A Probabilistic Model Against DNS Cache Poisoning Attack Under Multiple Resolvers

碩士 === 國立清華大學 === 資訊工程學系 === 98 === Domain name system (DNS) is one of the core services on the Internet. For DNS, the most famous attack is DNS cache poisoning attack. Via cache poisoning, records in DNS cache could be tampered by an adversary. If a client query the compromised DNS server, he would...

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Main Authors: Jeng , Jian-Ming, 鄭健明
Other Authors: Sun, Hung-Ming
Format: Others
Language:en_US
Published: 2010
Online Access:http://ndltd.ncl.edu.tw/handle/59364904777778432906
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spelling ndltd-TW-098NTHU53921082015-11-04T04:01:51Z http://ndltd.ncl.edu.tw/handle/59364904777778432906 A Probabilistic Model Against DNS Cache Poisoning Attack Under Multiple Resolvers 一個針對多解析器的網域名稱伺服器快取毒害攻擊的機率模型 Jeng , Jian-Ming 鄭健明 碩士 國立清華大學 資訊工程學系 98 Domain name system (DNS) is one of the core services on the Internet. For DNS, the most famous attack is DNS cache poisoning attack. Via cache poisoning, records in DNS cache could be tampered by an adversary. If a client query the compromised DNS server, he would connect to a malicious host located with an incorrect IP address. To prevent DNS cache poisoning, various approaches have been proposed to enhance DNS security. Without using cryptographic techniques, they can only raise the entropy rather than preventing from DNS cache poisoning. Several works raise the strength of security by querying multiple resolvers; returned results are used to verify the credibility of the IP addresses they connect with. However, the security is still not easy to evaluate as similar as conventional cryptographic approaches, e.g., DNSSEC. In this thesis, we propose a probabilistic model to evaluate the successful probability of cache poisoning under reasonable setting, e.g., ability of adversary or multiple resolvers architecture. Based on analyzed results we utilize our model to improve and promote the security of the approaches based on multiple resolvers. Sun, Hung-Ming 孫宏民 2010 學位論文 ; thesis 44 en_US
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description 碩士 === 國立清華大學 === 資訊工程學系 === 98 === Domain name system (DNS) is one of the core services on the Internet. For DNS, the most famous attack is DNS cache poisoning attack. Via cache poisoning, records in DNS cache could be tampered by an adversary. If a client query the compromised DNS server, he would connect to a malicious host located with an incorrect IP address. To prevent DNS cache poisoning, various approaches have been proposed to enhance DNS security. Without using cryptographic techniques, they can only raise the entropy rather than preventing from DNS cache poisoning. Several works raise the strength of security by querying multiple resolvers; returned results are used to verify the credibility of the IP addresses they connect with. However, the security is still not easy to evaluate as similar as conventional cryptographic approaches, e.g., DNSSEC. In this thesis, we propose a probabilistic model to evaluate the successful probability of cache poisoning under reasonable setting, e.g., ability of adversary or multiple resolvers architecture. Based on analyzed results we utilize our model to improve and promote the security of the approaches based on multiple resolvers.
author2 Sun, Hung-Ming
author_facet Sun, Hung-Ming
Jeng , Jian-Ming
鄭健明
author Jeng , Jian-Ming
鄭健明
spellingShingle Jeng , Jian-Ming
鄭健明
A Probabilistic Model Against DNS Cache Poisoning Attack Under Multiple Resolvers
author_sort Jeng , Jian-Ming
title A Probabilistic Model Against DNS Cache Poisoning Attack Under Multiple Resolvers
title_short A Probabilistic Model Against DNS Cache Poisoning Attack Under Multiple Resolvers
title_full A Probabilistic Model Against DNS Cache Poisoning Attack Under Multiple Resolvers
title_fullStr A Probabilistic Model Against DNS Cache Poisoning Attack Under Multiple Resolvers
title_full_unstemmed A Probabilistic Model Against DNS Cache Poisoning Attack Under Multiple Resolvers
title_sort probabilistic model against dns cache poisoning attack under multiple resolvers
publishDate 2010
url http://ndltd.ncl.edu.tw/handle/59364904777778432906
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