Proposed Framework for Effective Detection and Prediction of Advanced Persistent Threats Based on the Cyber Kill Chain

ავტორი: Faisal A. Garba, Sahalu B. Junaidu, Barroon I. Ahmad, Abdoulie M. S. Tekanyi
ორგანიზაცია: Department of Computer Science Education, Sa’adatu Rimi College of Education, Kano, Nigeria, Department of Computer Science, Ahmadu Bello University, Zaria, Nigeria, Department of Electrical & Computer Engineering, Ahmadu Bello University, Zaria, Nigeria

კატეგორია:

საკვანძო სიტყვები: Advanced Persistent Threat (APT), cyber kill chain (CKC), data breach, cyber attack, APT detection.
აბსტრაქტი. The cost of data breach resulting from cyber attacks is estimated to be $3.62 million dollars worldwide according to a report. Advanced Persistent Threat (APT) is a targeted cyber attack that is tailored, proceeds at a stealth and has a high objective. The state of the art security monitoring tools have failed in their attempts to detect APT. Therefore, there is a need for a solution that is fool-proof in the detection of an APT. This paper proposed the use of cyber kill chain to detect the various attack methodologies used in an APT campaign and to correlate and predict the existence of an APT attack. APT attack deploys various attack techniques which are mapped to the stages of the cyber kill chain. For each of those techniques, an attack detection methodology has been proposed in this paper. The detection result of each of these methodologies, will now be correlated in the correlation module to ascertain whether there is an ongoing APT attack and raise an alert. The result from this research work will be evaluated against a current related work. This research will therefore advance the state of the art in APT attack detection.

ბიბლიოგრაფია

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