Tiered architecture for threat detection and containment using system of wireless embedded sensors and robots

Madni, A.M.; Sridhar, P.

doi:10.1109/wac.2014.6936187

Cited by 1 publication

(2 citation statements)

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“…Threat-aware deployment of sensors and systems of robots can work in pair to identify, evaluate, quarantine and hold threats. [125] presents a model, a scheme and a categorized architectural operation of a threat detection system. Using a convergent architecture, [125] propose a varied set of operationally independent systems, ranging from in situ sensors, sensor robots (mobile sensors) to aerial reconnaissance sensors, each of which is capable of working in combination.…”

Section: Threat Containmentmentioning

confidence: 99%

“…[125] presents a model, a scheme and a categorized architectural operation of a threat detection system. Using a convergent architecture, [125] propose a varied set of operationally independent systems, ranging from in situ sensors, sensor robots (mobile sensors) to aerial reconnaissance sensors, each of which is capable of working in combination. As a way to improve the handling of a threat, [125] suggest a deployment strategy arranging in order of rank, which is especially attentive to data integrity and false alarm lessening [125].…”

Section: Threat Containmentmentioning

confidence: 99%

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Turning the Hunted into the Hunter via Threat Hunting: Life Cycle, Ecosystem, Challenges and the Great Promise of AI

Hillier¹,

Karroubi²

2022

Preprint

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The threat hunting lifecycle is a complex atmosphere that requires special attention from professionals to maintain security. This paper is a collection of recent work that gives a holistic view of the threat hunting ecosystem, identifies challenges, and discusses the future with the integration of artificial intelligence (AI). We specifically establish a life cycle and ecosystem for privacy-threat hunting in addition to identifying the related challenges. We also discovered how critical the use of AI is in threat hunting. This work paves the way for future work in this area as it provides the foundational knowledge to make meaningful advancements for threat hunting.

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Section: Threat Containmentmentioning

confidence: 99%