A Dynamic Approach to Spam Filtering

Total Page:16

File Type:pdf, Size:1020Kb

A Dynamic Approach to Spam Filtering International Journal of Pure and Applied Mathematics Volume 120 No. 6 2018, 179-200 ISSN: 1314-3395 (on-line version) url: http://www.acadpubl.eu/hub/ Special Issue http://www.acadpubl.eu/hub/ A DYNAMIC APPROACH TO SPAM FILTERING Indumathi.J 1, Gitanjali.J2 1Department of Information Science and Technology, Anna University,Chennai 600 025. Tamilnadu,India. 2School of Information Technology and Engineering VIT University, Vellore-632014, Tamil Nadu, India *Corresponding author E-mail: [email protected] July 13, 2018 Abstract Spam, the unsolicited guest in our inbox is showing in- credible proliferation in the recent period. Spam is encoun- tered by every internet user at one point or the other. Spam- mers are growing leaps and bounds and they tirelessly get equipped with the latest technologies; forcing the research community to devise new anti-spam techniques. The email service providers in spite of providing filters, find that it is challenging to keep up with the shifting sands of spam technology. Hence, development of anti-spam filtering tech- niques should be perpetually kept in stride with appropriate outcome solutions. The algorithms frequently, determine spams using statistical or heuristic schemes. The paper pro- poses a system with improved facilities that can overcome all the limitations of the existing system. The proposed Fac- tors Hyperbolic Tree (FHT) based algorithm merged with the Bayesian algorithm (unlike the lexical matching algo- rithms), handles spam filtering in a dynamic environment by considering various relevant factors like age, temperature 1 179 International Journal of Pure and Applied Mathematics Special Issue etc., A decision is made normally by considering a certain amount of factors along with specific reasoning along with the keywords. To express the relationship among decisions, factors objects, a FHT is used which can describe every ob- ject of interest with related factors. The outcomes of the experimentations show this practice professionally filters E- mail, along with enhancement of the filtering degree of pre- cision. In this paper, the proposed FHT algorithm, which, filters e-mail by conditional factors instead of word matching is enhanced. The enhance FHT is tested and proved to be apt for semantic analysis and decision supporting field. The results of the experiments, show that the proposed enhanced technique can more proficiently filter E-mail, and improve the filtering degree of precision, than the FHT algorithm. Experimentally, the enhance FHT is a more practical tech- nique to be used in anti-spam filters; and it outperforms the previous techniques, thereby proving it is more robust. Key Words:Spam,Ranked Term Frequency,Factors Hy- perbolic Tree,Bayesian algorithm 1 INTRODUCTION In the hands of a cybercriminal, spam not only improves subjective gains; it also opens the Pandoras Box, leading to pilfering a person’s identity or sell contraband or stalk preys or unnerve operations with malicious programs or disseminate malicious contents. When the entire planet is strenuous to realize the purpose in lifetime by making a difference in all the line of work, the spam flip-flops everything with its payloads. Spam, the unso- licited bulk mail is usually sent to several recipients, with payloads of virus and Trojans. Let us take a quick look at the significance, history of email spams and filtering techniques used. 1.1 HISTORY OF EMAIL SPAM The first documented spam is a note, promoting the availability of a new model of Digital Equipment Corporation (DEC) comput- ers; and was sent by Gary Thuerk to 393 recipients on ARPANET in 1978.His assistant, Carl Gartley, wrote a single mass e-mail for which the feedback from the net community was violently negative. 2 180 International Journal of Pure and Applied Mathematics Special Issue From the USENET, the world’s biggest online conferencing system, mailing, the computer nerds (who were big fans of Monty Python) recognized the mass mailing as spam and the name caught on. Af- ter this major recorded instance, many spam incidents have made quantum jumps. This unsolicited email was called spam. Table 1 in annexure gives a quick view of the spam timeline. 1.2 WHY DO WE CALL UNWANTED EMAILS ”SPAM”? The geneses of the term is hilarious. The word originates from Monty Pythons famous Spam sketch. It was the script of that spam skit the inexorable spam, spam, spam, spam, and the way that unwanted mail just throw up out of the PC the email connection was forged by the Monty Python sketch. As the scene develops, you can see why this outline is a great analogy for uninvited and unwelcome email. Till date, the term spam is used to indicate the uninvited junk mail which makes up around 80 to 85% of email. Likewise, the anoraks who tenanted the PC world were ardent Python fans. Monty Python sketch happens in a spoon cafe with a menu in which every single dish features spam. 1.3 MOTIVATION Surf-Controls Anti-Spam Prevalence Study (2002) points out that there are many reasons unsolicited commercial e-mail is such a prob- lem: Consumer perception: for many people the accessing of e-mail still• represents a bit of a struggle especially at peak traffic times, and network congestion can make it an laborious task to simply download your e-mail.