79,228 research outputs found

    BlogForever: D2.5 Weblog Spam Filtering Report and Associated Methodology

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    This report is written as a first attempt to define the BlogForever spam detection strategy. It comprises a survey of weblog spam technology and approaches to their detection. While the report was written to help identify possible approaches to spam detection as a component within the BlogForver software, the discussion has been extended to include observations related to the historical, social and practical value of spam, and proposals of other ways of dealing with spam within the repository without necessarily removing them. It contains a general overview of spam types, ready-made anti-spam APIs available for weblogs, possible methods that have been suggested for preventing the introduction of spam into a blog, and research related to spam focusing on those that appear in the weblog context, concluding in a proposal for a spam detection workflow that might form the basis for the spam detection component of the BlogForever software

    "May I borrow Your Filter?" Exchanging Filters to Combat Spam in a Community

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    Leveraging social networks in computer systems can be effective in dealing with a number of trust and security issues. Spam is one such issue where the "wisdom of crowds" can be harnessed by mining the collective knowledge of ordinary individuals. In this paper, we present a mechanism through which members of a virtual community can exchange information to combat spam. Previous attempts at collaborative spam filtering have concentrated on digest-based indexing techniques to share digests or fingerprints of emails that are known to be spam. We take a different approach and allow users to share their spam filters instead, thus dramatically reducing the amount of traffic generated in the network. The resultant diversity in the filters and cooperation in a community allows it to respond to spam in an autonomic fashion. As a test case for exchanging filters we use the popular SpamAssassin spam filtering software and show that exchanging spam filters provides an alternative method to improve spam filtering performance

    Political E-Mail: Protected Speech or Unwelcome Spam?

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    Candidates for political office are using unsolicited bulk e-mails to reach the electorate. Commonly known as political spam, this campaign tactic is an inexpensive supplement to television, radio, and print ads. Advocates claim that campaigning via the internet reduces candidates\u27 dependence on fundraising, but critics detest political spam as the latest nuisance. This iBrief examines the legal basis for political spam, distinguishes political spam from analogous regulated speech, and argues that political spam serves an interest worth protecting

    Political E-Mail: Protected Speech or Unwelcome Spam?

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    Candidates for political office are using unsolicited bulk e-mails to reach the electorate. Commonly known as political spam, this campaign tactic is an inexpensive supplement to television, radio, and print ads. Advocates claim that campaigning via the internet reduces candidates\u27 dependence on fundraising, but critics detest political spam as the latest nuisance. This iBrief examines the legal basis for political spam, distinguishes political spam from analogous regulated speech, and argues that political spam serves an interest worth protecting

    Spam

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    With the advent of the electronic mail system in the 1970s, a new opportunity for direct marketing using unsolicited electronic mail became apparent. In 1978, Gary Thuerk compiled a list of those on the Arpanet and then sent out a huge mailing publicising Digital Equipment Corporation (DEC—now Compaq) systems. The reaction from the Defense Communications Agency (DCA), who ran Arpanet, was very negative, and it was this negative reaction that ensured that it was a long time before unsolicited e-mail was used again (Templeton, 2003). As long as the U.S. government controlled a major part of the backbone, most forms of commercial activity were forbidden (Hayes, 2003). However, in 1993, the Internet Network Information Center was privatized, and with no central government controls, spam, as it is now called, came into wider use. The term spam was taken from the Monty Python Flying Circus (a UK comedy group) and their comedy skit that featured the ironic spam song sung in praise of spam (luncheon meat)—“spam, spam, spam, lovely spam”—and it came to mean mail that was unsolicited. Conversely, the term ham came to mean e-mail that was wanted. Brad Templeton, a UseNet pioneer and chair of the Electronic Frontier Foundation, has traced the first usage of the term spam back to MUDs (Multi User Dungeons), or real-time multi-person shared environment, and the MUD community. These groups introduced the term spam to the early chat rooms (Internet Relay Chats). The first major UseNet (the world’s largest online conferencing system) spam sent in January 1994 and was a religious posting: “Global alert for all: Jesus is coming soon.” The term spam was more broadly popularised in April 1994, when two lawyers, Canter and Siegel from Arizona, posted a message that advertized their information and legal services for immigrants applying for the U.S. Green Card scheme. The message was posted to every newsgroup on UseNet, and after this incident, the term spam became synonymous with junk or unsolicited e-mail. Spam spread quickly among the UseNet groups who were easy targets for spammers simply because the e-mail addresses of members were widely available (Templeton, 2003)

    Minimizing the Time of Spam Mail Detection by Relocating Filtering System to the Sender Mail Server

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    Unsolicited Bulk Emails (also known as Spam) are undesirable emails sent to massive number of users. Spam emails consume the network resources and cause lots of security uncertainties. As we studied, the location where the spam filter operates in is an important parameter to preserve network resources. Although there are many different methods to block spam emails, most of program developers only intend to block spam emails from being delivered to their clients. In this paper, we will introduce a new and efficient approach to prevent spam emails from being transferred. The result shows that if we focus on developing a filtering method for spams emails in the sender mail server rather than the receiver mail server, we can detect the spam emails in the shortest time consequently to avoid wasting network resources.Comment: 10 pages, 7 figure
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