Image Spam Detection: Problem and Existing Solution
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Technical and Legal Approaches to Unsolicited Electronic Mail, 35 USFL Rev
UIC School of Law UIC Law Open Access Repository UIC Law Open Access Faculty Scholarship 1-1-2001 Technical and Legal Approaches to Unsolicited Electronic Mail, 35 U.S.F. L. Rev. 325 (2001) David E. Sorkin John Marshall Law School, [email protected] Follow this and additional works at: https://repository.law.uic.edu/facpubs Part of the Computer Law Commons, Internet Law Commons, Marketing Law Commons, and the Privacy Law Commons Recommended Citation David E. Sorkin, Technical and Legal Approaches to Unsolicited Electronic Mail, 35 U.S.F. L. Rev. 325 (2001). https://repository.law.uic.edu/facpubs/160 This Article is brought to you for free and open access by UIC Law Open Access Repository. It has been accepted for inclusion in UIC Law Open Access Faculty Scholarship by an authorized administrator of UIC Law Open Access Repository. For more information, please contact [email protected]. Technical and Legal Approaches to Unsolicited Electronic Mailt By DAVID E. SORKIN* "Spamming" is truly the scourge of the Information Age. This problem has become so widespread that it has begun to burden our information infrastructure. Entire new networks have had to be constructed to deal with it, when resources would be far better spent on educational or commercial needs. United States Senator Conrad Burns (R-MT)1 UNSOLICITED ELECTRONIC MAIL, also called "spain," 2 causes or contributes to a wide variety of problems for network administrators, t Copyright © 2000 David E. Sorkin. * Assistant Professor of Law, Center for Information Technology and Privacy Law, The John Marshall Law School; Visiting Scholar (1999-2000), Center for Education and Research in Information Assurance and Security (CERIAS), Purdue University. -
Spamalytics: an Empirical Analysis of Spam Marketing Conversion
Spamalytics: An Empirical Analysis of Spam Marketing Conversion Chris Kanich∗ Christian Kreibich† Kirill Levchenko∗ Brandon Enright∗ Geoffrey M. Voelker∗ Vern Paxson† Stefan Savage∗ † ∗ International Computer Science Institute Dept. of Computer Science and Engineering Berkeley, USA University of California, San Diego, USA [email protected],[email protected] {ckanich,klevchen,voelker,savage}@cs.ucsd.edu [email protected] ABSTRACT Unraveling such questions is essential for understanding the eco- The “conversion rate” of spam — the probability that an unso- nomic support for spam and hence where any structural weaknesses licited e-mail will ultimately elicit a “sale” — underlies the entire may lie. Unfortunately, spammers do not file quarterly financial spam value proposition. However, our understanding of this critical reports, and the underground nature of their activities makes third- behavior is quite limited, and the literature lacks any quantitative party data gathering a challenge at best. Absent an empirical foun- study concerning its true value. In this paper we present a method- dation, defenders are often left to speculate as to how successful ology for measuring the conversion rate of spam. Using a parasitic spam campaigns are and to what degree they are profitable. For ex- infiltration of an existing botnet’s infrastructure, we analyze two ample, IBM’s Joshua Corman was widely quoted as claiming that spam campaigns: one designed to propagate a malware Trojan, the spam sent by the Storm worm alone was generating “millions and other marketing on-line pharmaceuticals. For nearly a half billion millions of dollars every day” [2]. While this claim could in fact be spam e-mails we identify the number that are successfully deliv- true, we are unaware of any public data or methodology capable of ered, the number that pass through popular anti-spam filters, the confirming or refuting it. -
A Rule Based Approach for Spam Detection
