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Modeling Intruder Reconnaissance Behavior through State Diagrams to Support Defensive Deception
by
Belalis, Ilias
, Spathoulas, Georgios
, Anagnostopoulos, Ioannis
in
Computer networks
/ Deception
/ Intelligence gathering
/ Mathematical models
/ modeling
/ Network security
/ reconnaissance
/ state diagrams
2023
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Modeling Intruder Reconnaissance Behavior through State Diagrams to Support Defensive Deception
by
Belalis, Ilias
, Spathoulas, Georgios
, Anagnostopoulos, Ioannis
in
Computer networks
/ Deception
/ Intelligence gathering
/ Mathematical models
/ modeling
/ Network security
/ reconnaissance
/ state diagrams
2023
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Do you wish to request the book?
Modeling Intruder Reconnaissance Behavior through State Diagrams to Support Defensive Deception
by
Belalis, Ilias
, Spathoulas, Georgios
, Anagnostopoulos, Ioannis
in
Computer networks
/ Deception
/ Intelligence gathering
/ Mathematical models
/ modeling
/ Network security
/ reconnaissance
/ state diagrams
2023
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Modeling Intruder Reconnaissance Behavior through State Diagrams to Support Defensive Deception
Journal Article
Modeling Intruder Reconnaissance Behavior through State Diagrams to Support Defensive Deception
2023
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Overview
Active reconnaissance is the primary source of information gathering about the infrastructure of a target network for intruders. Its main functions are host discovery and port scanning, the basic techniques of which are thoroughly analyzed in the present paper. The main contribution of the paper is the definition of a modeling approach regarding (a) all possible intruder actions, (b) full or partial knowledge of the intruder’s preferred methodology, and (c) the topology of the target network. The result of the modeling approach, which is based on state diagrams, is the extraction of a set of all probable paths that the intruder may follow. On top of this, a number of relevant metrics are calculated to enable the dynamic assessment of the risk to specific network assets according to the point on the paths at which the intruder is detected. The proposed methodology aims to provide a robust model that can enable the efficient and automated application of deception techniques to protect a given network. A series of experiments has also been performed to assess the required resources for the modeling approach when applied in real-world applications and provide the required results with bearable overhead to enable the online application of deception measures.
Publisher
MDPI AG
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