Reducing honeypot log storage capacity using cron job with PERL-SCRIPT / Nur Muhammad Irfan Abu Hassan
Honeypot is a decoy computer system that is used to attract and monitor hackers’ activities in the network. The aim of the honeypot is to collect information from the hackers in order to create more secure system. However, the log file generated by honeypot can grow very large when heavy traffic...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
2020
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| Subjects: | |
| Online Access: | https://ir.uitm.edu.my/id/eprint/27160/1/TD_NUR%20MUHAMMAD%20IRFAN%20ABU%20HASSAN%20CS%20R%2020_5.pdf |
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| Summary: | Honeypot is a decoy computer system that is used to attract and monitor hackers’
activities in the network. The aim of the honeypot is to collect information from the
hackers in order to create more secure system. However, the log file generated by
honeypot can grow very large when heavy traffic occurred in the system such as
Distributed Denial of Services’ (DDoS) attack which possess difficulty when it is
being processed and analysed by network administrator as it required a lot of time and
resources. To address this issue, the objective of this project is to configure a cron job
that will run a perl-script which parses the collected data into database in periodically
to decrease the log size. Three DDoS attack scenarios were conducted in this project
to show the increasing of the log size by sending a different amount of packet per
second for 8 hours in each scenario. In scenario 3, the size of the log file has increased
to 844MB which causes the honeypot to stop logging information due to the disk space
used in the system has reached 100%, and it takes 5 hour 20 minutes to parse the
content of the log file into the database which consumed a lot of system resources. At
this point, the system performance started to drop off in terms of availability, response
time, and processing speed. After using the cron job, the result shown that the log file
has been reduced to 118MB, the disk space used has decrease to 91%, and it only takes
40 minutes to parse the log file into the database, thus improved overall system
performance. This project had successfully reduced the log size by configuring the
cron job to transfer the content of the log file into the database hourly. |
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