Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/19487
DC FieldValueLanguage
dc.contributor高成炎zh_TW
dc.contributor陳朝欽zh_TW
dc.contributor高明達zh_TW
dc.contributor許舜欽zh_TW
dc.contributor詹進科zh_TW
dc.contributor洪國寶zh_TW
dc.contributor高勝助zh_TW
dc.contributor.advisor廖宜恩zh_TW
dc.contributor.author高國峰zh_TW
dc.contributor.authorKao, Kuo-Fongen_US
dc.contributor.other中興大學zh_TW
dc.date2009zh_TW
dc.date.accessioned2014-06-06T07:06:52Z-
dc.date.available2014-06-06T07:06:52Z-
dc.identifierU0005-2901200817351300zh_TW
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dc.identifier.urihttp://hdl.handle.net/11455/19487-
dc.description.abstract無線網路技術近幾年逐漸成熟,構成無線網路的兩大類裝置:無線區域網路存取點(Access Point)以及遠端無線裝置(Remote Device),在所有學校或企業組織當中也越來越普及。 這使得這些無線裝置的安全管理,成為一個迫切而且重要的研究課題。 非法無線區域網路存取點問題,便是其中一個備受矚目的問題。 非法無線區域網路存取點,指的是未經管理者允許,而由一般使用者或駭客,自行設立的無線區域網路存取點。 這些非法無線區域網路存取點,很容易造成網路安全的重大危害。 針對這個問題,有兩項功能對網路管理是特別有用的。第一項是非法無線區域網路存取點的偵測,第二項是遠端無線裝置的定位。 傳統上,要偵測非法無線區域網路存取點的存在,網管人員必須帶著無線電波偵測器,一一掃描管理區域的每一個角落。 這樣的工作方式,不但需要額外的硬體,又非常辛苦且沒有效率。 本論文提出一種基於網路封包分析,且不需要額外硬體的新方法。 這個方法藉由封包對技術,分析某個連線的客戶端瓶頸頻寬,藉此可以判斷該連線是否來自於非法無線區域網路存取點。 網管人員將可以在辦公室中藉由監控封包,輕鬆的完成非法無線區域網路存取點偵測的工作。 在我們的實驗當中,本論文所提出的方法,可以達到99\%以上的準確率。 實驗結果顯示,本方法確實可以減輕網管人員的負擔,並增加網路的安全性。 在找出非法無線區域網路存取點後,管理者可能需要找出透過非法無線區域網路存取點連線上來的遠端無線裝置的位置,以作進一步的處裡。 要達到這個目的,我們便需要遠端無線裝置的定位的功能。 而事實上,無線裝置的定位技術,除了能在解決非法無線區域網路存取點問題,扮演重要的角色,這技術更是情境感知服務的重要基礎。 在定位技術的研究當中,定位準確度是一個非常重要的課題。 傳統的定位演算法,只藉由感測到的訊號強度來定位。 本研究提出一個,藉由訊號強度以及偵測使用者方向,來改善準確度的方法。 理論上,若能掌握使用者的正確方向,我們便可以在預測位置時,只使用該方向的訓練資料來作為預測的依據。 因此,可以增加預測的準確度。 然而實務上,若方向性資訊,也是經由預測得知;那麼,在使用該方向性資訊時,便要非常小心。 因為,不正確的方向性資訊,反而會降低預測準確度。 為了能夠避免誤用方向性資訊的傷害,本研究提出一項假設。 我們假設,當方向預測錯誤時,該錯誤將不會偏於特定方向。 基於這個假設,本研究提出一個累進方向性強度演算法。 這個演算法,能夠讓我們恰當的使用正確的方向性資訊,並且避免使用錯誤的方向性資訊。 藉此,我們可以改善位置預測的整體準確度。 我們使用貝氏模型,來實做該系統,並以中興大學理學院大樓七樓為測試環境,來檢驗我們的假設及該演算法的效能。 實驗數據顯示,我們提出的方法,確實能夠改善準確度。 這將可以為解決非法無線區域網路存取點問題,以及建立情境感知服務,提供更有力的幫助。zh_TW
dc.description.abstractThe wireless LAN (WLAN), which contains Access Points (AP) and remote devices, has become increasingly popular due to its low price and easy installation. However, the popularity of the WLAN increases the threat of network security. One of the important security problems is the rogue AP problem. In unprotected areas, an unauthorized AP can be plugged into the LANs of most organizations quickly and easily, the matter which results in serious security problems. Network managers always look at two useful functions on the AP and the remote device to resist the invasion of the rogue AP. One is to detect whether illegal APs are deployed on the managed area. The second is to predict the position of a remote device from the rogue AP. To detect an AP, the network manager traditionally takes an electric wave sensor across the whole protected place. This method of detection is very difficult and inefficient. This study presents a new method to detect an AP without additional hardware and intense effort. This new method determines whether the network packets of an IP are routed from APs according to client-side bottleneck bandwidth. The network manager can then perform his job from his office by monitoring the packets passing through the core switch. The experimental results indicate that the accuracies of this method constantly remain above 99%. The proposed method can effectively reduce the detailed labor of the network manager and increase the network security. Once a rogue AP is detected, the next task is to find the location of the illegal user. Due to the rogue AP problem and the demand for context-aware services inside buildings, the WLAN-based location determination has emerged as a significant research topic. However, prediction accuracy remains a primary issue in the practicality of WLAN-based location determination systems. This study proposes an innovative scheme that utilizes mobile user orientation information to improve prediction accuracy. Theoretically, if the precise orientation of a user can be identified, then the location determination system can predict that user''s location with a high degree of accuracy by using the training data of this specific orientation. In reality, a mobile user''s orientation can be estimated only by comparing variations in received signal strength; and the predicted orientation may be incorrect. Incorrect orientation information causes the accuracy of the entire system to decrease. Therefore, this study presents an accumulated orientation strength algorithm which can utilize uncertain estimated orientation information to improve prediction accuracy. Implementation of this system is based on the Bayesian model, and the experimental results show the effectiveness of the proposed approach.en_US
