Mystery Meat: Where does spam come from, and why does it matter? 1
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Unsolicited commercial email or spam is recognized as a problem disrupting email communication and costing the community dearly. In order to protect recipients from receiving spam, anti-spam measures building on technologies, such as filters and block lists, have been deployed widely. There is some evidence that certain anti-spam measures based on the purported origin of the spam cause unintended consequences which relate to issues of equity of access which we term digital redlining. Spammers have an interest in bypassing such measures by obscuring the real origin of their messages. Investigating these effects means we need to determine the true origin of spam, despite the efforts of spammers to confuse us and spam filters. The aim to find the true origin of spam is different from the objective of most anti-spam developers who are mainly interested in identifying spam when it knocks on their front door (mail server). In this paper we discuss why the difference between originator and delivery host matters when investigating digital redlining. We also highlight some of the difficulties we are facing when trying to determine the originating host as opposed to the delivering host.Keywords:
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1. Introduction The use of electronic technology including e-mails, cellular phones, the Internet and cyberspace as contracting media in the modern commercial world is forever gaining momentum (Tang, 2007, p 42). The huge opportunities created by electronic technology have been paralleled by some innovative marketing practices. Consumers are flooded with countless numbers of business offers from all over the world, almost on a daily basis and many of which are unsolicited (Tladi, 2008, p 178). Different terms have been used to refer to spam. Geissler (2004, pp 24-31) uses the term such as 'Unsolicited Bulk E-mail' (UBE); 'Unsolicited Commercial E-mail (UCE). From the onset the author would like to point out that the word 'spam' will, in this text, be used in its narrow sense to refer to unsolicited commercial communication (UCC). According to Polanski (2007, p 403), unsolicited commercial communications, spam as it is often called, has become a global plague. The communication is regarded as 'unsolicited' because there exist no prior relationship the recipient and the sender to justify such communication. Moreover, the recipient never explicitly agreed to receive such communication (generally, Solkin, 2001, pp 325-384). Put simply, the recipient has not given permission for the unsolicited communication to be sent to him or her. There is a continuing need for consumers to be protected from unwanted or malicious spam by every national jurisdiction through more effective means, including more effective legislative intervention. This paper compares and examines the legislative and regulatory systems of spam in Canada, the European Union, and South Africa. The key issue in this survey is how these jurisdictions deal with the problem of errant spamming. Minimal or non-government intervention policy in favour of industry self-regulation, which was once the preferred method in Canada, for example, may prove to be ineffective. Since the requirements for the presentation of this paper does not allow an in-depth enquiry into all the measures designed to combat spam, the author will not deal with various technical, educational and administrative efforts to prevent spam. 2. Problems Created by Spam It has become increasingly difficult to tolerate Spam, and to control and prevent it, even by using the most sophisticated of Spam filters. The spammers, too, have become sophisticated and may easily bypass these filters, even the revered Optical Character Recognition (OCR) technology, which has been created to translate pictorial or graphical Spam into computer fonts (Polanski, 2007, p 406). The problems created by Spam and the costs associated with combating it are clearly described as follows: (a) the recipient pays far more, in time and trouble as well as money, than the sender does (unlike unrequested advertising through the postal service); (b) the recipient must take the time to request removal from the mailing list, and most spammers claim to remove names on request but rarely do so; (c )many spammers use intermediate systems without authorization to avoid blocks set up to avoid them; (d) many Spam messages are deceptive and partially or entirely fraudulent; and (e) the recipient ends up with the problem of technological Spam filters that also block non-spam messages (Levine, ; Delio, 2000, ). In South Africa the spam is reported to cost business between R7 billion and R13 billion yearly in lost productivity (Tladi, 2008, p 183). 3. Spam Regulatory and Legislative Measures 3.1 South Africa 3.1.1 Spam Specific Legislative Interventions E-commerce in South Africa is governed primarily by the Electronic Communications and Transactions Act (ECTA) 25 of 2002, which came into force on 30 August 2002, as South Africa's first comprehensive e-commerce legislation (Sibanda, 2008, p 321). …
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I. INTRODUCTION On July 24, 2005, Vardan Kushnir, notorious for sending spam1 to most of Russia's 17.6 million Internet users, was bludgeoned to death in his Moscow home.2 The reaction of the Russian media to Kushnir's murder was nothing short of jubilation,3 and while Kushnir's murder was ultimately attributed to a simple robbery,4 this visceral response illustrates the feeling many people have for spammers.5 In addition to being a nuisance, spam has a serious economic impact on consumers and corporations.6 Both consumers and Internet Service Providers (ISPs) must shoulder the burden of spam prevention, either through direct monetary costs or the more indirect impact on their productivity.7 Spam is also a common vehicle for fraud and other crimes.8 Most alarmingly, the proliferation of spam may cause some to abandon the use of email altogether.9 In response to the threat posed by spam, several countries have adopted legislation aimed at curbing its use. These laws vary greatly in their stringency and success rate, but