[Surf Control ”AntiSpam Prevalence Study” (2002) (last accessed 19 June 2005)] Cost shifting: The inexpensiveness of an e-mail is the main reason• for its soaring utility. From the advertisers perspective, the price of sending hundreds or thousands of messages per hour, is even more economical. But the costs of receiving it ranging from the long-distance charges or per-minute access charges for dialing into an Internet service provider (ISP) to the cost of connectivity and disk storage space at the ISP and the inevitable administrative 3 181 International Journal of Pure and Applied Mathematics Special Issue costs when the incoming flood outstrips capacity, results in system outages. These costs can be quite substantial. Here cost of oppor- tunities is possible lost because of system outages, delayed services, and overflowing mailboxes. .[Surf Control ”AntiSpam Prevalence Study” (2002) (last accessed 19 June 2005)] Fraud: In response to several surveys it is found that the consumers• hate to receive spams and, many ISPs have taken a variety of costly steps to reduce the volume of spam transmitted through their systems, including the build-up of extra capacity to accommodate the demands of filtering and storing. Global implications: Email is a wonderful tool of professional and• personal communication; there are even more far-reaching po- tentials of e-mail that may be lost if the medium’s functionality and utility get destroyed by the proliferation of junk e-mail. The In- ternet is an incredible tool for spreading information critical to the development of freedom and democracy around the world. .[Surf Control ”Anti-Spam Prevalence Study” (2002) (last accessed 19 June 2005)] Harm to the marketplace: The email message from the spam- mers• travels to million people, via numerous other systems en route to its destinations, once again shifting cost away from the origina- tor. The carriers in between precipitously are bearing the burden of carrying advertisements for the spammer.[Surf Control ”Anti-Spam Prevalence Study” (2002) (last accessed 19 June 2005)] Theft: The sending of spam results in one party’s imposing costs• on another, against the party’s will and without permission. Some have called unsolicited e-mail a form of postage-due market- ing or a form of theft. .[Surf Control ”AntiSpam Prevalence Study” (2002) (last accessed 19 June 2005)] This paper is organized as follows: In the subsequent section 2, the perils of spam are briefly reviewed and the relationship of spam with privacy and security are presented in Section 3. Possible solutions and antispam techniques are dealt in the sections 4 and 5.The notions of Factor Hyperbolic Tree, Ranked Term Frequency [RTF] are explained in section 6, 7.The results and analysis and the conclusions are given in Sections 8 and 9 respectively. 4 182 International Journal of Pure and Applied Mathematics Special Issue 2 WHY SPAM IS A PROBLEM? The most hostile of spam e-mails is that, these are not only as- saulting the users without their assent, but also invades the e-mail space of the user, discarding the network capacity and consumes prolonged time in checking and deleting the spam mails. To look at the tip of the iceberg, a few issues arising out of spams are dis- cussed. 2.1 DESTRUCTIONS CAUSED BY SPAM. Direct damages caused by spams are Loss of productivity and Use of corporate network resources like bandwidth, disk space. The indirect damages, like the risk of shifting spam accountability from one person to another or domain, are being recognized as spammers by the servers that have been sent spam deprived of knowing it and accidently deleting important valid messages erroneously when eradicating spam. Spam by propagation also leads to dangers like malware which does not have its own means of propagation: Trojans, key loggers, backdoors etc. There are cases wherein criminals, sent emails with attachments enclosing malware, and utilized it to access information stored on your computer. This known as ’invoice’ email scam steals bank details as the malicious software logs your online banking details, along with other financial information, and sends it to criminals. Trolls (http://www.digitalethics.org/essays/end-anonymous - emails) are individuals who hide their identity and behind an anonymous email address, derive pleasure in create an atmosphere of hate and discontent ranging from infrequent off-color remarks to full-blown daily bullying with far-reaching and sometimes tragic consequences. Just this year, a young girl committed suicide after being cyberbul- lied by anonymous posters on the site www.ask.fm.
