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Trendmicro™ Hosted Email Security
TrendMicro™ Hosted Email Security Best Practice Guide Trend Micro Incorporated reserves the right to make changes to this document and to the products described herein without notice. The names of companies, products, people, characters, and/or data mentioned herein are fictitious and are in no way intended to represent any real individual, company, product, or event, unless otherwise noted. Complying with all applicable copyright laws is the responsibility of the user. Copyright © 2016 Trend Micro Incorporated. All rights reserved. Trend Micro, the Trend Micro t-ball logo, and TrendLabs are trademarks or registered trademarks of Trend Micro, Incorporated. All other brand and product names may be trademarks or registered trademarks of their respective companies or organizations. No part of this publication may be reproduced, photocopied, stored in a retrieval system, or transmitted without the express prior written consent of Trend Micro Incorporated. Authors : Michael Mortiz, Jefferson Gonzaga Editorial : Jason Zhang Released : June 2016 Table of Contents 1 Best Practice Configurations ................................................................................................................................. 8 1.1 Activating a domain ....................................................................................................................................... 8 1.2 Adding Approved/Blocked Sender ................................................................................................................ 8 1.3 HES order -
Comodo Antispam Gateway Software Version 1.5
Comodo Antispam Gateway Software Version 1.5 Administrator Guide Guide Version 1.5.082412 Comodo Security Solutions 525 Washington Blvd. Jersey City, NJ 07310 Comodo Antispam Gateway - Administrator Guide Table of Contents 1 Introduction to Comodo Antispam Gateway........................................................................................................................... 4 1.1 Release Notes............................................................................................................................................................. 5 1.2 Purchasing License .................................................................................................................................................... 6 1.3 Adding more Users, Domains or Time to your Account .................................................................................................6 1.4 License Information................................................................................................................................................... 10 2 Getting Started................................................................................................................................................................... 13 2.1 Incoming Filtering Configuration ................................................................................................................................ 13 2.1.1 Configuring Your Mail Server.................................................................................................................................. -
A Survey of Learning-Based Techniques of Email Spam Filtering
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Unitn-eprints Research A SURVEY OF LEARNING-BASED TECHNIQUES OF EMAIL SPAM FILTERING Enrico Blanzieri and Anton Bryl January 2008 (Updated version) Technical Report # DIT-06-056 A Survey of Learning-Based Techniques of Email Spam Filtering Enrico Blanzieri, University of Trento, Italy, and Anton Bryl University of Trento, Italy, Create-Net, Italy [email protected] January 11, 2008 Abstract vertising pornography, pyramid schemes, etc. [68]. The total worldwide financial losses caused by spam Email spam is one of the major problems of the to- in 2005 were estimated by Ferris Research Analyzer day’s Internet, bringing financial damage to compa- Information Service at $50 billion [31]. nies and annoying individual users. Among the ap- Lately, Goodman et al. [39] presented an overview proaches developed to stop spam, filtering is an im- of the field of anti-spam protection, giving a brief portant and popular one. In this paper we give an history of spam and anti-spam and describing major overview of the state of the art of machine learn- directions of development. They are quite optimistic ing applications for spam filtering, and of the ways in their conclusions, indicating learning-based spam of evaluation and comparison of different filtering recognition, together with anti-spoofing technologies methods. We also provide a brief description of and economic approaches, as one of the measures other branches of anti-spam protection and discuss which together will probably lead to the final victory the use of various approaches in commercial and non- over email spammers in the near future. -
