An Anatomy for Recognizing Network Attack Intention
Anchit Bijalwan1, Satenaw Sando2, Muluneh Lemma3
1Anchit Bijalwan, Faculty of Electrical & Computer Engineering, Arba Minch University, Arba Minch, Ethiopia.
2Satenaw Sando, Faculty of Electrical & Computer Engineering, Arba Minch University, Arba Minch, Ethiopia.
3Muluneh Lemma, Dean Research, AMIT, Arba Minch University, Arba Minch, Ethiopia.
Manuscript received on 15 August 2019. | Revised Manuscript received on 25 August 2019. | Manuscript published on 30 September 2019. | PP: 803-816 | Volume-8 Issue-3 September 2019 | Retrieval Number: C4022098319/19©BEIESP | DOI: 10.35940/ijrte.C4022.098319
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Research in the field of Network forensics is tremendously expanding with the tendency to help in arbitrating, capturing and detaining the exponential growth of the cyber crimes. With this expansion, the field of Network forensics is still not clear and is uncertain. In this paper, we have presented the architecture of an analysis mechanism for network forensics. The work followed by generic process model for network forensics investigation is also presented and discussed in detail. Overall this paper presents an overview of the network forensics architecture, generic process models to help a user in the times of emergency by considering the incident and thus maintaining the privacy and security policies.
Index Terms: Network Forensics, Attack Intention, Traceback, Attribution, Incident response.
Scope of the Article: Sensor Networks, Actuators for Internet of Things