Recommended publications
  • 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.
    [Show full text]
  • Review on Email Spam Filtering Techniques
    International Journal of Scientific Engineering and Applied Science (IJSEAS) – Volume-2, Issue-3, March 2016 ISSN: 2395-3470 www.ijseas.com Review on Email Spam Filtering Techniques Shiva Sharma1, U. Dutta 2 Computer Science and Engineering Department, Maharana Pratap College of technology Putli Ghar Road, Near Collectorate, Gwalior-474006, Madhya Pradesh, India ABSTRACT- In this paper we present email online messages, blogs, forums, whatsapp and spam filtering and email authorship instant messaging services. Among all CMC, identification. Electronic mail is used by email has remained a key source of written millions of people to communicate around the communication, especially in the last few years. world daily and is a mission-critical Due to its salient features, it is the preferred application for many businesses. Over the last source of written communication for almost 10 years, unsolicited bulk email has become a every population (a part from illiterate) major problem for email users called senders connected to the Internet. It is a very quick, and receivers. And the recent years spam asynchronous written communication channel became as a big problem of internet and that is used for various purposes ranging from electronic communication known as users. formal to informal communication. Email There is developed lot of techniques to fight messages can be sent to a single receiver or them. We presents the overview of existing e- broadcasted to groups known as users. An email mail spam filtering methods is given. The message can reach to a number of receivers classification, valuation and juxtaposition of simultaneously and instantly at singe time. traditional and learning based methods are These days, the majority of individuals even provided.
    [Show full text]
  • 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.
    [Show full text]
  • Subject Line Labeling As a Weapon Against Spam
    Subject Line Labeling As a Weapon Against Spam A CAN-SPAM Act Report to Congress June 2005 Federal Trade Commission Deborah Platt Majoras, Chairman Orson Swindle, Commissioner Thomas B. Leary, Commissioner Pamela Jones Harbour, Commissioner Jon Leibowitz, Commissioner Table of Contents Executive Summary . i I. Introduction and Overview . 1 II. Subject Line Labeling Laws in the States and in Other Countries . 3 A. State Subject Line Labeling Laws . 3 1. Objectives of State Subject Line Labeling Requirements . 5 2. Enforcement of State Subject Line Labeling Requirements . 5 3. Effectiveness of State Subject Line Labeling Requirements . 6 B. Subject Line Labeling Laws in Other Countries . 7 III. The Commission Recommends Against Mandatory Subject Line Labeling . 9 A. Mandatory Subject Line Labeling Is Likely Not an Effective Tool For ISPs To Block and Filter Spam . 10 1. Mandatory subject line labeling will not enhance ISPs’ current techniques for combating spam . 10 2. Mandatory subject line labeling is an ineffective tool for ISPs because spammers will not comply with a labeling requirement . 13 B. Practical and Technological Concerns with Subject Line Labeling Requirements . 15 C. Mandatory Subject Line Labeling Would Not Strengthen Anti-Spam Law Enforcement . 17 IV. Conclusion . 18 Appendix 1: List of Interviews Appendix 2: Part III of the Commission’s National Do Not Email Registry Report Concurring Statement of Commissioner Pamela Jones Harbour Dissenting Statement of Commissioner Jon Leibowitz Executive Summary Executive Summary The Federal Trade Commission (the “FTC” or “Commission”) submits this Report pursuant to Section 11(2) of the Controlling the Assault of Non-Solicited Pornography and Marketing Act of 2003 (the “CAN-SPAM Act”), 15 U.S.C.