A RULE BASED APPROACH FOR SPAM DETECTION Thesis submitted in partial fulfillment of the requirements for the award of degree of Master of Engineering In Computer Science & Engineering By: Ravinder Kamboj (Roll No. 800832030) Under the supervision of: Dr. V.P Singh Mrs. Sanmeet Bhatia Assistant Professor Assistant Professor Computer Science & Engineering Department of SMCA COMPUTER SCIENCE AND ENGINEERING DEPARTMENT THAPAR UNIVERSITY PATIALA – 147004 JULY- 2010 i ii Abstract Spam is defined as a junk Email or unsolicited Email. Spam has increased tremendously in the last few years. Today more than 85% of e-mails that are received by e-mail users are spam. The cost of spam can be measured in lost human time, lost server time and loss of valuable mail. Spammers use various techniques like spam via botnet, localization of spam and image spam. According to the mail delivery process anti-spam measures for Email Spam can be divided in to two parts, based on Emails envelop and Email data. Black listing, grey listing and white listing techniques can be applied on the Email envelop to detect spam. Techniques based on the data part of Email like heuristic techniques and Statistical techniques can be used to combat spam. Bayesian filters as part of statistical technique divides the income message in to words called tokens and checks their probability of occurrence in spam e-mails and ham e-mails. Two types of approaches can be followed for the detection of spam e-mails one is learning approach other is rule based approach. Learning approach required a large dataset of spam e-mails and ham e-mails is required for the training of spam filter; this approach has good time characteristics filter can be retrained quickly for new Spam. -
Address Munging: the Practice of Disguising, Or Munging, an E-Mail Address to Prevent It Being Automatically Collected and Used
Address Munging: the practice of disguising, or munging, an e-mail address to prevent it being automatically collected and used as a target for people and organizations that send unsolicited bulk e-mail address. Adware: or advertising-supported software is any software package which automatically plays, displays, or downloads advertising material to a computer after the software is installed on it or while the application is being used. Some types of adware are also spyware and can be classified as privacy-invasive software. Adware is software designed to force pre-chosen ads to display on your system. Some adware is designed to be malicious and will pop up ads with such speed and frequency that they seem to be taking over everything, slowing down your system and tying up all of your system resources. When adware is coupled with spyware, it can be a frustrating ride, to say the least. Backdoor: in a computer system (or cryptosystem or algorithm) is a method of bypassing normal authentication, securing remote access to a computer, obtaining access to plaintext, and so on, while attempting to remain undetected. The backdoor may take the form of an installed program (e.g., Back Orifice), or could be a modification to an existing program or hardware device. A back door is a point of entry that circumvents normal security and can be used by a cracker to access a network or computer system. Usually back doors are created by system developers as shortcuts to speed access through security during the development stage and then are overlooked and never properly removed during final implementation. -
Successful Non-Governmental Threat Attribution
Successful Non-Governmental! Threat Attribution, Containment! and Deterrence: A Case Study! Joe St Sauver, Ph.D. ! [email protected] or [email protected]! Internet2 Nationwide Security Programs Manager! November 2nd, 2010, 1:15-2:30 PM, Chancellor I! http://pages.uoregon.edu/joe/attribute-contain-deter/! Disclaimer: The opinions expressed are those of the author and ! do not necessarily represent the opinion of any other party.! I. Introduction! 2! Cyberspace: Anonymous and Undeterred?! • General Keith Alexander, Director of the National Security Agency (DIRNSA), recently commented [1] that in cyberspace:! "" "“It is difficult to deliver an effective response if the ! " "attacker's identity isn't known,” and ! " "“It is unclear if the government's response to cyber ! " "threats and attacks have deterred criminals, ! " "terrorists, or nations.” ! • That's a provocatively framed (if equivocal) assessment, and one worthy of careful consideration given its source. ! 3! Is The Concept of Deterrence Even Relevant to ! Attacks on Private Critical Cyber Infrastructure?! • In pondering that quote, I also note the National Research Council's (NRC's) “Cyber Deterrence Research and Scholarship” question number 39, [2] which asked: ! "" "How and to what extent, if at all, is deterrence applicable! " "to cyber attacks on private companies (especially those that! " "manage U.S. critical infrastructure)? ! • Since the Office of the Director of National Intelligence (ODNI) requested the NRC's inquiry into cyber deterrence, and since General Alexander is now leading the new United States Cyber Command as well as the National Security Agency, it is appropriate to consider these two questions jointly. ! 