• Title/Summary/Keyword: garbage detection

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Analysis of the Connectivity of Monitoring Nodes and the Coverage of Normal Nodes for Behavior-based Attack Detection in Wireless Sensor Networks (무선 센서 네트워크에서 행위 기반 공격 탐지를 위한 감시 노드의 연결성과 일반 노드의 커버리지 분석)

  • Chong, Kyun-Rak
    • Journal of the Korea Society of Computer and Information
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    • v.18 no.12
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    • pp.27-34
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    • 2013
  • In wireless sensor networks, sensors need to communicate with each other to send their sensing data to the administration node and so they are susceptible to many attacks like garbage packet injection that cannot be prevented by using traditional cryptographic approaches. A behavior-based detection is used to defend against such attacks in which some specialized monitoring nodes overhear the communications of their neighbors to detect bad packets. As monitoring nodes use more energy, it is desirable to use the minimal number of monitoring nodes to cover the whole or maximal part of the network. The monitoring nodes can either be selected among the deployed normal nodes or differ in type from normal nodes. In this study, we have developed an algorithm for selecting the predefined number of monitoring nodes needed to cover the maximum number of normal nodes when the different types of normal nodes and monitoring nodes are deployed. We also have investigated experimentally how the number of monitoring nodes and their transmission range affect the connection ratio of the monitoring nodes and the coverage of the normal nodes.

A Study on the Ransomware Detection System Based on User Requirements Analysis for Data Restoration (데이터 복원이 가능한 사용자 요구사항 분석기반 랜섬웨어 탐지 시스템에 관한 연구)

  • Ko, Yong-Sun;Park, Jae-Pyo
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.20 no.4
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    • pp.50-55
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    • 2019
  • Recently Ransomware attacks are continuously increasing, and new Ransomware, which is difficult to detect just with a basic vaccine, continuously has its upward trend. Various solutions for Ransomware have been developed and applied. However, due to the disadvantages and limitations of existing solutions, damage caused by Ransomware has not been reduced. Ransomware is attacking various platforms no matter what platform it is, such as Windows, Linux, servers, IoT devices, and block chains. However, most existing solutions for Ransomware are difficult to apply to various platforms, and there is a limit that they are dependent on only some specific platforms while operating. This study analyzes the problems of existing Ransomware detection solutions and proposes the onboard module based Ransomware detection system; after the system defines the function of necessary elements through analyzing requirements that can actually reduce the damage caused by the Ransomware from the viewpoint of users, it supports various OS without pre-installation and is able to restore data even after being infected. We checked the feasibility of each function of the proposed system through the analysis of the existing technology and verified the suitability of the proposed techniques to meet the user's requirements through the questionnaire survey of a total of 264 users of personal and corporate PC users. As a result of statistical analysis of the questionnaire results, it was found that the score of intent to introduce the system was at 6.3 or more which appeared to be good, and the score of intent to change from existing solution to the proposed system was at 6.0 which appeared to be very high.