    [Show full text]
  • Amending Can-Spam & Aiming Toward a Global Solution
    COPYRIGHT © 2004 TRUSTEES OF BOSTON UNIVERSITY. THIS VERSION DOES NOT CONTAIN PARAGRAPH/PAGE REFERENCES. PLEASE CONSULT THE PRINT OR ON- LINE DATABASE VERSIONS FOR PROPER CITATION INFORMATION NOTE SPAM IN A BOX: AMENDING CAN-SPAM & AIMING TOWARD A GLOBAL SOLUTION ∗ Erika Hallace KikuchiTP PT TABLE OF CONTENTS I. INTRODUCTION...................................................................................... 56 II. THE SPAM PROBLEM ............................................................................. 58 A. Spam Statistics............................................................................... 58 B. The Spam Monster......................................................................... 60 III. THE HISTORY OF ANTI-SPAM TACTICS ................................................. 62 A. Self-Regulation and Technical Tactics to Combat Spam............... 62 B. Various Legal Tactics Used to Combat Spam ............................... 63 C. Attempts at Federal Spam Legislation Prior to the 108th Congress........................................................................................ 67 IV. THE CURRENT FEDERAL LEGISLATION ................................................. 69 A. The 108th Congress....................................................................... 69 1. Bills Introduced, But Not Passed............................................. 69 2. The CAN-SPAM Act of 2003 ................................................. 71 3. The Selection of CAN-SPAM ................................................. 75 B. Problems
    [Show full text]
  • Ljubljana, 2015 Zbornik Digitalna Forenzika, Seminarske Naloge 2014/2015
    2014/2015 Ljubljana, 2015 Zbornik Digitalna forenzika, Seminarske naloge 2014/2015 Editors: Andrej Brodnik, Luka Krsnik, Anˇze Mikec, Nejc Novak, ˇstudenti Ljubljana : Univerza v Ljubljani, Fakulteta za raˇcunalniˇstvo in informatiko, 2015. c These proceedings are for internal purposes and under copyright of University of Ljubljana, Faculty of Computer and Information Science. Any redistribution of the contents in any form is prohibited. All rights reserved. Kazalo 1 Povzetki (abstracts) 4 1.1 Distributed filesystem forensics: XtreemFS as a case study . .4 1.2 Pregled "Asset Risk Scoring in Enterprise Network with Mutually Reinforced Reputation Propagation" . .4 1.3 Pregled analiz in gradnja kriminalnih mreˇz . .4 1.4 Uspeˇsnostkampanj z nezaˇzelenopoˇstoin botneti . .5 1.5 Forenziˇcnaanaliza z DNSSEC . .5 1.6 Preiskovanje napadov povezanih z izvornimi vrati 0 . .5 1.7 Detecting NAT gateways and differenting host devices behind NAT for purposes of digital forensic investigations . .6 1.8 Steganografija v LTE (Long Term Evolution) sistemi . .6 1.9 Overview of PeerShark and other software for detecting peer-to-peer botnets . .6 1.10 Cloud Forensics: iCloud . .6 1.11 Towards a Forencsic-Aware Database Solution: Using a secured Database Replication Protocol and Transaction Management for Digital Investigations . .7 1.12 Prednosti in slabosti ˇzive in mrtve forenziˇcneanalize . .7 1.13 VMI-PL: Jezik za nadzor navideznih platform z vpogledom v navidezne stroje . .7 1.14 Impacts of increasing volume of digital forensics data: A survey and future research chal- lenges . .8 1.15 Video Evidence as Used in Court of Law and its Source Identification . .8 1.16 Pridobivanje skritih sporoˇciliz steganografskih slik .
