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Data and Applications Security Developments and Directions

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1 Data and Applications Security Developments and Directions
Dr. Bhavani Thuraisingham The University of Texas at Dallas Attacks to Databases Emerging Security Technologies Biometrics Secure Voting Machines April 15, 2011

2 Outline of the Unit 1. Brute-force (or not) cracking of weak or default usernames/passwords 2. Privilege escalation 3. Exploiting unused and unnecessary database services and functionality 4. Targeting unpatched database vulnerabilities 5. Stolen backup (unencrypted) tapes 6. SQL injection ml

3 Brute-force (or not) cracking of weak or default usernames/passwords
Older versions of Oracle and others database systems used well known default passwords New versions have changed this practice and don’t allow database systems to keep default passwords Even unique, non-default database passwords aren’t hacker-safe – with Bruce Force attacks and password cracking tools Steer clear of default passwords, and institute tight password management and regular change-ups.

4 Privilege Escalation There have been several insider attacks that came as a result of a malicious user possessing more system privileges than he or she should have had. Outside attackers sometimes have higher-level privileges by compromising the operating system. Privilege escalation usually has more to do with misconfiguration: A user is mistakenly granted more access and privileges on the database or related applications than he actually needs to do his job. Sometimes an inside attacker (or an outsider who has taken over a victim’s machine) can go from one application to the database, even if he doesn't have database credentials. Solution: Give users only the access and rights they need on the database, nothing more

5 Exploiting unused and unnecessary database services and functionality
One of the first things an outside attacker will look for is whether his potential victim is running the Listener feature on its Oracle database. Listener seeks out and forwards network connections to the Oracle database, and thus can expose users and database links. Via Google, an attacker can search and find exposed Listener services on databases. Other features, such as hooks between operating systems and the database, can leave the database exposed to an attack. Such a hook can become a communications link to the database. Often, database administrators run too many services and services may be open up to vulnerabilities Solution: Install only the database features you need.

6 Targeting unpatched database vulnerabilities
Oracle and other database vendors patch their vulnerabilities. However difficult for organizations to keep up with the patches Database vendors are careful not to disclose many details about the vulnerabilities and their patches fix so that attackers are not notified Some hacker sites post exploit scripts for known database vulnerabilities Solution: Organizations must be vigilant about installing patches in a timely manner.

7 Stolen backup (unencrypted) tapes
If the database data on the stolen are not encrypted and the tapes get into the wrong hands then there is a huge problem But this type of attack is more likely to occur with an insider selling the media to an attacker. Solution: Encrypt the critical data. Use a safe for sensitive database tapes

8 SQL Injection SQL injection attacks occur where the fields available for user input let SQL statements through to query the database directly. Outside of the client, Web applications typically are the weakest link. In some cases, if the attacker gets a screen on the application for username and password, all he has to do is provide a SQL statement or database command and that goes directly to the database If the application does not examine the content of the logon. “The problem is that the authentication and authorization has been moved to the application server. Now instead of a user name, it is a SQL command put into a packet and sent by the application server to the database. The database reads the SQL command, and it could shut down a database altogether

9 SQL Injection Solution is to look at the content the user is providing. SQL injection attacks can occur both from the Web application to the database, and from within the database itself. There are some programming practices that help prevent SQL injection flaws in applications, such as using what are called “bind variables,” or parameters for queries. In languages such as Java, that means using question marks as placeholders in the SQL statement and binding the “received” values to those placeholders Another practice is to avoid displaying certain database error messages to avoid giving away potentially sensitive information to a would-be attacker

10 SQL Injection Conasier ing a very simple web application that processes customer orders. Suppose Acme Widgets has a simple page for existing customers where they simply enter their customer number to retrieve all of their current order information. The page itself might be a basic HTML form that contains a textbox called CustomerNumber and a submit button. When the form is submitted, the following SQL query is executed: SELECT * FROM Orders WHERE CustomerNumber = CustomerNumber The results of this query are then displayed on the results page. During a normal customer inquiry, this form works quite well.

