Consistent, yet anonymous, Web access with LPWA

Gabber, Eran; Gibbons, Phillip B.; Kristol, David M.; Matias, Yossi; Mayer, Alain

doi:10.1145/293411.293447

Cited by 73 publications

(51 citation statements)

References 6 publications

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“…Chou et al introduced one such tool SpoofGuard [2], that determines if a web page is legitimate based on a series of domain and URL based tests. Gabber et al present a tool [10], that tries to protect a clients identity and password information. They define client persona in terms of username, password and email address and introduce a function which provides a client with different persona for different servers it visits.…”

Section: Related Workmentioning

confidence: 99%

A framework for detection and measurement of phishing attacks

Garera

Provos

Chew

et al. 2007

Proceedings of the 2007 ACM Workshop on Recurring Malcode

339

213

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Phishing is form of identity theft that combines social engineering techniques and sophisticated attack vectors to harvest financial information from unsuspecting consumers. Often a phisher tries to lure her victim into clicking a URL pointing to a rogue page. In this paper, we focus on studying the structure of URLs employed in various phishing attacks. We find that it is often possible to tell whether or not a URL belongs to a phishing attack without requiring any knowledge of the corresponding page data. We describe several features that can be used to distinguish a phishing URL from a benign one. These features are used to model a logistic regression filter that is efficient and has a high accuracy. We use this filter to perform thorough measurements on several million URLs and quantify the prevalence of phishing on the Internet today.

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Section: Related Workmentioning

confidence: 99%

A framework for detection and measurement of phishing attacks

Garera

Provos

Chew

et al. 2007

Proceedings of the 2007 ACM Workshop on Recurring Malcode

339

213

View full text Add to dashboard Cite

show abstract

“…Thus, the Web proxy hides the IP information of the user that is originating the request. However, the trace of all the traffic that is originated in and have as destination the proxy might reveal user's identity even SSL/TLS is used (Gabber et al, 1999;Danezis and Diaz, 2008;Li et al, 2011). Furthermore, the Web proxy knows all the information and can trace user's activity (Margasiński and Szczypiorski, 2005).…”

Section: Privacy Solutions For Tcp/ip Layermentioning

confidence: 99%

A survey on solutions and main free tools for privacy enhancing Web communications

Ruiz‐Martínez¹

2012

Journal of Network and Computer Applications

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Concern for privacy when users are surfing on the Web has increased recently. Nowadays, many users are aware that when they are accessing Web sites, these Web sites can track them and create profiles on the elements they access, the advertisements they see, the different links they visit, from which Web sites they come from and to which sites they exit, and so on. In order to maintain user privacy, several techniques, methods and solutions have appeared. In this paper we present an analysis of both these solutions and the main tools that are freely distributed or can be used freely and that implement some of these techniques and methods to preserve privacy when users and surfing on the Internet. This work, unlike previous reviews, shows in a comprehensive way, all the different risks when a user navigates on the Web, the different solutions proposed that finally have being implemented and being used to achieve Web privacy goal. Thus, users can decide which tools to use when they want navigate privately and what kind of risks they are assuming.

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“…Systems like Anonymizer [5], Lucent Personalized Web Assistant [6], PRA:Proxy for Responder Anonymity [12] and APFS Unicast [12] use an intermediate proxy to provide anonymity. As these systems trust the proxy for performance and anonymity guarantees, they are vulnerable to failure if the proxy is compromised or if the proxy fails.…”

Section: Anonymity By Proxymentioning

confidence: 99%

“…If A cannot decrypt the message then A performs one of two actions: it may just add the header to its header buffer or with some probability p inter it may go back and get the corresponding MSG from B. In the first case, A gossips with its neighbors that 6 This assumption holds true in applications with large responses (e.g. file-transfer and web-browsing).…”

Section: Data Dissemination In Muonmentioning

confidence: 99%

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MuON: Epidemic based mutual anonymity in unstructured P2P networks

et al. 2008

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A mutual anonymity system enables communication between a client and a service provider without revealing their identities. In general, the anonymity guarantees made by the protocol are enhanced when a large number of participants are recruited into the anonymity system. Peer-to-peer (P2P) systems are able to attract a large number of nodes and hence are highly suitable for anonymity systems. However, the churn (changes in system membership) within P2P networks, poses a significant challenge for low-bandwidth reliable anonymous communication in these networks. This paper presents MuON, a protocol to achieve mutual anonymity in unstructured P2P networks. MuON leverages epidemic-style data dissemination to deal with churn. Simulation results and security analysis indicate that MuON provides mutual anonymity in networks with high churn, while maintaining predictable latencies, high reliability, and low communication overhead.

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Consistent, yet anonymous, Web access with LPWA

Cited by 73 publications

References 6 publications

A framework for detection and measurement of phishing attacks

A framework for detection and measurement of phishing attacks

A survey on solutions and main free tools for privacy enhancing Web communications

MuON: Epidemic based mutual anonymity in unstructured P2P networks

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