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Click Trajectories: End-To-End Analysis of the Spam Value Chain
Click Trajectories: End-to-End Analysis of the Spam Value Chain ∗ ∗ ∗ ∗ z y Kirill Levchenko Andreas Pitsillidis Neha Chachra Brandon Enright Mark´ Felegyh´ azi´ Chris Grier ∗ ∗ † ∗ ∗ Tristan Halvorson Chris Kanich Christian Kreibich He Liu Damon McCoy † † ∗ ∗ Nicholas Weaver Vern Paxson Geoffrey M. Voelker Stefan Savage ∗ y Department of Computer Science and Engineering Computer Science Division University of California, San Diego University of California, Berkeley z International Computer Science Institute Laboratory of Cryptography and System Security (CrySyS) Berkeley, CA Budapest University of Technology and Economics Abstract—Spam-based advertising is a business. While it it is these very relationships that capture the structural has engendered both widespread antipathy and a multi-billion dependencies—and hence the potential weaknesses—within dollar anti-spam industry, it continues to exist because it fuels a the spam ecosystem’s business processes. Indeed, each profitable enterprise. We lack, however, a solid understanding of this enterprise’s full structure, and thus most anti-spam distinct path through this chain—registrar, name server, interventions focus on only one facet of the overall spam value hosting, affiliate program, payment processing, fulfillment— chain (e.g., spam filtering, URL blacklisting, site takedown). directly reflects an “entrepreneurial activity” by which the In this paper we present a holistic analysis that quantifies perpetrators muster capital investments and business rela- the full set of resources employed to monetize spam email— tionships to create value. Today we lack insight into even including naming, hosting, payment and fulfillment—using extensive measurements of three months of diverse spam data, the most basic characteristics of this activity. How many broad crawling of naming and hosting infrastructures, and organizations are complicit in the spam ecosystem? Which over 100 purchases from spam-advertised sites. -
DNS Zones Overview
DNS Zones Overview A DNS zone is the contiguous portion of the DNS domain name space over which a DNS server has authority. A zone is a portion of a namespace. It is not a domain. A domain is a branch of the DNS namespace. A DNS zone can contain one or more contiguous domains. A DNS server can be authoritative for multiple DNS zones. A non-contiguous namespace cannot be a DNS zone. A zone contains the resource records for all of the names within the particular zone. Zone files are used if DNS data is not integrated with Active Directory. The zone files contain the DNS database resource records that define the zone. If DNS and Active Directory are integrated, then DNS data is stored in Active Directory. The different types of zones used in Windows Server 2003 DNS are listed below: Primary zone Secondary zone Active Directory-integrated zone Reverse lookup zone Stub zone A primary zone is the only zone type that can be edited or updated because the data in the zone is the original source of the data for all domains in the zone. Updates made to the primary zone are made by the DNS server that is authoritative for the specific primary zone. Users can also back up data from a primary zone to a secondary zone. A secondary zone is a read-only copy of the zone that was copied from the master server during zone transfer. In fact, a secondary zone can only be updated through zone transfer. An Active Directory-integrated zone is a zone that stores its data in Active Directory. -
Passive Monitoring of DNS Anomalies Bojan Zdrnja1, Nevil Brownlee1, and Duane Wessels2
Passive Monitoring of DNS Anomalies Bojan Zdrnja1, Nevil Brownlee1, and Duane Wessels2 1 University of Auckland, New Zealand, b.zdrnja,nevil @auckland.ac.nz { } 2 The Measurement Factory, Inc., [email protected] Abstract. We collected DNS responses at the University of Auckland Internet gateway in an SQL database, and analyzed them to detect un- usual behaviour. Our DNS response data have included typo squatter domains, fast flux domains and domains being (ab)used by spammers. We observe that current attempts to reduce spam have greatly increased the number of A records being resolved. We also observe that the data locality of DNS requests diminishes because of domains advertised in spam. 1 Introduction The Domain Name System (DNS) service is critical for the normal functioning of almost all Internet services. Although the Internet Protocol (IP) does not need DNS for operation, users need to distinguish machines by their names so the DNS protocol is needed to resolve names to IP addresses (and vice versa). The main requirements on the DNS are scalability and availability. The DNS name space is divided into multiple zones, which are a “variable depth tree” [1]. This way, a particular DNS server is authoritative only for its (own) zone, and each organization is given a specific zone in the DNS hierarchy. A complete domain name for a node is called a Fully Qualified Domain Name (FQDN). An FQDN defines a complete path for a domain name starting on the leaf (the host name) all the way to the root of the tree. Each node in the tree has its label that defines the zone. -
