This paper presents a technique for deriving a scalable model for representing network attacks, and its application to identify actual attacks with greater ...
"The Derivation And Use Of A Scalable Model For Network Attack ...
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Nanda, Sanjeeb and Deo, Narsingh, "The Derivation And Use Of A Scalable Model For Network Attack Identification And Path Prediction" (2008). Scopus Export 2000s ...
Sep 15, 2020 · Bibliographic details on The Derivation and Use of a Scalable Model for Network Attack Identification and Path Prediction.
This study proposed a model that uses system vulnerability to predict the progression of attacks. ... Intrusion Detection Forecasting Using Time Series for ...
Missing: Derivation | Show results with:Derivation
Our model for representing attack graphs is highly scalable and the given algorithms that use it to identify attacks and predict their future targets, are ...
Missing: Derivation | Show results with:Derivation
Efficient intrusion-detection using programmable agents based on attack graph patterns. January 2008. N. Deo ...
Abstract— Current intrusion detection and prevention systems seek to detect a wide class of network intrusions (e.g., DoS attacks,.
Missing: Derivation | Show results with:Derivation
Oct 5, 2024 · Given the rapid growth of the internet and the explosion of usage, any malicious intrusion or attack on network vulnerability can lead to a ...
Many network attacks use adversarial concealment techniques in multiple stages, such as system intrusion, continuous latency, keep-alive communication, and data ...
Missing: Derivation | Show results with:Derivation
The results demonstrate the capability of our ap- proach in correlating isolated attack scenarios, identifying attack strategies and predicting future attacks.