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Prospects, Leads, and Subscribers
PAGE 2 YOU SHOULD READ THIS eBOOK IF: You are looking for ideas on finding leads. Spider Trainers can help You are looking for ideas on converting leads to Marketing automation has been shown to increase subscribers. qualified leads for businesses by as much as 451%. As You want to improve your deliverability. experts in drip and nurture marketing, Spider Trainers You want to better maintain your lists. is chosen by companies to amplify lead and demand generation while setting standards for design, You want to minimize your list attrition. development, and deployment. Our publications are designed to help you get started, and while we may be guilty of giving too much information, we know that the empowered and informed client is the successful client. We hope this white paper does that for you. We look forward to learning more about your needs. Please contact us at 651 702 3793 or [email protected] . ©2013 SPIDER TRAINERS PAGE 3 TAble Of cOnTenTS HOW TO cAPTure SubScriberS ...............................2 HOW TO uSe PAiD PrOGrAMS TO GAin Tipping point ..................................................................2 SubScriberS ...........................................................29 create e mail lists ...........................................................3 buy lists .........................................................................29 Pop-up forms .........................................................4 rent lists ........................................................................31 negative consent -
Towards Mitigating Unwanted Calls in Voice Over IP
FACULDADE DE ENGENHARIA DA UNIVERSIDADE DO PORTO Towards Mitigating Unwanted Calls in Voice Over IP Muhammad Ajmal Azad Programa Doutoral em Engenharia Electrotécnica e de Computadores Supervisor: Ricardo Santos Morla June 2016 c Muhammad Ajmal Azad, 2016 Towards Mitigating Unwanted Calls in Voice Over IP Muhammad Ajmal Azad Programa Doutoral em Engenharia Electrotécnica e de Computadores June 2016 I Dedicate This Thesis To My Parents and Wife For their endless love, support and encouragement. i Acknowledgments First and foremost, I would like to express my special gratitude and thanks to my advisor, Professor Dr. Ricardo Santos Morla for his continuous support, supervision and time. His suggestions, advice and criticism on my work have helped me a lot from finding a problem, design a solution and analyzing the solution. I am forever grateful to Dr. Morla for mentoring and helping me throughout the course of my doctoral research.. I would like to thanks my friends Dr. Arif Ur Rahman and Dr. Farhan Riaz for helping in understanding various aspects of research at the start of my Ph.D, Asif Mohammad for helping me in coding with Java, and Bilal Hussain for constructive debate other than academic research and continuous encouragements in the last three years. Of course acknowledgments are incomplete without thanking my parents, family members and loved ones. I am very thankful to my parents for spending on my education despite limited resources. They taught me about hard work, make me to study whenever I run away, encourage me to achieve the goals, self-respect and always encourage me for doing what i want. -
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. -
Technical Means to Combat Spam in the Voip Service
Section Four Technical Means to Combat Spam in the VoIP Service Spam refers in general to any unsolicited communication. Spam will also become one of the serious problems for multimedia communication in the near future. Spam in multimedia communication is referred to as SIP spam or SPIT (Spam over Internet Telephony), where SIP is used to manage the session between two end users. In this paper, the types of SIP spam are introduced and various pragmatic solutions applicable to combat the SIP spams are described including content filtering, white list, black list, and the reputation system. Finally, the detailed operation and principles for the authenticated identity in SIP header, which is a prerequisite for the solutions above, are also described. The possible solutions to combat the SIP spasm have been listed and the background technology to those solutions, an authenticated identity between the domains, is also introduced. Heung Youl Youm (PhD) Professor, Soonchunhyang University, South Korea Rapporteur, Q.9/SG17, ITU-T [email protected] 1 Introduction IP telephony is known as a technology that allows standard telephone voice signals to be compressed into data packets for transmission over the Internet or other IP network. The protocols used in carrying the voice signals over the IP networks are commonly referred to as Voice over IP (VoIP). The spam problem in email and instant messaging (IM) makes the email or the IM users to trust less of these tools and consequently reduce their usage. While the security mechanisms for the IP telephony are being studied, the spam problem in VoIP has not been studied extensively yet. -
