Classifying HTTP Traffic in the New Age
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A Survey of Network Performance Monitoring Tools
A Survey of Network Performance Monitoring Tools Travis Keshav -- [email protected] Abstract In today's world of networks, it is not enough simply to have a network; assuring its optimal performance is key. This paper analyzes several facets of Network Performance Monitoring, evaluating several motivations as well as examining many commercial and public domain products. Keywords: network performance monitoring, application monitoring, flow monitoring, packet capture, sniffing, wireless networks, path analysis, bandwidth analysis, network monitoring platforms, Ethereal, Netflow, tcpdump, Wireshark, Ciscoworks Table Of Contents 1. Introduction 2. Application & Host-Based Monitoring 2.1 Basis of Application & Host-Based Monitoring 2.2 Public Domain Application & Host-Based Monitoring Tools 2.3 Commercial Application & Host-Based Monitoring Tools 3. Flow Monitoring 3.1 Basis of Flow Monitoring 3.2 Public Domain Flow Monitoring Tools 3.3 Commercial Flow Monitoring Protocols 4. Packet Capture/Sniffing 4.1 Basis of Packet Capture/Sniffing 4.2 Public Domain Packet Capture/Sniffing Tools 4.3 Commercial Packet Capture/Sniffing Tools 5. Path/Bandwidth Analysis 5.1 Basis of Path/Bandwidth Analysis 5.2 Public Domain Path/Bandwidth Analysis Tools 6. Wireless Network Monitoring 6.1 Basis of Wireless Network Monitoring 6.2 Public Domain Wireless Network Monitoring Tools 6.3 Commercial Wireless Network Monitoring Tools 7. Network Monitoring Platforms 7.1 Basis of Network Monitoring Platforms 7.2 Commercial Network Monitoring Platforms 8. Conclusion 9. References and Acronyms 1.0 Introduction http://www.cse.wustl.edu/~jain/cse567-06/ftp/net_perf_monitors/index.html 1 of 20 In today's world of networks, it is not enough simply to have a network; assuring its optimal performance is key. -
Browser Versions Carry 10.5 Bits of Identifying Information on Average [Forthcoming Blog Post]
Browser versions carry 10.5 bits of identifying information on average [forthcoming blog post] Technical Analysis by Peter Eckersley This is part 3 of a series of posts on user tracking on the modern web. You can also read part 1 and part 2. Whenever you visit a web page, your browser sends a "User Agent" header to the website saying what precise operating system and browser you are using. We recently ran an experiment to see to what extent this information could be used to track people (for instance, if someone deletes their browser cookies, would the User Agent, alone or in combination with some other detail, be enough to re-create their old cookie?). Our experiment to date has shown that the browser User Agent string usually carries 5-15 bits of identifying information (about 10.5 bits on average). That means that on average, only one person in about 1,500 (210.5) will have the same User Agent as you. On its own, that isn't enough to recreate cookies and track people perfectly, but in combination with another detail like an IP address, geolocation to a particular ZIP code, or having an uncommon browser plugin installed, the User Agent string becomes a real privacy problem. User Agents: An Example of Browser Characteristics Doubling As Tracking Tools When we analyse the privacy of web users, we usually focus on user accounts, cookies, and IP addresses, because those are the usual means by which a request to a web server can be associated with other requests and/or linked back to an individual human being, computer, or local network. -
Best Practices for Network Monitoring
White Paper Best Practices for Network Monitoring How a Network Monitoring Switch Helps IT Teams Stay Proactive 26601 Agoura Road, Calabasas, CA 91302 | Tel: 818.871.1800 | Fax: 818.871.1805 | www.ixiacom.com | 915-6509-01 Rev. B, June 2013 2 Table of Contents Monitoring Challenges in Today’s Business Environment .......................................... 4 Giving Monitoring Tools Full Visibility to the Network ............................................... 5 Easing the Path to Upgrade ........................................................................................ 6 Making Monitoring Tools Work Better ........................................................................ 7 Filtering ...................................................................................................................... 7 Load Balancing ........................................................................................................... 8 Packet De-duplication ................................................................................................ 8 Packet Trimming ........................................................................................................ 8 MPLS Stripping .......................................................................................................... 9 Keeping Network Data Secure ................................................................................... 9 Improving Productivity in IT ....................................................................................... 9 Filter Libraries -
Large Scale Monitoring of Home Routers
IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications 21-23 September 2009, Rende (Cosenza), Italy Large scale monitoring of home routers S. Costas-Rodr´ıguez+,R.Mart´ınez-Alvarez´ +,F.J.Gonz´alez-Casta˜no∗+, F. Gil-Casti˜neira∗,R.Duro× +Gradiant, ETSI Telecomunicaci´on, Campus, 36310 Vigo, Spain ∗Departamento de Ingenier´ıa Telem´atica, Universidad de Vigo, Spain ×Grupo Integrado de Ingenier´ıa, Universidad de La Coru˜na, Spain Tel: +34 986 813788, fax: +34 986 812116 E-mail: {scostas,rmartinez}@gradiant.org,{javier,xil}@det.uvigo.es,[email protected] Abstract – This paper describes our experience with reception power, memory usage or uptime are useful to concurrent asynchronous monitoring of large populations of detect and fix many potential problems. end-user broadband-access routers. In our real tests we focused on home/office ADSL Despite of the wealth of research in large-scale monitoring, which assumes that it is possible to inquiry individual nodes routers, although our results are valid for any other access efficiently, end-user access routers usually have manual legacy technology. We monitored the routers of the Spanish ISP interfaces, either HTTP- or telnet-oriented. They seldom and VoIP operator Comunitel (www.comunitel.es). With offer a direct interface to other programs. Moreover, the our approach, a full monitoring cycle of 22,300 such uptime of end-user routers is unpredictable. For all these routers took less than five minutes. reasons, commercial large-scale monitoring tools such as SNMP collectors are useless. The rest of this paper is organized as follows: In This research is motivated by the fact that some telecom- section II we review the background, comprising academic munications operators do not let end-users buy their routers research and existing industrial solutions. -
Network Monitoring Using Nagios and Autoconfiguration for Cyber Defense Competitions
NETWORK MONITORING USING NAGIOS AND AUTOCONFIGURATION FOR CYBER DEFENSE COMPETITIONS Jaipaul Vasireddy B.Tech, A.I.E.T, Jawaharlal Nehru Technological University, India, 2006 PROJECT Submitted in partial satisfaction of the requirements for the degree of MASTER OF SCIENCE in COMPUTER SCIENCE at CALIFORNIA STATE UNIVERSITY, SACRAMENTO FALL 2009 NETWORK MONITORING USING NAGIOS AND AUTOCONFIGURATION FOR CYBER DEFENSE COMPETITIONS A Project by Jaipaul Vasireddy Approved by: __________________________________, Committee Chair Dr. Isaac Ghansah __________________________________, Second Reader Prof. Richard Smith __________________________ Date ii Student: Jaipaul Vasireddy I certify that this student has met the requirements for format contained in the University format manual, and that this Project is suitable for shelving in the Library and credit is to be awarded for the Project. __________________________, Graduate Coordinator ________________ Dr. Cui Zhang Date Department of Computer Science iii Abstract of NETWORK MONITORING USING NAGIOS AND AUTOCONFIGURATION FOR CYBER DEFENSE COMPETITIONS by Jaipaul Vasireddy The goal of the project is to monitor the services running on the CCDC (College Cyber Defense Competition) network, using Nagios which uses plugins to monitor the services running on a network. Nagios is configured by building configuration files for each machine which is usually done to monitor small number of systems. The configuration of Nagios can also be automated by using shell scripting which is generally done in an industry, where the numbers of systems to be monitored are large. Both the above methods of configuration have been implemented in this project. The project has been successfully used to know the status of each service running on the defending team’s network. -
Longitudinal Characterization of Browsing Habits
Please cite this paper as: Luca Vassio, Idilio Drago, Marco Mellia, Zied Ben Houidi, and Mohamed Lamine Lamali. 2018. You, the Web, and Your Device: Longitudinal Charac- terization of Browsing Habits. ACM Trans. Web 12, 4, Article 24 (November 2018), 30 1 pages. https://doi.org/10.1145/3231466 You, the Web and Your Device: Longitudinal Characterization of Browsing Habits LUCA VASSIO, Politecnico di Torino IDILIO DRAGO, Politecnico di Torino MARCO MELLIA, Politecnico di Torino ZIED BEN HOUIDI, Nokia Bell Labs MOHAMED LAMINE LAMALI, LaBRI, Université de Bordeaux Understanding how people interact with the web is key for a variety of applications – e.g., from the design of eective web pages to the denition of successful online marketing campaigns. Browsing behavior has been traditionally represented and studied by means of clickstreams, i.e., graphs whose vertices are web pages, and edges are the paths followed by users. Obtaining large and representative data to extract clickstreams is however challenging. The evolution of the web questions whether browsing behavior is changing and, by consequence, whether properties of clickstreams are changing. This paper presents a longitudinal study of clickstreams in from 2013 to 2016. We evaluate an anonymized dataset of HTTP traces captured in a large ISP, where thousands of households are connected. We rst propose a methodology to identify actual URLs requested by users from the massive set of requests automatically red by browsers when rendering web pages. Then, we characterize web usage patterns and clickstreams, taking into account both the temporal evolution and the impact of the device used to explore the web. -