all have ultimately failed to put a stop to spam. This failure is due largely to the global nature of the Internet and the ease with which spam can be sent from virtually anywhere on earth. Nations with spam problems have begun to recognize the international nature of spam and, as a result, have developed a patchwork quilt of bilateral and multilateral agreements. These ad hoc agreements are steps in the right direction but, because spam is a truly global problem, a comprehensive, global, solution is needed. Since the problem of international drug trafficking is analogous to that of spam on many levels, the international community should adopt a convention on spam modeled on earlier drug trafficking agreements. This Note discusses the problem of spam and proposes the use of existing drug trafficking agreements as a model for an international convention on spam. Part I of this Note discusses the nature of spam, including its negative impact on society. Part II explains domestic approaches to spam regulation in the United States and Australia-countries whose contrasting approaches to spam are emblematic of the various forms of domestic legislation. Part III examines the recent proliferation of bilateral and multilateral antispam agreements. Part IV discusses the failure of existing solutions and the need for a more comprehensive international solution. Finally, Part V examines the international approach to drug trafficking, explaining why these existing treaties are an ideal model for an anti-spam convention. II. SPAM AND ITS NEGATIVE IMPACT A. What Is Spam? While opinions differ on how to define spam,10 in its broadest terms it is best defined as bulk email dedicated to electronic advertising-the Internet equivalent of the conventional junk mail that lands on your doormat most days of the week.11 While many consider unsolicited email containing religious or political messages as spam,12 regulation of spam has been limited solely to commercial email.13 The lack of a clear definition for spam has made it difficult to precisely measure the amount of spam filling inboxes every year.14 Nevertheless, consensus suggests that the volume of spam is large and increasing.15 In 2003, a Senate committee warned that more than 2 trillion spam messages were expected to be sent in that year alone.16 A 2004 United Nations spam conference suggested that spam comprised seventy-six percent of all email worldwide.17 One anti-spam software company recendy reported that its filtering software blocked twelve pieces of spam per second.18 Whatever the measure, it is evident that spam up a considerable amount of all email traffic. B. The Negative Impact of Spam 1. Impact on Use and Enjoyment of Email Perhaps the most palatable effect of spam on the average email consumer is that it makes the Internet less friendly [,] and e-mail less useful. …
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E-mail is one of the most popular and frequently used ways of communication due to its worldwide accessibility, relatively fast message transfer, and low sending cost. The flaws in the e-mail protocols and the increasing amount of electronic business and financial transactions directly contribute to the increase in e-mail-based threats. Email spam is one of the major problems of the today's Internet, bringing financial damage to companies and annoying individual users. Spam emails are invading users without their consent and filling their mail boxes. They consume more network capacity as well as time in checking and deleting spam mails. The vast majority of Internet users are outspoken in their disdain for spam, although enough of them respond to commercial offers that spam remains a viable source of income to spammers. While most of the users want to do right think to avoid and get rid of spam, they need clear and simple guidelines on how to behave. In spite of all the measures taken to eliminate spam, they are not yet eradicated. Also when the counter measures are over sensitive, even legitimate emails will be eliminated. Among the approaches developed to stop spam, filtering is the one of the most important technique. Many researches in spam filtering have been centered on the more sophisticated classifier-related issues. In recent days, Machine learning for spam classification is an important research issue. The effectiveness of the proposed work is explores and identifies the use of different learning algorithms for classifying spam messages from e-mail. A comparative analysis among the algorithms has also been presented.
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The proliferation of unrestricted Internet access has brought the community spam which has become a serious problem costing companies billions of dollars per annum. Typical anti-spam measures, such as filtering and blocking techniques, exist but focus on solving the spam problem on the message transportation level. Using such techniques may have impacts beyond the realm of spam-filters and block lists. In this paper we argue that implementing typical anti-spam measures means that computers are assigned the power to assess legitimacy of email. This means, for example, that legitimate email might be rejected because the sender used the 'wrong' mail server or the wrong terminology. In this paper, we describe some of the core problems and discuss alternatives.
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Although email spam has been decreasing in recent years, it is still a significant problem. Unsolicited messages are not only an annoying waste of time, but may also lead users to dubious websites where their personal information is collected or malicious code is executed. In this paper, we study a relatively new trend in the world of spamming, localization of spam email. It seems spammers are now targeting people in smaller countries, such as Finland, by sending junk mail in their native languages. As a case study, we analyze a set of over 300 spam email messages written in Finnish and study how localization of messages is used to convince the victims to fall into spammers' traps. Our results indicate that localized and targeted spam is a significant threat which needs to be better addressed when planning security measures and educating the public.
