FlowScan A Network Traffic Reporting and Visualization Tool Dave Plonka

Slides:



Advertisements
Similar presentations
Network Monitoring System In CSTNET Long Chun China Science & Technology Network.
Advertisements

Characteristics of Network Traffic Flow Anomalies Paul Barford and David Plonka University of Wisconsin – Madison SIGCOMM IMW, 2001.
Managing P2P Applications or Where Did My Internet Bandwidth Go? David L. Merrifield University of Arkansas June 19, 2003.
FlowScan at the University of Wisconsin-Madison Copyright Dave Plonka and Perry Brunelli, This work is the intellectual property of the authors.
CISCO NETWORKING ACADEMY PROGRAM (CNAP)
The Latest In Denial Of Service Attacks: “Smurfing” Description and Information to Minimize Effects Craig A. Huegen Cisco Systems, Inc. NANOG 11 Interprovider.
CCNA 1 v3.1 Module 11 Review.
Firewalls and Intrusion Detection Systems
Monitoring a Large-Scale Network: Selecting the Right Tool Sayadur Rahman United International University & Network Manager, Financial Service.
Networking Theory (part 2). Internet Architecture The Internet is a worldwide collection of smaller networks that share a common suite of communication.
Network Monitoring: A Practical Approach Philip Smith/IT Services University of Windsor March 21, 2003.
Inside the Internet. INTERNET ARCHITECTURE The Internet system consists of a number of interconnected packet networks supporting communication among host.
NetFlow Analyzer Drilldown to the root-QoS Product Overview.
FIREWALLS & NETWORK SECURITY with Intrusion Detection and VPNs, 2 nd ed. 6 Packet Filtering By Whitman, Mattord, & Austin© 2008 Course Technology.
Implementing Standard and Extended Access Control List (ACL) in Cisco Routers.
Using Argus Audit Trails to Enhance IDS Analysis Jed Haile Nitro Data Systems
FIREWALL TECHNOLOGIES Tahani al jehani. Firewall benefits  A firewall functions as a choke point – all traffic in and out must pass through this single.
A Signal Analysis of Network Traffic Anomalies Paul Barford with Jeffery Kline, David Plonka, Amos Ron University of Wisconsin – Madison Summer, 2002.
Experiences in Analyzing Network Traffic Shou-Chuan Lai National Tsing Hua University Computer and Communication Center Nov. 20, 2003.
1 Netflow 6/12/07. 2 Overview Why use netflow? What is a flow? Deploying Netflow Performance Impact.
1 Chapter 6 Network Security Threats. 2 Objectives In this chapter, you will: Learn how to defend against packet sniffers Understand the TCP, UDP, and.
Packet Filtering. 2 Objectives Describe packets and packet filtering Explain the approaches to packet filtering Recommend specific filtering rules.
/dev/urandom Barry Britt, Systems Support Group Department of Computer Science Iowa State University.
FIREWALL Mạng máy tính nâng cao-V1.
NetfFow Overview SANOG 17 Colombo, Sri Lanka. Agenda Netflow –What it is and how it works –Uses and Applications Vendor Configurations/ Implementation.
Copyright © 2002 OSI Software, Inc. All rights reserved. PI-NetFlow and PacketCapture Eric Tam, OSIsoft.
Chapter 6: Packet Filtering
1 Semester 2 Module 10 Intermediate TCP/IP Yuda college of business James Chen
IP Flow Measurement & Analysis with FlowScan IPAM Workshop, Los Angeles, March 21, 2002 Dave Plonka Division of Information Technology,
1 The Research on Analyzing Time- Series Data and Anomaly Detection in Internet Flow Yoshiaki HARADA Graduate School of Information Science and Electrical.
NetFlow: Digging Flows Out of the Traffic Evandro de Souza ESnet ESnet Site Coordinating Committee Meeting Columbus/OH – July/2004.
FlowScan at the University of Wisconsin Perry Brunelli, Network Services.
1 CHAPTER 3 CLASSES OF ATTACK. 2 Denial of Service (DoS) Takes place when availability to resource is intentionally blocked or degraded Takes place when.
workshop eugene, oregon What is network management? System & Service monitoring  Reachability, availability Resource measurement/monitoring.
Transmission Control Protocol TCP. Transport layer function.
Packet Filtering Chapter 4. Learning Objectives Understand packets and packet filtering Understand approaches to packet filtering Set specific filtering.
MonNet – a project for network and traffic monitoring Detection of malicious Traffic on Backbone Links via Packet Header Analysis Wolfgang John and Tomas.
DoS attacks on transit network - David Harmelin ( ) Denial of Service attacks on transit networks David Harmelin DANTE.
OS Services And Networking Support Juan Wang Qi Pan Department of Computer Science Southeastern University August 1999.
Distributed Denial of Service Attacks
Packet Filtering COMP 423. Packets packets datagram To understand how firewalls work, you must first understand packets. Packets are discrete blocks of.
Module 10: How Middleboxes Impact Performance
April 4th, 2002George Wai Wong1 Deriving IP Traffic Demands for an ISP Backbone Network Prepared for EECE565 – Data Communications.
Open-Eye Georgios Androulidakis National Technical University of Athens.
UW-Madison - FlowScan and Rate Limiting Adventures I2 Techs Conference May 17, 2001 Michael Hare.
Interpreting Network Traffic Flows Bill Jensen, Paul Nazario and Perry Brunelli.
Advanced Packet Analysis and Troubleshooting Using Wireshark 23AF
Bradley Cowie Supervised by Barry Irwin Security and Networks Research Group Department of Computer Science Rhodes University DATA CLASSIFICATION FOR CLASSIFIER.
Chapter 8 Network Security Thanks and enjoy! JFK/KWR All material copyright J.F Kurose and K.W. Ross, All Rights Reserved Computer Networking:
17 Establishing Dial-up Connection to the Internet Using Windows 9x 1.Install and configure the modem 2.Configure Dial-Up Adapter 3.Configure Dial-Up Networking.
DoS/DDoS attack and defense
Silberschatz, Galvin and Gagne ©2011 Operating System Concepts Essentials – 8 th Edition Chapter 2: The Linux System Part 1.
COMPUTER NETWORKS Hwajung Lee. Image Source:
Network Devices and Firewalls Lesson 14. It applies to our class…
Firewalls. Overview of Firewalls As the name implies, a firewall acts to provide secured access between two networks A firewall may be implemented as.
FIREWALLS An Important Component in Computer Systems Security By: Bao Ming Soh.
© 2006 Cisco Systems, Inc. All rights reserved.Cisco Public 1 Version 4.0 Access Control Lists Accessing the WAN – Chapter 5.
Application Protocol - Network Link Utilization Capability: Identify network usage by aggregating application protocol traffic as collected by a traffic.
Could SP-NAT Save the Internet?
أمن المعلومات لـ أ. عبدالرحمن محجوب حمد mtc.edu.sd أمن المعلومات Information Security أمن المعلومات Information Security  أ. عبدالرحمن محجوب  Lec (5)
Chapter 2 Network Models
Port Scanning James Tate II
IT443 – Network Security Administration Instructor: Bo Sheng
CS222 Web Programming Course Outline
Access Control Lists CCNA 2 v3 – Module 11
Chapter 2: The Linux System Part 1
Networking Theory (part 2)
Session 20 INST 346 Technologies, Infrastructure and Architecture
Networking Theory (part 2)
Presentation transcript:

FlowScan A Network Traffic Reporting and Visualization Tool Dave Plonka

Presentation Overview  Introduction  FlowScan's Functionality  Hardware & Software Components  Sample Graphs  Short & Long Term Analyses, Events  Graphs by Autonomous Systems, Top ASNs  SubNetIO graphs  References

FlowScan A Network Traffic Reporting and Visualization Tool  FlowScan is a software package for open systems that is freely available under the terms of the GNU General Public License.  FlowScan analyzes and reports on flow data exported by Internet Protocol routers.  FlowScan produces graph images which provide a continuous, near real-time view of the network traffic across a network's border.  Development since December Beta release in September Released March 2000.

Background on Flows & Cisco NetFlow  The notion of flow profiling was introduced by the research community  Today, for performance and accounting reasons, flow profiling is built into some networking devices  Not yet standards-based  FlowScan utilizes flows defined and exported by Cisco's NetFlow feature. Essentially using the definition introduced by [ClaffyPB].  By this definition, an IP flow is a unidirectional series of IP packets of a given protocol, traveling between a source and destination, within a certain period of time.

Sample Flows ncftp GET session

Background on Flows & Cisco NetFlow  Diagram by Daniel W. McRobb, from the cflowd configuration documentation,

FlowScan's Functionality  FlowScan examines each flow and maintains counters based upon that flow's classification  FlowScan periodically reports what it finds into databases. Each database contains packet, byte, and flow counters  Counters are maintained based on these flow attributes:  IP protocol such as ICMP, TCP, and UDP  well-known service or application such as ftp-data, ftp, smtp, nntp, http, RealMedia, Quake, and Napster  the class A, B, C network, or CIDR block in which a "local" IP address resides  the AS (Autonomous System) pair between which the represented traffic was exchanged

FlowScan's Functionality

FlowScan Hardware Components  Works with most Cisco routers  Compatibility with Juniper's routers and RiverStone's Switch Router (formerly Cabletron's SSR) is being developed  Most FlowScan systems are Sun SPARC Solaris machines or Intel GNU/Linux or BSD machines  The fastest FlowScan machines appear to be multi- processor Intel PIII machines  GIF or PNG image files suitable for any web server, we use Apache

FlowScan Hardware Components

FlowScan Software Components  Perl  Perl modules  Patched cflowd  RRDtool  Unix or GNU/Linux  Cron  Make  Flowscan script  CampusIO report  SubNetIO report

Software

Short Term Analysis  Graphs over a short, recent time frame are based upon five-minute intervals.  Network abuse, such as flood-based Denial of Service attacks, are easily visible as "stalagmites" and "stalactites". These would be hidden in coarser-grained long-term graphs  This Example:  Flood of outbound 40-byte TCP RST reply packets  Flood of inbound 40-byte TCP ACK packets  Resulted in as much as 10,000 flows per second