    [Show full text]
  • Email Spam Filter Using Machine Learning
    Email Spam Filter using Machine Learning Research Manual Author: Hazel Murphy Student ID: C00230058 Project Supervisor: James Egan Date: Friday 13th November 2020 Email Spam Filter using Machine Learning Research Manual Abstract Emails are used daily worldwide. It is a method of exchanging messages between people using electronic devices. E-mail is one of the most secure methods for online communication and transferring data or messages through the internet. Around, 293.6 billion emails were sent per day in 2019. (How Many Emails Are Sent per Day: The Startling Truth [2020], 2020). However, as emails become more popular, spam has become a major problem on the internet. To try and stop the spread of spam, numerous techniques can be performed. These include spam filtering techniques. According to Statista, spam messages accounted for 53.95 percent of e-mail traffic in March 2020 (Spam statistics: spam e-mail traffic share 2019 | Statista, 2020). Discussed in the paper will be the different types of spam for example phishing, malspam, and advance-fee scams. Also, we will investigate the effectiveness of several spam filtering techniques and technologies. Our analysis was performed by simulating email traffic under different conditions. We show that algorithm-based spam filters perform best at server level and aim to justify that naïve Bayesian filters are the most appropriate for filtering at user level compared to support vector, random forest, and logistic regression. P a g e 2 | 58 Email Spam Filter using Machine Learning Research Manual
    [Show full text]
  • 1972 Can Be Made with the Use of a Blue Box and a Plastic Toy Whistle That Comes in Cap’N Crunch Cereal Boxes
    History 329/SI 311/RCSSCI 360 Computers and the Internet: A global history The Dark Side: Hackers, Spam, and Black Markets Today } Revisions to the syllabus and end of the course } Hackers } Spam } Vandalism on Wikipedia } Black markets on “darknets” } Next time Proposed changes to syllabus } April 7: session on China } Guest lecturer Silvia Lindtner } Last class April 12 — NO CLASS April 14 } No final exam — 1250-1500 word essay instead } Why does history matter? How has learning the history of computers changed your view of the present? } Adjustment to percentages for final grade } Midterms 1 and 2 – each 30 pct of grade (was 20) } Final essay — 10 pct of grade Hackers Tweet this John Draper, A.K.A. “Captain Crunch,” discovers that free phone calls 1972 can be made with the use of a blue box and a plastic toy whistle that comes in Cap’n Crunch cereal boxes. The whistle duplicates a 2600-hertz tone to unlock AT&T’s phone network. 1979 The first computer “worm” is created at Xerox’s Palo Alto Research Center. The program is meant to make computers more efcient, but later hackers modify worms into computer viruses that destroy or alter data. source (all blue slides): Dell Computer Captain Crunch (John Draper) } “Phreaking” } Built “blue boxes” } Connected with Homebrew computer club } 2600 magazine (1984-) PC hackers (1975-present) } Structure: distributed computing } Individual PCs in homes, offices } PC hacker culture } Far larger, highly fragmented group } Time of day no longer important } Mainframe and mini hackers: usually nighttime, to
    [Show full text]
  • Fakhraei Umd 0117E 18330.Pdf (5.635Mb)
    ABSTRACT Title of dissertation: COLLECTIVE MULTI-RELATIONAL NETWORK MINING Seyed Shobeir Fakhraei, Doctor of Philosophy, 2017 Dissertation directed by: Professor Lise Getoor Department of Computer Science Our world is becoming increasingly interconnected, and the study of networks and graphs are becoming more important than ever. Domains such as biological and pharmaceutical networks, online social networks, the World Wide Web, recom- mender systems, and scholarly networks are just a few examples that include explicit or implicit network structures. Most networks are formed between different types of nodes and contain different types of links. Leveraging these multi-relational and heterogeneous structures is an important factor in developing better models for these real-world networks. Another important aspect of developing models for network data to make predictions about entities such as nodes or links, is the connections between such entities. These connections invalidate the i.i.d. assumptions about the data in most traditional machine learning methods. Hence, unlike models for non-network data where predictions about entities are made independently of each other, the inter-connectivity of the entities in networks should cause the inferred in- formation about one entity to change the models belief about other related entities. In this dissertation, I present models that can effectively leverage the multi- relational nature of networks and collectively make predictions on links and nodes. In both tasks, I empirically show the importance of considering the multi-relational characteristics and collective predictions. In the first part, I present models to make predictions on nodes by leveraging the graph structure, links generation sequence, and making collective predictions.
