Information2016, 7(2), 23; doi:10.3390/info7020023 - published 26 April 2016 Show/Hide Abstract
Abstract: The most effective approach to evaluating the security of complex systems is to deliberately construct the systems using security patterns specifically designed to make them evaluable. Just such an integrated set of security patterns was created decades ago based on the Reference Monitor abstraction. An associated systematic security engineering and evaluation methodology was codified as an engineering standard in the Trusted Computer System Evaluation Criteria (TCSEC). This paper explains how the TCSEC and its Trusted Network Interpretation (TNI) constitute a set of security patterns for large, complex and distributed systems and how those patterns have been repeatedly and successfully used to create and evaluate some of the most secure government and commercial systems ever developed.
Information2016, 7(2), 22; doi:10.3390/info7020022 - published 14 April 2016 Show/Hide Abstract
Abstract: Knowledge management systems are widely used to manage the knowledge in organizations. Consulting experts is an effective way to utilize tacit knowledge. The paper aims to optimize the match between users and experts to improve the efficiency of tacit knowledge-sharing. Firstly, expertise, trust and feedback are defined to characterize the preference of users for experts. Meanwhile, factors including trust, relationship and knowledge distance are defined to characterize the preference of experts for users. Then, a new method for the measurement of satisfaction based on the principle of axiomatic design is proposed. Afterwards, in order to maximize the satisfaction of both experts and users, the optimization model is constructed and the optimal solution is shown in the matching results. The evaluation results show the approach is feasible and performs well. The approach provides new insights for research on tacit knowledge-sharing. It can be applied as a tool to match experts with users in the development of knowledge management systems. The fuzzy linguistic method facilitates the expression of opinions, and as a result, the users-system interaction is improved.
Information2016, 7(2), 21; doi:10.3390/info7020021 - published 29 March 2016 Show/Hide Abstract
Abstract: A user of a smartphone may feel convenient, happy, safe, etc., if his/her smartphone works smartly based on his/her context or the context of the device. In this article, we deal with the position of a smartphone on the body and carrying items like bags as the context of a device. The storing position of a smartphone impacts the performance of the notification to a user, as well as the measurement of embedded sensors, which plays an important role in a device’s functionality control, accurate activity recognition and reliable environmental sensing. In this article, nine storing positions, including four types of bags, are subject to recognition using an accelerometer on a smartphone. In total, 63 features are selected as a set of features among 182 systematically-defined features, which can characterize and discriminate the motion of a smartphone terminal during walking. As a result of leave-one-subject-out cross-validation, an accuracy of 0.801 for the nine-class classification is shown, while an accuracy of 0.859 is obtained against five classes, which merges the subclasses of trouser pockets and bags. We also show the basic performance evaluation to select the proper window size and classifier. Furthermore, the analysis of the contributive features is presented.
Information2016, 7(2), 20; doi:10.3390/info7020020 - published 23 March 2016 Show/Hide Abstract
Abstract: Data fusion is usually performed prior to classification in order to reduce the input space. These dimensionality reduction techniques help to decline the complexity of the classification model and thus improve the classification performance. The traditional supervised methods demand labeled samples, and the current network traffic data mostly is not labeled. Thereby, better learners will be built by using both labeled and unlabeled data, than using each one alone. In this paper, a novel network traffic data fusion approach based on Fisher and deep auto-encoder (DFA-F-DAE) is proposed to reduce the data dimensions and the complexity of computation. The experimental results show that the DFA-F-DAE improves the generalization ability of the three classification algorithms (J48, back propagation neural network (BPNN), and support vector machine (SVM)) by data dimensionality reduction. We found that the DFA-F-DAE remarkably improves the efficiency of big network traffic classification.
Information2016, 7(2), 19; doi:10.3390/info7020019 - published 23 March 2016 Show/Hide Abstract
Abstract: A minimax duality for a Gaussian mutual information expression was introduced by Yu. An interesting observation is the relationship between cost constraints on the transmit covariances and noise covariances in the dual problem via Lagrangian multipliers. We introduce a minimax duality for general MIMO interference networks, where noise and transmit covariances are optimized subject to linear conic constraints. We observe a fully symmetric relationship between the solutions of both networks, where the roles of the optimization variables and Lagrangian multipliers are inverted. The least favorable noise covariance itself provides a Lagrangian multiplier for the linear conic constraint on the transmit covariance in the dual network, while the transmit covariance provides a Lagrangian multiplier for the constraint on the interference plus noise covariance in the dual network. The degrees of freedom available for optimization are constituted by linear subspaces, where the orthogonal subspaces induce the constraints in the dual network. For the proof of our duality we make use of the existing polite water-filling network duality and as a by-product we are able to show that maximization problems in MIMO interference networks have a zero-duality gap for a special formulation of the dual function. Our minimax duality unifies and extends several results, including the original minimax duality and other known network dualities. New results and applications are MIMO transmission strategies that manage and handle uncertainty due to unknown inter-cell interference and information theoretic proofs concerning cooperation in networks and optimality of proper signaling.
Information2016, 7(1), 18; doi:10.3390/info7010018 - published 21 March 2016 Show/Hide Abstract
Abstract: Power talk is a method for communication among voltage control sources (VSCs) in DC microgrids (MGs), achieved through variations of the supplied power that is incurred by modulation of the parameters of the primary control. The physical medium upon which the communication channel is established is the voltage supply level of the common MG bus. In this paper, we show how to create power talk channels in all-to-all communication scenarios and implement the signaling and detection techniques, focusing on the construction and use of the constellations or arbitrary order. The main challenge to the proposed communication method stems from random shifts of the loci of the constellation symbols, which are due to random load variations in the MG. We investigate the impact that solutions that combat the effects of random load variations by re-establishing the detection regions have on the power talk rate.