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What spam is, how it works, and how it has shaped online communities and the Internet itself. The vast majority of all email sent every day is spam, a variety of idiosyncratically spelled requests to provide account information, invitations to spend money on dubious products, and pleas to send cash overseas. Most of it is caught by filters before ever reaching an in-box. Where does it come from? As Finn Brunton explains in Spam, it is produced and shaped by many different populations around the world: programmers, con artists, bots and their botmasters, pharmaceutical merchants, marketers, identity thieves, crooked bankers and their victims, cops, lawyers, network security professionals, vigilantes, and hackers. Every time we go online, we participate in the system of spam, with choices, refusals, and purchases the consequences of which we may not understand. This is a book about what spam is, how it works, and what it means. Brunton provides a cultural history that stretches from pranks on early computer networks to the construction of a global criminal infrastructure. The history of spam, Brunton shows us, is a shadow history of the Internet itself, with spam emerging as the mirror image of the online communities it targets. Brunton traces spam through three epochs: the 1970s to 1995, and the early, noncommercial computer networks that became the Internet; 1995 to 2003, with the dot-com boom, the rise of spam's entrepreneurs, and the first efforts at regulating spam; and 2003 to the present, with the war of algorithms-spam versus anti-spam. Spam shows us how technologies, from email to search engines, are transformed by unintended consequences and adaptations, and how online communities develop and invent governance for themselves.
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Spam e-mails have become a serious technological and economic problem. Up to now, by deploying complementary anti-spam measures, we have been reasonably able to withstand spam e-mails and use the Internet for regular communication. However, if we are to avert the danger of losing the Internet e-mail service in its capacity as a valuable, free and worldwide medium of open communication, anti-spam activities should be performed more systematically than is currently the case regarding the mainly heuristic, anti-spam measures in place. A formal framework, within which the existing delivery routes that a spam e-mail may take, and anti-spam measures and their effectiveness can be investigated, will perhaps encourage a shift in methodology and pave the way for new, holistic anti-spam measures. This paper presents a model of the Internet e-mail infrastructure as a directed graph and a deterministic finite automaton and draws on automata theory to formally derive the spam delivery routes. The most important anti-spam measures are then described. Methods controlling only specific delivery routes are evaluated in terms of how effectively they cover the modeled e-mail infrastructure; methods operating independently of any particular routes receive a more general assessment.
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The sending of unsolicited communications (commonly known as ‘spam’) is considered as a great intrusion into the privacy of the user of electronic communications services, and is therefore regulated in Article 13 of the ePrivacy directive. At the time of the adoption of the directive, the most common ways of spamming were via telephone, fax, electronic mail and SMS. Technological progress, however, has since created more types of spamming, one of which is Bluespam, i.e., the action of sending spam to Bluetooth-enabled devices, such as mobile phones, PDAs or laptop computers. Although, at first sight, it would seem that Bluespam should be considered as any other kind of spam, and would therefore fall under the ambit of Article 13 of the ePrivacy directive, a closer look reveals that the answer is in fact not so obvious.
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This paper discusses the spam detection and different machine learning models to detect these spam messages. The present work also discusses the testing and evaluation of spam messages. Spam messages have always been very dangerous for computers and networks. They have a very bad effect on the computer security. With the emergence of social media platforms, many people are dependent on emails to communicate, and, with this, there is always a need to detect and prevent spam mails before it enters a user’s inbox. The paper also presents the analyses of different machine learning techniques to detect spam messages. Finally, the paper describes the algorithm which is best to detect spam messages. Spam messages are basically redundant messages which are sent in a large number at once. They can be seen in many forms like free services, cheap SMS plans, lottery, etc. Growing spam messages in your mail can make your inbox filled with ridiculous mails, slow down your Internet speed, and retrieve your private information like credit card details, and has many more drawbacks. Therefore, it is important to prevent it in the best way possible.
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With the rapid adoption of Internet as an easy way to communicate, the amount of unsolicited e-mails, known as spam e-mails, has been growing rapidly. The major problem of spam e-mails is the loss of productivity and a drain on IT resources. Today, we receive spam more rapidly than the legitimate e-mails. Initially, spam e-mails contained only textual messages which were easily detected by the text-based spam filters. To evade such detection, spammers came up with a new sophisticated technique called image spam. Image spam consists in embedding the advertisement text in images rather than in the body of the e-mail, yet the image contents are not detected by most spam filters. In this paper, we examine the motivations and the challenges in image spam filtering research, and we review the recent trends in combating image spam e-mails. The review indicates that spamming is a business model and spammers are becoming more sophisticated in their approach to adapt to all challenges, and hence, defeating the conventional spam filtering technologies. Therefore, image spam detection techniques should be scalable and adaptable to meet the future tactics of the spammers.
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