4! Can We Identify An Example of Successful Attribution and Cyber Deterrence?! • If we are to prove that cyber deterrence is both relevant and possible, and that the difficulties associated with attribution can be overcome, we must be able to point to at least one example of successful attribution and cyber deterrence. -
Antivirus Software Before It Can Detect Them
Computer virus A computer virus is a computer program that can copy itself and infect a computer without the permission or knowledge of the owner. The term "virus" is also commonly but erroneously used to refer to other types of malware, adware, and spyware programs that do not have the reproductive ability. A true virus can only spread from one computer to another (in some form of executable code) when its host is taken to the target computer; for instance because a user sent it over a network or the Internet, or carried it on a removable medium such as a floppy disk, CD, DVD, or USB drive. Viruses can increase their chances of spreading to other computers by infecting files on a network file system or a file system that is accessed by another computer.[1][2] The term "computer virus" is sometimes used as a catch-all phrase to include all types of malware. Malware includes computer viruses, worms, trojan horses, most rootkits, spyware, dishonest adware, crimeware, and other malicious and unwanted software), including true viruses. Viruses are sometimes confused with computer worms and Trojan horses, which are technically different. A worm can exploit security vulnerabilities to spread itself to other computers without needing to be transferred as part of a host, and a Trojan horse is a program that appears harmless but has a hidden agenda. Worms and Trojans, like viruses, may cause harm to either a computer system's hosted data, functional performance, or networking throughput, when they are executed. Some viruses and other malware have symptoms noticeable to the computer user, but many are surreptitious. -
Technical and Legal Approaches to Unsolicited Electronic Mail†
35 U.S.F. L. REV. 325 (2001) Technical and Legal Approaches to Unsolicited Electronic Mail† By DAVID E. SORKIN* “Spamming” is truly the scourge of the Information Age. This problem has become so widespread that it has begun to burden our information infrastructure. Entire new networks have had to be constructed to deal with it, when resources would be far better spent on educational or commercial needs. United States Senator Conrad Burns (R-MT)1 UNSOLICITED ELECTRONIC MAIL, also called “spam,”2 causes or contributes to a wide variety of problems for network administrators, † Copyright © 2000 David E. Sorkin. * Assistant Professor of Law, Center for Information Technology and Privacy Law, The John Marshall Law School; Visiting Scholar (1999–2000), Center for Education and Research in Information Assurance and Security (CERIAS), Purdue University. The author is grateful for research support furnished by The John Marshall Law School and by sponsors of the Center for Education and Research in Information Assurance and Security. Paul Hoffman, Director of the Internet Mail Consortium, provided helpful comments on technical matters based upon an early draft of this Article. Additional information related to the subject of this Article is available at the author’s web site Spam Laws, at http://www.spamlaws.com/. 1. Spamming: Hearing Before the Subcomm. on Communications of the Senate Comm. on Commerce, Sci. & Transp., 105th Cong. 2 (1998) (prepared statement of Sen. Burns), available at 1998 WL 12761267 [hereinafter 1998 Senate Hearing]. 2. The term “spam” reportedly came to be used in connection with online activities following a mid-1980s episode in which a participant in a MUSH created and used a macro that repeatedly typed the word “SPAM,” interfering with others’ ability to participate. -
Adversarial Web Search by Carlos Castillo and Brian D
