A.Geri, F.M.Gatta, M.Maccioni, J.Dell’Olmo, F.Carere, M.A.Bucarelli, P.Poursoltan, N.Hadifar, M.Paulucci
The energy transition requires an increasing penetration of renewable resources, particularly at MV/LV levels. The emerging production scheme is characterized by distributed power plants, imposes a capillary control of produc-tion and consumption among the Distribution Network (DN). The implementa-tion of Demand-side Response (DSR) campaigns is widely seen as a solution that can increase grid stability, but they require a complex and expensive monitoring infrastructure to select the optimal operating point of the production/consumption systems. This paper suggests a cheap and reliable smart monitoring device based on Raspberry Pi technology. The communication infrastructure adopted in the smart building of ASM S.p.A., the Distribution System Operator (DSO) of Terni city, shows the feasibility of implementing this prototype on a large-scale.
N. Fotiou, V. A. Siris, G. Polyzos, Y. Kortesniemi, D. Lagutin
Capabilities-based access control is a promising paradigm that can handle the particularities of IoT systems.Nevertheless, existing systems are not interoperable and they have limitations, such as lack of proof of possession, inefficient revocation mechanisms, and reliance on trusted third parties. In this paper we overcome these limitations by designing and implementing a system that leverages Verifiable Credentials (VCs) to encode the access rights. Our solution specifies protocols for requesting and using VCs that can be mapped to OAuth 2.0, includes an efficient and privacy preserving proof of possession mechanism, and it supports revocation. We implement and evaluate our solution and we show that it can be directly used even by constrained devices. Index Terms—Decentralized Identifiers, OAuth 2.0, Proof-ofPossession, Internet of Things
A. Geri, F.M. Gatta, M. Maccioni, J. Dell’Olmo, F. Carere, M.A. Bucarelli, P. Poursoltan, N. Hadifar, M. Paulucci
The evolution of the distribution grids towards the smart grid paradigm requires the implementation of a telecommunication network overlayed to the distribution grid. To achieve this target a new generation of reliable, cheap, and easily deployable smart meters needs to be developed. This paper presents a smart meter that fits in a series of possible implementations from the household metering to the distributed generation monitoring. The Raspberry Pi ecosystem is chosen for this purpose due to low cost and a highly reliable technology to develop an easy-deployable smart meter, to collect the principal magnitudes of interest of the monitored side and make them accessible from Laptop or mobile phone. The designed device is realized and deployed in a secondary substation to monitor a PV power plant in the ASM Terni distribution network.
St. Bourou, A. El Saer, T.-H. Velivassaki, A. Voulkidis, Th. Zahariadis
Recent technological innovations along with the vast amount of available data worldwide, have led to the rise of cyberattacks against network systems. Intrusion Detection Systems (IDS) play a crucial role as a defense mechanism in networks, against adversarial attackers. Machine Learning methods provide various cybersecurity tools. However, these methods require plenty of data to be trained efficiently. Data which may be hard to collect or to use due to privacy reasons. One of the most notable Machine Learning tools is the Generative Adversarial Network (GAN) and it has great potential for Tabular data synthesis. In this work, we start by briefly presenting the most popular GAN architectures, VanillaGAN, WGAN and WGAN-GP. Focusing on tabular data generation, CTGAN, CopulaGAN and TableGAN models are used for the creation of synthetic IDS data. Specifically, the models are trained and evaluated on NSL-KDD dataset, considering the limitations and requirements that this procedure needs. Finally, based on certain quantitative and qualitative methods we argue and evaluate the most prominent GANs for tabular network data synthesis.
N. Eiling, J. Baude, S. Lankes, A. Monti
In high-performance computing and cloud computing the introduction of heterogeneous computing resources, such as GPU accelerator have led to a dramatic increase in performance and efficiency. While the benefits of virtualization features in these environments are well researched, GPUs do not offer virtualization support that enables fine-grained control, increased flexibility, and fault tolerance. In this article, we present Cricket: A transparent and low-overhead solution to GPU virtualization that enables future research into other virtualization techniques, due to its open-source nature. Cricket supports remote execution and checkpoint/restart of CUDA applications. Both features enable the distribution of GPU tasks dynamically and flexibly across computing nodes and the multi-tenant usage of GPU resources, thereby improving flexibility and utilization for high-performance and cloud computing.