Deploying F5 with Nagios Open Source Network Monitoring System Welcome to the F5 and Nagios Deployment Guide
DEPLOYMENT GUIDE Version 1.0 IMPORTANT: This guide has been archived. While the content in this guide is still valid for the products and version listed in the document, it is no longer being updated and may refer to F5 or 3rd party products or versions that have reached end-of-life or end-of-support. See https://support.f5.com/csp/article/K11163 for more information. Deploying the BIG-IP LTM with the Nagios Open Source Network Monitoring System Archived Deploying F5 with Nagios Open Source Network Monitoring System Welcome to the F5 and Nagios deployment guide. This guide provides detailed procedures for configuring F5 devices with the Nagios Open Source Network Monitoring System. Network Management Systems (NMS) provide insight to device and application performance, system stability, network trouble spots and a host of other items that affect a company's ability to provide computer network services. Recent advances in automated event correlation, data storage and retrieval, as well as open source systems that allow greater integration, have greatly improved today's Network Management Systems. The Nagios system and network monitoring application is an open source project. Nagios maintains network status information by polling objects for specific service responses. Examples of monitored network services include SMTP, DNS, HTTP, and so on. For more information on the Nagios project, see http://www.nagios.org/ or http://sourceforge.net/projects/nagios/. For further Nagios resources and information, see http://community.nagios.org/. For more information on F5 devices described in this guide, see http://www.f5.com/products/big-ip/. To provide feedback on this deployment guide or other F5 solution documents, contact us at [email protected]. -
Network Management
Chapter 12: Network Management Jian Ren and Tongtong Li, Michigan State University Introduction 2 Network Scanners . 25 OSI Network Management Model . .3 Packet Filters . 26 Network Management Layers . .4 Wireless Network Management 26 ISO Network Management Functions 6 Cellular Networks . 27 Configuration Management . .6 Location Management for Cellular Fault Management . .6 Networks . 28 Security Management . .7 Accounting Management . .7 Policy-based Network Management 29 What Is a Policy? . 30 Performance Management . .7 Benefits of PBNM . 31 Network Management Protocols 7 Architecture of a PBNM System . 31 SNMP/SNMPv1 . .8 Conclusion 32 SNMPv2 . 13 SNMPv3 . 15 Glossary 33 Remote Network Monitoring (RMON) 23 Acknowledgements 34 Network Management Tools 24 Network Monitors . 25 Acronyms 37 Abstract: The continuous growth in scale and diversity of computer networks and network components has made network management one of the most challenging issues facing network administrators. It has become impossible to carry out network management functions without the support of automated tools and applications. In this chapter, the major network management issues, including network management requirements, functions, techniques, security, some well- known network management protocols and tools, will be discussed. Location management for the wireless cellular networks will also be briefly described. Finally, policy-based network management, which is a promising direction for the next generation of network management, will be briefly described. Keywords: -
RSA Adaptive Authentication (On-Premise) 7.2 Integration Guide
RSA® Adaptive Authentication (On-Premise) 7.2 Integration Guide Contact Information Go to the RSA corporate website for regional Customer Support telephone and fax numbers: www.emc.com/domains/rsa/index.htm Trademarks RSA, the RSA Logo, BSAFE and EMC are either registered trademarks or trademarks of EMC Corporation in the United States and/or other countries. All other trademarks used herein are the property of their respective owners. For a list of EMC trademarks, go to www.emc.com/legal/emc-corporation-trademarks.htm#rsa. License agreement This software and the associated documentation are proprietary and confidential to EMC, are furnished under license, and may be used and copied only in accordance with the terms of such license and with the inclusion of the copyright notice below. This software and the documentation, and any copies thereof, may not be provided or otherwise made available to any other person. No title to or ownership of the software or documentation or any intellectual property rights thereto is hereby transferred. Any unauthorized use or reproduction of this software and the documentation may be subject to civil and/or criminal liability. This software is subject to change without notice and should not be construed as a commitment by EMC. Note on encryption technologies This product may contain encryption technology. Many countries prohibit or restrict the use, import, or export of encryption technologies, and current use, import, and export regulations should be followed when using, importing or exporting this product. Distribution Use, copying, and distribution of any EMC software described in this publication requires an applicable software license. -
Lab Exercise – HTTP