Detecting Phishing in Emails Srikanth Palla and Ram Dantu, University of North Texas, Denton, TX
1 Detecting Phishing in Emails Srikanth Palla and Ram Dantu, University of North Texas, Denton, TX announcements. The third category of spammers is called Abstract — Phishing attackers misrepresent the true sender and phishers. Phishing attackers misrepresent the true sender and steal consumers' personal identity data and financial account steal the consumers' personal identity data and financial credentials. Though phishers try to counterfeit the websites in account credentials. These spammers send spoofed emails and the content, they do not have access to all the fields in the lead consumers to counterfeit websites designed to trick email header. Our classification method is based on the recipients into divulging financial data such as credit card information provided in the email header (rather than the numbers, account usernames, passwords and social security content of the email). We believe the phisher cannot modify numbers. By hijacking brand names of banks, e-retailers and the complete header, though he can forge certain fields. We credit card companies, phishers often convince the recipients based our classification on three kinds of analyses on the to respond. Legislation can not help since a majority number header: DNS-based header analysis, Social Network analysis of phishers do not belong to the United States. In this paper we and Wantedness analysis. In the DNS-based header analysis, present a new method for recognizing phishing attacks so that we classified the corpus into 8 buckets and used social the consumers can be vigilant and not fall prey to these network analysis to further reduce the false positives. We counterfeit websites. Based on the relation between credibility introduced a concept of wantedness and credibility, and and phishing frequency, we classify the phishers into i) derived equations to calculate the wantedness values of the Prospective Phishers ii) Suspects iii) Recent Phishers iv) Serial email senders. -
Efficient Spam Filtering System Based on Smart Cooperative Subjective and Objective Methods*
Int. J. Communications, Network and System Sciences, 2013, 6, 88-99 http://dx.doi.org/10.4236/ijcns.2013.62011 Published Online February 2013 (http://www.scirp.org/journal/ijcns) Efficient Spam Filtering System Based on Smart * Cooperative Subjective and Objective Methods Samir A. Elsagheer Mohamed1,2 1College of Computer, Qassim University, Qassim, KSA 2Electrical Engineering Department, Faculty of Engineering, Aswan University, Aswan, Egypt Email: [email protected], [email protected] Received September 17, 2012; revised January 16, 2013; accepted January 25, 2013 ABSTRACT Most of the spam filtering techniques are based on objective methods such as the content filtering and DNS/reverse DNS checks. Recently, some cooperative subjective spam filtering techniques are proposed. Objective methods suffer from the false positive and false negative classification. Objective methods based on the content filtering are time con- suming and resource demanding. They are inaccurate and require continuous update to cope with newly invented spammer’s tricks. On the other side, the existing subjective proposals have some drawbacks like the attacks from mali- cious users that make them unreliable and the privacy. In this paper, we propose an efficient spam filtering system that is based on a smart cooperative subjective technique for content filtering in addition to the fastest and the most reliable non-content-based objective methods. The system combines several applications. The first is a web-based system that we have developed based on the proposed technique. A server application having extra features suitable for the enter- prises and closed work groups is a second part of the system. Another part is a set of standard web services that allow any existing email server or email client to interact with the system. -
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 -
IFIP AICT 394, Pp
