Design and analysis of key management schemes for distributed wireless sensor networks

Secure communications in distributed Wireless Sensor Networks (WSN) operating under adversarial conditions necessitate efficient key management schemes. In the absence of a priori knowledge of post-deployment network configuration and due to limited resources at sensor nodes, key management schemes cannot be based on post-deployment computations. Instead, a list of keys, called a key-chain, is distributed to each sensor node before the deployment. For secure communication, either two nodes should have a key in common in their key-chains, or they should establish a key through a secure-path on which every link is secured with a key. We first provide a comparative survey of well known key management solutions for WSN. Probabilistic, deterministic and hybrid key management solutions are presented, and they are compared based on their security properties and re-source usage. We provide a taxonomy of solutions, and identify trade-offs in them to conclude that there is no one size-fits-all solution. Second, we design and analyze deterministic and hybrid techniques to distribute pair-wise keys to sensor nodes before the deployment. We present novel deterministic and hybrid approaches based on combinatorial design theory and graph theory for deciding how many and which keys to assign to each key-chain before the sensor network deployment. Performance and security of the proposed schemes are studied both analytically and computationally. Third, we address the key establishment problem in WSN which requires key agreement algorithms without authentication are executed over a secure-path. The length of the secure-path impacts the power consumption and the initialization delay for a WSN before it becomes operational. We formulate the key establishment problem as a constrained bi-objective optimization problem, break it into two sub-problems, and show that they are both NP-Hard and MAX-SNP-Hard. Having established inapproximability results, we focus on addressing the authentication problem that prevents key agreement algorithms to be used directly over a wireless link. We present a fully distributed algorithm where each pair of nodes can establish a key with authentication by using their neighbors as the witnesses.

Use of brain computer interface to drive : preliminary results

This paper reports on the implementation of a non-invasive electroencephalography-based brain-computer interface to control functions of a car in a driving simulator. The system is comprised of a Cleveland Medical Devices BioRadio 150 physiological signal recorder, a MATLAB-based BCI and an OKTAL SCANeR advanced driving experience simulator. The system utilizes steady-state visual-evoked potentials for the BCI paradigm, elicited by frequency-modulated high-power LEDs and recorded with the electrode placement of Oz-Fz with Fz as ground. A three-class online brain-computer interface was developed and interfaced with an advanced driving simulator to control functions of the car, including acceleration and steering. The findings are mainly exploratory but provide an indication of the feasibility and challenges of brain-controlled on-road cars for the future, in addition to a safe, simulated BCI driving environment to use as a foundation for research into overcoming these challenges.

Designing a new robust on-line secondary path modeling technique for feedforward active noise control systems

Several approaches have been introduced in the literature for active noise control (ANC) systems. Since the filtered-x least-mean-square (FxLMS) algorithm appears to be the best choice as a controller filter, researchers tend to improve performance of ANC systems by enhancing and modifying this algorithm. This paper proposes a new version of the FxLMS algorithm, as a first novelty. In many ANC applications, an on-line secondary path modeling method using white noise as a training signal is required to ensure convergence of the system. As a second novelty, this paper proposes a new approach for on-line secondary path modeling on the basis of a new variable-step-size (VSS) LMS algorithm in feed forward ANC systems. The proposed algorithm is designed so that the noise injection is stopped at the optimum point when the modeling accuracy is sufficient. In this approach, a sudden change in the secondary path during operation makes the algorithm reactivate injection of the white noise to re-adjust the secondary path estimate. Comparative simulation results shown in this paper indicate the effectiveness of the proposed approach in reducing both narrow-band and broad-band noise. In addition, the proposed ANC system is robust against sudden changes of the secondary path model.

An efficient online secondary path estimation for feedback active noise control systems

In practical cases for active noise control (ANC), the secondary path has usually a time varying behavior. For these cases, an online secondary path modeling method that uses a white noise as a training signal is required to ensure convergence of the system. The modeling accuracy and the convergence rate are increased when a white noise with a larger variance is used. However, the larger variance increases the residual noise, which decreases performance of the system and additionally causes instability problem to feedback structures. A sudden change in the secondary path leads to divergence of the online secondary path modeling filter. To overcome these problems, this paper proposes a new approach for online secondary path modeling in feedback ANC systems. The proposed algorithm uses the advantages of white noise with larger variance to model the secondary path, but the injection is stopped at the optimum point to increase performance of the algorithm and to prevent the instability effect of the white noise. In this approach, instead of continuous injection of the white noise, a sudden change in secondary path during the operation makes the algorithm to reactivate injection of the white noise to correct the secondary path estimation. In addition, the proposed method models the secondary path without the need of using off-line estimation of the secondary path. Considering the above features increases the convergence rate and modeling accuracy, which results in a high system performance. Computer simulation results shown in this paper indicate effectiveness of the proposed method.

