DGD: An Intrusion Detection System for Providing Security to Web Applications

2017 ◽  
Vol 1 (1) ◽  
pp. 27-32 ◽  
Author(s):  
K. Asish Vardhan ◽  
◽  
M. Murali Krishna ◽  
Keyword(s):  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Web Applications ◽  
Detection System

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 An Invariant-Based Approach for Detecting Attacks Against Data in Web Applications

2014 ◽  
Vol 5 (1) ◽  
pp. 19-38
Author(s):  
Romaric Ludinard ◽  
Éric Totel ◽  
Frédéric Tronel ◽  
Vincent Nicomette ◽  
Mohamed Kaâniche ◽  
...  
Keyword(s):  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Web Application ◽  
Web Applications ◽  
Detection System ◽  
Source Code ◽  
Web Attacks ◽  
Application Profile ◽  
The Web ◽  
Ruby On Rails

RRABIDS (Ruby on Rails Anomaly Based Intrusion Detection System) is an application level intrusion detection system (IDS) for applications implemented with the Ruby on Rails framework. The goal of this intrusion detection system is to detect attacks against data in the context of web applications. This anomaly based IDS focuses on the modelling of the normal application profile using invariants. These invariants are discovered during a learning phase. Then, they are used to instrument the web application at source code level, so that a deviation from the normal profile can be detected at run-time. This paper illustrates on simple examples how the approach detects well-known categories of web attacks that involve a state violation of the application, such as SQL injections. Finally, an assessment phase is performed to evaluate the accuracy of the detection provided by the proposed approach.

scholarly journals A Closer Look at Intrusion Detection System for Web Applications

2018 ◽  
Vol 2018 ◽  
pp. 1-27 ◽  
Author(s):  
Nancy Agarwal ◽  
Syed Zeeshan Hussain
Keyword(s):  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Web Applications ◽  
Detection System ◽  
Web Traffic ◽  
Comprehensive Overview ◽  
Web Based ◽  
Efficient System ◽  
Detection Systems ◽  
Web Attacks

Intrusion Detection System (IDS) acts as a defensive tool to detect the security attacks on the web. IDS is a known methodology for detecting network-based attacks but is still immature in monitoring and identifying web-based application attacks. The objective of this research paper is to present a design methodology for efficient IDS with respect to web applications. In this paper, we present several specific aspects which make it challenging for an IDS to monitor and detect web attacks. The article also provides a comprehensive overview of the existing detection systems exclusively designed to observe web traffic. Furthermore, we identify various dimensions for comparing the IDS from different perspectives based on their design and functionalities. We also propose a conceptual framework of a web IDS with a prevention mechanism to offer systematic guidance for the implementation of the system. We compare its features with five existing detection systems, namely, AppSensor, PHPIDS, ModSecurity, Shadow Daemon, and AQTRONIX WebKnight. This paper will highly facilitate the interest groups with the cutting-edge information to understand the stronger and weaker sections of the domain and provide a firm foundation for developing an intelligent and efficient system.

AIWAS

2012 ◽  
Vol 3 (1) ◽  
pp. 73-91
Author(s):  
Toan Huynh ◽  
James Miller
Keyword(s):  
Machine Learning ◽  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Web Applications ◽  
Detection System ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Anomaly Intrusion Detection ◽  
Help System

A recent report states that 63 percent of documented vulnerabilities exist in Web applications. Hence, Web applications represent an ideal platform for malicious attackers to target. This paper presents an anomaly intrusion detection system (AIWAS) to help system administrators protect their Web applications from these attacks. AIWAS maps each user’s input into an Instance Model (IM). The IM, which contains attackable features of the input, allows machine learning algorithms to classify the input as either benign or malicious. AIWAS then prevents malicious inputs from reaching the protected Web applications. A case study demonstrates the effectiveness of AIWAS against actual attacks.

scholarly journals An Invariant-Based Approach for Detecting Attacks Against Data in Web Applications

2018 ◽  
pp. 1073-1094
Author(s):  
Romaric Ludinard ◽  
Éric Totel ◽  
Frédéric Tronel ◽  
Vincent Nicomette ◽  
Mohamed Kaâniche ◽  
...  
Keyword(s):  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Web Application ◽  
Web Applications ◽  
Detection System ◽  
Source Code ◽  
Web Attacks ◽  
Application Profile ◽  
The Web ◽  
Ruby On Rails

RRABIDS (Ruby on Rails Anomaly Based Intrusion Detection System) is an application level intrusion detection system (IDS) for applications implemented with the Ruby on Rails framework. The goal of this intrusion detection system is to detect attacks against data in the context of web applications. This anomaly based IDS focuses on the modelling of the normal application profile using invariants. These invariants are discovered during a learning phase. Then, they are used to instrument the web application at source code level, so that a deviation from the normal profile can be detected at run-time. This paper illustrates on simple examples how the approach detects well-known categories of web attacks that involve a state violation of the application, such as SQL injections. Finally, an assessment phase is performed to evaluate the accuracy of the detection provided by the proposed approach.

Hybrid Intrusion Detection System for Detecting DDoS Attacks on Web Applications Using Machine Learning

2022 ◽  
pp. 797-805
Author(s):  
Madhura Shekhar Potnis ◽  
Sanjyot Kedar Sathe ◽  
Purva Govind Tugaonkar ◽  
Gayatri Laxmikant Kulkarni ◽  
Shilpa Shrikant Deshpande
Keyword(s):  
Machine Learning ◽  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Web Applications ◽  
Detection System ◽  
Ddos Attacks
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