Open AccessPERANCANGAN SISTEM PENDETKSI SERANGAN PADA SERVER JARINGAN KOMPUTER MENGGUNAKAN SNORT BERBASIS SMS GETEWAY
Author(s) -
Tria Aprilianto,
Sunu Jatmika,
Ihsan Wicaksono
Publication year - 2019
Publication title -
jurnal teknika
Language(s) - English
Resource type - Journals
eISSN - 2620-4770
pISSN - 2085-0859
DOI - 10.30736/jt.v11i1.287
Subject(s) - computer science , login , operating system , web server , internet authentication service , system administrator , appleshare , computer security , application server , server , the internet , client–server model
Server on a network becomes an important point because its function is to serve all requests required by all clients on a network. For that, maintaining the security of a server is also very important because if the server is experiencing a problem then there is no one the network can serve the request from the client. This makes a server administrator must see traffic to the server at any time. For this reason, it is important to conduct an attack detection system research in order to help the performance of administrators. Detection of attacks directed to the server is an early solution in securing a server from attack. For attack detection systems, SNORT is generally able to detect almost any attack because it has many rules that can be modified. Detection system by configuring and adding the rule first on the server. If there is an incoming attack then SNORT will compare the attack with the existing rule, SNORT will later categorize the attack into 3 types of High, Medium and Low. The design of attack detection system using SNORT and web server is planted on Raspberry Pi. Web server that is planted on Raspberry Pi as information system or container of attack records. In addition, Raspberry Pi also implemented database to store attack log which will be sent via sms gateway. The overall test results of the system built on this final project work well. The admin user can login the web server and do the user creation properly. Among the 6 rule attacks that have been implemented, all rules can read the attack accurately and able to save it into the database. From 75 attacks recorded in the database, only 80% attack detection can be displayed in the web server. And the web server is capable of sending 77.3% of attack notifications to the admin.