Design of detection system against the denial of service attack in 3G1x system

2004 ◽  
Author(s):  
J. Park ◽  
F. Liu ◽  
C.-C.J. Kuo
Keyword(s):  
Detection System ◽  
Denial Of Service ◽  
Denial Of Service Attack ◽  
Service Attack

Multilevel Intrusion Detection System to Mitigate Denial-of-Service Attack in Wireless Sensor Networks

2020 ◽  
Vol 17 (6) ◽  
pp. 2451-2458
Author(s):  
Shilpy Ghai ◽  
Vijay Kumar
Keyword(s):  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Detection System ◽  
Denial Of Service ◽  
Data Encryption ◽  
Denial Of Service Attack ◽  
Malicious Behavior ◽  
Result Show ◽  
Service Attack ◽  
Open Issue

Malicious activities over WSN is quite hard to detect as sensors operate in an open network environment. Researchers have offered several solutions but still intrusion detection/prevention is an open issue. In this paper, a scheme is introduced that can analyze the malicious behavior of the nodes over multiple layers. It uses AES algorithm for data encryption and its integrity is insured using SHA512 method. Simulation results show that it outperforms as compared to traditional WatchDog method under QoS constraints. Simulation result show that it outperforms as compared to traditional watchdog scheme.

scholarly journals Exploring Defense of SQL Injection Attack in Penetration Testing

2017 ◽  
Vol 9 (4) ◽  
pp. 62-71
Author(s):  
Alex Zhu ◽  
Wei Qi Yan
Keyword(s):  
Intrusion Detection System ◽  
Detection System ◽  
Denial Of Service ◽  
Network Resources ◽  
Sql Injection ◽  
Qualitative And Quantitative ◽  
Denial Of Service Attack ◽  
Confidential Data ◽  
Service Attack ◽  
Long Time

SQLIA is adopted to attack websites with and without confidential information. Hackers utilized the compromised website as intermediate proxy to attack others for avoiding being committed of cyber-criminal and also enlarging the scale of Distributed Denial of Service Attack (DDoS). The DDoS is that hackers maliciously turn down a website and make network resources unavailable to web users. It is extremely difficult to effectively detect and prevent SQLIA because hackers adopt various evading SQLIA Intrusion Detection System techniques. Victims may not be even aware of that their confidential data has been compromised for a long time. In this paper, our contribution is that we evaluate several most popular open source SQLIA tools and SQLIA prevention tools with both qualitative and quantitative assessments.

Machine Learning Based Intrusion Detection System for Denial of Service Attack

2021 ◽  
pp. 29-47
Author(s):  
Ashish Pandey ◽  
Neelendra Badal
Keyword(s):  
Machine Learning ◽  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Detection System ◽  
Denial Of Service ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Dos Attack ◽  
Denial Of Service Attack ◽  
Service Attack

Machine learning-based intrusion detection system (IDS) is a research field of network security which depends on the effective and accurate training of models. The models of IDS must be trained with new attacks periodically; therefore, it can detect any security violations in the network. One of most frequent security violations that occurs in the network is denial of service (DoS) attack. Therefore, training of IDS models with latest DoS attack instances is required. The training of IDS models can be more effective when it is performed with the help of machine learning algorithms because the processing capabilities of machine learning algorithms are very fast. Therefore, the work presented in this chapter focuses on building a model of machine learning-based intrusion detection system for denial of service attack. Building a model of IDS requires sample dataset and tools. The sample dataset which is used in this research is NSL-KDD, while WEKA is used as a tool to perform all the experiments.

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