dc.description.tableofcontents1. Introduction 1 1.1. Research Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2. Objectives and Main Contributions . . . . . . . . . . . . . . . . . . . 2 1.3. Organization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 2. Related Work 9 2.1. Research on Rogue AP Detection . . . . . . . . . . . . . . . . . . . . 9 2.2. Research on Localization . . . . . . . . . . . . . . . . . . . . . . . . . 10 2.2.1. Location Determination Systems . . . . . . . . . . . . . . . . 11 2.2.2. Impact of the Orientation on RSS . . . . . . . . . . . . . . . . 13 3. Algorithm for Rogue AP Detection 16 3.1. Detecting AP based on Client-side Bottleneck Bandwidth . . . . . . . 16 3.1.1. Client-side Bottleneck Bandwidth . . . . . . . . . . . . . . . 16 3.1.2. Measuring Bottleneck Bandwidth by Packet Pair Technique . 18 3.1.3. Generating Stable Features by Sliding Window Technique . . 19 3.1.4. Rogue AP Detection as a Classication Problem . . . . . . . . 20 3.2. Testbed and Experimental Analysis . . . . . . . . . . . . . . . . . . 21 3.2.1. Experimental Setup . . . . . . . . . . . . . . . . . . . . . . . . 22 3.2.2. E®ectiveness of Inter-Packet Space and Client-side Bottleneck Bandwidth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 3.2.3. Prediction Accuracy of Client-side Bottleneck Bandwidth with Sliding Window . . . . . . . . . . . . . . . . . . . . . . . . . . 25 3.3. Contributions and Limitations . . . . . . . . . . . . . . . . . . . . . . 27 3.3.1. Contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 3.3.2. Limitations . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 4. Algorithm for Improving Localization Accuracy 29 4.1. Bayesian Estimation Model . . . . . . . . . . . . . . . . . . . . . . . 29 4.2. Using Orientation Information to Improve Accuracy . . . . . . . . . . 32 4.2.1. Orientation Information by RSS Variance . . . . . . . . . . . . 32 4.2.2. Accumulated Orientation Strength . . . . . . . . . . . . . . . 34 4.3. RSS Data Set Generation and E®ects of Orientation . . . . . . . . . . 37 4.3.1. RSS Data Set Generation . . . . . . . . . . . . . . . . . . . . 37 4.3.2. Distribution of the RSS . . . . . . . . . . . . . . . . . . . . . 40 4.3.3. Benet and Loss of Using Orientation Information . . . . . . . 43 4.3.4. Distribution of Incorrect Estimated Locations . . . . . . . . . 44 4.4. Evaluation of AOS Algorithm . . . . . . . . . . . . . . . . . . . . . . 46 4.4.1. Generation of Walking Path Data . . . . . . . . . . . . . . . . 46 4.4.2. Choosing the Parameters . . . . . . . . . . . . . . . . . . . . . 47 4.4.3. Accuracy of Localization . . . . . . . . . . . . . . . . . . . . . 51 4.5. Contributions and Limitations . . . . . . . . . . . . . . . . . . . . . . 56 4.5.1. Contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 4.5.2. Limitations . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 5. Conclusions and Future Work 59 5.1. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 5.2. Future Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60en_US
dc.language.isoen_USzh_TW
dc.publisher資訊科學與工程學系所zh_TW
dc.relation.urihttp://www.airitilibrary.com/Publication/alDetailedMesh1?DocID=U0005-2901200817351300en_US
dc.subjectAP Detectionen_US
dc.subject無線區域網路存取點偵測zh_TW
dc.subjectPacket Pairen_US
dc.subjectRogue APen_US
dc.subjectPacket Analysisen_US
dc.subjectSecurityen_US
dc.subjectLocalizationen_US
dc.subjectLocation Awareen_US
dc.subjectReceived Signal Strengthen_US
dc.subjectOrientationen_US
dc.subjectWireless LANen_US
dc.subject封包對zh_TW
dc.subject非法無線區域網路存取點zh_TW
dc.subject無線基地台zh_TW
dc.subject封包分析zh_TW
dc.subject定位zh_TW
dc.subject情境感知zh_TW
dc.subject訊號強度zh_TW
dc.subject方向性zh_TW
dc.subject無線網路zh_TW
dc.subject網路安全zh_TW
dc.title非法無線存取點偵測與無線裝置定位之研究zh_TW
dc.titleA Study on Rogue Access Point Detection and Wireless Device Localizationen_US
dc.typeThesis and Dissertationzh_TW
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