scholarly journals Analisis Keamanan Transaksi E-Commerce Menggunakan Intrusion Detection System (IDS) Berbasis Snort

2020 ◽  
Vol 12 (1) ◽  
pp. 40
Author(s):  
Tri Lestari ◽  
Imam Riadi ◽  
Rusydi Umar
Keyword(s):  
Network Security ◽  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Detection System ◽  
Security Analysis ◽  
Digital Age ◽  
The Internet ◽  
Technology Infrastructure ◽  
Transaction Process ◽  
The Many

AbstractThe digital age is a sign of the progress of the internet that has made everything easy and fast. Tix Id is one of the many e-commerce applications that have developed in the digital age. This application requires that consumers are satisfied with promotions and services. Even though the Tix Id application already provides the best service, there are still some customers who feel unsatisfied using the application, a problem that often occurs is that there is often a one-sided ticket booking cancellation by Tix Id, the transaction process has been successfully carried out, besides that the consumer is also harmed by Tix's complaints My ID-consumer refunds remain reduced, and there are also often errors that contain seats not available. One way to optimize this application in the transaction process, namely by improving the information infrastructure, before improving the technology infrastructure, security analysis will be done first by using the intrusion detection system (IDS) [1], and this IDS is the process of finding active solutions suspicious on a system or network so that it can be identified the cause that occurs in the Tix Id application transaction process. The results obtained from this study are errors that often occur in Tix Id applications can not be identified whether it is an attack or not, but this research has resulted in the design of the need to optimize network security in Tix Id applications.Keywords: Security, Transactions, Tix Id, Intrusion Detection System (IDS), SnortAbstrakEra digital merupakan tanda kemajuan internet yang menyebabkan semua menjadi mudah dan cepat. Tix Id adalah salah satu dari sekian banyak aplikasi e-commerce yang berkembang di era digital. Aplikasi ini berusaha agar konsumen merasa puas dengan promosi dan pelayanan. Meskipun aplikasi Tix Id sudah berusaha memberikan pelayanan terbaik namun masih ada beberapa konsumen yang merasa kurang puas menggunakan aplikasi tersebut, masalah yang sering terjadi adalah sering terjadi pembatalan pemesanan tiket sepihak oleh Tix Id padahal proses transaksi sudah berhasil dilakukan, selain itu konsumen juga merasa dirugikan ketika pihak Tix Id me-refund konsumen namun saldo konsumen tetap berkurang, dan juga sering terjadi error yang berisi pesan kursi tidak tersedia. Salah satu cara untuk mengoptimasi aplikasi tersebut kususnya dalam proses transaksi, yaitu dengan memperbaiki infrastruktur teknologi informasi, sebelum diperbaiki infrastruktur teknologinya, akan dilakukan terlebih dahulu analisis keamanan dengan menggunakan metode intrusion detection system (IDS) [1], dimana IDS ini merupakan proses untuk mendeteksi aktivias mencurigakan pada sebuah sistem atau jaringan sehingga dapat diketahui penyebab kesalahan yang terjadi pada proses transaksi aplikasi Tix Id. Hasil yang diperoleh dari penelitian ini adalah kesalahan yang sering terjadi pada aplikasi Tix Id belum dapat teridentifikasi apakah merupakan serangan atau bukan, namun penelitian ini telah menghasilkan rancangan kebutuhan untuk mengoptimalisasi keamanan jaringan pada aplikasi Tix Id.Kata Kunci: Keamanan, Transaksi, Tix Id, Intrusion Detection System (IDS), Snort

scholarly journals Spatio Temporal with Scalable Automatic Bisecting-Kmeans for Network Security Analysis in Matagaruda Project

2019 ◽  
Vol 7 (1) ◽  
pp. 83-104
Author(s):  
Masfu Hisyam ◽  
Ali Ridho Barakbah ◽  
Iwan Syarif ◽  
Ferry Astika S
Keyword(s):  
Network Security ◽  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Detection System ◽  
Security Analysis ◽  
Spatiotemporal Analysis ◽  
The Internet ◽  
Massive Data ◽  
Spatio Temporal ◽  
Better Than

Internet attacks are a frequent occurrence and the incidence is always increasing every year, therefore Matagaruda project is built to monitor and analyze internet attacks using IDS (Intrusion Detection System). Unfortunately, the Matagaruda project has lacked in the absence of trend analysis and spatiotemporal analysis. It causes difficulties to get information about the usual seasonal attacks, then which sector is the most attacked and also the country or territory where the internet attack originated. Due to the number of unknown clusters, this paper proposes a new method of automatic bisecting K-means with the average of SSE is 93 percents better than K-means and bisecting K-means. The usage of big spark data is highly scalable for processing massive data attack.

