Cybersecurity and Government
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ItemScientific Knowledge of the Human Side of Information Security as a Basis for Sustainable Trainings in Organizational Practices( 2018-01-03)Comprehensive digitization leads to new chal-lenges because of cybercrime and related security countermeasures. There is no doubt that this will fundamentally affect our lives and is leading to an increase in the importance of information security (IS). However, technology solutions alone are not sufficient to ensure IS countermeasures. The human side of security is important to protect organizational assets like user information and systems. The paper illustrates these relationships in terms of information security awareness (ISA), examining its goals and the factors influencing it through the systematic analysis and review of scientific literature and the transfer of scientific knowledge for practical purposes. We reviewed the publications of leading academic journals in the field of IS over the past decade.
ItemMultivariate Stochastic Approximation to Tune Neural Network Hyperparameters for Criticial Infrastructure Communication Device Identification( 2018-01-03)The e-government includes Wireless Personal Area Network (WPAN) enabled internet-to-government pathways. Of interest herein is Z-Wave, an insecure, low-power/cost WPAN technology increasingly used in critical infrastructure. Radio Frequency (RF) Fingerprinting can augment WPAN security by a biometric-like process that computes statistical features from signal responses to 1) develop an authorized device library, 2) develop classifier models and 3) vet claimed identities. For classification, the neural network-based Generalized Relevance Learning Vector Quantization-Improved (GRLVQI) classifier is employed. GRLVQI has shown high fidelity in classifying Z-Wave RF Fingerprints; however, GRLVQI has multiple hyperparameters. Prior work optimized GRLVQI via a full factorial experimental design. Herein, optimizing GRLVQI via stochastic approximation, which operates by iterative searching for optimality, is of interest to provide an unconstrained optimization approach to avoid limitations found in full factorial experimental designs. The results provide an improvement in GRLVQI operation and accuracy. The methodology is further generalizable to other problems and algorithms.
ItemA Conceptual Framework for Addressing IoT Threats: Challenges in Meeting Challenges( 2018-01-03)The Internet of Things (IoT) is rapidly growing, and offers many economical and societal potentials and benefits. Nevertheless, the IoT also introduces new threats to our Security, Privacy and Safety (SPS). The existing work on mitigating these SPS threats often fails to address the fundamental challenges behind the mitigation measures proposed, and fails to make the relations between different mitigation measures explicit. This paper, therefore, offers a conceptual framework for understanding and approaching the challenges and obstacles that arise in addressing the SPS threats of the IoT. This contribution aims to help policymakers in adopting policies and strategies that stimulate others to develop, deploy and use IoT devices, applications and services in secure, privacy-friendly and safe ways.