Da Silva, Don Fransiskus Chandra (2017) PACKET SNIFFER PROGRAM USING PYTHON FOR MALWARES IDENTIFY. Other thesis, Unika Soegijapranata.
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Abstract
Today the internet is becoming a basic need in terms of communication, sharing information and transaction over long distances. One of the problems in the internet is malware. Malware is software that can damage or disrupt the computer operating systems. The spread of malware can be through email or any application that uses the internet media. Whenever the computer is connected to the internet, there is possibilities to be attacked by malware. In order to avoid malware attacks, special knowledge is required about the type of malware and how the spread process occurs. This can be done by monitoring and checking data traffic on computer networks, The tool that can be used is packet sniffer. Packet sniffer is a tool that can collect packet data in the network for the monitor. Packet sniffer is useful for analyzing disturbances, what data is received and transmitted over the network and shows information about interacting computers. In this project, a packet sniffer program will be created. Packet data captured with this program, can be analyzed to determine the traffic data activity that is malware or not. With a known malware attack then the right action can be done immediately. Packet sniffer program is created with python. For monitoring data which generated by a packet sniffer, web-based program will be created by using PHP programming language. This tool only helps in recording the data traffic in the local network to be analyzed. To get the activity pattern of malware, the results depends on the expertise of the users in analyzing the network. . Keyword: Internet, Malware, Network, Packet Sniffer
| Item Type: | Thesis (Other) |
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| Subjects: | 000 Computer Science, Information and General Works > 004 Data processing & computer science |
| Divisions: | Faculty of Computer Science > Department of Informatics Engineering |
| Depositing User: | Mr Ign. Setya Dwiana |
| Date Deposited: | 05 Dec 2017 07:49 |
| Last Modified: | 06 Sep 2021 01:21 |
| URI: | http://repository.unika.ac.id/id/eprint/15373 |
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