distributed intrusion detection

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Distributed Intrusion Detection Mamata Desai (99305903) M.Tech.,CSE dept, IIT Bombay

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Distributed Intrusion Detection. Mamata Desai (99305903) M.Tech.,CSE dept, IIT Bombay. Overview. What is intrusion ? Dealing with intrusion Intrusion detection principles Our problem definition Packages analyzed Our approach Experiments and Results Conclusions. What is intrusion ?. - PowerPoint PPT Presentation

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Page 1: Distributed Intrusion Detection

Distributed Intrusion Detection

Mamata Desai (99305903)

M.Tech.,CSE dept,

IIT Bombay

Page 2: Distributed Intrusion Detection

Overview

What is intrusion ? Dealing with intrusion Intrusion detection principles Our problem definition Packages analyzed Our approach Experiments and Results Conclusions

Page 3: Distributed Intrusion Detection

What is intrusion ? The potential possibility of a deliberate

unauthorized attempt to:1. Access information2. Manipulate information3. Render a system unreliable or unusable

Types of intrusions:– External attacks

• Password cracks, network sniffing, machine & services discovery utilities, packet spoofing, flooding utilities, DOS attacks

– Internal penetrations – Masqueraders, clandestine users

– Misfeasors – authorized misuse

Page 4: Distributed Intrusion Detection

Example attacks

Password cracking Buffer overflow Network reconnaissance Denial of service (DoS) IP spoofing

Page 5: Distributed Intrusion Detection

Dealing with intrusion Prevention

– isolate from n/w, strict auth, encryption

Preemption – “do unto others, before they do unto you”

Deterrence – dire warnings: “we have a bomb too”

Deflection – diversionary techniques to lure away

Counter measures Detection

Page 6: Distributed Intrusion Detection

Intrusion Detection principles

Anomaly-based– Form an opinion on what constitutes “normal”,

and decide on a threshold to flag as “abnormal”– Cannot distinguish illegal from abnormal

Signature-based– Model signatures of previous attacks and flag

matching patterns– Cannot detect new intrusions

Compound

Page 7: Distributed Intrusion Detection

System characteristics

Time of detection Granularity of data processing Source of audit data Response to detected intrusions

– passive v/s active Locus of data-processing Locus of data-collection Security Degree of inter-operability

Page 8: Distributed Intrusion Detection

Host-based v/s Network-based IDS

Host-based IDS1. Verifies success or failure of an attack

2. Monitors specific system activities

3. Detects attacks that n/w based systems miss

4. Well-suited for encrypted and switched environments

5. Near-real-time detection and response

6. Requires no additional hardware

7. Lower cost of entry

Page 9: Distributed Intrusion Detection

…contd.

Network-based IDS1. Lower cost of ownership

2. Detects attacks that host-based systems miss

3. More difficult for an attacker to remove evidence

4. Real-time detection and response

5. Detects unsuccessful attacks and malicious intent

6. Operating system independence

7. Performance issues

Page 10: Distributed Intrusion Detection

Our problem definition

Portscanning Our laboratory setup

– Multiple machines with similar configuration

Portscan on a single machine Distributed portscan - Small evasive scans

on multiple machines Aim – Detect such distributed scans

Page 11: Distributed Intrusion Detection

Typical lab setup

Page 12: Distributed Intrusion Detection

Types of Portscans

Scan types:– TCP connect() scan– Stealth SYN scan– Stealth FIN scan– Xmas scan– Null scan

