Downloads: 131 | Views: 263
Survey Paper | Computer Science & Engineering | India | Volume 5 Issue 1, January 2016 | Popularity: 6.4 / 10
A Survey Paper on an On-Line Intrusion Detection Approach to Identify Low-Rate Dos Attacks
Dipali Vaidya, Prof. Sonal Fatangare
Abstract: High rate Denial of service attacks, happen in relatively small amount of time, low rate DoS attack consume resources relatively at slower rate but cause eventual crash of the service providing server. The problem of detection of Slow Denial of Service attacks within small time is a challenging task because the approaches either have scalability limitations due to inherent computational costs or these approaches lack timely detection. To overcome this problem, here analysis focuses on the quantity of data directed from the transport layer to the application layer. Frequency of such transfers is taken as input and analysis has been done to identify patterns that show possible Low rate DoS attacks within expected time. It has been discovered in frequency domain analysis that patterns differ between legitimate and anomalous transactions in time horizon proving that fast detection is possible.
Keywords: denial of service, anomaly detection, Fourier transform, slow dos attack
Edition: Volume 5 Issue 1, January 2016
Pages: 163 - 165
Make Sure to Disable the Pop-Up Blocker of Web Browser
Similar Articles
Downloads: 1 | Weekly Hits: ⮙1 | Monthly Hits: ⮙1
Analysis Study Research Paper, Computer Science & Engineering, India, Volume 10 Issue 1, January 2021
Pages: 1659 - 1668Anomaly Detection: Enhancing Systems with Machine Learning
Yogananda Domlur Seetharama
Downloads: 2 | Weekly Hits: ⮙1 | Monthly Hits: ⮙1
Analysis Study Research Paper, Computer Science & Engineering, India, Volume 13 Issue 8, August 2024
Pages: 832 - 839Leveraging Artificial Intelligence for Enhanced Cybersecurity: A Systematic Approach
Mohammed Saleem Sultan, Mohammed Shahid Sultan
Downloads: 2 | Weekly Hits: ⮙1 | Monthly Hits: ⮙2
Research Paper, Computer Science & Engineering, United States of America, Volume 13 Issue 11, November 2024
Pages: 844 - 850Data-Driven Decision Making: Advanced Database Systems for Business Intelligence
Maria Anurag Reddy Basani, Anudeep Kandi
Downloads: 3 | Weekly Hits: ⮙1 | Monthly Hits: ⮙1
Research Paper, Computer Science & Engineering, India, Volume 11 Issue 9, September 2022
Pages: 1284 - 1287Leveraging Deep Learning for Enhanced Fraud Detection in Banking: A Comprehensive Analysis of Strategies and Future Directions
Harish Narne
Downloads: 3 | Weekly Hits: ⮙1 | Monthly Hits: ⮙1
Research Paper, Computer Science & Engineering, India, Volume 12 Issue 8, August 2023
Pages: 2571 - 2575Enhancing IoT Cybersecurity with Graph Neural Networks: Advanced Anomaly Detection and Threat Mitigation
Harish Narne