Transcript Lecture 2 - The University of Texas at Dallas

Digital Forensics
Dr. Bhavani Thuraisingham
The University of Texas at Dallas
Lecture #2
Supporting Technologies
August 27, 2008
Objective of the Unit
 This unit will provide an overview of the supporting technologies
Outline of Part I: Information Security
 Operating Systems Security
 Network Security
 Designing and Evaluating Systems
 Web Security
 Other Security Technologies
Operating System Security
 Access Control
- Subjects are Processes and Objects are Files
- Subjects have Read/Write Access to Objects
- E.g., Process P1 has read acces to File F1 and write access to
File F2
 Capabilities
- Processes must presses certain Capabilities / Certificates to
access certain files to execute certain programs
- E.g., Process P1 must have capability C to read file F
Mandatory Security
 Bell and La Padula Security Policy
- Subjects have clearance levels, Objects have sensitivity levels;
clearance and sensitivity levels are also called security levels
- Unclassified < Confidential < Secret < TopSecret
- Compartments are also possible
- Compartments and Security levels form a partially ordered
lattice
 Security Properties
- Simple Security Property: Subject has READ access to an object
of the subject’s security level dominates that of the object
- Star (*) Property: Subject has WRITE access to an object if the
subject’s security level is dominated by that of the object
Covert Channel Example
 Trojan horse at a higher level covertly passes data to a Trojan
horse at a lower level
 Example:
- File Lock/Unlock problem
- Processes at Secret and Unclassified levels collude with
one another
- When the Secret process lock a file and the Unclassified
process finds the file locked, a 1 bit is passed covertly
- When the Secret process unlocks the file and the
Unclassified process finds it unlocked, a 1 bit is passed
covertly
- Over time the bits could contain sensitive data
Network Security
 Security across all network layers
- E.g., Data Link, Transport, Session, Presentation,
Application
 Network protocol security
Ver5ification and validation of network protocols
 Intrusion detection and prevention
- Applying data mining techniques
 Encryption and Cryptography
 Access control and trust policies
 Other Measures
- Prevention from denial of service, Secure routing, - - -
-
Data Security: Access Control
 Access Control policies were developed initially for file systems
- E.g., Read/write policies for files
 Access control in databases started with the work in System R and
Ingres Projects
- Access Control rules were defined for databases, relations,
tuples, attributes and elements
- SQL and QUEL languages were extended

GRANT and REVOKE Statements

Read access on EMP to User group A Where
EMP.Salary < 30K and EMP.Dept <> Security
- Query Modification:

Modify the query according to the access control rules

Retrieve all employee information where salary < 30K and
Dept is not Security
Steps to Designing a Secure System
 Requirements, Informal Policy and model
 Formal security policy and model
 Security architecture
- Identify security critical components; these components must be
trusted
 Design of the system
 Verification and Validation
Product Evaluation
 Orange Book
- Trusted Computer Systems Evaluation Criteria
 Classes C1, C2, B1, B2, B3, A1 and beyond
- C1 is the lowest level and A1 the highest level of assurance
- Formal methods are needed for A1 systems
 Interpretations of the Orange book for Networks (Trusted Network
Interpretation) and Databases (Trusted Database Interpretation)
 Several companion documents
- Auditing, Inference and Aggregation, etc.
 Many products are now evaluated using the federal Criteria
Security Threats to Web/E-commerce
Security
Threats and
Violations
Access
Control
Violations
Denial of
Service/
Infrastructure
Attacks
Integrity
Violations
Fraud
Sabotage
Confidentiality
Authentication
Nonrepudiation
Violations
Approaches and Solutions
 End-to-end security
- Need to secure the clients, servers, networks, operating
systems, transactions, data, and programming languages
- The various systems when put together have to be secure

