Preventing DDoS using Bloom Filter: A Survey

Distributed Denial-of-Service (DDoS) is a menace for service provider and prominent issue in network security. Defeating or defending the DDoS is a prime challenge. DDoS make a service unavailable for a certain time. This phenomenon harms the service providers, and hence, loss of business revenue. Therefore, DDoS is a grand challenge to defeat. There are numerous mechanism to defend DDoS, however, this paper surveys the deployment of Bloom Filter in defending a DDoS attack. The Bloom Filter is a probabilistic data structure for membership query that returns either true or false. Bloom Filter uses tiny memory to store information of large data. Therefore, packet information is stored in Bloom Filter to defend and defeat DDoS. This paper presents a survey on DDoS defending technique using Bloom Filter.Comment: 9 pages, 1 figure. This article is accepted for publication in EAI Endorsed Transactions on Scalable Information System

Power electronics options for large wind farm integration : VSC-based HVDC transmission

This paper describes the use of voltage source converter based HVDC transmission (VSC transmission) system for grid integration of large wind farms over long distance. The wind farms can be based on either doubly-fed induction generator (DFIG) or fixed speed induction generator (FSIG). The paper describes the operation principles and control strategies of the proposed system. Automatic power balancing during network AC fault is achieved without communication between the two converters. PSCAD/EMTDC simulations are presented to demonstrate the robust performance and to validate the proposed system during various operating conditions such as variations of generation and AC fault conditions. The proposed VSC transmission system has technical and economic advantages over a conventional AC connection for integrating large wind farms over long distanc

A traffic classification method using machine learning algorithm

Applying concepts of attack investigation in IT industry, this idea has been developed to design a Traffic Classification Method using Data Mining techniques at the intersection of Machine Learning Algorithm, Which will classify the normal and malicious traffic. This classification will help to learn about the unknown attacks faced by IT industry. The notion of traffic classification is not a new concept; plenty of work has been done to classify the network traffic for heterogeneous application nowadays. Existing techniques such as (payload based, port based and statistical based) have their own pros and cons which will be discussed in this literature later, but classification using Machine Learning techniques is still an open field to explore and has provided very promising results up till now