scholarly journals Sistem Reporting Keamanan pada Jaringan Cloud Computing Melalui bot Telegram dengan Menggunakan Teknik Intrussion Detection and Prevention System

2019 ◽  
Vol 5 (2) ◽  
Author(s):  
Eddy Prasetyo Nugroho
Keyword(s):  
Cloud Computing ◽  
Intrusion Detection ◽  
Instant Messaging ◽  
Detection System ◽  
Prevention System ◽  
Port Scan ◽  
Intrusion Detection And Prevention

Serangan Siber merupakan ancaman yang serius bagi kemanan jaringan, terutama pada jaringan yang bersifat publik sehingga bisa diakses oleh siapapun dari seluruh dunia. Akibat dari serangan siber sangat berdampak besar jika sampai berhasil mengganggu suatu kinerja jaringan bahkan hingga bisa menguasainya, terutama pada jaringan yang menyediakan layanan bagi public. Seorang administrator jaringan harus siap tanggap dalam menangani setiap serangan pada server yang dikelolanya. Langkah pertama dalam mencegah serangan yang bisa mengancam suatu jaringan yaitu dengan merancang suatu sistem untuk mendeteksi dan memberikan peringatan dini akan adanya suatu serangan yang dinamakan Intruision Detection System (IDS). Aplikasi yang digunakan sebagai IDS yaitu Snort yang berfungsi untuk mendeteksi serangan berdasarkan rules yang akan dicocokan dengan signature dari serangan tersebut, dan akan disimpan ke database untuk diteruskan  kepada administrator melalui aplikasi instant messaging Telegram. Telegram digunakan sebagai media untuk menyempaikan peringatan dini jika terjadi upaya serangan, sehingga administrator dapat  melakukan upaya penanggulangan terhadap serangan tersebut. Untuk menanggulangi serangan yang terjadi, digunakan aplikasi Fail2Ban dan Port Scan Attack Detector (PSAD) untuk menutup akses dari IP penyerang. Hasil dari penggunaan IDS dengan notifikasi melalui bot Telegram menggunakan bahasa pemrograman PHP mampu mendeteksi serangan DoS, Port Scanning, dan SSH Bruteforce berdasar rules yang dikonfigurasi pada Snort. Berdasarkan hasil analisis respon waktu pengiriman notifikasi didapatkan hasil yaitu SSH Bruteforce 18 detik, Port Scanning 20 detik, dan DoS yaitu 30 detik.Keyword—kemanan jaringan, cloud computing, intrusion detection and prevention system (IDSP), snort, telegram, bot

Using response action with intelligent intrusion detection and prevention system against web application malware

2014 ◽  
Vol 22 (5) ◽  
pp. 431-449 ◽  
Author(s):  
Ammar Alazab ◽  
Michael Hobbs ◽  
Jemal Abawajy ◽  
Ansam Khraisat ◽  
Mamoun Alazab
Keyword(s):  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Web Application ◽  
Web Applications ◽  
Detection Efficiency ◽  
Detection System ◽  
Content Type ◽  
Novel Approach ◽  
Prevention System ◽  
Intrusion Detection And Prevention

Purpose – The purpose of this paper is to mitigate vulnerabilities in web applications, security detection and prevention are the most important mechanisms for security. However, most existing research focuses on how to prevent an attack at the web application layer, with less work dedicated to setting up a response action if a possible attack happened. Design/methodology/approach – A combination of a Signature-based Intrusion Detection System (SIDS) and an Anomaly-based Intrusion Detection System (AIDS), namely, the Intelligent Intrusion Detection and Prevention System (IIDPS). Findings – After evaluating the new system, a better result was generated in line with detection efficiency and the false alarm rate. This demonstrates the value of direct response action in an intrusion detection system. Research limitations/implications – Data limitation. Originality/value – The contributions of this paper are to first address the problem of web application vulnerabilities. Second, to propose a combination of an SIDS and an AIDS, namely, the IIDPS. Third, this paper presents a novel approach by connecting the IIDPS with a response action using fuzzy logic. Fourth, use the risk assessment to determine an appropriate response action against each attack event. Combining the system provides a better performance for the Intrusion Detection System, and makes the detection and prevention more effective.

scholarly journals A HYBRID APPROACH OF INTRUSION DETECTION SYSTEM BASED ON NEURAL NETWORK AND NORMALIZATION

2016 ◽  
Vol 2 (2) ◽  
Author(s):  
Kavita Patil ◽  
Dr. Bhupesh Gour ◽  
Mr. Deepak Tomar
Keyword(s):  
Neural Network ◽  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Detection System ◽  
Hybrid Approach ◽  
Attack Detection ◽  
Proper Action ◽  
Prevention System ◽  
Event Handling ◽  
Intrusion Detection And Prevention

In the whole world, the most famous threat that are spread around is done by the intruder computers over the internet. The types of external activity found over the system are termed as intrusion and the mechanism that is applied for the preservation of the information against these intrusions are called as intrusion detection system. For protecting the network, first there is a need to detect the attacks then take the proper action regarding it. There are techniques applied for scanning and analysing for highlighting the susceptibilities and loop-holes within the components of security, various aspects of network that are not secured and also implementation of the intrusion-detection and prevention-system techniques are also described here. In this paper, proposed methods based on Neural Network is described that provides better way of attack detection, that are required in various applications of security such as network forensics, portable computer and the event handling systems by applying various different approaches. Proposed work is implemented in MATALB.

scholarly journals RELEVANCE OF THE DEVELOPMENT OF AN INTRUSION DETECTION SYSTEM WITH A TRAP MODULE

2020 ◽  
Vol 8 (1) ◽  
pp. 165-167
Author(s):  
Midat O. Maxudov ◽  
Ivan E. Doroshenko ◽  
Andrey S. Grehov ◽  
Diana G. Makarova
Keyword(s):  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Detection System ◽  
Detailed Report ◽  
Prevention System ◽  
Intrusion Detection And Prevention

The article presents the relevance of developing an intrusion detection system with a trap module. The trap module implemented as a part of the intrusion detection system allows providing a detailed report and information about the attacker for the intrusion detection and prevention system SNORT.

scholarly journals Behavioral Host-Based Intrusion Detection and Prevention System for Android

2021 ◽  
Vol 9 (VI) ◽  
pp. 5268-5274
Author(s):  
Yashavant Darange
Keyword(s):  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Detection System ◽  
Training Dataset ◽  
User Privacy ◽  
Android Malware ◽  
Android Malware Detection ◽  
Prevention System ◽  
Evaluation Outcome ◽  
Intrusion Detection And Prevention

Intrusion Detection System (IDS) is vital to protect smartphones from about to happen security breach and make sure user privacy. Android is the most popular mobile Operating System (OS), holding many markets share. Android malware detection has received important concentration, existing solutions typically rely on performing resource intensive analysis on a server, assuming an uninterrupted link between the device and the server. In this paper, we propose a behavior Host-based IDS (HIDS) by using permissions incorporating arithmetical and ML algorithms. The benefit of our proposed IDS is two folds. First, it is completely independent and runs on the smartphone device, without need any link to a server. Second, it requires only training dataset consisting of some of examples from both benign and malicious datasets for tuning. though, in put into practice, collecting malicious examples is exciting since its important infecting the device and collecting many of samples in order to characterize the malware’s behavior and the labelling has to be done. The evaluation outcome show that the proposed IDS gives a very hopeful accuracy.

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