Transcript Lecture 2 - The University of Texas at Dallas

Introduction to Biometrics
Dr. Bhavani Thuraisingham
The University of Texas at Dallas
Lecture #2
Information Security
August 24, 2005
Outline
 Operating Systems Security
 Network Security
 Designing and Evaluating Systems
 Web Security
 Other Security Technologies
 Data and Applications Security
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 objects
- Star (*) Property: Subject has WRITE access to an object if the
subject’s security level is dominated by that of the objects\
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, - - -
-
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
E-Commerce Transactions
 E-commerce functions are carried out as transactions
- Banking and trading on the internet
- Each data transaction could contain many tasks
 Database transactions may be built on top of the data transaction
service
- Database transactions are needed for multiuser access to web
databases
- Need to enforce concurrency control and recovery techniques
Types of Transaction Systems
 Stored Account Payment
- e.g., Credit and debit card transactions
- Electronic payment systems
- Examples: First Virtual, CyberCash, Secure Electronic Transaction
 Stored Value Payment
- Uses bearer certificates
- Modeled after hard cash

Goal is to replace hard cash with e-cash
- Examples: E-cash, Cybercoin, Smart cards
What is E-Cash?
 Electronic Cash is stored in a hardware token
 Token may be loaded with money
- Digital cash from the bank
 Buyer can make payments to seller’s token (offline)
 Buyer can pay to seller’s bank (online)
 Both cases agree upon protocols
 Both parties may use some sort of cryptographic key mechanism to
improve security
Other Security Technologies
 Data and Applications Security
 Middleware Security
 Insider Threat Analysis
 Risk Management
 Trust and Economics
 Biometrics
Developments in Data and Applications
Security: 1975 - Present
 Access Control for Systems R and Ingres (mid 1970s)
 Multilevel secure database systems (1980 – present)
- Relational database systems: research prototypes and products;
Distributed database systems: research prototypes and some
operational systems; Object data systems; Inference problem
and deductive database system; Transactions
 Recent developments in Secure Data Management (1996 – Present)
- Secure data warehousing, Role-based access control (RBAC); Ecommerce; XML security and Secure Semantic Web; Data
mining for intrusion detection and national security; Privacy;
Dependable data management; Secure knowledge management
and collaboration
Developments in Data and Applications
Security: Multilevel Secure Databases - I
 Air Force Summer Study in 1982
 Early systems based on Integrity Lock approach
 Systems in the mid to late 1980s, early 90s
- E.g., Seaview by SRI, Lock Data Views by Honeywell, ASD and
ASD Views by TRW
- Prototypes and commercial products
- Trusted Database Interpretation and Evaluation of Commercial
Products
 Secure Distributed Databases (late 80s to mid 90s)
- Architectures; Algorithms and Prototype for distributed query
processing; Simulation of distributed transaction management
and concurrency control algorithms; Secure federated data
management
Developments in Data and Applications
Security: Multilevel Secure Databases - II
 Inference Problem (mid 80s to mid 90s)
- Unsolvability of the inference problem; Security constraint
processing during query, update and database design
operations; Semantic models and conceptual structures
 Secure Object Databases and Systems (late 80s to mid 90s)
- Secure object models; Distributed object systems security;
Object modeling for designing secure applications; Secure
multimedia data management
 Secure Transactions (1990s)
- Single Level/ Multilevel Transactions; Secure recovery and
commit protocols
Some Directions and Challenges for Data and
Applications Security - I
 Secure semantic web
- Single/multiple security models?
- Different application domains
 Secure Information Integration
- How do you securely integrate numerous and heterogeneous
data sources on the web and otherwise
 Secure Sensor Information Management
- Fusing and managing data/information from distributed and
autonomous sensors
 Secure Dependable Information Management
- Integrating Security, Real-time Processing and Fault Tolerance
 Data Sharing vs. Privacy
- Federated database architectures?
Some Directions and Challenges for Data and
Applications Security - II
 Data mining and knowledge discovery for intrusion detection
- Need realistic models; real-time data mining
 Secure knowledge management
- Protect the assets and intellectual rights of an organization
 Information assurance, Infrastructure protection, Access
Control
- Insider cyber-threat analysis, Protecting national databases,
Role-based access control for emerging applications
 Security for emerging applications
- Geospatial, Biomedical, E-Commerce, etc.
 Other Directions
- Trust and Economics, Trust Management/Negotiation, Secure
Peer-to-peer computing,
Layered Architecture for Dependable
Semantic Web
0Adapted from Tim Berners Lee’s description of the Semantic Web
S
E
C
U
R
I
T
Y
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: Security and Privacy cut across all layers;
Integration of Services; Composability
Secure Sensor Information Management:
Directions for Research
 Individual sensors may be compromised and attacked; need
techniques for detecting, managing and recovering from such
attacks
 Aggregated sensor data may be sensitive; need secure storage sites
for aggregated data; variation of the inference and aggregation
problem?
 Security has to be incorporated into sensor database management
- Policies, models, architectures, queries, etc.
 Evaluate costs for incorporating security especially when the sensor
data has to be fused, aggregated and perhaps mined in real-time
 Need secure dependable information management for sensor data
Secure Dependable Information Management
 Dependable information management includes
- secure information management
- fault tolerant information
- High integrity and high assurance computing
- Real-time computing
 Conflicts between different features
- Security, Integrity, Fault Tolerance, Real-time Processing
- E.g., A process may miss real-time deadlines when access
control checks are made
- Trade-offs between real-time processing and security
- Need flexible security policies; real-time processing may be
critical during a mission while security may be critical during
non-operational times
Secure Dependable Information Management
Example: Next Generation AWACS
Navigation
Data Analysis Programming
Group (DAPG)
Data Links
Sensors
Sensor
Detections
Multi-Sensor
Tracks
Technology
Future
App
provided by
Future
App
the project
Data
Mgmt.
Data
Xchg.
MSI
App
Infrastructure Services
Real-time Operating System
Hardware
Future
App
Display
Processor
&
Refresh
Channels
Consoles
(14)
•Security being considered after
the system has been designed
and prototypes implemented
•Challenge: Integrating real-time
processing, security and
fault tolerance
Research Directions for Privacy

Why this interest now on privacy?
-
Data Mining for National Security
Data Mining is a threat to privacy
Balance between data sharing/mining and privacy

Privacy Preserving Data Mining

Inference Problem as a Privacy Problem

Data Sharing Across Coalitions
Data Mining to Handle Security Problems
 Data mining tools could be used to examine audit data and flag
abnormal behavior
 Much recent work in Intrusion detection
- e.g., Neural networks to detect abnormal patterns
 Tools are being examined to determine abnormal patterns for
national security
- Classification techniques, Link analysis
 Fraud detection
- Credit cards, calling cards, identity theft etc.
What can we do?:
Privacy Preserving Data Mining
 Prevent useful results from mining
- limit data access to ensure low confidence and support
- Extra data (“cover stories”) to give “false” results with Providing
only samples of data can lower confidence in mining results;
 Idea: If adversary is unable to learn a good classifier from the data,
then adversary will be unable to learn good
- rules, predictive functions
 Approach: Only make a sample of data available
- Limits ability to learn good classifier
 Several recent research efforts have been reported
Inference Problem as a Privacy Problem:
Privacy Constraint Processing
User Interface Manager
Privacy
Constraints
Constraint
Manager
Query Processor:
Constraints during
query and release
operations
DBMS
Database Design
Tool
Update
Processor:
Constraints during
database design
operation
Constraints
during update
operation
Database
Secure Data Sharing Across Coalitions
Data/Policy for Coalition
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