11 SQL Injection Suppose John visits the page and enters his customer ID (14). The following query would retrieve his results: SELECT * FROM Orders WHERE CustomerNumber = However, the same code can be a dangerous weapon in the hands of a malicious user. Imagine that Mal comes along and enters the following data in the CustomerNumber field: “14; DROP TABLE Orders”. This would cause the following query to execute: SELECT * FROM Orders WHERE CustomerNumber = 14; DROP TABLE Orders

12 SQL Injection Solutions: Implement parameter checking on all applications. For example, if you’re asking someone to enter a customer number, make sure the input is numeric before executing the query. You may wish to go a step further and perform additional checks to ensure the customer number is the proper length, valid, Limit the permissions of the account that executes SQL queries. The rule of least privilege applies. If the account used to execute the query doesn’t have permission to drop tables, the table dropping will not succeed! Use stored procedures (or similar techniques) to prevent users from directly interacting with SQL code. As with many security principles, an ounce of prevention is worth a pound of cure. Take the time to verify the code running on your servers

13 Outline Digital Identity Management Identity Theft Management
Digital Forensics Digital Watermarking Risk Analysis Economic Analysis Secure Electronic Voting Machines Biometrics Other Applications Lecture on Introduction to Biometrics

14 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

15 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

16 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

17 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

18 Digital Forensics - II Digital Forensics Techniques
Intrusion detection Data Mining Analyzing log files Use criminal profiling and develop a psychological profiling Analyze messages Lawyers, Psychologists, Sociologists, Crime investigators and Technologists have to worm together International Journal of Digital Evidence is a useful source

19 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

20 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

21 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

22 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

23 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

24 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

25 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

26 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

27 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

28 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

29 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

30 Introduction to Biometrics
Dr. Bhavani Thuraisingham The University of Texas at Dallas Introduction to Biometrics

31 Outline Introduction to Biometrics What is Biometrics?
What is the Process? Why Biometrics? Biometrics Resources What is Secure Biometrics Revisiting Topics to be covered Some exploratory research areas Some useful reference books

32 What is Biometrics? Biometrics are automated methods of recognizing a person based on a physiological or behavioral characteristic Features measured: Face, Fingerprints, Hand geometry, handwriting, Iris, Retinal, Vein and Voice Identification and personal certification solutions for highly secure applications Numerous applications: medical, financial, child care, computer access etc.

33 What is the Process? Three-steps: Capture-Process-Verification
Capture: A raw biometric is captured by a sensing device such as fingerprint scanner or video camera Process: The distinguishing characteristics are extracted from the raw biometrics sample and converted into a processed biometric identifier record Called biometric sample or template Verification and Identification Matching the enrolled biometric sample against a single record; is the person really what he claims to be? Matching a biometric sample against a database of identifiers

34 Why Biometrics? Biometrics replaces Traditional Authentication Methods
Provides better security More convenient Better accountability Applications on Fraud detection and Fraud deterrence Dual purpose Cyber Security and National Security

35 Why Biometrics? (Continued)
Authentication mechanisms often used are User ID and Passwords However password mechanisms have vulnerabilities Stealing passwords etc. Biometrics systems are less prone to attacks Need sophisticated techniques for attacks Cannot steal facial features and fingerprints Need sophisticated image processing techniques for modifying facial features

36 Why Biometrics? (Continued)
Biometrics systems are more convenient Need not have multiple passwords or difficult passwords E.g., characters, numbers and special symbols Need not remember passwords Need not carry any cards or tokens Better accountability Can determine who accessed the system with less complexity

37 Why Biometrics? (Concluded)
Dual Purpose Cyber Security and National Security Access to computer systems and networks Fraud detection Who has intruded the system? Who has entered the building Surveillance and monitoring Fraud Deterrence Because of biometrics systems, people are nervous to commit crimes Stealing from supermarkets and shops, etc.

38 Biometrics Resources Biometrics Consortium is the major resource
Another Resource Has Information on Who is doing what Academia, Industry and Government White papers on Biometrics technologies Fingerprint detection, facial recognition, Iris scanning,

39 Biometrics Resources: What is academia doing?
Michigan State University Developing algorithms for fingerprint detection, etc. West Virginia University Forensic identification initiative San Jose State University Mathematical concepts

40 Biometrics Resources: What is Industry doing?
Focus is on building faster and cheaper devices More accuracy, less false positives and negatives Incorporating biometrics into mobile devices, Smartcards Biometrics in healthcare: delivering medication to correct patients Biometrics in child care: Children are picked up by those authorized Protecting digital content Ensuring that voice and video are not altered Vendors:

41 Biometrics Resources: What is Government doing?
NSA (National Security Agency) Research on protecting critical information systems DoD (Department of Defense) Biometrics Management Office Provide Armed forces access to Biometrics systems for combat operations INS/DHS (Department of Homeland Security; Immigration and Nationalization Service) Biometrics technologies at Airports NIST (National Institute of Standards and Technologies) Major player in Biometrics

