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The digitalization of energy generation and distribution systems opens new opportunities for devising network operation and traffic engineering strategies capable of adapting to the energy availability and sources. Despite the potential, developing and testing new approaches are challenging in production environments. Furthermore, no simulators support such integration between the communication infrastructure and the power grid. Thus, this paper introduces Flexcomm Simulator, a tool based on ns-3 that supports developing and assessing multiple strategies toward green networking and communications driven by real-time information from the power grid (i.e., Energy Flexibility). The proof-of-concept results demonstrate this contribution's potential by implementing an energy-aware routing algorithm that adapts to real-world Energy Flexibility data in a Metropolitan Area Network (MAN). Also, it showcases the simulator's capacity to deal with large-scale simulations through MPI-based distributed environments.

Abstract
The increasing use of microservices architectures has been accompanied by the profusion of tools for their design and operation. One relevant tool is API Gateways, which work as a proxy for microservices, hiding their internal APIs, providing load balancing, and multiple encoding support. Particularly in cloud environments, where the inherent flexibility allows on-demand resource deployment, API Gateways play a key role in seeking quality of service. Although multiple solutions are currently available, a comparative performance assessment under real workloads to support selecting the more suitable one for a specific service is time-consuming. In this way, the present work introduces AGE, a service capable of automatically deploying multiple API Gateways scenarios and providing a simple comparative performance indicator for a defined workload and infrastructure. The designed proof of concept shows that AGE can speed up API Gateway deployment and testing in multiple environments. © 2023 IEEE.

Abstract
Cryptographic ransomware attacks are constantly evolving by obfuscating their distinctive features (e.g., I/O patterns) to bypass detection mechanisms and to run unnoticed at infected servers. Thus, efficiently exploring the I/O behavior of ransomware families is crucial so that security analysts and engineers can better understand these and, with such knowledge, enhance existing detection methods. In this paper, we propose CRIBA, an open-source framework that simplifies the exploration, analysis, and comparison of I/O patterns for Linux cryptographic ransomware. Our solution combines the collection of comprehensive information about system calls issued by ransomware samples, with a customizable and automated analysis and visualization pipeline, including tailored correlation algorithms and visualizations. Our study, including 5 Linux ransomware families, shows that CRIBA provides comprehensive insights about the I/O patterns of these attacks while aiding in exploring common and differentiating traits across families.

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