Composable properties for security
 Access control rules, enforce security policies, auditing,
intrusion detection
 Verification and validation
 Security solutions proposed by W3C and OMG
 Java Security
 Firewalls
 Digital signatures and Message Digests, Cryptography
Other Security Technologies
 Middleware Security
 Insider Threat Analysis
 Risk Management
 Trust and Economics
 Biometrics
 Secure Voting Machines
 -----
Outline of Part II: Data Management
 Concepts in database systems
 Types of database systems
 Distributed Data Management
 Heterogeneous database integration
 Federated data management
 Information Management
An Example Database System
Application
Programs
Database Management System
Database
Adapted from C. J. Date, Addison Wesley, 1990
Users
Metadata
 Metadata describes the data in the database
- Example:
Database D consists of a relation EMP with
attributes SS#, Name, and Salary
 Metadatabase stores the metadata
- Could be physically stored with the database
 Metadatabase may also store constraints and administrative
information
 Metadata is also referred to as the schema or data dictionary
Functional Architecture
Data Management
User Interface Manager
Schema
(Data Dictionary)
Manager
(metadata)
Query
Manager
Security/
Integrity
Manager
Transaction Manager
Storage Management
File
Manager
Disk
Manager
DBMS Design Issues
 Query Processing
- Optimization techniques
 Transaction Management
- Techniques for concurrency control and recovery
 Metadata Management
- Techniques for querying and updating the metadatabase
 Security/Integrity Maintenance
- Techniques for processing integrity constraints and enforcing
access control rules
 Storage management
- Access methods and index strategies for efficient access to the
database
Federated Data and Policy Management
Data/Policy for Federation
Export
Data/Policy
Export
Data/Policy
Export
Data/Policy
Component
Data/Policy for
Agency A
Component
Data/Policy for
Agency C
Component
Data/Policy for
Agency B
What is Information Management?
 Information management essentially analyzes the data and makes
sense out of the data
 Several technologies have to work together for effective information
management
- Data Warehousing: Extracting relevant data and putting this data
into a repository for analysis
- Data Mining: Extracting information from the data previously
unknown
- Multimedia: managing different media including text, images,
video and audio
- Web: managing the databases and libraries on the web
Data Warehouse
Users
Query
the Warehouse
Oracle
DBMS for
Employees
Data Warehouse:
Data correlating
Employees With
Medical Benefits
and Projects
Sybase
DBMS for
Projects
Could be
any DBMS;
Usually based on
the relational
data model
Informix
DBMS for
Medical
Data Mining
Information Harvesting
Knowledge Mining
Data Mining
Knowledge Discovery
in Databases
Data Dredging
Data Archaeology
Data Pattern Processing
Database Mining
Knowledge Extraction
Siftware
The process of discovering meaningful new correlations, patterns, and trends by
sifting through large amounts of data, often previously unknown, using pattern
recognition technologies and statistical and mathematical techniques
(Thuraisingham 1998)
Semantic Web
0Adapted from Tim Berners Lee’s description of the Semantic Web
T
R
U
S
T
P
R
I
V
A
C
Y
Logic, Proof and Trust
Rules/Query
RDF, Ontologies
Other
Services
XML, XML Schemas
URI, UNICODE
0 Some Challenges: Interoperability between Layers; Security and
Privacy cut across all layers; Integration of Services; Composability
Knowledge Management Components
Knowledge
Components of
Management:
Components,
Cycle and
Technologies
Components:
Strategies
Processes
Metrics
Cycle:
Knowledge, Creation
Sharing, Measurement
And Improvement
Technologies:
Expert systems
Collaboration
Training
Web
Part III: Emerging Technologies in Data and
Applications Security
 Digital Identity Management
 Identity Theft Management
 Digital Watermarking
 Risk Analysis
 Economic Analysis
 Secure Electronic Voting Machines
 Biometrics
 Digital Forensics
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
-
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
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
Digital Forensics
 Digital forensics is about the investigation of crime including
using digital/computer methods
 More formally: “Digital forensics, also known as computer
forensics, involved the preservation, identification, extraction,
and documentation of computer evidence stored as data or
magnetically encoded information”, by John Vacca
 Digital evidence may be used to analyze cyber crime (e.g.
Worms and virus), physical crime (e.g., homicide) or crime
committed through the use of computers (e.g., child
pornography)
Digital Forensics - II
 The steps include the following:
- When a crime occurs, law enforcement officials gather
every piece of evidence including information from the
crime scene as well as from the computers
- The evidence gathered is analyzed
- Techniques include
 Intrusion detection
 Data Mining
 Analyzing log files
 Analyze email messages
 Lawyers, Psychologists, Sociologists, Crime investigators
and Technologists have to work together
 International Journal of Digital Evidence is a useful source