Lab Exercise – HTTP Objective HTTP (HyperText Transfer Protocol) is the main protocol underlying the Web. HTTP functions as a re- quest–response protocol in the client–server computing model. A web browser, for example, may be the client and an application running on a computer hosting a website may be the server. The client submits an HTTP request message to the server. The server, which provides resources such as HTML files and other content, or performs other functions on behalf of the client, returns a response message to the client. The response contains completion status information about the request and may also contain requested con- tent in its message body. A web browser is an example of a user agent (UA). Other types of user agent include the indexing software used by search providers (web crawlers), voice browsers, mobile apps, and other software that accesses, consumes, or displays web content. HTTP is designed to permit intermediate network elements to improve or enable communications between clients and servers. High-traffic web- sites often benefit from web cache servers that deliver content on behalf of upstream servers to improve response time. Web browsers cache previously accessed web resources and reuse them when possible to reduce network traffic. HTTP is an application layer protocol designed within the framework of the Inter- net protocol suite. Its definition presumes an underlying and reliable transport layer protocol and Trans- mission Control Protocol (TCP) is commonly used. Step 1: Open the http Trace Browser behavior can be quite complex, using more HTTP features than the basic exchange, this trace will show us how much gets transferred. -
Working with User Agent Strings in Stata: the Parseuas Command
JSS Journal of Statistical Software February 2020, Volume 92, Code Snippet 1. doi: 10.18637/jss.v092.c01 Working with User Agent Strings in Stata: The parseuas Command Joss Roßmann Tobias Gummer Lars Kaczmirek GESIS – Leibniz Institute GESIS – Leibniz Institute University of Vienna for the Social Sciences for the Social Sciences Abstract With the rising popularity of web surveys and the increasing use of paradata by survey methodologists, assessing information stored in user agent strings becomes inevitable. These data contain meaningful information about the browser, operating system, and device that a survey respondent uses. This article provides an overview of user agent strings, their specific structure and history, how they can be obtained when conducting a web survey, as well as what kind of information can be extracted from the strings. Further, the user written command parseuas is introduced as an efficient means to gather detailed information from user agent strings. The application of parseuas is illustrated by an example that draws on a pooled data set consisting of 29 web surveys. Keywords: user agent string, web surveys, device detection, browser, paradata, Stata. 1. Introduction In recent years, web surveys have become an increasingly popular and important data collec- tion mode, and today, they account for a great share of the studies in the social sciences. Web surveys have been used to complement traditional offline surveys as a less expensive form of pre-test or a mode of choice for respondents who are not willing to use “traditional” modes, such as face-to-face or telephone interviews. Along with the rising popularity of web surveys, survey methodologists have taken an increas- ing interest in paradata, which are collected as a byproduct of the survey process (Couper 2000). -
Comparative Analysis of Two Open Source Network Monitoring Systems: Nagios & Opennms
Master Thesis Computer Science Thesis no: MCS-2010-37 December 2010 Comparative Analysis of two Open Source Network Monitoring Systems: Nagios & OpenNMS Muhammad Qadir Muhammad Adnan SchoolSchool of Computing of Computing BlekingeBlekinge Institute Institute of Technology of Technology SE –Box 371 520 79 Karlskrona SwedenSE – 372 25 Ronneby Sweden This thesis is submitted to the School of Computing at Blekinge Institute of Technology in partial fulfillment of the requirements for the degree of Master of Science in Computer Science. The thesis is equivalent to 20 weeks of full time studies. Contact Information: Author(s): Muhammad Qadir Folkparksvagen 18:03 Ronneby 372 40, Sweden [email protected] Muhammad Adnan Folkparksvagen 14:11 Ronneby 372 40, Sweden [email protected] University advisor(s): Jeff Winter School of Computing School of Computing Blekinge Institute of Technology Internet : www.bth.se/com SE – 371 79 Karlskrona Phone : +46 455 38 50 00 Sweden Fax : +46 455 38 50 57 1 ABSTRACT Context: Extensive and rapid continuous growth in Internet Protocol (IP) based networks and as the result of increasing dependencies on these networks makes them extremely challenging to manage and keep them running all the time. 24/7 non-stop monitoring is important to minimize the down time of the network. For this reason dependency on automated network monitoring has been increased. Objectives: There are many tools and systems available for network monitoring. This includes expensive commercial solutions to open source products. Nagios and OpenNMS are two of the most popular systems and they are considered to be close competitors. Comparison discussions about them are very common at different forums on internet.