A Two level Detection of Routing layer attacks in Hierarchical Wireless Sensor Networks using learning based energy prediction

최초 등록일
2017.09.07
최종 저작일
2017.09
18페이지/파일확장자 어도비 PDF
가격 5,300원 할인쿠폰받기
판매자한국학술정보(주)
다운로드
장바구니
자격시험 이용후기 이벤트

* 본 문서는 배포용으로 복사 및 편집이 불가합니다.

서지정보

발행기관 : 한국인터넷정보학회 수록지정보 : KSII Transactions on Internet and Information Systems (TIIS) / 9권 / 11호
저자명 : ( Jeevaa Katiravan ) , ( Duraipandian N ) , ( Dharini N )

영어 초록

Wireless sensor networks are often organized in the form of clusters leading to the new framework of WSN called cluster or hierarchical WSN where each cluster head is responsible for its own cluster and its members. These hierarchical WSN are prone to various routing layer attacks such as Black hole, Gray hole, Sybil, Wormhole, Flooding etc. These routing layer attacks try to spoof, falsify or drop the packets during the packet routing process. They may even flood the network with unwanted data packets. If one cluster head is captured and made malicious, the entire cluster member nodes beneath the cluster get affected. On the other hand if the cluster member nodes are malicious, due to the broadcast wireless communication between all the source nodes it can disrupt the entire cluster functions. Thereby a scheme which can detect both the malicious cluster member and cluster head is the current need. Abnormal energy consumption of nodes is used to identify the malicious activity. To serve this purpose a learning based energy prediction algorithm is proposed. Thus a two level energy prediction based intrusion detection scheme to detect the malicious cluster head and cluster member is proposed and simulations were carried out using NS2-Mannasim framework. Simulation results achieved good detection ratio and less false positive.

참고 자료

없음

자료문의

제휴사는 별도로 자료문의를 받지 않고 있습니다.

판매자 정보

한국학술정보(주)는 콘텐츠 제작에 도움이 되는 솔루션을 기반으로 풍부한 문화 콘텐츠를 생성하여 새로운 삶의 가치를 창조합니다.

본 학술논문은 한국학술정보(주)와 각 학회간에 저작권계약이 체결된 것으로 AgentSoft가 제공 하고 있습니다.
본 저작물을 불법적으로 이용시는 법적인 제재가 가해질 수 있습니다.

우수 콘텐츠 서비스 품질인증 획득
최근 본 자료더보기
A Two level Detection of Routing layer attacks in Hierarchical Wireless Sensor Networks using learning based energy prediction