Scan sweeps:– One-to-one, one-to-many, many-to-one, many-

to-many

Page 13: Distributed Intrusion Detection

Source TargetNetwork Messages

Send SYN, seq=x

Receive SYN segment

Send SYN, seq=y, ACK x+1Receive SYN +ACK segment

Send ACK y+1

Receive ACK segment

Send ACK+FIN+RST

Receive ACK+FIN+RST

… more packet exchanges

Normal sequence of packets

Page 14: Distributed Intrusion Detection

Source TargetNetwork Messages

Send SYN, seq=x

Receive SYN segment

Send SYN, seq=y, ACK x+1Receive SYN +ACK segment

Send RST

Receive RST

Stealth SYN scan

Page 15: Distributed Intrusion Detection

Source TargetNetwork Messages

Stealth FIN scan

Send FIN

Receive FIN

Page 16: Distributed Intrusion Detection

Source TargetNetwork Messages

Stealth Xmas scan

Send FIN+PSH+URG

Receive FIN+PSH+URG

Page 17: Distributed Intrusion Detection

Packages analyzed

Sniffit (http://sniffit.rug.ac.be/sniffit/sniffit.html)

– A network sniffer for TCP/UDP/ICMP packets

– Interactive mode

Tcpdump (http://www.tcpdump.org)

– A tool for network monitoring and data acquisition

Nmap (http://www.nmap.org)

– “Network mapper” for network exploration, security auditing

– Various types of TCP/UDP scans, ping scans

Page 18: Distributed Intrusion Detection

…contd Portsentry (http://www.psionic.com/abacus/portsentry)

– Host-based TCP/UDP portscan detection and active defense system

– Stealth scan detection

– Reacts to portscans by blocking hosts

– Internal state engine to remember previously connected hosts

– All violations reported to syslog

Snort (http://www.snort.org)

– Network-based IDS – real-time analysis and traffic logging

– Content searching/matching to detect attacks and probes – buffer overflows, CGI attacks, SMB probes, OS fingerprinting attacks

– Rules language to describe traffic to collect or pass

– Alerts via syslog, user files, WinPopUp messages

– 3 functional modes – sniffer, packet logger, NIDS

Page 19: Distributed Intrusion Detection

…contd

Portsentry– Binds to all ports to be monitored– A static “list” of ports monitored– State engine – different hosts

Snort– Preprocessor – connections to P ports in T

seconds– V1.8 – only one-to-one and one-to-many

portscans detected

Page 20: Distributed Intrusion Detection

Our approach Pick up network packets Based on which type of portscan is to be

analyzed, identify the scan signature Add each source and target IP address, to

the correlation lists Use the correlation lists to infer the scan

sweep – one-to-one, one-to-many, many-to-one, many-to-many

Page 21: Distributed Intrusion Detection

Experimental Setup

Page 22: Distributed Intrusion Detection

Detection algorithm

Examine each TCP packet on the network. Extract source and target IP addrs and ports. For each scan type to be detected, maintain

a list of “valid” connections. When a scan signature is detected, add

source and target IP addrs to 2 correlation lists pointed to by srcIP and tarIP, remove entry from connections list.

Page 23: Distributed Intrusion Detection

…contd

Identical correlation lists record source and target IP addrs info, along with number of scans.

Scan sweeps one-to-one, one-to-many, many-to-one, and many-to-many are detected by passes thru the correlation lists.

Page 24: Distributed Intrusion Detection
Page 25: Distributed Intrusion Detection

ExperimentsSource Target TCP ports

pro-13 pro-19 25, 119

pro-15 pro-21 21, 23, 80

pro-17 pro-23 22, 79

Source Target TCP ports

pro-13 pro-19

pro-21

pro-23

7, 20, 21

22, 23, 25, 53

69, 79, 80, 88

pro-15 pro-19

pro-21

110, 111, 119

139, 143, 194, 220

One-to-one scan

One-to-many scan

Page 26: Distributed Intrusion Detection

…contdSource Target TCP ports

pro-13 pro-21 443, 513, 518

pro-15 pro-21 873, 3130, 6667

pro-17 pro-21 107, 20, 21, 23

Source Target TCP ports

pro-13 pro-19

pro-21

pro-23

7, 20, 21, 79

80, 113, 119, 139

143, 194, 667

pro-15 … …

pro-17 … …

Many-to-one scan

Many-to-many scan

Page 27: Distributed Intrusion Detection

Conclusions

All the scans performed by nmap were detected successfully by our detector and the correlations were accurate.

Some stray incidents of ident lookups did get classified as scans, due to the way closed ports behave.