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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