Foundations and TrendsR in Information Retrieval Vol. 4, No. 5 (2010) 377–486 c 2011 C. Castillo and B. D. Davison DOI: 10.1561/1500000021 Adversarial Web Search By Carlos Castillo and Brian D. Davison Contents 1 Introduction 379 1.1 Search Engine Spam 380 1.2 Activists, Marketers, Optimizers, and Spammers 381 1.3 The Battleground for Search Engine Rankings 383 1.4 Previous Surveys and Taxonomies 384 1.5 This Survey 385 2 Overview of Search Engine Spam Detection 387 2.1 Editorial Assessment of Spam 387 2.2 Feature Extraction 390 2.3 Learning Schemes 394 2.4 Evaluation 397 2.5 Conclusions 400 3 Dealing with Content Spam and Plagiarized Content 401 3.1 Background 402 3.2 Types of Content Spamming 405 3.3 Content Spam Detection Methods 405 3.4 Malicious Mirroring and Near-Duplicates 408 3.5 Cloaking and Redirection 409 3.6 E-mail Spam Detection 413 3.7 Conclusions 413 4 Curbing Nepotistic Linking 415 4.1 Link-Based Ranking 416 4.2 Link Bombs 418 4.3 Link Farms 419 4.4 Link Farm Detection 421 4.5 Beyond Detection 424 4.6 Combining Links and Text 426 4.7 Conclusions 429 5 Propagating Trust and Distrust 430 5.1 Trust as a Directed Graph 430 5.2 Positive and Negative Trust 432 5.3 Propagating Trust: TrustRank and Variants 433 5.4 Propagating Distrust: BadRank and Variants 434 5.5 Considering In-Links as well as Out-Links 436 5.6 Considering Authorship as well as Contents 436 5.7 Propagating Trust in Other Settings 437 5.8 Utilizing Trust 438 5.9 Conclusions 438 6 Detecting Spam in Usage Data 439 6.1 Usage Analysis for Ranking 440 6.2 Spamming Usage Signals 441 6.3 Usage Analysis to Detect Spam 444 6.4 Conclusions 446 7 Fighting Spam in User-Generated Content 447 7.1 User-Generated Content Platforms 448 7.2 Splogs 449 7.3 Publicly-Writable Pages 451 7.4 Social Networks and Social Media Sites 455 7.5 Conclusions 459 8 Discussion 460 8.1 The (Ongoing) Struggle Between Search Engines and Spammers 460 8.2 Outlook 463 8.3 Research Resources 464 8.4 Conclusions 467 Acknowledgments 468 References 469 Foundations and TrendsR in Information Retrieval Vol. -
A Survey on Spam Detection Techniques
ISSN (Online) : 2278-1021 ISSN (Print) : 2319-5940 International Journal of Advanced Research in Computer and Communication Engineering Vol. 3, Issue 12, December 2014 A survey on spam detection techniques Anjali Sharma1, Manisha 2, Dr.Manisha 3 , Dr.Rekha Jain 4 1,2,3,4 Bansthali Vidyapith, Jaipur Campus, India Abstract: Today e-mails have become one of the most popular and economical forms of communication for Internet users. Thus due to its popularity, the e-mail is going to be misused. One such misuse is the posting of unwelcome, unwanted e-mails known as spam or junk e-mails [1]. E-mail spam has various consequences. It reduces productivity, takes extra space in mail boxes, extra time, extend software damaging viruses, and materials that contains potentially harmful information for Internet users, destroy stability of mail servers, and as a result users spend lots of time for sorting incoming mail and deleting unwanted correspondence. So there is a need of spam detection so that its consequences can be reduced [2]. In this paper, we present various spam detection techniques. Keywords: Spam, Spam detection techniques, Email classification I. INTRODUCTION Spam refers to unsolicited commercial email. Also known firewalls; therefore, it is an especially useful way for as junk mail, spam floods Internet users’ electronic spammers. It targets the users when they join any chat mailboxes. These junk mails can contain various types of room to find new friends. It spoils enjoy of people and messages such as pornography, commercial advertising, waste their time also. doubtful product, viruses or quasi legal services [3]. -
Before the FEDERAL COMMUNICATIONS COMMISSION Washington, D.C
Before the FEDERAL COMMUNICATIONS COMMISSION Washington, D.C. 20554 In the Matter of ) Petition of Twilio Inc. for an Expedited ) WT Docket No. 08-7 ) Declaratory Ruling Stating That Messaging Services Are Title II Services ) ) REPLY COMMENTS OF MOBILE FUTURE Mobile Future submits these reply comments opposing the Petition for Expedited Declaratory Ruling of Twilio Inc.1 in the above referenced docket, which seeks counterproductive common carrier regulation of some forms of mobile messaging, but not others. Mobile messaging has become an integral method of communication for American consumers. Consumers rely on messaging not only to stay in touch with relatives and friends, but also to conduct business and receive critical information, such as emergency and medical alerts. Messaging exists as we know it today in part because of the proactive efforts the industry has taken to ensure that the platform remains free from spam and harmful, unwanted communications such as phishing attempts or those that contain malware. Twilio’s Petition to treat messaging as a common carrier service would disrupt those spam filtering efforts, and could cause consumers to be inundated with unwanted communications. Twilio’s Petition similarly fails as a matter of law, and should therefore be rejected. 