Dr. Bhavani Thuraisingham
The University of Texas at Dallas
Network and Application Forensics
September 28, 2011

 Network Forensics
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Network Attacks
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Security Measures
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Network Forensics and Tools
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Types of Networks
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Other info
 Summary/Conclusion and Links
 Special presentation of network forensic
 http://www.infragard.net/library/congress_05/computer_foren sics/network_primer.pdf

 Denial of service
Denial of service attacks cause the service or program to cease functioning or prevent others from making use of the service or program.
 These may be performed at the network layer by sending carefully crafted and malicious datagrams that cause network connections to fail.
 They may also be performed at the application layer, where carefully crafted application commands are given to a program that cause it to become extremely busy or stop functioning.
 Preventing suspicious network traffic from reaching hosts and preventing suspicious program commands and requests are the best ways of minimizing the risk of a denial of service attack.
 It is useful to know the details of the attack method, so you should educate yourself about each new attack as it gets publicized.

 Spoofing
This type of attack causes a host or application to mimic the actions of another.
 Typically the attacker pretends to be an innocent host by following IP addresses in network packets.
 For example, a well-documented exploit of the BSD rlogin service can use this method to mimic a TCP connection from another host by guessing TCP sequence numbers.
 To protect against this type of attack, verify the authenticity of datagrams and commands.
 Prevent datagram routing with invalid source addresses. Introduce unpredictablility into connection control mechanisms, such as TCP sequence numbers and the allocation of dynamic port addresses .

 Eavesdropping
This is the simplest type of attack.
 A host is configured to "listen" to and capture data not belonging to it.
Carefully written eavesdropping programs can take usernames and passwords from user login network connections.
 Broadcast networks like Ethernet are especially vulnerable to this type of attack.
 To protect against this type of threat, avoid use of broadcast network technologies and enforce the use of data encryption.
 IP firewalling is very useful in preventing or reducing unauthorized access, network layer denial of service, and IP spoofing attacks.
 It not very useful in avoiding exploitation of weaknesses in network services or programs and eavesdropping.

 Need measures to secure a network and prevent breaches
 Apply patches; User a layered network defense strategy
 NSA (National Security Agency) ahs developed DiD Defense in Depth) and has three models of protection
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People, Technology, Operations
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People: Employees are trained well
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Technology: Strong network architecture and testing tools
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Operations: applying security patches, anti-virus software, etc.

 Network security starts from authenticating any user, most likely a username and a password.
 Once authenticated, a stateful firewall enforces access policies such as what services are allowed to be accessed by the network users
 Though effective to prevent unauthorized access, this component fails to check potentially harmful contents such as computer worms being transmitted over the network.
 An intrusion prevention system (IPS) helps detect and prevent such malware. IPS also monitors for suspicious network traffic for contents, volume and anomalies to protect the network from attacks such as denial of service.
 Communication between two hosts using the network could be encrypted to maintain privacy.
 Individual events occurring on the network could be tracked for audit purposes and for a later high level analysis .

 Honeypots , essentially decoy network-accessible resources, could be deployed in a network as surveillance and earlywarning tools.
 Techniques used by the attackers that attempt to compromise these decoy resources are studied during and after an attack to keep an eye on new exploitation techniques.
 Such analysis could be used to further tighten security of the actual network being protected by the honeypot
 Some tools: Firewall, Antivirus software and Internet Security
Software. For authentication , use strong passwords and change it on a bi-weekly/monthly basis. When using a wireless connection, use a robust password. Network analyzer to monitor and analyze the network.

 What is Network Forensics?
http://searchsecurity.techtarget.com/sDefinition/0,,sid14_ gci859579,00.html
 Network Forensics Analysis
 Relationship to Honeynets/Honeypots
 Policies for Networks Forensics
 Example Prototype System
 Some Popular Networks Forensics Analysis Tools (NFAT)

 Network forensics is the process of capturing information that moves over a network and trying to make sense of it in some kind of forensics capacity.
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Network forensics is the capture, recording, and analysis of network events in order to discover the source of security attacks or other problem incidents.
 A network forensics appliance is a device that automates this process.
 Wireless forensics is the process of capturing information that moves over a wireless network and trying to make sense of it in some kind of forensics capacity.

 Network forensics systems can be one of two kinds:
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"Catch-it-as-you-can" systems, in which all packet s passing through a certain traffic point are captured and written to storage with analysis being done subsequently in batch mode. This approach requires large amounts of storage, usually involving a RAID system.
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"Stop, look and listen" systems, in which each packet is analyzed in a rudimentary way in memory and only certain information saved for future analysis. This approach requires less storage but may require a faster processor to keep up with incoming traffic.

