University of Sannio

About: University of Sannio is a education organization based out in Benevento, Italy. It is known for research contribution in the topics: Gravitational wave & LIGO. The organization has 1278 authors who have published 6125 publications receiving 167577 citations. The organization is also known as: Università degli Studi del Sannio & Universita degli Studi del Sannio.

Toward the automation of threat modeling and risk assessment in IoT systems

Abstract: The Internet of Things (IoT) has recently become one of the most relevant emerging technologies in the IT landscape. IoT systems are characterized by the high heterogeneity of involved architectural components (e.g., device platforms, services, networks, architectures) and involve a multiplicity of application domains. In the IoT scenario, the identification of specific security requirements and the security design are very complex and expensive tasks, since they heavily depend on the configuration deployment actually in place and require security experts. In order to overcome these issues, we propose an approach aimed at supporting the security analysis of an IoT system by means of an almost completely automated process for threat modeling and risk assessment, which also helps identify the security controls to implement in order to mitigate existing security risks. We demonstrate the effectiveness of the approach by discussing its application to a home automation system, built on top of commercial IoT products.

The miR-27a-calreticulin axis affects drug-induced immunogenic cell death in human colorectal cancer cells

Abstract: Immunogenic cell death (ICD) evoked by chemotherapeutic agents implies emission of selected damage-associated molecular patterns (DAMP) such as cell surface exposure of calreticulin, secretion of ATP and HMGB1. We sought to verify whether miR-27a is implicated in ICD, having demonstrated that it directly targets calreticulin. To this goal, we exposed colorectal cancer cell lines, genetically modified to express high or low miR-27a levels, to two bona fide ICD inducers (mitoxantrone and oxaliplatin). Low miR-27a-expressing cells displayed more ecto-calreticulin on the cell surface and increased ATP and HMGB1 secretion than high miR-27a-expressing ones in time-course experiments upon drug exposure. A calreticulin target protector counteracted the miR-27a effects while specific siRNAs mimicked them, confirming the results reported. In addition, miR-27a negatively influenced the PERK-mediated route and the late PI3K-dependent secretory step of the unfolded protein response to endoplasmic reticulum stress, suggesting that miR-27a modulates the entire ICD program. Interestingly, upon chemotherapeutic exposure, low miR-27a levels associated with an earlier and stronger induction of apoptosis and with morphological and molecular features of autophagy. Remarkably, in ex vivo setting, under the same chemotherapeutic induction, the conditioned media from high miR-27a-expressing cells impeded dendritic cell maturation while increased the secretion of specific cytokines (interleukin (IL)-4, IL-6, IL-8) and negatively influenced CD4(+) T-cell interferon γ production and proliferation, all markers of a tumor immunoevasion strategy. In conclusion, we provide the first evidence that miR-27a impairs the cell response to drug-induced ICD through the regulatory axis with calreticulin.

Improving IR-based Traceability Recovery Using Smoothing Filters

Abstract: Information Retrieval methods have been largely adopted to identify traceability links based on the textual similarity of software artifacts. However, noise due to word usage in software artifacts might negatively affect the recovery accuracy. We propose the use of smoothing filters to reduce the effect of noise in software artifacts and improve the performances of traceability recovery methods. An empirical evaluation performed on two repositories indicates that the usage of a smoothing filter is able to significantly improve the performances of Vector Space Model and Latent Semantic Indexing. Such a result suggests that other than being used for traceability recovery the proposed filter can be used to improve performances of various other software engineering approaches based on textual analysis.

Entropy approach for 2D velocity distribution in open-channel flow

Abstract: In this paper, considering time-averaged velocity as a random variable, two-dimensional (2D) velocity distributions in open-channel flow have been derived based on the Shannon entropy concept and the principle of maximum entropy. The velocity distributions so derived have limited practical use, since they contain too many parameters that need to be experimentally calibrated and hence are not convenient to apply. This work develops a new entropy-based approach for deriving a 2D velocity distribution in open-channel flow, thereby investigating a rectangular geometric domain. The derived distribution is parsimonious, and the values determined using the proposed distribution are found to be in good agreement with the experimentally-measured velocity values.