MICIE: A model for identifying and collecting intrusion evidences

Ahmed, Abdulghani Ali and Kit, Yee Wai (2017) MICIE: A model for identifying and collecting intrusion evidences. In: 12th International Conference on Signal Image Technology and Internet-Based Systems (SITIS 2016) , 28 November - 1 December 2016 , Naples, Italy. pp. 288-294.. ISBN 978-1-5090-5698-9

[img] Pdf
MICIE- A Model for Identifying and Collecting Intrusion Evidences.pdf
Restricted to Repository staff only
Download (539kB) | Request a copy
[img]
Preview
 Pdf
MICIE- A Model for Identifying and Collecting Intrusion Evidences 1.pdf
Download (184kB) | Preview

Abstract

Today it is very important to maintain an intermediary level of security to ensure safe and trusted communication for daily usage. Secured data communication over internet and any other network is hard to achieve due to the threat of intrusions and misuse. Unfortunately, none of the existing systems have proved to be flawless, though various approaches have been used to thwart network intrusion activities. This paper proposes an investigation Model for Identifying and Collecting Intrusion Evidences (MICIE). In particular, the proposed model MICIE comprises three main features, SNORT as IDS, MySQL as database and BASE for result viewing. These features were installed on Raspberry Pi, which was used to aid the data collection process. The results demonstrated that the proposed model is promising for identifying and collecting evidence of network intrusions in real time.

Item Type: Conference or Workshop Item (Speech)
Additional Information: Indexed by Scopus
Uncontrolled Keywords: Intrusion evidence; Cloud computing; Forensic investigation; Raspberry Pi.
Subjects: Q Science > QA Mathematics > QA76 Computer software
Faculty/Division: Faculty of Computer System And Software Engineering
Depositing User: Mrs. Neng Sury Sulaiman
Date Deposited: 18 Jul 2018 06:23
Last Modified: 18 Jul 2018 06:23
URI: http://umpir.ump.edu.my/id/eprint/18220
Download Statistic: View Download Statistics

Actions (login required)

View Item View Item