42 Activities of NIST Measurements, Testing and Standards is NIST’s mission Focus on Biometrics Standards Activities Biometrics Consortium Common Biometric Exchange File Format Biometric Interoperability, Performance and Assurance Working Group BioAPI Consortium Various Standards

43 Activities of NIST (Continued)
Biometrics Consortium is the Government focal point for research, development and testing of Biometric products and technologies Common Biometric Exchange File Format is a product of the consortium to develop common fingerprint template formats Biometrics Interoperability working group promotes common definitions and concepts for exchanging information between national and international partners BioAPI consortium develops common Application Programming Interfaces for biometrics technologies

44 Activities of NIST (Concluded)
NIST is developing standards for the following: Finger image format for data Interchange Face image format for data interchange Iris image format for data interchange Signature image format for data interchange NIST is working with International standards organizations for joint standards ISO (International Standards Organization)

45 What is Secure Biometrics?
Study the attacks of biometrics systems Modifying fingerprints Modifying facial features Develop a security policy and model for the system Application independent and Application specific policies Enforce Security constraints Entire face is classified but the nose can be displayed Develop a formal model Formalize the policy Design the system and identify security critical components Reference monitor for biometrics systems

46 Security Vulnerabilities
Type 1 attack: present fake biometric such a synthetic biometric Type 2 attack: Submit a previously intercepted biometric data: replay Type 3 attack: Compromising the feature extractor module to give results desired by attacker Type 4 attack: Replace the genuine feature values produced by the system by fake values desired by attacker Type 5 attack: Produce a high number of matching results Type 6 attack: Attack the template database: add templates, modify templates etc.

47 Security and Privacy for Biometrics
Privacy of the Individuals have to be protected CNN News Release: August 29, 2005 Distorting Biometrics Enhances Security and Privacy Biometric data converted to numerical strings by mathematical algorithm for later use If the mathematical templates are stolen could be dangerous Researchers have developed method to alter the images in a defined and repeated way Hackers steal the distortion not the original face or fingerprint

48 Secure Electronic Voting Machines
Dr. Bhavani Thuraisingham The University of Texas at Dallas

49 References and Disclaimer
Analysis of an Electronic Voting System TADAYOSHI KOHNO ADAM STUBBLEFIELD AVIEL D. RUBIN DAN S. WALLACH IEEE Symposium on Security and Privacy 2004 Security Analysis of the Diebold AccuVote-TS Voting Machine Ariel J. Feldman, J. Alex Halderman, and Edward W. Felten The views expressed in this presentation are obtained entirely from the above two papers. Prof. Bhavani Thuraisingham has not carried out any analysis of the electronic voting machine discussed in this presentation.

50 Properties of a Good Voting System
The anonymity of a voter’s ballot must be preserved, both to guarantee the voter’s safety and to guarantee that voters have no evidence that proves which candidates received their votes. The voting system must also be tamper-resistant to thwart a wide range of attacks ( including ballot stuffing by voters and incorrect tallying by insiders) “Butterfly ballots” in the Florida 2000 presidential election is the importance of human factors. A voting system must be comprehensible to and usable by the entire voting population, regardless of age, infirmity, or disability. Flaws in any of these aspects of a voting system can lead to indecisive/incorrect election results.

51 Electronic Voting System
As a result of the Florida 2000 presidential election the inadequacies of widely-used punch card voting systems have become well understood by the general population. This has led to increasingly widespread adoption of “direct recording electronic” (DRE) voting systems. Voters go to their home precinct and prove that they are allowed to vote there by presenting say an ID card. The voter is then typically given a PIN, a smartcard, or some other token User then enters the token at a voting terminal and then votes When the voter’s selection is complete, DRE systems will typically present a summary of the voter’s selections The ballot is “cast” The most fundamental problem with such a voting system is that the entire election hinges on the correctness,

52 What is the problem? The problem with such a voting system is that the entire election hinges on the correctness, robustness, and security of the software within the voting terminal. Should that code have security relevant flaws, they might be exploitable either by unscrupulous voters or by malicious insiders. If flaws are introduced into the voting system software then the results of the election cannot be assured to accurately reflect the votes legally cast by the voters.