A Review on Intrusion Detection Systems and Techniques

2020 ◽  
Vol 28 (Supp02) ◽  
pp. 65-91
Author(s):  
Nitesh Singh Bhati ◽  
Manju Khari ◽  
Vicente García-Díaz ◽  
Elena Verdú
Keyword(s):  
Network Security ◽  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Detection System ◽  
Security System ◽  
Intrusion Detection Systems ◽  
The Internet ◽  
Detection Techniques ◽  
Detection Systems ◽  
Network Security System

An Intrusion Detection System (IDS) is a network security system that detects, identifies, and tracks an intruder or an invader in a network. As the usage of the internet is growing every day in our society, the IDS is becoming an essential part of the network security system. Therefore, the proper research and implementation of IDSs are required. Today, with the help of improved technologies at our disposal, many solutions have been found to create many intrusion detection systems. However, it is difficult to identify the perfect solution from the vast options we have available. Hence, motivated by the need of a better security system, this paper presents a survey of different published solutions that have been developed and/or researched on the topic of intrusion detection techniques during the period from 2000 to 2019, including the accuracy of the output. With the help of this survey, an all-inclusive view of the different papers would be at one’s disposal.

scholarly journals Intrusion Detection Based on Big Data Fuzzy Analytics

2021 ◽  
Author(s):  
Farah Jemili ◽  
Hajer Bouras
Keyword(s):  
Big Data ◽  
Network Security ◽  
Intrusion Detection ◽  
Intrusion Detection System ◽  
High Performance ◽  
Detection System ◽  
Training Dataset ◽  
False Alarms ◽  
Massive Datasets ◽  
Detection Rates

In today’s world, Intrusion Detection System (IDS) is one of the significant tools used to the improvement of network security, by detecting attacks or abnormal data accesses. Most of existing IDS have many disadvantages such as high false alarm rates and low detection rates. For the IDS, dealing with distributed and massive data constitutes a challenge. Besides, dealing with imprecise data is another challenge. This paper proposes an Intrusion Detection System based on big data fuzzy analytics; Fuzzy C-Means (FCM) method is used to cluster and classify the pre-processed training dataset. The CTU-13 and the UNSW-NB15 are used as distributed and massive datasets to prove the feasibility of the method. The proposed system shows high performance in terms of accuracy, precision, detection rates, and false alarms.

scholarly journals Towards Deep-Learning-Driven Intrusion Detection for the Internet of Things

Sensors ◽  
2019 ◽  
Vol 19 (9) ◽  
pp. 1977 ◽  
Author(s):  
Geethapriya Thamilarasu ◽  
Shiven Chawla
Keyword(s):  
Deep Learning ◽  
Internet Of Things ◽  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Learning Algorithm ◽  
Detection System ◽  
Cyber Attacks ◽  
The Internet ◽  
Critical Systems ◽  
The Internet Of Things

Cyber-attacks on the Internet of Things (IoT) are growing at an alarming rate as devices, applications, and communication networks are becoming increasingly connected and integrated. When attacks on IoT networks go undetected for longer periods, it affects availability of critical systems for end users, increases the number of data breaches and identity theft, drives up the costs and impacts the revenue. It is imperative to detect attacks on IoT systems in near real time to provide effective security and defense. In this paper, we develop an intelligent intrusion-detection system tailored to the IoT environment. Specifically, we use a deep-learning algorithm to detect malicious traffic in IoT networks. The detection solution provides security as a service and facilitates interoperability between various network communication protocols used in IoT. We evaluate our proposed detection framework using both real-network traces for providing a proof of concept, and using simulation for providing evidence of its scalability. Our experimental results confirm that the proposed intrusion-detection system can detect real-world intrusions effectively.

Campus Network Security Program Based on Snort Network Security Intrusion Detection System

2012 ◽  
Vol 433-440 ◽  
pp. 3235-3240
Author(s):  
Ling Jia
Keyword(s):  
Network Security ◽  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Detection System ◽  
Collocation Methods ◽  
Campus Network ◽  
Security Risks ◽  
Network Layer ◽  
Defense Strategies

This paper studies the security problems of campus network and summarizes the current on the current security risks and threats that campus network faces, focusing on analysis of attack-defense strategies on DOS network layer, proposing the security program of campus network which uses firewall as well as network security intrusion detection system snort. This paper analyzes the functional advantages of the program and presents in details the setup deployment and collocation methods of network security intrusion detection system based on snort in the campus network, and its application results are also summarized.

ANALISIS NETWORK SECURITY SNORT METODE INTRUSION DETECTION SYSTEM UNTUK OPTIMASI KEAMANAN JARINGAN KOMPUTER

Jursima ◽  
2018 ◽  
Vol 6 (1) ◽  
pp. 1
Author(s):  
Parningotan Panggabean
Keyword(s):  
Network Security ◽  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Detection System ◽  
Denial Of Service

<p><em>Perkembangan teknologi informasi, khususnya jaringan komputer memungkinkan terjadinya pertukaran informasi yang mudah, cepat dan semakin kompleks. Keamanan jaringan komputer harus diperhatikan guna menjaga validitas dan integritas data serta informasi yang berada dalam jaringan tersebut. Masalah yang dihadapi adalah adanya Log Bug yang didapatkan pada komputer server Dinas Lingkungan Hidup Kota Batam yang diindikasikan adanya serangan Denial of Service (DoS) pada komputer tersebut. Berdasarkan masalah diatas maka penulis mencoba membuat sebuah penelitian yang berjudul “Analisis Network Security Snort menggunakan metode  Intrusion Detection System (IDS) untuk Optimasi  Keamanan Jaringan Komputer” dan diharapkan dapat mendeteksi serangan Denial of Service (DoS). Intrusion Detection System (IDS)  adalah sebuah tool, metode, sumber daya yang memberikan bantuan untuk melakukan identifikasi, memberikan laporan terhadap aktivitas jaringan komputer. Aplikasi yang digunakan untuk mendeteksi serangan menggunakan Snort. Snort dapat mendeteksi serangan DoS. Serangan DoS dilakukan dengan menggunakan aplikasi Loic.</em></p>

Sign in / Sign up

Export Citation Format

Share Document