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Localization of spoofing attackers b...
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Madithati, Roopesh Kumar Reddy.
Localization of spoofing attackers by using spatial correlation of received signal strength.
紀錄類型:
書目-語言資料,手稿 : Monograph/item
正題名/作者:
Localization of spoofing attackers by using spatial correlation of received signal strength./
作者:
Madithati, Roopesh Kumar Reddy.
面頁冊數:
1 online resource (40 pages)
附註:
Source: Masters Abstracts International, Volume: 55-03.
Contained By:
Masters Abstracts International55-03(E).
標題:
Electrical engineering. -
電子資源:
click for full text (PQDT)
ISBN:
9781339430591
Localization of spoofing attackers by using spatial correlation of received signal strength.
Madithati, Roopesh Kumar Reddy.
Localization of spoofing attackers by using spatial correlation of received signal strength.
- 1 online resource (40 pages)
Source: Masters Abstracts International, Volume: 55-03.
Thesis (M.S.)
Includes bibliographical references
This item is not available from ProQuest Dissertations & Theses.
A spoofing attack in a wireless network context occurs when a person unauthorized to access the network pretends to be someone else by falsifying data. The spoofer thus receives illegitimate access to the network, and can inflict significant damage to network operations.
Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018
Mode of access: World Wide Web
ISBN: 9781339430591Subjects--Topical Terms:
596380
Electrical engineering.
Index Terms--Genre/Form:
554714
Electronic books.
Localization of spoofing attackers by using spatial correlation of received signal strength.
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A spoofing attack in a wireless network context occurs when a person unauthorized to access the network pretends to be someone else by falsifying data. The spoofer thus receives illegitimate access to the network, and can inflict significant damage to network operations.
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The current project presents a method to protect wireless networks from spoofing attacks by using received signal strength (RSS) measurements, which are difficult to falsify. The method identifies attackers by using the RSS measurements and spatial information to determine which nodes have a different location than legitimate wireless users. Using cluster analysis and a learning algorithm based on "support vector machines" the proposed method can: detect the occurrence of a spoofing attack; determine the number of attackers when there are multiple spoofers using the same identity; localize the attackers and eliminate them from a network. Simulation results show that the RSS-based spatial correlation method is highly effective in detecting and determining the number of attackers in the network.
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