 Network Forensics is the process of collecting and analyzing raw network data and then tracking network traffic to determine how an attack took place
 When intruders break into a network they leave a trail. Need to spot variations in network traffic; detect anomalies
 Network forensics can usually help to determine whether network has been attacked or there is a user error
 Examiners must establish standards procedures to carry out forensics

 Find analysis techniques developed for one type of network and apply it to another type of network
 Types of networks
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Computer and Communication Networks
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Telecommunication Network
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Transportation networks
 Highways, Railroad, Air Traffic
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Human networks
 Terror networks, Relationship networks

 IDS attempts to detect activity that violates an organization’s security policy by implementing a set of rules describing preconfigures patterns of interest
 Firewall allows or disallows traffic to or from specific networks, machine addresses and port numbers
 NFAT synergizes with IDSs and Firewalls.
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Preserves long term record of network traffic
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Allows quick analysis of trouble spots identified by IDSs and Firewalls
 NFATs must do the following:
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Capture network traffic
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Analyze network traffic according to user needs
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Allow system users discover useful and interesting things about the analyzed traffic

 Traffic Capture
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What is the policy?
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What is the traffic of interest?
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Intermal/Externasl?
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Collect packets: tcpdump
 Traffic Analysis
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Sessionizing captured traffic (organize)
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Protocol Parsing and analysis
 Check for strings, use expert systems for analysis
 Interacting with NFAT
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Appropriate user interfaces, reports, examine large quantities of information and make it manageable

 NetworkMiner is a Network Forensic Analysis Tool (NFAT) for
Windows.
 NetworkMiner can be used as a passive network sniffer /packet capturing tool in order to detect operating systems, sessions, hostnames, open ports etc. without putting any traffic on the network.
 The purpose of NetworkMiner is to collect data (such as forensic evidence) about hosts on the network rather than to collect data regarding the traffic on the network.
 The main view is host centric (information grouped per host) rather than packet centric (information showed as a list of packets/frames).

 Network Forensics and honeynet systems have the same features of collecting information about computer misuses
 Honeynet system can lure attackers and gain information about new types of intrusions
 Network forensics systems analyze and reconstruct he attack behaviors
 These two systems integrated together build a active self learning and response system to profile the intrusion behavior features and investigate the original source of the attack.

 Honeynet project was established to make information about network attacks and solutions widely available
 Objectives: Awareness, information, tools
 Attacks: distributed Denial of Service, Zero day attacks
 Honeypot is a computer set up to lure attackers
 Honeywalls are computers set up to monitor what is happening to the honeypots in the network

 Probing
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Attackers reconnaissance
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Attackers create a profile of an organization's structure, network capabilities and content, security posture
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Attacker finds the targets and devices plans to circumvent the security mechanism
 Penetration
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Exploit System Configuration errors and vulnerabilities
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Install Trojans, record passwords, delete files, etc.
 Cover tracks
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Configure event logging to a previous state
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Clear event logs and hide files

 Retaining information
 Planning the response
 Training
 Accelerating the investigation
 Preventing anonymous activities
 Protect the evidence

 Network Forensics Analysis mechanisms should meet the following:
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Short response times; User friendly interfaces
 Questions addresses
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How likely is a specific host relevant to the attack? What is the role the host played in the attack? How strong are two hosts connected to the attack?
 Features of the prototype
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Preprocessing mechanism to reduce redundancy in intrusion alerts
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Graph model for presenting and interacting with th3 evidence
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Hierarchical reasoning framework for automated inference of attack group identification

 Evidence collection module
 Evidence preprocessing module
 Attack knowledge base
 Assets knowledge base
 Evidence graph generation module
 Attack reasoning module
 Analyst interface module
 Reference
 http://delivery.acm.org/10.1145/1420000/1410238/a4wang.pdf?key1=1410238&key2=9838895521&coll=GUIDE&dl=
GUIDE&CFID=57276464&CFTOKEN=77054716
 https://www.dfrws.org/2005/proceedings/wang_evidencegrap hs.pdf

 Network Forensics tools help in the monitoring of the network
 Example: the records that Ps tools generate can prove that an employee ran a program without permission
 Can also monitor machines/processes that may be harmful
 Problem is the attacker can get administrator rights and start using the tools
 Chapter 11 discusses tools for Windows and Linux

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Raytheon’s SilentRunner
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Gives administrators help as they attempt to protect their company’s assets
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Collector, Analyzer and Visualize Modules
Sandstorm Enterprise’s NetIntercept
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Hardware appliance focused on capturing network traffic
Niksun’s NetDetector
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Its an appliance like NetIntercept
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Has an alerting mechanism
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Integrates with Cicso IDS for a complete forensic analysis