1 Petition of Twilio, Inc. for an Expedited Declaratory Ruling Stating That Messaging Services Are Title II Services (filed Aug. 28, 2015). I. CONSUMERS RELY ON AN UNPRECEDENTED NUMBER OF OPTIONS TO COMMUNICATE VIA MOBILE TEXT Mobile messaging has quickly become -
Battling the Internet Water Army: Detection of Hidden Paid Posters
Battling the Internet Water Army: Detection of Hidden Paid Posters Cheng Chen Kui Wu Venkatesh Srinivasan Xudong Zhang Dept. of Computer Science Dept. of Computer Science Dept. of Computer Science Dept. of Computer Science University of Victoria University of Victoria University of Victoria Peking University Victoria, BC, Canada Victoria, BC, Canada Victoria, BC, Canada Beijing, China Abstract—We initiate a systematic study to help distinguish on different online communities and websites. Companies are a special group of online users, called hidden paid posters, or always interested in effective strategies to attract public atten- termed “Internet water army” in China, from the legitimate tion towards their products. The idea of online paid posters ones. On the Internet, the paid posters represent a new type of online job opportunity. They get paid for posting comments is similar to word-of-mouth advertisement. If a company hires and new threads or articles on different online communities enough online users, it would be able to create hot and trending and websites for some hidden purposes, e.g., to influence the topics designed to gain popularity. Furthermore, the articles opinion of other people towards certain social events or business or comments from a group of paid posters are also likely markets. Though an interesting strategy in business marketing, to capture the attention of common users and influence their paid posters may create a significant negative effect on the online communities, since the information from paid posters is usually decision. In this way, online paid posters present a powerful not trustworthy. When two competitive companies hire paid and efficient strategy for companies. -
The History of Digital Spam
The History of Digital Spam Emilio Ferrara University of Southern California Information Sciences Institute Marina Del Rey, CA [email protected] ACM Reference Format: This broad definition will allow me to track, in an inclusive Emilio Ferrara. 2019. The History of Digital Spam. In Communications of manner, the evolution of digital spam across its most popular appli- the ACM, August 2019, Vol. 62 No. 8, Pages 82-91. ACM, New York, NY, USA, cations, starting from spam emails to modern-days spam. For each 9 pages. https://doi.org/10.1145/3299768 highlighted application domain, I will dive deep to understand the nuances of different digital spam strategies, including their intents Spam!: that’s what Lorrie Faith Cranor and Brian LaMacchia ex- and catalysts and, from a technical standpoint, how they are carried claimed in the title of a popular call-to-action article that appeared out and how they can be detected. twenty years ago on Communications of the ACM [10]. And yet, Wikipedia provides an extensive list of domains of application: despite the tremendous efforts of the research community over the last two decades to mitigate this problem, the sense of urgency ``While the most widely recognized form of spam is email spam, the term is applied to similar abuses in other media: instant remains unchanged, as emerging technologies have brought new messaging spam, Usenet newsgroup spam, Web search engine spam, dangerous forms of digital spam under the spotlight. Furthermore, spam in blogs, wiki spam, online classified ads spam, mobile when spam is carried out with the intent to deceive or influence phone messaging spam, Internet forum spam, junk fax at scale, it can alter the very fabric of society and our behavior.