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Data Mining for Security Applications Dr. Bhavani Thuraisingham Dr. Doug Harris The University of Texas at Dallas [email protected] March 2005

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Page 1: Data Mining for Security Applications Dr. Bhavani Thuraisingham Dr. Doug Harris The University of Texas at Dallas bhavani.thuraisingham@utdallas.edu March

Data Mining for Security Applications

Dr. Bhavani ThuraisinghamDr. Doug Harris

The University of Texas at Dallas

[email protected]

March 2005

Page 2: Data Mining for Security Applications Dr. Bhavani Thuraisingham Dr. Doug Harris The University of Texas at Dallas bhavani.thuraisingham@utdallas.edu March

204/20/23 18:19

Outline

0 National Security/Cyber Security : Threats and Countermeasures

0 Overview of Data Mining0 Data Mining for National Security/Cyber Security0 Privacy Concerns0 Some Projects at UTD

Page 3: Data Mining for Security Applications Dr. Bhavani Thuraisingham Dr. Doug Harris The University of Texas at Dallas bhavani.thuraisingham@utdallas.edu March

304/20/23 18:19

Aspects of Counterterrorism

0 National Security Measures

=Protection from Non-real-time Threats

=Protection from Real-time Threats

0 Protection from Cyberterrorism

- Cyber security

0 Protection from Bioterrorism

0 Preventing/Detecting/Containing Terrorist activities

Page 4: Data Mining for Security Applications Dr. Bhavani Thuraisingham Dr. Doug Harris The University of Texas at Dallas bhavani.thuraisingham@utdallas.edu March

404/20/23 18:19

Some National Security Measures

0 Border Security

- Protecting National/State Borders

- Protecting Information Flows across borders

- Managing and Mitigating Risks

0 First/Emergency Responses

- Detecting attacks (cyber or otherwise) and responding to attacks in a timely manner

- Containing the damage

0 Continued Monitoring and Management

- Manage attacks, lessons learned and prevent future attacks

- Surveillance, vigilance

Page 5: Data Mining for Security Applications Dr. Bhavani Thuraisingham Dr. Doug Harris The University of Texas at Dallas bhavani.thuraisingham@utdallas.edu March

504/20/23 18:19

Protection Objects for National Security

0 Services

- Transportation, Financial, Medical, Insurance, Education, - - -

0 Infrastructures

- Telecommunication networks, Power systems, water supply/tanks/reservoirs

0 Information related

- Computing systems and networks, National databases, Financial databases., Medical databases, - - -

Page 6: Data Mining for Security Applications Dr. Bhavani Thuraisingham Dr. Doug Harris The University of Texas at Dallas bhavani.thuraisingham@utdallas.edu March

604/20/23 18:19

Cyber Security Measures

0 Protection from Trojan Horses and Viruses

0 Protection from Jamming

0 Recovering from network and system failures through malicious attacks

0 Intrusion detection/prevention, auditing

0 Secure clients, secure servers, secure networks and protocols, secure middleware

0 Develop and enforce security policies for Intranets and Internet

0 Secure collaboration, e-commerce, transactions

0 Access control, identification, authentication, nonrepudiation

Page 7: Data Mining for Security Applications Dr. Bhavani Thuraisingham Dr. Doug Harris The University of Texas at Dallas bhavani.thuraisingham@utdallas.edu March

704/20/23 18:19

National Security vs Cyber Security

0 Cannot separate the two; Much of the data is now or will be on the web

0 Digital libraries have emerged; semantic web is a matter of time

0 Example: Border security measures include physically protecting the borders as well as protecting information flow across borders

0 Transportation security

0 Effective cyber security measures could prevent national security disasters

- e.g., monitoring email and data on the web

Page 8: Data Mining for Security Applications Dr. Bhavani Thuraisingham Dr. Doug Harris The University of Texas at Dallas bhavani.thuraisingham@utdallas.edu March

804/20/23 18:19

Some common threads

0 Identify threats and group/classify threats

0 Learn from experiences, prior situations

0 Develop techniques to prevent attacks

0 Develop techniques to detect attacks, deal with attacks in a timely manner

0 Develop techniques to monitor and prevent future attacks

Page 9: Data Mining for Security Applications Dr. Bhavani Thuraisingham Dr. Doug Harris The University of Texas at Dallas bhavani.thuraisingham@utdallas.edu March

904/20/23 18:19

What is Data Mining?

Data Mining Knowledge MiningKnowledge Discoveryin Databases

Data Archaeology

Data DredgingDatabase Mining

Knowledge Extraction

Data Pattern Processing

Information Harvesting

Siftware

The process of discovering meaningful new correlations, patternsand trends, often previously unknown, by sifting through large amounts of data, using pattern recognition, statistical and mathematical techniques

Page 10: Data Mining for Security Applications Dr. Bhavani Thuraisingham Dr. Doug Harris The University of Texas at Dallas bhavani.thuraisingham@utdallas.edu March

1004/20/23 18:19

Steps to Data Mining

Data sources

Integratedatasources

Clean/modifydatasources

Minethe data

Examine/pruneresults

Report/evaluateresults

The cycle may continue; add new data, use different algorithms

Page 11: Data Mining for Security Applications Dr. Bhavani Thuraisingham Dr. Doug Harris The University of Texas at Dallas bhavani.thuraisingham@utdallas.edu March

1104/20/23 18:19

What’s going on in data mining?

