研究生: |
呂東學 Lu, Tung-Hsueh |
---|---|
論文名稱: |
移動式感測網路中安全的蒙特卡羅定位法 A Secure Monte Carlo Localization Algorithm for Mobile Sensor Networks |
指導教授: |
許健平
Sheu, Jang-Ping |
口試委員: | |
學位類別: |
碩士 Master |
系所名稱: |
電機資訊學院 - 資訊工程學系 Computer Science |
論文出版年: | 2010 |
畢業學年度: | 98 |
語文別: | 英文 |
論文頁數: | 39 |
中文關鍵詞: | 安全性定位法 、移動式無線感測網路 、無線網路 |
外文關鍵詞: | Secure localization, wireless mobile sensor networks, wireless networks |
相關次數: | 點閱:4 下載:0 |
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在無線感測網路中,安全性定位法是一個很重要的議題。近年來随著移動式無線感測網路的蓬勃發展,如何在移動式無線感測網路中定位也逐漸獲得重視。然而這類大部分定位的研究都是假設在安全的環境下,但是在現實中應用,無線感測器有很大的機率會被佈建在危險的環境中,導致定位誤差擴大。例如:因為大多數的定位法都需要感測器間的訊息交換,如果其中有惡意的感測器故意發佈錯誤的資訊,可能會導致定位結果不準確。但是大部分關於安全式的定位法都是假設在靜態的感測網路下,在移動式網路中的安全定位相對來說較少。因此在這篇論文中,我們對目前很有名的蒙特卡羅定位法提出一個安全的策略,利用我們提出的方法,我們有盡可能的抓出潛在的攻擊者並刪除這些錯誤的位置資訊。在我們的模擬中,結果顯示在我們的方法下,攻擊者被偵測出來的機率很高而且在危險環境中的定位誤差也很接近在安全環境中的定位誤差。
The security of localization is an important issue in wireless sensor networks. Recently with rapidly development of wireless mobile sensor networks, localization in wireless mobile sensor networks has attracted much attention, and many localization algorithms have been proposed for this research area. However, most of them are assumed in secure environments. In fact, sensors are most likely to be deployed in hostile environments, and malicious nodes perform harmful behaviors to interfere with the localization process, for example, malicious nodes (attackers) send wrong location information to normal nodes so as to disrupt the localization process. Therefore, the behaviors of malicious nodes may lead to estimate locations incorrect and inaccurate. However, most localization research for security focuses on static sensor networks. Few of them consider about the security of localization in mobile sensor networks. In this paper, we propose a secure strategy to improve the security of Monte Carlo Localization (MCL) algorithm. Moreover, with the secure MCL, the attackers can be detected as many as possible, and the location messages sent by attackers will be discarded. Simulation results show that the ratio of detecting attackers in our proposed algorithm is high, and the average localization error is closed to the secure environments.
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