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An Example Database System Adapted from C. J. Date, Addison Wesley, 1990
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Building Trustworthy Semantic Webs
Dr. Bhavani ThuraisinghamThe University of Texas at Dallas
Lecture #3Supporting Technologies: Databases, Information
Management and Information Security
August 2006
Database System
Consists of database, hardware, Database Management System (DBMS), and users
Database is the repository for persistent data Hardware consists of secondary storage volumes, processors, and
main memory DBMS handles all users’ access to the database Users include application programmers, end users, and the
Database Administrator (DBA) Need: Reduced redundancy, avoids inconsistency, ability to share
data, enforce standards, apply security restrictions, maintain integrity, balance conflicting requirements
We have used the definition of a database management system given in C. J. Date’s Book (Addison Wesley, 1990)
An Example Database System
Database
Database Management SystemApplicationPrograms
Users
Adapted from C. J. Date, Addison Wesley, 1990
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
User Interface Manager
QueryManager
Transaction Manager
Schema(Data Dictionary)Manager (metadata)
Security/IntegrityManager
FileManager Disk
Manager
Data Management
Storage Management
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
Relational Database: ExampleRelation S:
S# SNAME STATUS CITYS1 Smith 20 LondonS2 Jones 10 ParisS3 Blake 30 ParisS4 Clark 20 LondonS5 Adams 30 Athens
Relation P:
P# PNAME COLOR WEIGHT CITYP1 Nut Red 12 LondonP2 Bolt Green 17 ParisP3 Screw Blue 17 RomeP4 Screw Red 14 LondonP5 Cam Blue 12 ParisP6 Cog Red 19 London
Relation SP:
S# P# QTYS1 P1 300S1 P2 200S1 P3 400S1 P4 200S1 P5 100S1 P6 100S2 P1 300S2 P2 400S3 P2 200S4 P2 200S4 P4 300S4 P5 400
Concepts in Object Database Systems
Objects- every entity is an object- Example: Book, Film, Employee, Car
Class - Objects with common attributes are grouped into a class
Attributes or Instance Variables- Properties of an object class inherited by the object instances
Class Hierarchy- Parent-Child class hierarchy
Composite objects- Book object with paragraphs, sections etc.
Methods- Functions associated with a class
A Definition of a Distributed Database System
A collection of database systems connected via a network The software that is responsible for interconnection is a Distributed
Database Management System (DDBMS) Each DBMS executes local applications and should be involved in at
least one global application (Ceri and Pelagetti) Homogeneous environment
Architecture
Communication NetworkDistributed Processor 1
DBMS 1
Data-base 1 Data-
base 3
Data-base 2 DBMS 2
DBMS 3
Distributed Processor 2
Distributed Processor 3
Site 1
Site 2
Site 3
Data Distribution
EMP1
SS# Name Salary1 John 20 2 Paul 303 James 404 Jill 50
605 Mary6 Jane 70
D#102020 201020
DnameD# MGR
10 30 40
Jane David Peter
DEPT1SITE 1
SITE 2EMP2
SS# Name Salary9 Mathew 70
D#50
DnameD# MGR
50 Math John
Physics
DEPT2
David 80 30Peter 90 40
78
C. Sci. English French
20 Paul
Interoperability of Heterogeneous Database Systems
Database System A Database System B
Network
Database System C(Legacy)
Transparent accessto heterogeneousdatabases - both usersand application programs;Query, Transactionprocessing
(Relational) (Object-Oriented)
Federated Database ManagementDatabase System A Database System B
Database System C
Cooperating databasesystems yet maintainingsome degree ofautonomy
Federation F1
Federation F2
Federated Data and Policy Management
ExportData/Policy
ComponentData/Policy for
Agency A
Data/Policy for Federation
ExportData/Policy
ComponentData/Policy for
Agency C
ComponentData/Policy for
Agency B
ExportData/Policy
Current Status and Directions Developments- Several prototypes and some commercial products- Tools for schema integration and transformation- Standards for interoperable database systems
Challenges being addressed- Semantic heterogeneity- Autonomy and federation- Global transaction management- Integrity and Security
New challenges- Scale- Web data management
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
OracleDBMS forEmployees
SybaseDBMS forProjects
InformixDBMS forMedical
Data Warehouse:Data correlatingEmployees WithMedical Benefitsand Projects
Could beany DBMS; Usually based on the relational data model
UsersQuerythe Warehouse
Multidimensional Data Model
Project Name
Project Leader
Project Sponsor
Project Cost
Project Duration
Dollars
Pounds
Yen
Years
Months
Weeks
Data Mining
Data Mining Knowledge Mining
Knowledge Discoveryin Databases
Data Archaeology
Data Dredging
Database MiningKnowledge Extraction
Data Pattern Processing
Information Harvesting
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)
Multimedia Information Management
VideoSource Scene
ChangeDetection
SpeakerChange
Detection
SilenceDetection
CommercialDetection
Key FrameSelection
StorySegmentation
NamedEntityTagging
Broadcast News Editor (BNE) Broadcast NewsNavigator (BNN)
Video and
Metadata
MultimediaDatabase
ManagementSystem
Web-based Search/Browse by Program, Person, Location, ...
