digital forensics
DESCRIPTION
Digital Forensics. Dr. Bhavani Thuraisingham The University of Texas at Dallas Application Forensics October 26, 2009. Outline. Email Forensics UTD work on Email worm detection - revisited Mobile System Forensics Note: Other Application/systems related forensics - PowerPoint PPT PresentationTRANSCRIPT
Digital Forensics
Dr. Bhavani ThuraisinghamThe University of Texas at Dallas
Application Forensics
October 26, 2009
Outline
Email Forensics- UTD work on Email worm detection - revisited- Mobile System Forensics- Note: Other Application/systems related forensics
Database forensics, Network forensics (already discussed)
- Reference: Chapters 12 and 13 of text book Military Forensics Overview
- Papers to discuss week of November 2 Optional paper to read:
- http://www.mindswap.org/papers/Trust.pdf
Email Forensics
Email Investigations Client/Server roles Email crimes and violations Email servers Email forensics tools
Email Investigations
Types of email investigations- Emails have worms and viruses – suspicious emails- Checking emails in a crime – homicide
Types of suspicious emails- Phishing emails i- they are in HTML format and redirect to
suspicious web sites- Nigerian scam- Spoofing emails
Client/Server Roles
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
- Intranet – local environment- Internet – public: example: yahoo, hotmail etc.
Email Crimes and Violations
Goal is to determine who is behind the crime such as who sent the email
Steps to email forensics- Examine email message- Copy email message – also forward email - View and examine email header: tools available for
outlook and other email clients- Examine additional files such as address books- Trace the message using various Internet tools- Examine network logs (netflow analysis)
Note: UTD Netflow tools SCRUB are in SourceForge
Email Servers
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
Email Forensics Tools
Several tools for Outlook Express, Eudora Exchange, Lotus notes
Tools for log analysis, recovering deleted emails, Examples:
- AccessData FTK- FINALeMAIL- EDBXtract- MailRecovery
Worm Detection: Introduction What are worms?
- Self-replicating program; Exploits software vulnerability on a victim; Remotely infects other victims
Evil worms- Severe effect; Code Red epidemic cost $2.6 Billion
Goals of worm detection- Real-time detection
Issues- Substantial Volume of Identical Traffic, Random Probing
Methods for worm detection- Count number of sources/destinations; Count number of failed connection
attempts Worm Types
- Email worms, Instant Messaging worms, Internet worms, IRC worms, File-sharing Networks worms
Automatic signature generation possible - EarlyBird System (S. Singh -UCSD); Autograph (H. Ah-Kim - CMU)
Email Worm Detection using Data Mining
Training data
Feature extraction
Clean or Infected ?
Outgoing Emails
ClassifierMachine Learning
Test data
The Model
Task: given some training instances of both “normal” and “viral” emails, induce a hypothesis to detect “viral” emails.
We used:Naïve BayesSVM
Assumptions
Features are based on outgoing emails. Different users have different “normal” behaviour. Analysis should be per-user basis. Two groups of features
- Per email (#of attachments, HTML in body, text/binary attachments)
- Per window (mean words in body, variable words in subject)
Total of 24 features identified Goal: Identify “normal” and “viral” emails based on
these features
Feature sets
- Per email features Binary valued Features
Presence of HTML; script tags/attributes; embedded images; hyperlinks;
Presence of binary, text attachments; MIME types of file attachments
Continuous-valued FeaturesNumber of attachments; Number of words/characters in
the subject and body- 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
Data Mining Approach
Classifier
SVM Naïve Bayesinfected?
Clean?
Clean
Clean/ Infected
Clean/ Infected
Test instance
Test instance
Data set
Collected from UC Berkeley.- 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
Our Implementation and Analysis Implementation
- Naïve Bayes: Assume “Normal” distribution of numeric and real data; smoothing applied
- SVM: with the parameter settings: one-class SVM with the radial basis function using “gamma” = 0.015 and “nu” = 0.1.
Analysis
- NB alone performs better than other techniques
- 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)
- The feature-based approach seems to be useful only when we have
identified the relevant featuresgathered enough training dataImplement classifiers with best parameter settings
Mobile Device/System Forensics
Mobile device forensics overview Acquisition procedures Summary
Mobile Device Forensics Overview
What is stored in cell phones- Incoming/outgoing/missed calls- Text messages- Short messages- Instant messaging logs- Web pages- Pictures- Calendars- Address books- Music files- Voice records
Mobile Phones
Multiple generations- Analog, Digital personal communications, Third
generations (increased bandwidth and other features) Digital networks
- CDMA, GSM, TDMA, - - - Proprietary OSs SIM Cards (Subscriber Identity Module)
- Identifies the subscriber to the network- Stores personal information, addresses books, etc.
