Advanced Snort Driven Collaborative Framework for DDOS Attack Detection in Network Classification
Mehaboob Arshiya1, V Srikanth2

1Mehaboob Arshiya, Department of CSE, Koneru Lakshmaiah Education Foundation, Vaddeswaram (A.P), India.
2Dr. V Srikanth, Department of CSE, Koneru Lakshmaiah Education Foundation, Vaddeswaram (A.P), India.

Manuscript received on 01 May 2019 | Revised Manuscript received on 15 May 2019 | Manuscript published on 30 May 2019 | PP: 1300-1304 | Volume-8 Issue-7, May 2019 | Retrieval Number: G6369058719/19©BEIESP
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Abstract: Distributed denial of service (DDOS) attacks is the major and consistent security and privacy problem in wireless ad hoc networks. Detection of denial of service attacks is a challenging task which comes under distributed and high-end networks. DDOS attacks are appeared based on different features in network classification. Traditionally mutual feature based approaches were introduced can handle relevant features relates to detection of DDOS attacks in cases of network intrusion detection. So that in this paper, we propose and present Distributed and Collaborative Protection in Network Classification (DCPNC) for the identification of DDOS attacks in wireless network classification. Proposed approach composed with detection of intrusion in network systems located in internet service provider (ISP) at wireless network communications. Proposed approach also consists of virtual protection rings around the network to exchange data throughout all nodes present in network classification. Proposed approach applied in real world knowledge based data set for the detection of network classification. Experimental results of proposed approach gives better and support low overhead with different network parameters in network classification.
Keyword: Wireless network communication, Feature based selection, Internet Service Provider, KDD Cup Data Sets, Network Classification.
Scope of the Article: Classification.