    [Show full text]
  • Clustering Spam Domains and Hosts: Anti-Spam Forensics with Data Mining
    CLUSTERING SPAM DOMAINS AND HOSTS: ANTI-SPAM FORENSICS WITH DATA MINING by CHUN WEI ALAN P. SPRAGUE, COMMITTEE CHAIR ANTHONY SKJELLUM CHENGCUI ZHANG KENT R. KERLEY RANDAL VAUGHN A DISSERTATION Submitted to the graduate faculty of The University of Alabama at Birmingham, in partial fulfillment of the requirements for the degree of Doctor of Philosophy BIRMINGHAM, ALABAMA 2010 Copyright by Chun Wei 2010 TABLE OF CONTENTS Page ABSTRACT ....................................................................................................................... iv LIST OF TABLES ...............................................................................................................v LIST OF FIGURES ........................................................................................................... vi LIST OF ABBREVIATIONS .......................................................................................... viii CHAPTER 1 INTRODUCTION ...........................................................................................................1 1.1 Current Spam Trend....................................................................................................1 1.2 Protective Mechanisms of Spammers ........................................................................2 1.2.1 Word Obfuscation ...............................................................................................2 1.2.2 Botnet ..................................................................................................................3 1.2.3 Spam
    [Show full text]
  • Research Report Prepare for Voip Spam
    Eindhoven University of Technology MASTER Prepare for VoIP Spam Baaijens, M.W. Award date: 2008 Link to publication Disclaimer This document contains a student thesis (bachelor's or master's), as authored by a student at Eindhoven University of Technology. Student theses are made available in the TU/e repository upon obtaining the required degree. The grade received is not published on the document as presented in the repository. The required complexity or quality of research of student theses may vary by program, and the required minimum study period may vary in duration. General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain EINDHOVEN UNIVERSITY OF TECHNOLOGY (TUE) Department of Mathematics and Computer Science and SWISSCOM AG Network Development Prepare for VoIP Spam by Mark Baaijens (m.w.baaijens 'at' gmail.com) “As in many computer security issues, the only way to make sure that you never receive a spam message is to never connect your computer to the Internet. Unfortunately, the unconnected user never receives the many benefits of the most important communications application for business either.” [25] Supervisors: Bart Jacobs, TUE, Eindhoven, the Netherlands Robert Muralt, Swisscom AG, Bern, Switzerland Version 2, 16 November 2007 Research Report Prepare for VoIP Spam Preface From 26 February 2007 until 27 October 2007 I lived in Bern (Switzerland) and worked for Swisscom.
    [Show full text]
  • A Brief History of Email
    A BRIEF HISTORY OF EMAIL 1971 1976 1978 1982 1982 Computer engineer Queen Elizabeth II The first electronic The word “email” is The first ever smiley Ray Tomlinson sends becomes the first head advertisement is sent first used. “emoticon” is invented the first electronic mail of state to send an over a network of by Scott Fahlman. message. electronic mail government and message. university computers. Email SEND : ) 1997 1997 1997 1996 1989 Warner Bros. releases Microsoft Outlook is Microsoft buys Hotmail A few companies Elwood Edwards You’ve Got Mail which released. for about $400 million. including the fledgling records the iconic AOL grosses $250 million at Hotmail begin to offer “Welcome,” “Files’s the box office. free, use-anywhere, done,” “Goodbye,” & internet email. “You’ve got mail!” 1 1998 1999 2003 2004 2004 The word “spam” is A fraudulent email George W. Bush signs LOL and other Internet Federal Trade officially recognised in claims that Bill Gates into law the CAN-SPAM acronyms are officially Commission codifies the Oxford English plans to share his Act, the US’ first recognised in the email spam laws. Dictionary. wealth with Internet national standards for Oxford English users starts to sending commercial Dictionary. circulate. It is emails. SPAM. shared by millions! LOL! Aa $$$ SPAM. 2008 2007 2007 2005 2004 Presidential candidate Anti-phishing security Google makes Gmail SPF, the first Multimedia emails are Barack Obama protocol DKIM is available to the general technology that introduced after the compiles a database adopted by the Internet public worldwide. verifies email senders’ MMS World Congress of over 13 million email Engineering Task identities, is in Vienna.
    [Show full text]