Order statistic filters for image matching

The rank and census are two filters based on order statistics which have been applied to the image matching problem for stereo pairs. Advantages of these filters include their robustness to radiometric distortion and small amounts of random noise, and their amenability to hardware implementation. In this paper, a new matching algorithm is presented, which provides an overall framework for matching, and is used to compare the rank and census techniques with standard matching metrics. The algorithm was tested using both real stereo pairs and a synthetic pair with ground truth. The rank and census filters were shown to significantly improve performance in the case of radiometric distortion. In all cases, the results obtained were comparable to, if not better than, those obtained using standard matching metrics. Furthermore, the rank and census have the additional advantage that their computational overhead is less than these metrics. For all techniques tested, the difference between the results obtained for the synthetic stereo pair, and the ground truth results was small.

Adaptive metering algorithm for electronic commercial vehicle preclearance systems

This paper presents an adaptive metering algorithm for enhancing the electronic screening (e-screening) operation at truck weight stations. This algorithm uses a feedback control mechanism to control the level of truck vehicles entering the weight station. The basic operation of the algorithm allows more trucks to be inspected when the weight station is underutilized by adjusting the weight threshold lower. Alternatively, the algorithm restricts the number of trucks to inspect when the station is overutilized to prevent queue spillover. The proposed control concept is demonstrated and evaluated in a simulation environment. The simulation results demonstrate the considerable benefits of the proposed algorithm in improving overweight enforcement with minimal negative impacts on nonoverweighed trucks. The test results also reveal that the effectiveness of the algorithm improves with higher truck participation rates in the e-screening program.

Algorithm for queue estimation with loop detector of time occupancy in off-ramps on signalized motorways

Long traffic queues on off-ramps significantly compromise the safety and throughput of motorways. Obtaining accurate queue information is crucial for countermeasure strategies. However, it is challenging to estimate traffic queues with locally installed inductive loop detectors. This paper deals with the problem of queue estimation with the interpretation of queuing dynamics and the corresponding time-occupancy distribution over motorway off-ramps. A novel algorithm for real-time queue estimation with two detectors is presented and discussed. Results derived from microscopic traffic simulation validated the effectiveness of the algorithm and revealed some of its useful features: (a) long and intermediate traffic queues could be accurately measured, (b) relatively simple detector input (i.e., time occupancy) was required, and (c) the estimation philosophy was independent with signal timing changes and provided the potential to cooperate with advanced strategies for signal control. Some issues concerning field implementation are also discussed.

A Kalman filter based queue estimation algorithm using time occupancies for motorway on-ramps

The primary objective of this study is to develop a robust queue estimation algorithm for motorway on-ramps. Real-time queue information is the most vital input for a dynamic queue management that can treat long queues on metered on-ramps more sophistically. The proposed algorithm is developed based on the Kalman filter framework. The fundamental conservation model is used to estimate the system state (queue size) with the flow-in and flow-out measurements. This projection results are updated with the measurement equation using the time occupancies from mid-link and link-entrance loop detectors. This study also proposes a novel single point correction method. This method resets the estimated system state to eliminate the counting errors that accumulate over time. In the performance evaluation, the proposed algorithm demonstrated accurate and reliable performances and consistently outperformed the benchmarked Single Occupancy Kalman filter (SOKF) method. The improvements over SOKF are 62% and 63% in average in terms of the estimation accuracy (MAE) and reliability (RMSE), respectively. The benefit of the innovative concepts of the algorithm is well justified by the improved estimation performance in the congested ramp traffic conditions where long queues may significantly compromise the benchmark algorithm’s performance.

Overvoltage prevention in LV smart grid using customer resources coordination

Voltage rise is one of the main factors which limits the capacity of Low Voltage (LV) network to accommodate more Renewable Energy (RE) sources. This paper proposes a robust and effective approach to coordinate customers’ resources and manage voltage rise in residential LV networks. PV is considered as the customer RE source. The suggested coordination approach in this paper includes both localized control strategy, based on local measurement, and distributed control strategy based on consensus algorithm. This approach can completely avoid maximum permissible voltage limit violation. A typical residential LV network is used as the case study where the simulated results are shown to verify the effectiveness of the proposed approach.

Adaptive dynamic path re-planning RRT algorithms with game theory for UAVs

The main aim of this paper is to describe an adaptive re-planning algorithm based on a RRT and Game Theory to produce an efficient collision free obstacle adaptive Mission Path Planner for Search and Rescue (SAR) missions. This will provide UAV autopilots and flight computers with the capability to autonomously avoid static obstacles and No Fly Zones (NFZs) through dynamic adaptive path replanning. The methods and algorithms produce optimal collision free paths and can be integrated on a decision aid tool and UAV autopilots.

The Australian Business Assessment of Computer User Security (ABACUS): A national survey.

The Australian Business Assessment of Computer User Security (ABACUS) survey is a nationwide assessment of the prevalence and nature of computer security incidents experienced by Australian businesses. This report presents the findings of the survey which may be used by businesses in Australia to assess the effectiveness of their information technology security measures.