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]. -
Presentations Made by Senders
SES ���� ��� � �� � � � � � � � ������������� DomainKeys ��������� SPF ��������������������� ���������� ����������������� ������������������������������������������������ Contents Introduction 3 Deployment: For Email Receivers 6 Audience 3 Two Sides of the Coin 6 How to Read this White Paper 3 Recording Trusted Senders Who Passed Authentication 6 A Vision for Spam-Free Email 4 Whitelisting Incoming Forwarders 6 The Problem of Abuse 4 What To Do About Forgeries 6 The Underlying Concept 4 Deployment: For ISPs and Enterprises 7 Drivers; or, Who’s Buying It 4 Complementary considerations for ISPs 7 Vision Walkthrough 5 Deployment: For MTA vendors 8 About Sender Authentication 8 Which specification? 8 An Example 8 Conformance testing 8 History 8 Perform SRS and prepend headers when forwarding 8 How IP-based Authentication Works 9 Add ESMTP support for Submitter 8 The SPF record 9 Record authentication and policy results in the headers 8 How SPF Classic Works 9 Join the developers mailing list 8 How Sender ID works 9 Deployment: For MUA vendors 9 How Cryptographic Techniques Work 0 Displaying Authentication-Results 9 Using Multiple Approaches Automatic switching to port 587 9 Reputation Systems Deployment: For ESPs 20 Deployment: For Email Senders 2 Don’t look like a phisher! 20 First, prepare. 2 Delegation 20 Audit Your Outbound Mailstreams 2 Publish Appropriately 20 Construct the record 2 Deployment: For Spammers 2 Think briefly about PRA and Mail-From contexts. 3 Two Types of Spammers 2 Test the record, part 3 Publish SPF and sign with DomainKeys. 2 Put the record in DNS 3 Stop forging random domains. 2 Test the record, part 2 4 Buy your own domains. 2 Keep Track of Violations 4 Reuse an expired domain. -
Secure Email Gateway - Market Quadrant 2016 ∗
. The Radicati Group, Inc. Palo Alto, CA 94301 . Phone: (650) 322-8059 . www.radicati.com . THE RADICATI GROUP, INC. Secure Email Gateway - Market Quadrant 2016 ∗ ......... An Analysis of the Market for Secure Email Gateway Solutions, Revealing Top Players, Trail Blazers, Specialists and Mature Players. November 2016 SM ∗ Radicati Market Quadrant is copyrighted November 2016 by The Radicati Group, Inc. Reproduction in whole or in part is prohibited without expressed written permission of the Radicati Group. Vendors and products depicted in Radicati Market QuadrantsSM should not be considered an endorsement, but rather a measure of The Radicati Group’s opinion, based on product reviews, primary research studies, vendor interviews, historical data, and other metrics. The Radicati Group intends its Market Quadrants to be one of many information sources that readers use to form opinions and make decisions. Radicati Market QuadrantsSM are time sensitive, designed to depict the landscape of a particular market at a given point in time. The Radicati Group disclaims all warranties as to the accuracy or completeness of such information. The Radicati Group shall have no liability for errors, omissions, or inadequacies in the information contained herein or for interpretations thereof. Secure Email Gateway - Market Quadrant 2016 TABLE OF CONTENTS RADICATI MARKET QUADRANTS EXPLAINED .................................................................................. 2 MARKET SEGMENTATION – SECURE EMAIL GATEWAYS ................................................................. -
Account Administrator's Guide
ePrism Email Security Account Administrator’s Guide - V10.4 4225 Executive Sq, Ste 1600 Give us a call: Send us an email: For more info, visit us at: La Jolla, CA 92037-1487 1-800-782-3762 [email protected] www.edgewave.com © 2001—2016 EdgeWave. All rights reserved. The EdgeWave logo is a trademark of EdgeWave Inc. All other trademarks and registered trademarks are hereby acknowledged. Microsoft and Windows are either registered trademarks or trademarks of Microsoft Corporation in the United States and/or other countries. Other product and company names mentioned herein may be the trademarks of their respective owners. The Email Security software and its documentation are copyrighted materials. Law prohibits making unauthorized copies. No part of this software or documentation may be reproduced, transmitted, transcribed, stored in a retrieval system, or translated into another language without prior permission of EdgeWave. 10.4 Contents Chapter 1 Overview 1 Overview of Services 1 Email Filtering (EMF) 2 Archive 3 Continuity 3 Encryption 4 Data Loss Protection (DLP) 4 Personal Health Information 4 Personal Financial Information 5 Document Conventions 6 Other Conventions 6 Supported Browsers 7 Reporting Spam to EdgeWave 7 Contacting Us 7 Additional Resources 7 Chapter 2 Portal Overview 8 Navigation Tree 9 Work Area 10 Navigation Icons 10 Getting Started 11 Logging into the portal for the first time 11 Logging into the portal after registration 12 Changing Your Personal Information 12 Configuring Accounts 12 Chapter 3 EdgeWave Administrator -
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.