On performing semantic queries in small devices

Costea, Cristinel; Petrovan, Adrian; Neamt, Liviu; Chiver, Olivian

doi:10.1088/1757-899x/144/1/012005

Cited by 2 publications

(1 citation statement)

References 12 publications

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“…The local ontology is saved only at the gateway level in an Apache Jena triplestore. As shown in [42], Apache Jena is one of the top triplestore solutions and it can be successfully installed on small devices that can play the role of the gateway, such as Raspberry Pi [43].…”

Section: Semantic Security Gatewaymentioning

confidence: 99%

Named-Entity-Recognition-Based Automated System for Diagnosing Cybersecurity Situations in IoT Networks

Georgescu

Iancu

Zurini

2019

Sensors

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The aim of this paper was to enhance the process of diagnosing and detecting possible vulnerabilities within an Internet of Things (IoT) system by using a named entity recognition (NER)-based solution. In both research and practice, security system management experts rely on a large variety of heterogeneous security data sources, which are usually available in the form of natural language. This is challenging as the process is very time consuming and it is difficult to stay up to date with the constant findings in the areas of security threats, vulnerabilities, attacks, countermeasures, and risks. The proposed system is conceived as a semantic indexing solution of existing vulnerabilities and serves as an information tool for security management experts. By integrating the proposed system, the users can easily discover the potential vulnerabilities of their IoT devices. The proposed solution integrates ontologies and NER techniques in order to obtain a high rate of automation with the scope of reaching a self-maintained and up-to-date system in terms of vulnerabilities and common exposures knowledge. To achieve this, a total of 312 CVEs (common vulnerabilities and exposures) specific to the IoT field were identified. CVEs are arguably one of the most important cybersecurity resources nowadays, containing information about the latest discovered vulnerabilities. This set is further used as data corpus for an NER model designed to identify the main entities and relations that are relevant to IoT security. The goal is to automatically monitor cybersecurity information relevant to IoT, and filter and present it in an organized and structured framework based on users’ needs. The taxonomies specific to IoT security are implemented via a domain ontology, which is later used to process natural language. Relevant tokens are marked as entities and the relations between them identified. The text analysis solution is connected to a gateway which scans the environment and identifies the main IoT devices and communication technologies. The strength of the approach proposed within this research is that the designed semantic gateway is using context-aware searches in the modeled IoT security database and can identify possible vulnerabilities before they can be exploited.

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Section: Semantic Security Gatewaymentioning

confidence: 99%