The need for implementing adequate security services in industrial applications is increasing. Verifying the physical proximity or location of a device has become an important security service in ...ad-hoc wireless environments. Distance-bounding is a prominent secure neighbor detection method that cryptographically determines an upper bound for the physical distance between two communicating parties based on the round-trip time of cryptographic challenge-response pairs. This paper gives a brief overview of distance-bounding protocols and discusses the possibility of implementing such protocols within industrial RFID and real-time location applications, which requires an emphasis on aspects such as reliability and real-time communication. The practical resource requirements and performance tradeoffs involved are illustrated using a sample of distance-bounding proposals, and some remaining research challenges with regards to practical implementation are discussed.
Distance bounding is often proposed as a countermeasure to relay attacks and distance fraud in RFID proximity identification systems. Although several distance-bounding protocols have been proposed ...the security of these proposals are dependent on the underlying communication channel. Conventional communication channels have been shown to be inappropriate for implementing distance bounding, as these channels introduce latency that can be exploited to obscure attempted attacks. Distance-bounding channels for RFID tokens have been proposed but have failed to address distance fraud or have not been practically implemented in an RFID environment. This paper describes a near-field, bit-exchange channel design that minimizes latency and allows for more secure distance-bounding measurements, while still allowing for a resource-constrained prover. Results from a proof-of-concept implementation is also presented, which illustrates that a channel that is resistant to both relay attacks and distance fraud is feasible in current RFID systems.
This Special Section on "Security, privacy, and trust for Industrial Internet of Things" of the IEEE Transactions on Industrial Informatics (TII) highlights the main research challenges in the ...industrial Internet of Things (IoT) security, privacy, and trust. The designated nine high-quality research articles cover a wide range of the special section theme, including innovative solutions and novel technologies. These articles are briefly summarized.
This paper describes the design and implementation of an embedded wireless vibration condition monitoring device. The goal was to design a device that uses machine learning techniques for fault ...diagnosis. A MEMS accelerometer attached to a microcontroller measures vibration and transmits the data wirelessly to a gateway. It is shown that the device is able to diagnose faults.
In wireless underground sensor networks (WUSNs), due to the dynamic underground channel characteristics and the heterogeneous network architecture, the connectivity analysis is much more complicated ...than in the terrestrial wireless sensor networks and ad hoc networks, which was not addressed before, to our knowledge. In this paper, a mathematical model is developed to analyze the dynamic connectivity in WUSNs, which captures the effects of the environmental parameters such as the soil composition and the soil moisture, and the system parameters such as the operating frequency, the sensor burial depth, the sink antenna height, the density of the sensor and sink devices, the tolerable latency of the networks, and the number and the mobility of the above-ground sinks. The lower and upper bounds of the connectivity probability are derived to analytically provide principles and guidelines for the design and deployment of WUSNs in various environmental conditions.
Multi-functional grid-tied inverters (MFGTIs) have been investigated recently for improving the power quality (PQ) of microgrids (MGs) by exploiting the residual capacity (RC) of distributed ...generators. Several centralized and decentralized methods have been proposed to coordinate the MFGTIs. However, with the increasing number of the MFGTIs, it demands a method with improved reliability and flexibility, which are characteristics of distributed framework that has not been introduced into the PQ improvement (PQI) field before. In this paper, we propose a distributed consensus method to undertake the PQI task. The task is proportionally shared among the MFGTIs according to their instant RCs. Besides, most of the existing methods assume that the RCs of the MFGTIs are sufficient for tackling the PQ problem (PQP), which is not always true. In the case of insufficient RC, the active power output of each MFGTI is scaled down by the same factor determined by a proposed leader-follower protocol to make room for the task. In summary, the PQP is dealt with in both cases of sufficient and insufficient RC under the distributed control framework. Finally, simulations and hardware-in-the-loop experiments of an MG consisting of three 10kVA MFGTIs are presented to verify the effectiveness of the proposed methods.
The forward consecutive mean excision (FCME) algorithm is one of the most effective adaptive threshold estimation algorithms presently deployed for threshold adaptation in cognitive radio (CR) ...systems. However, its effectiveness is often limited by the manual parameter tuning process and by the lack of prior knowledge pertaining to the actual noise distribution considered during the parameter modeling process of the algorithm. In this paper, we propose a new model that can automatically and accurately tune the parameters of the FCME algorithm based on a novel integration with the cuckoo search optimization (CSO) algorithm. Our model uses the between-class variance function of the Otsu’s algorithm as the objective function in the CSO algorithm in order to auto-tune the parameters of the FCME algorithm. We compared and selected the CSO algorithm based on its relatively better timing and accuracy performance compared to some other notable metaheuristics such as the particle swarm optimization, artificial bee colony (ABC), genetic algorithm, and the differential evolution (DE) algorithms. Following close performance values, our findings suggest that both the DE and ABC algorithms can be adopted as favorable substitutes for the CSO algorithm in our model. Further simulation results show that our model achieves reasonably lower probability of false alarm and higher probability of detection as compared to the baseline FCME algorithm under different noise-only and signal-plus-noise conditions. In addition, we compared our model with some other known autonomous methods with results demonstrating improved performance. Thus, based on our new model, users are relieved from the cumbersome process involved in manually tuning the parameters of the FCME algorithm; instead, this can be done accurately and automatically for the user by our model. Essentially, our model presents a fully blind signal detection system for use in CR and a generic platform deployable to convert other parameterized adaptive threshold algorithms into fully autonomous algorithms.
The authors of this paper explore the use of IPv6 over Low power Wireless Personal Area Networks (6LoWPAN), IPv6 Routing Protocol for Low power and Lossy Networks (RPL) and Constrained Application ...Protocol (CoAP) as a possible solution for realising the Internet of Things (IOT) vision in Industrial Wireless Sensor Networks (IWSNs), The aim of this paper is to investigate the feasibility of using Internet Engineering Task Force (IETF) standards in industrial environments by identifying and quantifying several attributes of a 6LoWPAN, RPL and CoAP based IWSNs relating to bounded time interval communications. The paper identifies several possible causes of latency in IWSNs and can be used as a basis for deploying Internet Protocol (IP) based IWSNs requiring IOT connectivity.
In this paper, we compare local and global adaptive threshold estimation techniques for energy detection in Cognitive Radio (CR). By this comparison, a sum-up synopsis is provided regarding the ...effective performance range and the operating conditions under which both classes best apply in CR. Representative methods from both classes were implemented and trained using synthesized signals to fine tune each algorithm’s parameter values. Further tests were conducted using real-life signals acquired via a spectrum survey exercise and results were analyzed using the probability of detection and the probability of false alarm computed for each algorithm. It is observed that while local based methods may be adept at maintaining a low constant probability of false alarm, they however suffer a grossly low probability of detection over a wide variety of CR spectra. Consequently, we concluded that global adaptive threshold estimation techniques are more suitable for signal detection in CR than their local adaptive thresholding counterparts.
PDF