Sidekick Suspicious Domain Classification in the .Nl Zone
Master Thesis as part of the major in Security & Privacy at the EIT Digital Master School SIDekICk SuspIcious DomaIn Classification in the .nl Zone delivered by Moritz C. M¨uller [email protected] at the University of Twente 2015-07-31 Supervisors: Andreas Peter (University of Twente) Maarten Wullink (SIDN) Abstract The Domain Name System (DNS) plays a central role in the Internet. It allows the translation of human-readable domain names to (alpha-) numeric IP addresses in a fast and reliable manner. However, domain names not only allow Internet users to access benign services on the Internet but are used by hackers and other criminals as well, for example to host phishing campaigns, to distribute malware, and to coordinate botnets. Registry operators, which are managing top-level domains (TLD) like .com, .net or .nl, disapprove theses kinds of usage of their domain names because they could harm the reputation of their zone and would consequen- tially lead to loss of income and an insecure Internet as a whole. Up to today, only little research has been conducted with the intention to fight malicious domains from the view of a TLD registry. This master thesis focuses on the detection of malicious domain names for the .nl country code TLD. Therefore, we analyse the characteristics of known malicious .nl domains which have been used for phishing and by botnets. We confirm findings from previous research in .com and .net and evaluate novel characteristics including query patterns for domains in quar- antine and recursive resolver relations. Based on this analysis, we have developed a prototype of a detection system called SIDekICk. -
Proactive Cyberfraud Detection Through Infrastructure Analysis
PROACTIVE CYBERFRAUD DETECTION THROUGH INFRASTRUCTURE ANALYSIS Andrew J. Kalafut Submitted to the faculty of the Graduate School in partial fulfillment of the requirements for the degree Doctor of Philosophy in Computer Science Indiana University July 2010 Accepted by the Graduate Faculty, Indiana University, in partial fulfillment of the requirements of the degree of Doctor of Philosophy. Doctoral Minaxi Gupta, Ph.D. Committee (Principal Advisor) Steven Myers, Ph.D. Randall Bramley, Ph.D. July 19, 2010 Raquel Hill, Ph.D. ii Copyright c 2010 Andrew J. Kalafut ALL RIGHTS RESERVED iii To my family iv Acknowledgements I would first like to thank my advisor, Minaxi Gupta. Minaxi’s feedback on my research and writing have invariably resulted in improvements. Minaxi has always been supportive, encouraged me to do the best I possibly could, and has provided me many valuable opportunities to gain experience in areas of academic life beyond simply doing research. I would also like to thank the rest of my committee members, Raquel Hill, Steve Myers, and Randall Bramley, for their comments and advice on my research and writing, especially during my dissertation proposal. Much of the work in this dissertation could not have been done without the help of Rob Henderson and the rest of the systems staff. Rob has provided valuable data, and assisted in several other ways which have ensured my experiments have run as smoothly as possible. Several members of the departmental staff have been very helpful in many ways. Specifically, I would like to thank Debbie Canada, Sherry Kay, Ann Oxby, and Lucy Battersby. -
Fast-Flux Botnet Detection Based on Traffic Response and Search Engines Credit Worthiness
ISSN 1330-3651 (Print), ISSN 1848-6339 (Online) https://doi.org/10.17559/TV-20161012115204 Original scientific paper Fast-Flux Botnet Detection Based on Traffic Response and Search Engines Credit Worthiness Davor CAFUTA, Vlado SRUK, Ivica DODIG Abstract: Botnets are considered as the primary threats on the Internet and there have been many research efforts to detect and mitigate them. Today, Botnet uses a DNS technique fast-flux to hide malware sites behind a constantly changing network of compromised hosts. This technique is similar to trustworthy Round Robin DNS technique and Content Delivery Network (CDN). In order to distinguish the normal network traffic from Botnets different techniques are developed with more or less success. The aim of this paper is to improve Botnet detection using an Intrusion Detection System (IDS) or router. A novel classification method for online Botnet detection based on DNS traffic features that distinguish Botnet from CDN based traffic is presented. Botnet features are classified according to the possibility of usage and implementation in an embedded system. Traffic response is analysed as a strong candidate for online detection. Its disadvantage lies in specific areas where CDN acts as a Botnet. A new feature based on search engine hits is proposed to improve the false positive detection. The experimental evaluations show that proposed classification could significantly improve Botnet detection. A procedure is suggested to implement such a system as a part of IDS. Keywords: Botnet; fast-flux; IDS 1 INTRODUCTION locations DoS attack against the web site becomes very difficult as it must be effective on every server in the field The Domain Name System (DNS) is a hierarchical [7, 8]. -
Domain Name System 1 Domain Name System
