01574nam a22001577a 4500999001700000100006300017245006600080260003000146300000800176500095500184700004101139856003301180942001101213952009001224952010201314  c65460d65457  aRoheen Qamara17MSCS18aSupervisor Dr. Fareed Ahmed Jokhio  aClassification of ddos attack using artificial neural network  aNawabshah:bQUEST,c2019.  a49p  aABSTRACT


Distributed Denial of Service (DDoS) attack is one of the well-known threats to any computer or Internet Service. DDoS attack is an attempt to make a network resource or internet unavailable to its intended users. Internet is running on a large numbers servers kept in data centers. When a server or its network is overloaded with users request then the server or networks stop functioning properly and deny service to the genuine requests. As the internet growing we face large amount of cyber-attack. This research  work presents the DDoS attack through various angles including we first recognize different kinds of DDoS attacks and then propose a new methodology to develop a Model for detecting the DDoS attacks using Neural Networks. We used three ANN networks and compare them to detect the DDoS attack.
Keywords: DDoS Attack, Feed forward Neural Network, Case Case Forward Neural Network, Fitting Neural Network,  KDD Cup dataset.
  aDepartment of Information Technology  uhttps://tinyurl.com/mr2wpepb  cTHESIS  00104070aRESEARCHbRESEARCHd2019-09-27l0pMP/46-526r2019-09-27 00:00:00yTHESIS  00104070aRESEARCHbRESEARCHd2023-12-18l0pMP/55-697r2023-12-18 00:00:00w2023-12-18yTHESIS