 Open source tools
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Wireshark
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Kismet
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Snort
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OSSEC
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NetworkMiner is an open source Network Forensics Tool available at SourceForge .
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Xplico is an Internet/IP Traffic Decoder (NFAT). Protocols supported: HTTP, SIP, FTP, IMAP, POP, SMTP, TCP, UDP,
IPv4, IPv6

 Deep Analysis Tools (data mining based tools)
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E-Detective
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ManTech International Corporation
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Network Instruments
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NIKSUN's NetDetector
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PacketMotion
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Sandstorm's NetIntercept
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Mera Systems NetBeholder
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InfoWatch Traffic Monitor

 Flow-Based Systems
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Arbor Networks
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GraniteEdge Networks
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Lancope http://www.lancope.com/
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Mazu Networks http://www.mazunetworks.com/
 Hybrid Systems
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These systems combine flow analysis, deep analysis, and security event monitoring and reporting.
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Q1 Labs http://www.q1labs.com/

 Insert bootable forensics CD in the suspect system
 Keep a log of all the actions
 Send collected information to a network drive
 Copy the physical memory
 Determine if root kit is present; access system’s firmware, - -
 Get forensics hash value of all files

 Setup NetCat listener to send the forensics data
 Load Helix CD in the CD-ROM drive
 Click appropriate buttons – System Information; Glad arrow etc
 Click Acquire Live Image if Widows System
 Connect to NetCat listener to send the collected data (e.g., enter IP address of NetCat listener)
 Click Incidence Response Tools
 Click on appropriate tools to collect data

 Standard installation image, hash schemes (e.g., MD5, SHA-1)
 Fix vulnerabilities if intrusion is detected
 Retrieve volatile data (RAM, processes)
 Acquire compromised drive and make forensics image of it
 Compare forensics image and standard image and determine if anything has changed

 Network logs record traffic in and out of network
 Network servers, routers, firewalls record activities and events that move through them
 One ways is to run Tcpdump
 When viewing network log, port information can give clues about suspicious activity
 Use network analysis tool

 Devices or software to monitor (sniff) traffic
 TCP/IP sniffers operate at the Packet level; in OSI operates at the Layer 2 or 3 level (e.g. Data link or Network layers)
 Some sniffers perform packet captures, some perform analysis and some perform both
 Tools exist for examining (i) packets with certain flags set (ii) email headers (iii) IRC chats

 Network Forensics is the process of collecting and analyzing raw network data and then tracking network traffic to determine how an attack took place
 Layered defense strategies to the network architecture
 Live acquisitions are needed to retrieve volatile items
 Standard procedure are needed to establish how to proceed after a network attack occurs
 By monitoring network traffic can establish normal operations; then determine if there is an anomaly
 Network tools used to monitor networks; but intruders can get admin rights to attack from the inside
 Tools are available for monitoring network traffic for both
Windows and Linux systems
 Honeynet project enables people to learn latest intrusion techniques

 https://www.dfrws.org/2005/proceedings/wang_evidencegraphs.pdf
 http://www.cs.fsu.edu/~yasinsac/Papers/MY01.pdf
 http://www.sandstorm.net/support/netintercept/downloads/niieee.pdf
 http://www.giac.org/certified_professionals/practicals/gsec/2478.php
 http://www.infragard.net/library/congress_05/computer_forensics/net work_primer.pdf
 http://dfrws.org/2003/presentations/Brief-Casey.pdf
 http://delivery.acm.org/10.1145/1070000/1066749/p302ren.pdf?key1=1066749&key2=0512850911&coll=GUIDE&dl=GUIDE&C
FID=36223233&CFTOKEN=49225512
 http://dfrws.org/

 Email Forensics
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UTD work on Email worm detection - revisited
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Mobile System Forensics
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Note: Other Application/systems related forensics
 Database forensics, Network forensics (already discussed)
 Military Forensics Overview
 Optional paper to read:
http://www.mindswap.org/papers/Trust.pdf

 Email Investigations
 Client/Server roles
 Email crimes and violations
 Email servers
 Email forensics tools

 Types of email investigations
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Emails have worms and viruses – suspicious emails
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Checking emails in a crime – homicide
 Types of suspicious emails
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Phishing emails i- they are in HTML format and redirect to suspicious web sites
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Nigerian scam
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Spoofing emails

 Client-Server architecture
 Email servers runs the email server programs – example
Microsoft Exchange Server
 Email runs the client program – example Outlook
 Identitication/authntictaion is used for client to access the server
 Intranet/Internet email servers
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Intranet – local environment
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Internet – public: example: yahoo, hotmail etc.

