Measurement of situation awareness among diverse agents in cyber security

Purpose The purpose of this paper is to investigate security decision-making during risk and uncertain conditions and to propose a normative model capable of tracing the decision rationale. Design/methodology/approach The proposed risk rationalisation model is grounded in literature and studies on security analysts’ activities. The model design was inspired by established awareness models including the situation awareness and observe–orient–decide–act (OODA). Model validation was conducted using cognitive walkthroughs with security analysts. Findings The results indicate that the model may adequately be used to elicit the rationale or provide traceability for security decision-making. The results also illustrate how the model may be applied to facilitate design for security decision makers. Research limitations/implications The proof of concept is based on a hypothetical risk scenario. Further studies could investigate the model’s application in actual scenarios. Originality/value The paper proposes a novel approach to tracing the rationale behind security decision-making during risk and uncertain conditions. The research also illustrates techniques for adapting decision-making models to inform system design.

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On detection and visualization techniques for cyber security situation awareness

10.1117/12.2015887 ◽

2013 ◽

Cited By ~ 1

Author(s):

Wei Yu ◽

Shixiao Wei ◽

Dan Shen ◽

Misty Blowers ◽

Erik P. Blasch ◽

...

Keyword(s):

Situation Awareness ◽

Cyber Security ◽

Visualization Techniques

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Survey on Cyber Security and Defensive Measures

International Journal of Scientific Research in Computer Science Engineering and Information Technology ◽

10.32628/cseit206130 ◽

2020 ◽

pp. 144-151

Author(s):

Hemlata. R. Kosare ◽

Kiran V. Likhar ◽

Pranali Manapure

Keyword(s):

Pattern Recognition ◽

Risk Management ◽

Decision Support ◽

Decision Support Systems ◽

Situation Awareness ◽

Cyber Security ◽

Developmental Level ◽

Cyber Defense ◽

Digital Protection ◽

Defensive Measures

The progression of advanced data is developing a regular routine making it gradually hard to oversee and structure it or even to isolate what is significant based on what is pointless. Looked with this test, new encouraging achievement advancements are being created to bring 'information examination's to the following developmental level. Man-made reasoning (AI), specifically, is required to wind up huge in numerous fields. A few types of AI empower AI like profound learning can be utilized to perform prescient scrutiny. Their possible for the defense domain is huge as AI solutions are expected to develop in serious fields such as cyber defense, decision-support systems, risk management, pattern recognition, cyber situation awareness, projection, malware detection and data relationship to name but a few. One of the potential uses of AI in digital protection might be to empower the setting up of self-designing systems. It would imply that AI agendas could recognize vulnerabilities (programming bugs) and perform reaction activities such as self-fixing. This opens better approaches to fortifying correspondences and data frameworks security by giving system strength, avoidance and insurance against digital dangers.

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