arXiv subjects

Vinicius V. Cogo

Publications and source records attributed to Vinicius V. Cogo.

3 recordsLinked to original sources

arXiv2026

A Survey on Semantic Modeling for Building Energy Management

Building Energy Management (BEM) is central to reducing energy use and CO2 emissions in the building sector. Although IoT technologies now provide extensive operational data, heterogeneous data models, device descriptions, and contextual representations continue to limit semantic interoperability, limiting the development of generalisable, autonomous, context-aware BEM applications. Ontologies address this challenge by providing structured, machine-interpretable representations of building data, systems, and operational context. This survey examines semantic modelling for BEM during the building operational phase. It reviews 60 semantic models and analyses more than 20 ontology-based BEM use cases. It further quantifies Ontology Instantiation Rates (OIR) and missing concepts across those use cases. To support evidence-based assessment of ontology use, we introduce the notion of Ontology Evidence Completeness (OEC), a measure of whether studies explicitly map operational concepts to the ontology classes used to represent them. Findings show that current semantic models more consistently represent physical building structure, technical systems, sensing devices, and observable operational data than abstract and dynamic operational concepts. Concepts such as key performance indicators, assessments, services, control logic, optimisation tasks, and computational workflows remain less consistently covered. Applied BEM studies therefore frequently depend on ontology reuse, integration, specialisation, external inheritance, or application-specific extension to address coverage and interoperability gaps across BEM. By synthesising these patterns, this survey clarifies the capabilities of existing semantic models and identifies directions for more interoperable, generalisable, and context-aware BEM systems.

cs.AI↗

arXiv2024

SecScore: Enhancing the CVSS Threat Metric Group with Empirical Evidences

Background: Timely prioritising and remediating vulnerabilities are paramount in the dynamic cybersecurity field, and one of the most widely used vulnerability scoring systems (CVSS) does not address the increasing likelihood of emerging an exploit code. Aims: We present SecScore, an innovative vulnerability severity score that enhances CVSS Threat metric group with statistical models from empirical evidences of real-world exploit codes. Method: SecScore adjusts the traditional CVSS score using an explainable and empirical method that more accurately and promptly captures the dynamics of exploit code development. Results: Our approach can integrate seamlessly into the assessment/prioritisation stage of several vulnerability management processes, improving the effectiveness of prioritisation and ensuring timely remediation. We provide real-world statistical analysis and models for a wide range of vulnerability types and platforms, demonstrating that SecScore is flexible according to the vulnerability's profile. Comprehensive experiments validate the value and timeliness of SecScore in vulnerability prioritisation. Conclusions: SecScore advances the vulnerability metrics theory and enhances organisational cybersecurity with practical insights.

cs.CR↗

arXiv2020

Auditable Register Emulations

The widespread prevalence of data breaches amplifies the importance of auditing storage systems. In this work, we initiate the study of auditable storage emulations, which provide the capability for an auditor to report the previously executed reads in a register. We precisely define the notion of auditable register and its properties, and establish tight bounds and impossibility results for auditable storage emulations in the presence of faulty storage objects. Our formulation considers loggable read-write registers that securely store data using information dispersal and support fast reads. In such a scenario, given a maximum number~$f$ of faulty storage objects and a minimum number~$τ$ of data blocks required to recover a stored value, we prove that (1) auditability is impossible if $τ\leq 2f $; (2) implementing a weak form of auditability requires $τ\geq 3f+1$; and (3) a stronger form of auditability is impossible. We also show that signing read requests overcomes the lower bound of weak auditability, while totally ordering operations or using non-fast reads enables strong auditability.

cs.DC↗