Model-Driven Cyber Range Training: A Cyber Security Assurance Perspective

Security demands are increasing for all types of organisations, due to the ever-closer integration of computing infrastructures and smart devices into all aspects of the organisational operations. Consequently, the need for security-aware employees in every role of an organisation increases in accordance. Cyber Range training emerges as a promising solution, allowing employees to train in both realistic environments and scenarios and gaining hands-on experience in security aspects of varied complexity, depending on their role and level of expertise. To that end, this work introduces a model-driven approach for Cyber Range training that facilitates the generation of tailor-made training scenarios based on a comprehensive model-based description of the organisation and its security posture. Additionally, our approach facilitates the auto- mated deployment of such training environments, tailored to each defined scenario, through simulation and emulation means. To further highlight the usability of the proposed approach, this work also presents scenarios focusing on phishing threats, with increasing level of complexity and difficulty

A GENERAL FRAMEWORK FOR CONSENSUS NETWORKS

A new framework for the analysis of consensus networks is developed. The theory consists of necessary and sufficient conditions and it is flexible enough to comprise a variety of consensus systems. Under mild connectivity assumptions, the discussion ranges from linear, nonlinear, ordinary, functional and leader-follower models. The establishment of explicit estimates on the rate of convergence is the central objective. Our work extends and unifies past related works in the literature. Illustrative examples and simulations are presented to outline the theoretical results.US AFOSR MURI grant FA9550-09-1-0538, NSF grant CNS-1035655, NIST grant 70NANB11H14

A new type of lordosis and vertebral body compression in Gilthead seabream, Sparus aurata Linnaeus, 1758: aetiology, anatomy and consequences for survival

A new type of vertebral malformation is described, consisting of deformed cartilaginous neural and haemal processes and the compression and fusion of vertebral bodies. The malformation is designated as haemal vertebral compression and fusion (haemal VCF). We studied the aetiology of the malformations and described microanatomical histopathological alterations. The malformations were detected during routine quality control in one of six monitored Gilthead sea bream populations. Haemal VCF affected the posterior part of the vertebral column (haemal vertebrae). In 20% of the deformed specimens, haemal VCF was combined with lordosis. At 35dph (days post-hatching), early anatomical signs of the haemal VCF consisted of abnormal centrum mineralization, malformed cartilaginous neural and haemal processes and developing lordotic alterations. The histological examination of the deformed individuals revealed that haemal VCF is preceded by notochord abnormalities. The frequency of deformed individuals was three times higher at 35 than at 61dph (50.3% vs. 17.2%, n=157 and n=250, respectively). No signs of repair or reversion of malformations have been observed. Thus, the steep decrease in deformities in older animals suggests that haemal VCF is linked to high mortality rates. The results are discussed in respect of the possible causative factors of haemal VCF

Risk of Cascading Collisions in Network of Vehicles with Delayed Communication

This work explores cascading failures in networked control systems by employing a platoon of vehicles that exchange information over a time-delayed communication graph as a model. We study the roles of network connectivity, system dynamics, communication time-delay, and uncertainty in the emergence of these failure phenomena. Our results yield closed-form expressions for the average value-at-risk (AV@R), which we utilize as a coherent risk measure to quantify the cascading effect of vehicle collisions within a platoon. These findings are further extended with several standard communication graphs with symmetries to reveal the impact of graph design parameters on the risk of cascading collisions. By presenting the boundedness of the steady-state statistics of the inter-vehicle distances, we present the best achievable risk of cascading collision with general graph topologies, which is further specified for special communication graph such as the complete graph. Our theoretical findings pave the way for the development of a robust framework designed to mitigate the risk of cascading collisions in vehicle platoons by exploring how platoon reacts to the various existing failures and the change of communication links