PDAs (Personal digital assistant)- Combines mobile phone and laptop technologies
Acquisition procedures
Mobile devices have volatile memory, so need to retrieve RAM before losing power
Isolate device from incoming signals- Store the device in a special bag- Need to carry out forensics in a special lab (e.g., SAIAL)
Examine the following- 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
Mobile Forensics Tools 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
Papers to discuss: October 28, 2009 FORZA – Digital forensics investigation framework that
incorporate legal issues- http://dfrws.org/2006/proceedings/4-Ieong.pdf
A cyber forensics ontology: Creating a new approach to studying cyber forensics
- http://dfrws.org/2006/proceedings/5-Brinson.pdf Arriving at an anti-forensics consensus: Examining how to define
and control the anti-forensics problem- http://dfrws.org/2006/proceedings/6-Harris.pdf
Papers to discuss November 2-4, 2008 Forensic feature extraction and cross-drive analysis
- http://dfrws.org/2006/proceedings/10-Garfinkel.pdf A correlation method for establishing provenance of timestamps in
digital evidence- http://dfrws.org/2006/proceedings/13-%20Schatz.pdf
Applications Forensics – Part II
Dr. Bhavani ThuraisinghamThe University of Texas at Dallas
Information Warfare and Military Forensics
October 26, 2009
Outline
Information Warfare- Defensive Strategies for Government and Industry- Military Tactics- Terrorism and Information Warfare- Tactics of Private Corporations- Future IW strategies- Surveillance Tools- The Victims of Information Warfare
Military Forensics Relevant Papers
What is Information Warfare?
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
Defensive Strategies for Government and Industry
Are US and Foreign governments prepared for Information Warfare
- According to John Vacca, US will be most affected with 60% of the world’s computing power
- Stealing sensitive information as well as critical, information to cripple an economy (e.g., financial information)
What have industry groups done- 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
Defensive Strategies for Government and Industry
What are International organizations?- Think Tanks and Research agencies- Book cites several countries from Belarus to Taiwan
engaged in Economic Espionage and Information Warfare Risk-based analysis Military alliances
- Coalition forces – US, UK, Canada, Australia have regular meetings on Information Warfare
Legal implications Strong parallels between National Security and Cyber
Security
Military Tactics Supporting Technologies
- Agents, XML, Human Computer Interaction Military tactics
- Planning, Security, Intelligence Tools
- Offensive Ruinous IW tools Launching massive distributed denial of service
attacks- 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
Military Tactics Tools (continued)
- Defensive Preventive IW Tools Monitor networks
- Defensive Ruinous IW tools Information operations
- Defensive Responsive Containment IW tools Handle hacking, viruses.
Other aspects- Dealing with sustained terrorist IW tactics, Dealing with
random terrorist IW tactics
Terrorism and Information Warfare
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?
- 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?- Need super forensics tools
Tactics of Private Corporations
Defensive tactics- Open course intelligence, Gather business intelligence
Offensive tactics- Packet sniffing, Trojan horse etc.
Prevention tactics- Security techniques such as encryption
Survival tactics- Forensics tools
Future IW Tactics
Electromagnetic bomb- Technology, targeting and delivery
Improved conventional method- Virus, worms, trap doors, Trojan horse
Global positioning systems Nanotechnology developments
- Nano bombs
Surveillance Tools
Data emanating from sensors:- Video data, surveillance data- Data has to be analyzed- Monitoring suspicious events
Data mining- Determining events/activities that are abnormal
Biometrics technologies Privacy is a concern
Victims of Information Warfare
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
Military Forensics
CFX-2000: Computer Forencis Experiment 2000- Information Directorate (AFRL) partnership with
NIJ/NLECTC- Hypothesis: possible to determine the motives, intent,
targets, sophistication, identity and location of cyber terrorists by deploying an integrated forensics analysis framework
- 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
Papers to be Discussed (November 2-4, 2009)1. Cyber Forensics: a Military Perspective
https://www.utica.edu/academic/institutes/ecii/publications/articles/A04843F3-99E5-632B-FF420389C0633B1B.pdf
How to Reuse Knowledge about Forensic Investigations2. Danilo Bruschi, Mattia Monga, Universit`a degli Studi di Milanohttp://dfrws.org/2004/day3/D3-Martignoni_Knowledge_reuse.pdf3. John Lowry, BBN Systems: Adversary Modeling to Develop
Forensic Observableshttp://dfrws.org/2004/day2/
Adversary_Modeling_to_Develop_Forensic_Observables.pdf4. Dr. Golden G. Richard III, University of New Orleans, New
Orleans, LA: Breaking the Performance Wall: The Case for Distributed Digital Forensics
http://dfrws.org/2004/day2/Golden-Perfromance.pdf