Security assessment in IoT ecosystems

The Internet of Things (IoT) and "Smart Everything" trend is a reality that is becoming part of our daily lives. Consequently, there is a gradual increase in the deployment of real world IoT systems that attempt to make use of the various possibilities and benefits the IoT offers. However, the connection of billions of-usually inherently insecure-devices in a network, paired with the lack of a clear security framework for the development of IoT systems and platforms has widened the attack surface of these systems leading to them being targeted by malicious actors. In this paper, we explore the problem and related research, devise an assets taxonomy and focus on the security requirements for each asset category. Then, we discuss countermeasures and good practices as well as new approaches based on AI that improve security and intrusion detection capabilities. We also introduce a metric that can be incorporated by automated security auditing methods. The relevance of this metric is evaluated with respect to correlation across findings from a real-world study. Copyright © 2020 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0)

Parallel model exploration for tumor treatment simulations

Computational systems and methods are often being used in biological research, including the understanding of cancer and the development of treatments. Simulations of tumor growth and its response to different drugs are of particular importance, but also challenging complexity. The main challenges are first to calibrate the simulators so as to reproduce real-world cases, and second, to search for specific values of the parameter space concerning effective drug treatments. In this work, we combine a multi-scale simulator for tumor cell growth and a genetic algorithm (GA) as a heuristic search method for finding good parameter configurations in reasonable time. The two modules are integrated into a single workflow that can be executed in parallel on high performance computing infrastructures. In effect, the GA is used to calibrate the simulator, and then to explore different drug delivery schemes. Among these schemes, we aim to find those that minimize tumor cell size and the probability of emergence of drug resistant cells in the future. Experimental results illustrate the effectiveness and computational efficiency of the approach. © 2022 Wiley Periodicals LLC