 Goal is to determine who is behind the crime such as who sent the email
 Steps to email forensics
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Examine email message
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Copy email message – also forward email
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View and examine email header: tools available for outlook and other email clients
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Examine additional files such as address books
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Trace the message using various Internet tools
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Examine network logs (netflow analysis)
 Note: UTD Netflow tools SCRUB are in SourceForge

 Need to work with the network administrator on how to retrieve messages from the server
 Understand how the server records and handles the messages
 How are the email logs created and stored
 How are deleted email messages handled by the server? Are copies of the messages still kept?
 Chapter 12 discussed email servers by UNIX, Microsoft,
Novell

 Several tools for Outlook Express, Eudora Exchange, Lotus notes
 Tools for log analysis, recovering deleted emails,
 Examples:
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AccessData FTK
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FINALeMAIL
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EDBXtract
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MailRecovery

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What are worms?
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Self-replicating program; Exploits software vulnerability on a victim;
Remotely infects other victims
Evil worms
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Severe effect; Code Red epidemic cost $2.6 Billion
Goals of worm detection
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Real-time detection
Issues
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Substantial Volume of Identical Traffic, Random Probing
Methods for worm detection
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Count number of sources/destinations; Count number of failed connection attempts
Worm Types
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Email worms, Instant Messaging worms, Internet worms, IRC worms, Filesharing Networks worms
Automatic signature generation possible
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EarlyBird System (S. Singh -UCSD); Autograph (H. Ah-Kim - CMU)

Task: given some training instances of both
“normal” and “viral” emails, induce a hypothesis to detect “viral” emails.
We used:
Naïve Bayes
SVM
Outgoing
Emails
Test data
Feature extraction
Machine
Learning
Classifier
Training data
Clean or Infected ?

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Features are based on outgoing emails.
Different users have different “normal” behaviour.
 Analysis should be per-user basis.
 Two groups of features
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Per email (#of attachments, HTML in body, text/binary attachments)
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Per window (mean words in body, variable words in subject)
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Total of 24 features identified
Goal: Identify “normal” and “viral” emails based on these features

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Per email features
 Binary valued Features
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Presence of HTML; script tags/attributes; embedded images; hyperlinks;
Presence of binary, text attachments; MIME types of file attachments
Continuous-valued Features
Number of attachments; Number of words/characters in the subject and body
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Per window features
 Number of emails sent; Number of unique email recipients;
Number of unique sender addresses; Average number of words/characters per subject, body; average word length:;
Variance in number of words/characters per subject, body;
Variance in word length
 Ratio of emails with attachments

Test instance
Test instance
SVM
Classifier infected
?
Naïve Bayes
Clean
?
Clean/
Infected
Clean/
Infected
Clean

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Collected from UC Berkeley.
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Contains instances for both normal and viral emails.
Six worm types:
bagle.f, bubbleboy, mydoom.m,
mydoom.u, netsky.d, sobig.f
Originally Six sets of data:
training instances: normal (400) + five worms (5x200)
testing instances: normal (1200) + the sixth worm (200)
Problem: Not balanced, no cross validation reported
Solution: re-arrange the data and apply cross-validation

 Implementation
Naïve Bayes: Assume “Normal” distribution of numeric and real data; smoothing applied
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SVM: with the parameter settings: one-class SVM with the radial basis function using “gamma” = 0.015 and “nu” = 0.1.
 Analysis
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NB alone performs better than other techniques
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SVM alone also performs better if parameters are set correctly
mydoom.m and VBS.Bubbleboy data set are not sufficient (very low detection accuracy in all classifiers)
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The feature-based approach seems to be useful only when we have identified the relevant features gathered enough training data
Implement classifiers with best parameter settings

 Mobile device forensics overview
 Acquisition procedures
 Summary

 What is stored in cell phones
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Incoming/outgoing/missed calls
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Text messages
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Short messages
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Instant messaging logs
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Web pages
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Pictures
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Calendars
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Address books
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Music files
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Voice records

 Multiple generations
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Analog, Digital personal communications, Third generations (increased bandwidth and other features)
 Digital networks
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CDMA, GSM, TDMA, - - -
 Proprietary OSs
 SIM Cards (Subscriber Identity Module)
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Identifies the subscriber to the network
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Stores personal information, addresses books, etc.
 PDAs (Personal digital assistant)
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Combines mobile phone and laptop technologies

