parameters used for state scheduling. The advantages, disadvantages, and results of the algorithms are tabulated. In addition, we highlight future research directions in designing state scheduling-based topology control algorithms.

Cooperative hybrid self‐healing scheme for secure and data reliability in unattended wireless sensor networks

Unattended wireless sensor networks (UWSNs) are operated in hostile environments without constant supervision by a trusted sink; so it faces the risk of compromising by adversaries (ADVs). In this study, proposed is a cooperative hybrid self-healing randomised distributed (CHSHRD) scheme, a new mechanism to enhance the confidentiality of the data collected by UWSNs. The proposed scheme employs both proactive and reactive peers to ensure both backward secrecy and data reliability. It helps the unattended sensors to self-heal and restore their backward secrecy by asking for help from the best qualified neighbours to generate a new secret key to regain their secrecy. The sick sensors also use the best qualified neighbours to distribute the data parts among them to protect the data from eavesdropping and this will enhance the data reliability. In this study, they also present a powerful, realistic and agile ADV model and show how CHSHRD scheme can result in sensor regaining secrecy and achieving high data reliability, despite the adversary efforts to the contrary. The evaluation of the proposed scheme relies on both theoretical probabilistic results and simulation results that compare the proposed scheme to other protection schemes. The results show that this hybrid scheme provides better protection than other schemes that use either proactive or reactive peers.