This document discusses malicious traffic on computer networks. It defines malicious traffic as any traffic anomalies caused by hardware/software failures or intentionally modified internet packets. Several types of malicious traffic are described, including scanners, worms, spam, backscatter, and denial-of-service (DOS) attacks. Methods for detecting and preventing malicious traffic involve anomaly detection techniques, signature scanning, intrusion detection systems, quality-of-service metrics, and network filters. The conclusion emphasizes the importance of security awareness to help mitigate internet misuse.

1. MALICIOUS TRAFFIC
Presented by Ishraq Fataftah

2. Agenda
 Introduction.
 What is Malicious traffic.
 Malicious traffic types.
 Malicious traffic detection and prevention.
 Conclusion.

3. Introduction
 As the internet become more
mature, management of its resources to
provide guaranteed services is crucial.
 The success of the Internet has increased its
vulnerability to misuse and performance
problems.

4. Introduction
 It has been frequently abused by people
mostly with hostile intentions.
 We have been under various kinds of attacks
such as viruses, worms and commonly a
bunch of spam mails every day.

5. Introduction

6. Malicious Traffic
 It is hard to detect and distinguish malicious
packet and legitimate packets in the traffic.
 The behavior of Internet traffic is very far from
being regular.
 Presents large variations in its throughput at
all scales.

7. Malicious Traffic
 Any traffic anomalies that occur from hardware
or software failures to internet packets with
maliciously modified options.
 Generated from what is called botnets.

8. Malicious Traffic: Botnets

9. Malicious Traffic
 Monitoring the flow of packets.
 Malicious traffic usually exhausts the legitimate
resources by sending a lot of traffic.
 Monitoring traffic targeting unused addresses
in the network.

10. Malicious Traffic Types
 Scanners.
 Worms.
 Malicious Spam.
 Backscatters.
 DOS, DDOS.

11. Scanners
 Single source.
 Strikes the same port on many machines.
 Different ports on the same machine.
 Generates
a lot of flows.

12. Worms
 Self-replicating virus that does not alter files
but resides in active memory and duplicates
itself.
 CodeRed worm infected 395,000 computers
and resulted in approximately $2.6 billion in
damage.
 Results in an increase in service
activity, especially if service is law traffic.

13. Worms
MyTob Worm, 2005
 Copies itself as %System%msnmsgs.exe
 Adds the value: “MSN” = “msnmsgs.exe” to
IRC Server registry:
HKEY_LOCAL_MACHINESoftwareMicrosoftWindowsCurrentVersionRun
HKEY_LOCAL_MACHINESoftwareMicrosoftWindowsCurrentVersion
RunServices
HKEY_CURRENT_USERSOFTWAREMicrosoftWindowsCurrentVersionRun
HKEY_CURRENT_USERSoftwareMicrosoftOLE
HKEY_CURRENT_USERSYSTEMCurrentControlSetControlLsa
 W32.Mytob@mm runs every time Windows starts
User Zone Server Zone

14. Malicious Spam
 Spamming is flooding the network with a huge
amount of unsolicited email messages to force
people to receive them.
 Contains malware or links to malicious sites.

15. Backscatter
 Email bounces for emails that a person didn’t
send.
 Spammer is spoofing the Reply-to field in
email.
 When sent to email server, it is bounces to the
reply-to address rather than the sender.
 Used to overcome spam filters and in DOS
attacks.

16. DOS, DDOS
 Generate a huge amount of adverse traffic to a
target server to make it unavailable.
 Attempt to exhaust the resources of the victim.
 They are difficult to detect and prevent.
 DDOS attacks are simultaneously launched
from several sources destined to the same
target.

17. DOS, DDOS

18. Malicious traffic Detection and
Prevention
 Anomaly detection techniques.
 Signature-scan techniques.
 Intrusion detection and prevention systems.
 QoS metrics.
 Tools such as Snort.
 Network filters such as ACLs.
 Honeypots.

19. Anomaly detection techniques
 Differentiates between normal and malicious
traffic by:
 Studying the normal behavior of users, resources.
 Create patterns for these activities.
 Any behavior that deviates from this pattern is
considered malicious.

20. Signature-scan techniques
 Uses a database that store signatures.
 Passive scan for network traffic, any patterns
match these stored signatures are considered
malicious traffic.
 Effective for known attacks.

21. Intrusion detection and prevention
systems
 Software or hardware that is designed to
detect and prevent any malicious attack or
activity on the network.
 Monitor the network traffic.
 Analyze any suspicious event.
 Log these events and report them to the
network administrator for actions.

22. QoS metrics
 Studying the behavior of the network traffic
under normal and malicious attacks.
 Extracting parameters from network traffic.

23. Snort
 Open source tool that is used in intrusion
detection systems.
 Real time analysis on the network traffic.
 Intrusion detection system to monitor the
traffic, analyzes it and inform the network
administrator for suspicious activities.

24. ACLs
 Installed in routers and used to match packet
headers against a pre-defined list of rules and
takes pre-defined actions on any matching
packets.

25. Honeypots
“a security resource whose value lies in being
probed, attacked or compromised”
 Any attempt to interact with honeypots incurs a
malicious activity or attack.

26. Conclusion
 Malicious traffic is any traffic anomalies occurs
from failure in traffic packets that is
intentionally modified for malicious acts.
 By studying malicious attacks we can obtain
better understanding of malicious traffic and
how to detect and prevent these attacks.
 An increase in the awareness toward the
importance of security will help in mitigation
against internet misuse.