 Mobile devices have volatile memory, so need to retrieve RAM before losing power
 Isolate device from incoming signals
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Store the device in a special bag
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Need to carry out forensics in a special lab (e.g., SAIAL)
 Examine the following
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Internal memory, SIM card, other external memory cards,
System server, also may need information from service provider to determine location of the person who made the call

 Reads SIM Card files
 Analyze file content (text messages etc.)
 Recovers deleted messages
 Manages PIN codes
 Generates reports
 Archives files with MD5, SHA-1 hash values
 Exports data to files
 Supports international character sets

 Information Warfare
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Defensive Strategies for Government and Industry
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Military Tactics
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Terrorism and Information Warfare
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Tactics of Private Corporations
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Future IW strategies
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Surveillance Tools
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The Victims of Information Warfare
 Military Forensics
 Relevant Papers

 Information warfare is the use and management of information in pursuit of a competitive advantage over an opponent. Information warfare may involve collection of tactical information, assurance that one's own information is valid, spreading of propaganda or disinformation to demoralize the enemy and the public, undermining the quality of opposing force information and denial of information collection opportunities to opposing forces.
 http://en.wikipedia.org/wiki/Information_warfare

 Are US and Foreign governments prepared for Information
Warfare
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According to John Vacca, US will be most affected with
60% of the world’s computing power
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Stealing sensitive information as well as critical, information to cripple an economy (e.g., financial information)
 What have industry groups done
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IT-SAC: Information Technology Information Sharing and
Analysis
 Will strategic diplomacy help with Information Warfare?
 Educating the end user is critical according to John Vacca

 What are International organizations?
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Think Tanks and Research agencies
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Book cites several countries from Belarus to Taiwan engaged in Economic Espionage and Information Warfare
 Risk-based analysis
 Military alliances
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Coalition forces – US, UK, Canada, Australia have regular meetings on Information Warfare
 Legal implications
 Strong parallels between National Security and Cyber
Security

 Supporting Technologies
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Agents, XML, Human Computer Interaction
 Military tactics
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Planning, Security, Intelligence
 Tools
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Offensive Ruinous IW tools
 Launching massive distributed denial of service attacks
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Offensive Containment IW tools
 Operations security, Military deception, Psychological operations, Electronic warfare (use electromagnetic energy), Targeting: Disable enemy's C2 (c0mmand and control) system and capability

 Tools (continued)
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Defensive Preventive IW Tools
 Monitor networks
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Defensive Ruinous IW tools
 Information operations
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Defensive Responsive Containment IW tools
 Handle hacking, viruses.
 Other aspects
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Dealing with sustained terrorist IW tactics, Dealing with random terrorist IW tactics

 Terrorists are using the web to carry out terrorism activities
 What are the profiles of terrorists? Are they computer literate?
 Hacker controlled tanks, planes and warships
 Is there a Cyber underground network?
 What are their tools?
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Information weapons, HERF gun (high power radio energy at an electronic target), Electromagnetic pulse. Electric power disruptive technologies
 Why are they hard to track down?
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Need super forensics tools

 Defensive tactics
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Open course intelligence, Gather business intelligence
 Offensive tactics
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Packet sniffing, Trojan horse etc.
 Prevention tactics
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Security techniques such as encryption
 Survival tactics
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Forensics tools

 Electromagnetic bomb
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Technology, targeting and delivery
 Improved conventional method
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Virus, worms, trap doors, Trojan horse
 Global positioning systems
 Nanotechnology developments
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Nano bombs

 Data emanating from sensors:
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Video data, surveillance data
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Data has to be analyzed
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Monitoring suspicious events
 Data mining
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Determining events/activities that are abnormal
 Biometrics technologies
 Privacy is a concern

 Loss of money and funds
 Loss of shelter, food and water
 Spread of disease
 Identity theft
 Privacy violations
 Death and destruction
 Note: Computers can be hacked to loose money and identity; computers can be used to commit a crime resulting in death and destruction

 CFX-2000: Computer Forencis Experiment 2000
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Information Directorate (AFRL) partnership with
NIJ/NLECTC
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Hypothesis: possible to determine the motives, intent, targets, sophistication, identity and location of cyber terrorists by deploying an integrated forensics analysis framework
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Tools included commercial products and research prototypes
http://www.afrlhorizons.com/Briefs/June01/IF0016.html
http://rand.org/pubs/monograph_reports/MR1349/MR1349.
appb.pdf

Dr. Bhavani Thuraisingham
The University of Texas at Dallas
Appendix
Social Network Analysis and Forensics
October 8, 2010