Imagery
Audio
ClosedCaptionText
Segregate VideoStreams
Analyze and Store Video and Metadata
StoryGIST Theme
FrameClassifier
ClosedCaption
Preprocess
Correlation
Token Detection
BroadcastDetection
Extracting Relations from Text for Mining: An Example
TextCorpus Repository
ConceptExtraction
AssociationRuleProduct
Person1 Person2Natalie Allen Linden Soles 117Leon Harris Joie Chen 53Ron Goldman Nicole Simpson 19
. . .Mobotu SeseSeko
Laurent Kabila 10
Goal: FindCooperating/Combating Leadersin a territory
Image Processing:Example: Change Detection:
Trained Neural Network to predict “new” pixel from “old” pixel- Neural Networks good for multidimensional continuous data- Multiple nets gives range of “expected values”
Identified pixels where actual value substantially outside range of expected values- Anomaly if three or more bands (of seven) out of range
Identified groups of anomalous pixels
Semantic Web
0 Some Challenges: Interoperability between Layers; Security and Privacy cut across all layers; Integration of Services; Composability
XML, XML Schemas
Rules/Query
Logic, Proof and TrustTRUST Other
ServicesRDF, Ontologies
URI, UNICODE
PRIVACY
0Adapted from Tim Berners Lee’s description of the Semantic Web
Semantic Web Technologies
Web Database/Information Management- Information retrieval and Digital Libraries
XML, RDF and Ontologies- Representation information
Information Interoperability- Integrating heterogeneous data and information sources
Intelligent agents- Agents for locating resources, managing resources, querying
resources and understanding web pages Semantic Grids- Integrating semantic web with grid computing technologies
Information Management for Collaboration
Team B
Teams A and BCollaboratingon a geographicalproblem
Team A
Some Emerging Information Management Technologies
Visualization- Visualization tools enable the user to better understand the
information Peer-to-Peer Information Management- Peers communicate with each other, share resources and carry
out tasks Sensor and Wireless Information Management- Autonomous sensors cooperating with one another, gathering
data, fusing data and analyzing the data- Integrating wireless technologies with semantic web
technologies
What is Knowledge Management?
Knowledge management, or KM, is the process through which organizations generate value from their intellectual property and knowledge-based assets
KM involves the creation, dissemination, and utilization of knowledge
Reference: http://www.commerce-database.com/knowledge-management.htm?source=google
Knowledge Management Components
Components:StrategiesProcessesMetrics
Cycle:Knowledge, CreationSharing, Measurement And Improvement
Technologies:Expert systemsCollaborationTrainingWeb
Components ofKnowledge Management: Components,Cycle and Technologies
Identification Creation
Diffusion - Tacit, Explicit
Integration Modification
Action
Organizational Learning Process
Metrics
Source: Reinhardt and Pawlowsky
Incentives
also see: Tools in Organizational Learninghttp://duplox.wz-berlin.de/oldb/forslin.html
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
SecurityThreats andViolations
AccessControlViolations
IntegrityViolations Fraud
Denial ofService/InfrastructureAttacks
Sabotage
ConfidentialityAuthenticationNonrepudiationViolations
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 Data and Applications Security Middleware Security Insider Threat Analysis Risk Management Trust and Economics Biometrics