A Scalable Spam Filtering Architecture Nuno Ferreira1, Gracinda Carvalho1, and Paulo Rogério Pereira2 1 Universidade Aberta, Portugal 2 INESC-ID, Instituto Superior Técnico, Technical University of Lisbon, Portugal [email protected], [email protected], [email protected] Abstract. The proposed spam filtering architecture for MTA1 servers is a component based architecture that allows distributed processing and centralized knowledge. This architecture allows heterogeneous systems to coexist and benefit from a centralized knowledge source and filtering rules. MTA servers in the infrastructure contribute to a common knowledge, allowing for a more rational resource usage. The architecture is fully scalable, ranging from all-in- one system with minimal components instances, to multiple components instances distributed across multiple systems. Filtering rules can be implemented as independent modules that can be added, removed or modified without impact on MTA servers operation. A proof-of-concept solution was developed. Most of spam is filtered due to a grey-listing effect from the architecture itself. Using simple filters as Domain Name System black and white lists, and Sender Policy Framework validation, it is possible to guarantee a spam filtering effective, efficient and virtually without false positives. Keywords: spam filtering, distributed architecture, component based, centralized knowledge, heterogeneous system, scalable deployment, dynamic rules, modular implementation. 1 Introduction Internet mail spam2 is a problem for most organizations and individuals. Receiving spam on mobile devices, and on other connected appliances, is yet a bigger problem, as these platforms are not the most appropriate for spam filtering. Spam can be seen as belonging to one of two major categories: Fraud and Commercial. -
DNS Manager User Guide VF
Vodafone Hosted Services: DNS Manager User Guide DNS Manager User Guide 1 Vodafone Hosted Services: DNS Manager User Guide DNS Manager What is DNS Manager ? DNS Manager allows the end-user to edit their domain’s zone file, including A (address) records, CNAME (canonical name) records and MX (mail exchange) records. What is the Default Zone File ? If the end-user selects “Edit Zone File” and clicks “Next”, their current zone file will be displayed at the top of the screen. By default, their zone file will contain several important records. Any changes to these records may cause serious problems with their website and email performance. What is DNS ? DNS (Domain Name System or Domain Name Service) catalogs and updates information in regards to domain names. DNS converts domain names into IP addresses. DNS usually contains a set of zone files that lists the types of redirection that will be done. 2 Vodafone Hosted Services: DNS Manager User Guide What are Zone Files ? Four types of records are important in a zone file: • A records • CNAME records • MX records • Start of Authority (SOA) domain.com points to 216.251.43.17 mail.domain.com points to 69.49.123.241 mail will be delivered to 10 mx1c1.megamailservers.com first mail will be delivered to 100 mx2c1.megamailservers.com second mail will be delivered to 110 Resource Record Abbreviations The end-users domain name is called their “origin”. The origin is appended to all names in the zone file that do not end in a dot. For example, if their domain is yourname.com, the entry “www” in the zone file is equal to www.yourname.com. -
Master Thesis Characterizing Sender Policy Framework Configurations At
Master Thesis Characterizing Sender Policy Framework Configurations at Scale Gabri¨elMathay Kahraman Monday 7th September, 2020 A thesis presented for the degree of Master of Science Computer Science Design and Analysis of Communication Systems (DACS) Chair: prof. dr. ir. Aiko Pras Supervisor: dr. ir. Mattijs Jonker Co-supervisors: ir. Olivier van der Toorn and dr. Doina Bucur Abstract Phishing involves disguising oneself as a trustworthy entity in electronic communication, for example, by pretending to send e-mail on behalf of a company. Phishing e-mails can be prevented if domains implement e-mail security techniques. One of the techniques to improve e-mail security is the Sender Policy Framework (SPF). To enable SPF, the administrator of a domain can specify an SPF policy in the DNS zone of the domain. The SPF policy determines which IP addresses are authorised to send e-mail from the administrator's domain. When an e-mail server receives an e-mail, the e-mail server retrieves the SPF policy of the sender's domain. Next, the IP address of the sender will be queried against the SPF record, and the response of this query determines how to handle the incoming e-mail. The SPF standard was released over six years ago. Even though six years have passed, the research community does not yet have a thorough understanding of the characteristics of SPF use. What we miss is an understanding of how SPF policies are configured, how SPF policies have changed over time, and what the problematic trends are of SPF use. In this Thesis, we address the missing of a large scale analysis on SPF policies over time. -
Email Services Deployment Administrator Guide Email Services Deployment Administrator Guide
