From Monitoring Templates to Security Monitoring and Threat Detection

Amálio, Nuno; Spanoudakis, George

doi:10.1109/securware.2008.58

Cited by 7 publications

(9 citation statements)

References 20 publications

(27 reference statements)

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“…The process of defining analysis goals may require domain knowledge and skill in building and analysing models. However, the process can be partially or fully automated by following the pattern-based approach proposed of [11]. [11] uses the Formal Template Language [19], [13] to represent patterns of EC models together with their associated security monitoring goals.…”

Section: Discussionmentioning

confidence: 99%

“…However, the process can be partially or fully automated by following the pattern-based approach proposed of [11]. [11] uses the Formal Template Language [19], [13] to represent patterns of EC models together with their associated security monitoring goals. [11] defines templates of such goals that are of the security violation type, but patterns of suspicious goals can also be defined if we know in advance what can arouse suspicion.…”

Section: Discussionmentioning

confidence: 99%

“…The approach presented here emerges from its preceding work on threat detection [11]. [11] uses an EC model of requirements and planning to find threats at run-time.…”

Section: Related Workmentioning

confidence: 99%

“…[11] uses an EC model of requirements and planning to find threats at run-time. In [11], however, the goals used to detect threats are more rigid than the ones used here; they say with absolute certainty whether there is an attack or not when the goal is satisfied. In the approach presented here, there is no certainty of attack if a suspicious goal is satisfied, the plans that reach the goal just give us threats (possible attacks).…”

Section: Related Workmentioning

confidence: 99%

“…It would be possible to incorporate our approach based on suspicion as a strategy in looking for threats at run-time. Then, the probabilistic component of such a system (like the one of [11]) would try to assign a probability to the computed threats. Here we use suspicion to look for threats in requirements to avoid systems with security vulnerabilities.…”

Section: Related Workmentioning

confidence: 99%

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Suspicion-Driven Formal Analysis of Security Requirements

Amálio

2009

2009 Third International Conference on Emerging Security Information, Systems and Technologies

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Increasingly, engineers need to approach security and software engineering in a unified way. This paper presents an approach to the formal analysis of security requirements that is based on planning and uses the concept of suspicion to guide the search for threats and security vulnerabilities in requirements. The approach is tested and illustrated by conducting two experiments: one focussing on a system with a confidentiality security property, and another with an integrity security property enforced through the separation of duty principle. The paper shows that suspicion plays an important rôle in finding vulnerabilities and security threats in requirements.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

“…The approach presented here emerges from its preceding work on threat detection [11]. [11] uses an EC model of requirements and planning to find threats at run-time.…”

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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Suspicion-Driven Formal Analysis of Security Requirements

Amálio

2009

2009 Third International Conference on Emerging Security Information, Systems and Technologies

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Data-Driven and Artificial Intelligence (AI) Approach for Modelling and Analyzing Healthcare Security Practice: A Systematic Review

Yeng

Nweke

Woldaregay

et al. 2020

Advances in Intelligent Systems and Computing

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Data breaches in healthcare continue to grow exponentially, calling for a rethinking into better approaches of security measures towards mitigating the menace. Traditional approaches including technological measures, have significantly contributed to mitigating data breaches but what is still lacking is the development of the "human firewall," which is the conscious care security practices of the insiders. As a result, the healthcare security practice analysis, modeling and incentivization project (HSPAMI) is geared towards analyzing healthcare staffs' security practices in various scenarios including big data. The intention is to determine the gap between staffs' security practices and required security practices for incentivization measures. To address the state-of-the art, a systematic review was conducted to pinpoint appropriate AI methods and data sources that can be used for effective studies. Out of about 130 articles, which were initially identified in the context of human-generated healthcare data for security measures in healthcare, 15 articles were found to meet the inclusion and exclusion criteria. A thorough assessment and analysis of the included article reveals that, KNN, Bayesian Network and Decision Trees (C4.5) algorithms were mostly applied on Electronic Health Records (EHR) Logs and Network logs with varying input features of healthcare staffs' security practices. What was found challenging is the performance scores of these algorithms which were not sufficiently outlined in the existing studies.

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