Transcript Lecture26 - The University of Texas at Dallas

Data and Applications Security
Developments and Directions
Dr. Bhavani Thuraisingham
The University of Texas at Dallas
Lecture #26
Emerging Technologies in Data and Applications
Security
April 14, 2005
Outline
 Digital Identity Management
 Identity Theft Management
 Digital Forensics
 Digital Watermarking
 Risk Analysis
 Economic Analysis
 Secure Electronic Voting Machines
 Biometrics
 Other Applications
Digital Identity Management
 Digital identity is the identity that a user has to access an
electronic resource
 A person could have multiple identities
- A physician could have an identity to access medical
resources and another to access his bank accounts
 Digital identity management is about managing the multiple
identities
- Manage databases that store and retrieve identities
- Resolve conflicts and heterogeneity
- Make associations
- Provide security
 Ontology management for identity management is an
emerging research area
Digital Identity Management - II
 Federated Identity Management
- Corporations work with each other across organizational
boundaries with the concept of federated identity
- Each corporation has its own identity and may belong to
multiple federations
Individual identity management within an organization
and federated identity management across organizations
 Technologies for identity management
- Database management, data mining, ontology
management, federated computing
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Identity Theft Management
 Need for secure identity management
- Ease the burden of managing numerous identities
- Prevent misuse of identity: preventing identity theft
 Identity theft is stealing another person’s digital identity
 Techniques for preventing identity thefts include
- Access control, Encryption, Digital Signatures
- A merchant encrypts the data and signs with the public
-
key of the recipient
Recipient decrypts with his private key
Digital Forensics
 Digital forensics is about the investigation of Cyber crime
 Follows the procedures established for Forensic medicine
 The steps include the following:
- When a computer crime occurs, law enforcement officials
-
who are cyber crime experts gather every piece of
evidence including information from the crime scene (i.e.
from the computer)
Gather profiles of terrorists
Use history information
Carry pout analysis
Digital Forensics - II
 Digital Forensics Techniques
- Intrusion detection
- Data Mining
- Analyzing log files
- Use criminal profiling and develop a psychological
profiling
- Analyze email messages
 Lawyers, Psychologists, Sociologists, Crime investigators
and Technologists have to worm together
 International Journal of Digital Evidence is a useful source
Steganography and Digital Watermarking
 Steganography is about hiding information within other
information
- E.g., hidden information is the message that terrorist may
be sending to their pees in different parts of the worlds
- Information may be hidden in valid texts, images, films
etc.
- Difficult to be detected by the unsuspecting human
 Steganalysis is about developing techniques that can analyze
text, images, video and detect hidden messages
- May use data mining techniques to detect hidden patters
 Steganograophy makes the task of the Cyber crime expert
difficult as he/she ahs to analyze for hidden information
- Communication protocols are being developed
Steganography and Digital Watermarking - II
 Digital water marking is about inserting information without
being detected for valid purposes
- It has applications in copyright protection
- A manufacturer may use digital watermarking to copyright
a particular music or video without being noticed
- When music is copies and copyright is violated, one can
detect two the real owner is by examining the copyright
embedded in the music or video
Risk Analysis
 Analyzing risks
- Before installing a secure system or a network one needs
to conduct a risk analysis study
- What are the threats? What are the risks?
 Various types of risk analysis methods
Quantitative approach: Events are ranked in the order of
risks and decisions are made based on then risks
Qualitative approach: estimates are used for risks
-
Economics Analysis
 Security vs Cost
- If risks are high and damage is significant then it may be
worth the cost of incorporating security
- If risks and damage are not high, then security may be an
additional cost burden
 Economists and technologists need to work together
- Develop cost models
- Cost vs. Risk/Threat study
Secure Electronic Voting Machines
 We are slowly migrating to electronic voting machines
 Current electronic machines have many security
vulnerabilities
 A person can log into the system multiple times from different
parts of the country and cast his/her vote
 Insufficient techniques for ensuring that a person can vote
only once
 The systems may be attacked and compromised
 Solutions are being developed
 Johns Hopkins University is one of the leaders in the field of
secure electronic voting machines
Biometrics
 Early Identication and Authentication (I&A) systems, were
based on passwords
 Recently physical characteristics of a person are being sued
for identification
- Fingerprinting
- Facial features
- Iris scans
- Blood circulation
- Facial expressions
 Biometrics techniques will provide access not only to
computers but also to building and homes
 Other Applications
Biometric Technologies
 Pattern recognition
 Machine learning
 Statistical reasoning
 Multimedia/Image processing and management
 Managing biometric databases
 Information retrieval
 Pattern matching
 Searching
 Ontology management
 Data mining
Data Mining for Biometrics
 Determine the data to be analyzed
- Data may be stored in biometric databases
- Data may be text, images, video, etc.
 Data may be grouped using classification techniques
 As new data arrives determine the group this data belongs to
- Pattern matching, Classification
 Determine what the new data is depending on the prior
examples and experiments
 Determine whether the new data is abnormal or normal
behavior
 Challenge: False positives, False negatives
Secure Biometrics
 Biometrics systems have to be secure
 Need to study the attacks for biometrics systems
 Facial features may be modified:
- E.g., One can access by inserting another person’s
features
Attacks on biometric databases is a major concern
 Challenge is to develop a secure biometric systems
-
Secure Biometrics - II
 Security policy for as biometric system
- Application specific and applicatyion independent
policies
- Security constraints
 Security model for a biometrics systems
Determine the operations to be performed
- Need to include both text, images and video/animation
 Architecure foe a biometric system
- Need to idenify securiy critical components
Reference monitor
 Detecting intrusions in a biometric system
-
-
Other Applications
 Email security
- Encryption
- Filtering
- Data mining
 Benchmarking
- Benchmarks for secure queries and transactions
 Simulation and performance studies
 Security for machine translation and text summarization
 Covert channel analysis
 Robotics security
- Need to ensure policies are enforced correctly when
operating robots