RISS 학술연구정보서비스

검색
다국어 입력

http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.

변환된 중국어를 복사하여 사용하시면 됩니다.

예시)
  • 中文 을 입력하시려면 zhongwen을 입력하시고 space를누르시면됩니다.
  • 北京 을 입력하시려면 beijing을 입력하시고 space를 누르시면 됩니다.
닫기
    인기검색어 순위 펼치기

    RISS 인기검색어

      KCI등재

      A Precise Algorithm for Detecting Malicious Sybil Nodes in Mobile Wireless Sensor Networks

      한글로보기

      https://www.riss.kr/link?id=A105984824

      • 0

        상세조회
      • 0

        다운로드
      서지정보 열기
      • 내보내기
      • 내책장담기
      • 공유하기
      • 오류접수

      부가정보

      다국어 초록 (Multilingual Abstract)

      A Sybil attack, where a malicious node creates multiple fake or captured identities, is one of the most well-known attacks against wireless sensor networks (WSNs). This attack can leave devastating effects on operational and routing protocols, such as...

      A Sybil attack, where a malicious node creates multiple fake or captured identities, is one of the most well-known attacks against wireless sensor networks (WSNs). This attack can leave devastating effects on operational and routing protocols, such as voting, data aggregation, resource allocation, and misbehavior detection. In this paper, a simple and precise algorithm for detecting Sybil attacks in mobile WSNs is proposed. Considering the rapid growth of Internet of Things (IoTs) devices and WSNs’ popularity, the threat from this attack is serious. The main underlying idea of the proposed algorithm is to use neighbors’ information and observer nodes to detect Sybil nodes during the network lifetime. In the proposed algorithm, some observer nodes first walk the network and record necessary information about other nodes. Each observer node then uses this collected information to detect Sybil nodes. The proposed algorithm is compared with other algorithms according to criteria including memory, communication, and computation overhead. Also, the proposed algorithm is implemented with the J-SIM simulator, and its performance is compared in a series of experiments with other algorithms using the criteria of true- and falsedetection rates. The simulation results indicate that the proposed algorithm can detect 100% of the Sybil nodes, so its false-detection rate is 0%, regarding the study assumptions.

      더보기

      목차 (Table of Contents)

      • Abstract
      • 1. Introduction
      • 2. Related Work
      • 3. System Assumptions, the Attack Model, and symbols
      • 4. The Proposed Algorithm
      • Abstract
      • 1. Introduction
      • 2. Related Work
      • 3. System Assumptions, the Attack Model, and symbols
      • 4. The Proposed Algorithm
      • 5. Performance Evaluation and Simulation Results
      • 6. Conclusion
      • References
      더보기

      동일학술지(권/호) 다른 논문

      분석정보

      View

      상세정보조회

      0

      Usage

      원문다운로드

      0

      대출신청

      0

      복사신청

      0

      EDDS신청

      0

      동일 주제 내 활용도 TOP

      더보기

      주제

      연도별 연구동향

      연도별 활용동향

      연관논문

      연구자 네트워크맵

      공동연구자 (7)

      유사연구자 (20) 활용도상위20명

      이 자료와 함께 이용한 RISS 자료

      나만을 위한 추천자료

      해외이동버튼