Short Term Analysis

Short Term Analysis Bits, Packets, Flows Graphs 48 hours, 4-6 Nov 2000  2000/11/05 ~0200 -> ~1000 Apparently peering w/Abilene was down. (This was due to changes at AADS)  2000/11/05 ~0415 -> ~1100 outbound flood of UDP packets ~10,000 packets per second  2000/11/05 ~0800, ~0830 inbound flood of 1500 byte ICMP ECHO and ECHOREPLY packets destined for a campus dial-up user. This amounted to as much as 25 Mb/s.  2000/11/05 ~1400 -> ? Apparently peering w/Abilene was down again. StarTAP too. (More problems at AADS)  2000/11/06 ~0730 AADS got things back together connectivity to Abilene and StarTAP restored.

CampusIO ISP Traffic, NOV 2000  Graph by Alexander Kunz, 2000.

CampusIO University of Wisconsin - Parkside Nov 2000  Graph by Steven Premeau, 2000.

Long Term Analysis  Daily average graphs aid capacity planning and traffic shaping efforts.  This example:  Graph produced 2000/09/21 over past 550 days  academic calendar dramatically influences the traffic levels, but only to and from ResNet.  increase in outbound ftp traffic from the Computer Sciences department within the past year.  outbound traffic has consistently exceeded our inbound traffic level, the discrepancy between the two appears to be increasing.

CampusIO Long Term Analysis 550 days prior to 21 Sep 2000

CampusIO Napster Daily Averages March Through September 2000  Note that these are daily averages, five minute peak Napster traffic would be higher  Note two "horns" or spikes in late March and Septemember. These represent some of the highest outbound daily averages observed and will be explored in the subsequent slides.

CampusIO Napster Daily Averages March Through September 2000

CampusIO Events RedHat 6.2 Release C. Wednesday 29 Mar 2000  Spent an hour or two investigating increased CS traffic before coming in that morning  Found traffic to be TCP on ports >1024, host addresses indicated that it was likely to be PASV mode ftp data  Jump was from ~5Mb/s to ~30Mb/s  David Parter of CS informed me that their RedHat mirror was made active about that time

CampusIO Events RedHat 6.2 Release c. Wednesday 29 Mar 2000

CampusIO Events RedHat 7 Release "Black" Monday, 25 Sep 2000  PASV mode ftp detection built-into CampusIO by this time  Jump from 5-10Mb/s to 50-60Mb/s for CS; another RedHat mirror is in the "blue", Student Information Technology  Notice flat-topping in daily peaks. This is due to the hitting capacity of WiscNet's commodity internet connectivity to Chicago  at capacity of upstream links for nearly entire days

CampusIO Events RedHat 7 Release "Black" Monday, 25 Sep 2000

CampusIO Events "All in 2 day's work" Monday & Tuesday, Oct 2000  Note arrow of time and events occur left to right:  2000/10/ peer router upgrade, RSP4 -> RSP8, OC3 -> OC12  2000/10/ campus to peer cutover from OC3 to OC12  2000/10/ experimenting with rate-limits  2000/10/ napster.com outage?  2000/10/ byte TCP inbound DoS flood  2000/10/ ResNet -> world rate-limit applied  2000/10/ byte TCP SYN outbound DoS flood

CampusIO Events "All in 2 day's work" Monday & Tuesday, Oct 2000

 A method to visualize "events" and correlate real-world incidents with automated measurement  Working on a generalized approach for instrumenting the Internet to provide this sort of info to sites and researchers

CampusIO Events "All in 2 day's work" Monday & Tuesday, Oct 2000

CampusIO ASNs UW-Madison Peers  There is the need in large networks to determine the amount of traffic that each other Autonomous System (AS) sources, sinks, or carries for your institution  These information is used to make informed peering and provisioning decisions  UW-Madison peers with many others, most of our traffic is passed to WiscNet and Abilene

CampusIO ASNs UW-Madison Peers Wednesday & Thursday, 1-2 Nov 2000

CampusIO ASNs Top Origin ASNs

CampusIO ASNs Top "Path" ASNs

SubNetIO Report  SubNetIO is another "canned" FlowScan report  It is derived from CampusIO; It reports traffic to and from campus done by individual subnets  These examples:  WiscWorld 33.6K and 56K bps dial pool traffic; note inbound DoS attack to at about 3PM  DoIT DSL service rivals the amount of traffic with only a fraction of the number of users; graphs is more erratic because of the smaller population of users

SubNetIO Wednesday & Thursday, 1-2 Nov 2000

FlowScan Credits & Thanks  Daniel McRobb and CAIDA for cflowd  Tobi Oetiker and CAIDA for RRDtool  Perl authors and developers for perl and CPAN  Free Software Foundation for GNU  UW-Madison DoIT's Network Operations and Network Engineering Technology groups for mentoring and support

FlowScan A Network Traffic Reporting and Visualization Tool /~plonka/FlowScan/