Domain Name System 1 Domain Name System The Domain Name System (DNS) is a hierarchical distributed naming system for computers, services, or any resource connected to the Internet or a private network. It associates various information with domain names assigned to each of the participating entities. A Domain Name Service translates queries for domain names (which are easier to understand and utilize when accessing the internet) into IP addresses for the purpose of locating computer services and devices worldwide. An often-used analogy to explain the Domain Name System is that it serves as the phone book for the Internet by translating human-friendly computer hostnames into IP addresses. For example, the domain name www.example.com translates to the addresses 192.0.43.10 (IPv4) and 2620:0:2d0:200::10 (IPv6). The Domain Name System makes it possible to assign domain names to groups of Internet resources and users in a meaningful way, independent of each entity's physical location. Because of this, World Wide Web (WWW) hyperlinks and Internet contact information can remain consistent and constant even if the current Internet routing arrangements change or the participant uses a mobile device. Internet domain names are easier to remember than IP addresses such as 208.77.188.166 (IPv4) or 2001:db8:1f70::999:de8:7648:6e8 (IPv6). Users take advantage of this when they recite meaningful Uniform Resource Locators (URLs) and e-mail addresses without having to know how the computer actually locates them. The Domain Name System distributes the responsibility of assigning domain names and mapping those names to IP addresses by designating authoritative name servers for each domain. -
Detection of Fast-Flux Networks Using Various DNS Feature Sets
Detection of Fast-Flux Networks Using Various DNS Feature Sets Z. Berkay Celik and Serna Oktug Department of Computer Engineering Istanbul Technical University Maslak, Istanbul, Turkey 34469 { zbcelik,oktug}@itu.edu.tr Abstract-In this work, we study the detection of Fast-Flux imperfect, e.g., they may suffer from high detection latency Service Networks (FFSNs) using DNS (Domain Name System) (i.e., extracting features as a timescale greater than Time response packets. We have observed that current approaches do To Live (TTL), or multiple DNS lookups) or false positives not employ a large combination of DNS features to feed into detected by utilizing imperfect and insufficient features. the proposed detection systems. The lack of features may lead to high false positive or false negative rates triggered by benign The work presented here is related to the detection of activities including Content Distribution Networks (CDNs). In FFSNs, in particular, by jointly building timing, domain name, this paper, we study recently proposed detection frameworks to spatial, network and DNS answer features which are extracted construct a high-dimensional feature vector containing timing, network, spatial, domain name, and DNS response information. from the first DNS response packet. We consider many rather In the detection system, we strive to use features that are delay than a few features and also their combinations which are free, and lightweight in terms of storage and computational constructed by surveying the recent literature. The main aim of cost. Feature sub-spaces are evaluated using a C4.5 decision tree this survey is to study and analyze the benefits of the features classifier by excluding redundant features using the information and also, in some cases, the necessity of applying joint feature gain of each feature with respect to each class. -
DNS) Administration Guide
Edgecast Route (DNS) Administration Guide Disclaimer Care was taken in the creation of this guide. However, Edgecast cannot accept any responsibility for errors or omissions. There are no warranties, expressed or implied, including the warranty of merchantability or fitness for a particular purpose, accompanying this product. Trademark Information EDGECAST is a registered trademark of Verizon Digital Media Services Inc. About This Guide Route (DNS) Administration Guide Version 2.40 8/28/2021 ©2021 Verizon Media. All rights reserved. Table of Contents Route ............................................................................................................................................................. 1 Introduction .............................................................................................................................................. 1 Scope ......................................................................................................................................................... 1 Module Comparison ................................................................................................................................. 2 Managed (Primary) or Secondary DNS Module .................................................................................... 2 DNS Health Checks Module .................................................................................................................. 3 Billing Activation ...................................................................................................................................... -
Acceptable Use and Takedown Policy
