Cybersecurity vulnerability management: A conceptual ontology and cyber intelligence alert system

Syed, Romilla

doi:10.1016/j.im.2020.103334

Cited by 66 publications

(28 citation statements)

References 41 publications

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“…Kiran et al [49] present enhanced security-aware technique and ontology data access control in cloud computing. Syed et al [97] present a conceptual ontology and cyber intelligence alert system for cybersecurity vulnerability management. An ontologybased cyber security policy implementation in Saudi Arabia has been presented in Talib et al [98].…”

Section: Knowledge Representation Uncertainty Reasoning and Expert System Modelingmentioning

confidence: 99%

AI-Based Modeling: Techniques, Applications and Research Issues Towards Automation, Intelligent and Smart Systems

Sarker¹

2022

Preprint

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Artificial Intelligence (AI) is a leading technology of the current age of the Fourth Industrial Revolution (Industry 4.0 or 4IR), with the capability of incorporating human behavior and intelligence into machines or systems. Thus AI-based modeling is the key to building automated, intelligent, and smart systems according to today's needs. To solve real-world issues various types of AI such as analytical, functional, interactive, textual, and visual AI can be applied to enhance the intelligence and capabilities of an application. However, developing an effective AI model is a challenging task due to the dynamic nature and variation in real-world problems and data. In this paper, we present a comprehensive view on "AI-based Modeling" with the principles and capabilities of potential AI techniques that can play an important role in developing intelligent and smart systems in various real-world application areas including business, finance, healthcare, agriculture, smart cities, cybersecurity and many more. We also emphasize and highlight the research issues within the scope of our study. Overall, the goal of this paper is to provide a broad overview of AI-based modeling that can be used as a reference guide by academics and industry people as well as decision-makers in various real-world scenarios and application domains.

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Section: Knowledge Representation Uncertainty Reasoning and Expert System Modelingmentioning

confidence: 99%

AI-Based Modeling: Techniques, Applications and Research Issues Towards Automation, Intelligent and Smart Systems

Sarker¹

2022

Preprint

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“…This study has focused on developing and evaluating an ontology model for analyzing cyber influence campaigns in conflicts conducted in social media networks. Social media networks can also give indications of emerging cyber security threats [119]- [123]. One interesting future work direction is to adapt our ontology model to uncover the sources and agents behind emerging cyber threats.…”

Section: F Limitations and Future Researchmentioning

confidence: 99%

Semantically Modeling Cyber Influence Campaigns (CICs): Ontology Model and Case Studies

et al. 2021

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“…Because, as Huysmans argues, OST is founded upon relational security practices and the ability to perceive which are and are not manifest security threats is hotly in contention and is driven “by ‘securitizing’ the unknown into an identifiable threat” (Steele, 2017). The unknown in this case can be typified, though not flippantly, by the “half a billion cyber security breaches in first semester of 2014” (Oltramari et al, 2014) or the “16,555 vulnerabilities between January 1, 2018, and December 31, 2018” (Syed, 2020). This picture of the cyber horizon is made even more chaotic when one recognizes that “65% of the victims of intrusion and information theft in the private sector are notified by third parties and that the detection process usually takes up to 13 months” (quoted in Syed, 2020).…”

Section: Ontological Security Theory Cyber Conflict and Visionmentioning

confidence: 99%

“…The unknown in this case can be typified, though not flippantly, by the “half a billion cyber security breaches in first semester of 2014” (Oltramari et al, 2014) or the “16,555 vulnerabilities between January 1, 2018, and December 31, 2018” (Syed, 2020). This picture of the cyber horizon is made even more chaotic when one recognizes that “65% of the victims of intrusion and information theft in the private sector are notified by third parties and that the detection process usually takes up to 13 months” (quoted in Syed, 2020).…”

Section: Ontological Security Theory Cyber Conflict and Visionmentioning

confidence: 99%

“…For those in the cyber security community (computer scientists, data systems managers, and cyber security analysts) this means creating a common language to describe threats and to properly allocate culpability. They describe the problem as “ cognizance ” or the ability to create a “reliable perception of the elements of the environment and…the explicit representation of their semantics” (Syed, 2020, p. 54). The promotion of a shared conceptualization of chaotic and often covert threat attempts to, “shape that chaos into a framework of meaningful chunks of knowledge, turning the operational disarray into a systematic model” that gives practitioners and theorists purchase on dealing with cyber threats.…”

Section: Ontological Security Theory Cyber Conflict and Visionmentioning

confidence: 99%

See 1 more Smart Citation

Ontological (In)visibility and Cyber Conflict: The Problem of Sight and Vision in Establishing Threat

Whooley

2021

Alternatives: Global, Local, Political

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This paper builds on the work of scholars working on ontological security, cyber security, and computer science to understand the problem of threat assessment and vision before, during, and after cyber-attacks. The previous use of ontological security theory (OST) has been limited because it has relied upon an overly simplistic vision of threat assessment at the international, state, and individual level. While previous scholars have examined the background, latent, or assumed visions of security threats as interpreted by agents and how their conditions do or do not effectively capture the anxieties of populations and practitioners this piece seeks to put these issues in conversation. In conceiving of ‘the state’ and ‘threat’ this piece examines the notion of vision, because as states conceive of threats in terms of terrorism (overt and theatrical) and cyber (covert and private) a mismatch of responses is noted. This piece reads the current cyber security landscape (2009-2019) in the United States through a lens of repeated and rambunctious cyber-threats and attacks and a largely passive response by the US citizenry through OST alongside: (1) the literature on computer science dealing with the concept of ontology, (2) the traditional threat framework found in the terrorism literature around response to threat with a comparison to the cyber-conflict literature, an (3) examination of the interplay between the public and government around the visibility and salience of cyberthreats.

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Cybersecurity vulnerability management: A conceptual ontology and cyber intelligence alert system

Cited by 66 publications

References 41 publications

AI-Based Modeling: Techniques, Applications and Research Issues Towards Automation, Intelligent and Smart Systems

AI-Based Modeling: Techniques, Applications and Research Issues Towards Automation, Intelligent and Smart Systems

Semantically Modeling Cyber Influence Campaigns (CICs): Ontology Model and Case Studies

Ontological (In)visibility and Cyber Conflict: The Problem of Sight and Vision in Establishing Threat

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