A new online secondary path modelling method for feedforward active noise control systems

An online secondary path modelling method using a white noise as a training signal is required in many applications of active noise control (ANC) to ensure convergence of the system. Not continually injection of white noise during system operation makes the system more desirable. The purposes of the proposed method are two folds: controlling white noise by preventing continually injection, and benefiting white noise with a larger variance. The modelling accuracy and the convergence rate increase when a white noise with larger variance is used, however larger the variance increases the residual noise, which decreases performance of the system. This paper proposes a new approach for online secondary path modelling in feedfoward ANC systems. The proposed algorithm uses the advantages of the white noise with larger variance to model the secondary path, but the injection is stopped at the optimum point to increase performance of the system. Comparative simulation results shown in this paper indicate effectiveness of the proposed approach in controlling active noise.

Experimental and computer simulation validation of ultrasound phase interference created by lateral inhomogeneity of transit time in replica bone marrow composite models

Purpose: The measurement of broadband ultrasonic attenuation (BUA) in cancellous bone for the assessment of osteoporosis follows a parabolic-type dependence with bone volume fraction; having minima values corresponding to both entire bone and entire marrow. Langton has recently proposed that the primary BUA mechanism may be significant phase interference due to variations in propagation transit time through the test sample as detected over the phase-sensitive surface of the receive ultrasound transducer. This fundamentally simple concept assumes that the propagation of ultrasound through a complex solid : liquid composite sample such as cancellous bone may be considered by an array of parallel ‘sonic rays’. The transit time of each ray is defined by the proportion of bone and marrow propagated, being a minimum (tmin) solely through bone and a maximum (tmax) solely through marrow. A Transit Time Spectrum (TTS), ranging from tmin to tmax, may be defined describing the proportion of sonic rays having a particular transit time, effectively describing lateral inhomogeneity of transit time over the surface of the receive ultrasound transducer. Phase interference may result from interaction of ‘sonic rays’ of differing transit times. The aim of this study was to test the hypothesis that there is a dependence of phase interference upon the lateral inhomogenity of transit time by comparing experimental measurements and computer simulation predictions of ultrasound propagation through a range of relatively simplistic solid:liquid models exhibiting a range of lateral inhomogeneities. Methods: A range of test models was manufactured using acrylic and water as surrogates for bone and marrow respectively. The models varied in thickness in one dimension normal to the direction of propagation, hence exhibiting a range of transit time lateral inhomogeneities, ranging from minimal (single transit time) to maximal (wedge; ultimately the limiting case where each sonic ray has a unique transit time). For the experimental component of the study, two unfocused 1 MHz ¾” broadband diameter transducers were utilized in transmission mode; ultrasound signals were recorded for each of the models. The computer simulation was performed with Matlab, where the transit time and relative amplitude of each sonic ray was calculated. The transit time for each sonic ray was defined as the sum of transit times through acrylic and water components. The relative amplitude considered the reception area for each sonic ray along with absorption in the acrylic. To replicate phase-sensitive detection, all sonic rays were summed and the output signal plotted in comparison with the experimentally derived output signal. Results: From qualtitative and quantitative comparison of the experimental and computer simulation results, there is an extremely high degree of agreement of 94.2% to 99.0% between the two approaches, supporting the concept that propagation of an ultrasound wave, for the models considered, may be approximated by a parallel sonic ray model where the transit time of each ray is defined by the proportion of ‘bone’ and ‘marrow’. Conclusions: This combined experimental and computer simulation study has successfully demonstrated that lateral inhomogeneity of transit time has significant potential for phase interference to occur if a phase-sensitive ultrasound receive transducer is implemented as in most commercial ultrasound bone analysis devices.

Algebraic analysis of Trivium-like ciphers

Trivium is a bit-based stream cipher in the final portfolio of the eSTREAM project. In this paper, we apply the approach of Berbain et al. to Trivium-like ciphers and perform new algebraic analyses on them, namely Trivium and its reduced versions: Trivium-N, Bivium-A and Bivium-B. In doing so, we answer an open question in the literature. We demonstrate a new algebraic attack on Bivium-A. This attack requires less time and memory than previous techniques which use the F4 algorithm to recover Bivium-A's initial state. Though our attacks on Bivium-B, Trivium and Trivium-N are worse than exhaustive keysearch, the systems of equations which are constructed are smaller and less complex compared to previous algebraic analysis. Factors which can affect the complexity of our attack on Trivium-like ciphers are discussed in detail.

Computer-based assessments of expected satiety predict behavioural measures of portion-size selection and food intake

Previously, expected satiety (ES) has been measured using software and two-dimensional pictures presented on a computer screen. In this context, ES is an excellent predictor of self-selected portions, when quantified using similar images and similar software. In the present study we sought to establish the veracity of ES as a predictor of behaviours associated with real foods. Participants (N = 30) used computer software to assess their ES and ideal portion of three familiar foods. A real bowl of one food (pasta and sauce) was then presented and participants self-selected an ideal portion size. They then consumed the portion ad libitum. Additional measures of appetite, expected and actual liking, novelty, and reward, were also taken. Importantly, our screen-based measures of expected satiety and ideal portion size were both significantly related to intake (p < .05). By contrast, measures of liking were relatively poor predictors (p > .05). In addition, consistent with previous studies, the majority (90%) of participants engaged in plate cleaning. Of these, 29.6% consumed more when prompted by the experimenter. Together, these findings further validate the use of screen-based measures to explore determinants of portion-size selection and energy intake in humans.