Email Services Deployment Administrator Guide Email Services Deployment Administrator Guide Documentation version: 1.0 Legal Notice Copyright 2016 Symantec Corporation. All rights reserved. Symantec, the Symantec Logo, and the Checkmark Logo are trademarks or registered trademarks of Symantec Corporation or its affiliates in the U.S. and other countries. Other names may be trademarks of their respective owners. The product described in this document is distributed under licenses restricting its use, copying, distribution, and decompilation/reverse engineering. No part of this document may be reproduced in any form by any means without prior written authorization of Symantec Corporation and its licensors, if any. THE DOCUMENTATION IS PROVIDED "AS IS" AND ALL EXPRESS OR IMPLIED CONDITIONS, REPRESENTATIONS AND WARRANTIES, INCLUDING ANY IMPLIED WARRANTY OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE OR NON-INFRINGEMENT, ARE DISCLAIMED, EXCEPT TO THE EXTENT THAT SUCH DISCLAIMERS ARE HELD TO BE LEGALLY INVALID. SYMANTEC CORPORATION SHALL NOT BE LIABLE FOR INCIDENTAL OR CONSEQUENTIAL DAMAGES IN CONNECTION WITH THE FURNISHING, PERFORMANCE, OR USE OF THIS DOCUMENTATION. THE INFORMATION CONTAINED IN THIS DOCUMENTATION IS SUBJECT TO CHANGE WITHOUT NOTICE. The Licensed Software and Documentation are deemed to be commercial computer software as defined in FAR 12.212 and subject to restricted rights as defined in FAR Section 52.227-19 "Commercial Computer Software - Restricted Rights" and DFARS 227.7202, et seq. "Commercial Computer Software and Commercial Computer Software Documentation," as applicable, and any successor regulations, whether delivered by Symantec as on premises or hosted services. Any use, modification, reproduction release, performance, display or disclosure of the Licensed Software and Documentation by the U.S. -
White Paper Barracuda • Comprehensive Email Filtering
Comprehensive Email Filtering White Paper Barracuda • Comprehensive Email Filtering Email has undoubtedly become a valued communications tool among organizations worldwide. With Spam History frequent virus attacks and the alarming influx of spam, email loses the efficiency to communicate. Spam Spam is one form of abuse messages represent the vast majority of email traffic on the Internet. Spam is no longer a simple annoyance; of the Simple Mail Transfer it is a significant security issue and a massive drain on financial resources. Protocol (SMTP), which is implemented in email systems This is simply astounding and unacceptable. It’s time to take control of spam and virus attacks. on the basis of RFC 524. First proposed in 1973, RFC 524 was Filtering Email in Two Advanced Processes developed during a time when computer security was not a Today, there are a number of solutions designed to help alleviate the spam problem. Barracuda Networks significant concern. As such, designed the affordable Barracuda Email Security Gateway as an easy-to-use, enterprise-class hardware and RFC 524 is no longer a secure software solution for businesses of all sizes that comprehensively evaluates each email, using two main command set, making it and classes of sophisticated algorithms and techniques: Connection Management and Mail Scanning. SMTP susceptible to abuse. During the connection management process, emails are filtered through five defense layers to verify Most spam-making tools authenticity of envelope information, and any inappropriate incoming mail connections are dropped exploit the security holes in even before receiving the message. Any emails that survive the connection verification process must then SMTP. -
Email Filtering for Providers
Email Filtering for providers How email service providers and ISPs can use anti-phishing, anti-ransomware and graymail filtering as a strategic weapon. Win new customers, keep your current ones, and avoid being stuck in commodity pricing hell. Table of Contents Summary .............................................................................................. 3 Introduction ......................................................................................... 4 What is an ISP or Host To Do? ....................................................... 5 The Spectrum of Email Threats and Nuisances ........................ 5 Spam ................................................................................................... 6 Graymail .............................................................................................. 7 Phishing and Spear Phishing ............................................................... 8 Malware through Phishing and Spear Phishing Campaigns ................10 Stopping Spear Phishing is Difficult ...................................................11 Hard Costs of Email Threats and Nuisances ............................ 11 Opportunity Costs of Email Security .......................................... 12 Mitigating the Full Spectrum of Email Threats .......................... 12 Heuristic Filtering and Rules to Fight Graymail and Spam ..................13 Anti-Phishing/Spear Phishing ............................................................14 Anti-Malware and Attachment Analysis .............................................15