ACCEPTABLE USE AND TAKEDOWN POLICY BNP Paribas (“the Registry”) as the operator of the TLD .bnpparibas attaches great value to the secure use and usability of the services available under the TLD .bnpparibas. Abuses of .bnpparibas are a threat to the stability and security of the Registry, registrars, registrants and the security of Internet users generally. This Acceptable Use Policy (« AUP ») sets forth the terms and conditions for the use by a Registrant of any domain name registered or renewed under .bnpparibas. The Registry reserves the right to modify or amend this AUP at any time in order to comply with applicable laws and terms and/or any conditions set forth by ICANN. Acceptable Use Overview All domain name registrants must act responsibly in their use of any .bnpparibas domain or website hosted on any .bnpparibas domain, and in accordance with this policy, ICANN registry agreement, and applicable laws, including those that relate to privacy, data collection, consumer protection (including in relation to misleading and deceptive conduct), fair lending, and intellectual property rights. The Registry will not tolerate abusive, malicious, or illegal conduct in registration of a domain name; nor will the Registry tolerate such content on a website hosted on a .bnpparibas domain name. This AUP will govern the Registry’s actions in response to abusive, malicious, or illegal conduct of which the Registry becomes aware. The Registry reserves the right to bring the offending sites into compliance using any of the methods described herein, or others as may be necessary in the Registry’s discretion, whether or not described in this Acceptable Use Policy. -
Fast-Flux Networks While Considering Domain-Name Parking
Proceedings Learning from Authoritative Security Experiment Results LASER 2017 Arlington, VA, USA October 18-19, 2017 Proceedings of LASER 2017 Learning from Authoritative Security Experiment Results Arlington, VA, USA October 18–19, 2017 ©2017 by The USENIX Association All Rights Reserved This volume is published as a collective work. Rights to individual papers remain with the author or the author’s employer. Permission is granted for the noncommercial reproduction of the complete work for educational or research purposes. Permission is granted to print, primarily for one person’s exclusive use, a single copy of these Proceedings. USENIX acknowledges all trademarks herein. ISBN 978-1-931971-41-6 Table of Contents Program . .. v Organizing Committee . vi Program Committee . vi Workshop Sponsors . vii Message from the General Chair . viii Program Understanding Malware’s Network Behaviors using Fantasm . 1 Xiyue Deng, Hao Shi, and Jelena Mirkovic, USC/Information Sciences Institute Open-source Measurement of Fast-flux Networks While Considering Domain-name Parking . 13 Leigh B. Metcalf, Dan Ruef, and Jonathan M. Spring, Carnegie Mellon University Lessons Learned from Evaluating Eight Password Nudges in the Wild . 25 Karen Renaud and Joseph Maguire, University of Glasgow; Verena Zimmerman, TU Darmstadt; Steve Draper, University of Glasgow An Empirical Investigation of Security Fatigue: The Case of Password Choice after Solving a CAPTCHA . 39 Kovila P.L. Coopamootoo and Thomas Gross, Newcastle University; Muhammad F. R. Pratama Dead on Arrival: Recovering from Fatal Flaws in Email Encryption Tools . 49 Juan Ramón Ponce Mauriés, University College London; Kat Krol, University of Cambridge; Simon Parkin, Ruba Abu-Salma, and M. -
DNS) Deployment Guide
Archived NIST Technical Series Publication The attached publication has been archived (withdrawn), and is provided solely for historical purposes. It may have been superseded by another publication (indicated below). Archived Publication Series/Number: NIST Special Publication 800-81 Revision 1 Title: Secure Domain Name System (DNS) Deployment Guide Publication Date(s): April 2010 Withdrawal Date: September 2013 Withdrawal Note: SP 800-81 Revision 1 is superseded in its entirety by the publication of SP 800-81-2 (September 2013). Superseding Publication(s) The attached publication has been superseded by the following publication(s): Series/Number: NIST Special Publication 800-81-2 Title: Secure Domain Name System (DNS) Deployment Guide Author(s): Ramaswamy Chandramouli, Scott Rose Publication Date(s): September 2013 URL/DOI: http://dx.doi.org/10.6028/NIST.SP.800-81-2 Additional Information (if applicable) Contact: Computer Security Division (Information Technology Lab) Latest revision of the SP 800-81-2 (as of August 7, 2015) attached publication: Related information: http://csrc.nist.gov/ Withdrawal N/A announcement (link): Date updated: ƵŐƵƐƚϳ, 2015 Special Publication 800-81r1 Sponsored by the Department of Homeland Security Secure Domain Name System (DNS) Deployment Guide Recommendations of the National Institute of Standards and Technology Ramaswamy Chandramouli Scott Rose i NIST Special Publication 800-81r1 Secure Domain Name System (DNS) Deployment Guide Sponsored by the Department of Homeland Security Recommendations of the National Institute of Standards and Technology Ramaswamy Chandramouli Scott Rose C O M P U T E R S E C U R I T Y Computer Security Division/Advanced Network Technologies Division Information Technology Laboratory National Institute of Standards and Technology Gaithersburg, MD 20899 April 2010 U.S.