53 A solution? A solution for securing electronic voting machines is to introduce a “voter-verifiable audit trail”. A DRE system with a printer attachment, or even a traditional optical scan system will satisfy this requirement by having a piece of paper for voters to read and verify that their intent is correct reflected. This paper is stored in ballot boxes and is considered to be the primary record of a voter’s intent. If the printed paper has some kind of error, it is considered to be a “spoiled ballot” and can be mechanically destroyed, giving the voter the chance to vote again. The correctness of any voting software no longer matters; either a voting terminal prints correct ballots or it is taken out of service. If there is any discrepancy in the vote tally, the paper ballots will be available to be recounted

54 Certified Voting Systems and issues
“CERTIFIED” DRE SYSTEMS. Many government entities have adopted paperless DRE systems Such systems have been “certified” for use without any public release of the analyses The CVS source code repository for Diebold’s AccuVote-TS DRE voting system recently appeared on the Internet. Rubin et al discovered significant and wide-reaching security vulnerabilities in their analysis of the AccuVote-TS voting terminal Voters can easily program their own smartcards to simulate the behavior of valid smartcards used in the election. With such homebrew cards a voter can cast multiple ballots without leaving any trace. A voter can also perform actions that normally require administrative privileges (e.g. viewing partial results and terminating the election early)

55 Certified Voting Systems and issues
The protocols used when the voting terminals communicate with their home base both to fetch election configuration information and to report final election results do not use cryptographic techniques to authenticate either end of the connection nor do they check the integrity of the data in transit. Given that these voting terminals could potentially communicate over insecure phone lines or even wireless Internet connections, even unsophisticated attackers can perform untraceable “man-in- the-middle” attacks.

56 Certified Voting Systems and issues
Rubin et al considered both the specific ways that the code uses cryptographic techniques and the general software engineering quality of its construction. They state neither provides them with any confidence of the system’s correctness. Cryptography, when used at all, is used incorrectly. In many places where cryptography would seem obvious and necessary, none is used. No evidence of disciplined software engineering processes. Comments in the code and the revision change logs indicate the engineers were aware of some problems No evidence of any change-control process that might restrict a developer’s ability to insert arbitrary patches to the code. Software is written entirely in C++. Rubin et al state when programming in a language like C++, which is not type-safe, programmers must exercise tight discipline to prevent their programs from being vulnerable to buffer overflow attacks and other weaknesses.

57 What happened next? Following the release of our results, the state of Maryland hired SAIC and RABA and the state of Ohio hired Compuware to perform independent analyses of Diebold’s AccuVote-TS systems These analyses supported Rubin’s findings; also showed that many of the issues raised and attacks identified still apply to more recent versions of the AccuVote-TS system These analyses also identified security problems with the back- end GEMS server.

58 Security Threats Smartcards
Exploiting the lack of cryptography; Creating homebrew smartcards; Casting multiple votes ; Accessing administrator and poll worker functionality Election configurations and election data Tampering with the system configuration; Tampering with ballot definitions; Impersonating legitimate voting terminals; Key management and other cryptographic issues with the vote and audit records; Tampering with election results and linking voters with their votes; Audit logs ; Attacking the start of an election Software engineering Code legacy; Coding style; Coding process; Code completeness and correctness

59 Rubin’s conclusions Using publicly available source code, they performed an analysis of the April snapshot of Diebold’s AccuVote-TS electronic voting system. They found significant security flaws: voters can trivially cast multiple ballots with no built-in traceability, administrative functions can be performed by regular voters, and the threats posed by insiders such as poll workers, software developers, and janitors is even greater Based on the analysis of the development environment, including change logs and comments, they believe that an appropriate level of programming discipline for a project was not maintained. There is little difference in the way code is developed for voting machines relative to other commercial endeavors. They believe that an open process would result in more careful development as more scientists and software engineers would solve problems. Need to use appropriate encryptions and security models

60 Analysis of Feldman et al
Malicious software running on a single voting machine can steal votes with little if any risk of detection. The malicious software can modify all of the records, audit logs, and counters kept by the voting machine, so that even careful forensic examination of these records will find nothing amiss. The authors have constructed demonstration software that carries out this vote-stealing attack. Anyone who has physical access to a voting machine, or to a memory card that will later be inserted into a machine, can install said malicious software using a simple method that takes as little as one minute. In practice, poll workers and others often have unsupervised access to the machines.

61 Analysis of Feldman et al
AccuVote-TS machines are susceptible to voting-machine viruses; computer viruses that can spread malicious software automatically and invisibly from machine to machine during normal pre- and post election activity. Authors have constructed a demonstration virus that spreads in this way, installing their demonstration vote-stealing program on every machine it infects. While some of these problems can be eliminated by improving Diebold’s software, others cannot be remedied without replacing the machines’ hardware. Changes to election procedures would also be required to ensure security.


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