0 What are the technologies for data mining?

- Database management, machine learning, statistics, pattern recognition, visualization, parallel processing, . . .

0 What can data mining do for you?

- Data mining outcomes: Classification, Clustering, Association, Anomaly detection, Prediction, Estimation, . . .

0 How do you carry out data mining?

- Data mining techniques: Decision trees, Neural networks, Market-basket analysis, Genetic algorithms, . . .

0 What is the current status?

- Many commercial products mine relational databases

0 What are some of the challenges?

- Mining unstructured data, extracting useful patterns, web mining

Page 12: Data Mining for Security Applications Dr. Bhavani Thuraisingham Dr. Doug Harris The University of Texas at Dallas bhavani.thuraisingham@utdallas.edu March

1204/20/23 18:19

Infrastructure Support for Data Mining

0 We can have the best data mining tools, but without the infrastructure we cannot carry out effective data mining

0 Infrastructure includes

- High performance computing systems and networks

- Mass storage systems

- Caches for real-time applications

- Software environments for processing heterogeneous data from multiple data sources

- Trained personnel

- Management commitment

- . . . . . .

Page 13: Data Mining for Security Applications Dr. Bhavani Thuraisingham Dr. Doug Harris The University of Texas at Dallas bhavani.thuraisingham@utdallas.edu March

1304/20/23 18:19

Data Mining Needs for Counterterrorism: Non-real-time Data Mining

0 Gather data from multiple sources

- Information on terrorist attacks: who, what, where, when, how

- Personal and business data: place of birth, ethnic origin, religion, education, work history, finances, criminal record, relatives, friends and associates, travel history, . . .

- Unstructured data: newspaper articles, video clips, speeches, emails, phone records, . . .

0 Integrate the data, build warehouses and federations

0 Develop profiles of terrorists, activities/threats

0 Mine the data to extract patterns of potential terrorists and predict future activities and targets

0 Find the “needle in the haystack” - suspicious needles?

0 Data integrity is important

0 Techniques have to SCALE

Page 14: Data Mining for Security Applications Dr. Bhavani Thuraisingham Dr. Doug Harris The University of Texas at Dallas bhavani.thuraisingham@utdallas.edu March

1404/20/23 18:19

Data Mining Needs for Counterterrorism: Real-time Data Mining

0 Nature of data

- Data arriving from sensors and other devices

=Continuous data streams

- Breaking news, video releases, satellite images

- Some critical data may also reside in caches

0 Rapidly sift through the data and discard unwanted data for later use and analysis (non-real-time data mining)

0 Data mining techniques need to meet timing constraints

0 Quality of service (QoS) tradeoffs among timeliness, precision and accuracy

0 Presentation of results, visualization, real-time alerts and triggers

Page 15: Data Mining for Security Applications Dr. Bhavani Thuraisingham Dr. Doug Harris The University of Texas at Dallas bhavani.thuraisingham@utdallas.edu March

1504/20/23 18:19

Data Mining Needs for Counterterrorism: Cybersecurity

0 Determine nature of threats and vulnerabilities

- e.g., emails, trojan horses and viruses

0 Classify and group the threats

0 Profiles of potential cyberterrorist groups and their capabilities

0 Data mining for intrusion detection

- Real-time/ near-real-time data mining

- Limit the damage before it spreads

0 Data mining for preventing future attacks

0 Data mining for Digital forensics and Biometrics

Page 16: Data Mining for Security Applications Dr. Bhavani Thuraisingham Dr. Doug Harris The University of Texas at Dallas bhavani.thuraisingham@utdallas.edu March

1604/20/23 18:19

Data Mining Needs for Counterterrorism: Protection from Bioterrorism

0 Determine nature of threats

- Biological weapons and agents, Chemical weapons and agents

0 Classify and group the threats

0 Identify the types of substances used

0 Prevention and detection mechanisms

- Intelligence gathering, detecting symptoms

0 Determine actions to be taken to avoid fatal and dangerous situations

Page 17: Data Mining for Security Applications Dr. Bhavani Thuraisingham Dr. Doug Harris The University of Texas at Dallas bhavani.thuraisingham@utdallas.edu March

1704/20/23 18:19

Data Mining Outcomes and Techniques for Counter-terrorism

Association:John and Jamesoften seen together after anattack

Link Analysis:Follow chain from A to B to C to D

Clustering: Divide population; People from country X of a certain religion; people from Country Y Interested in airplanes

Classification:Build profiles ofTerrorist and classify terrorists

Anomaly Detection:John registers at flight school;but des not care about takeoff or landing

Data Mining Outcomes and Techniques

Page 18: Data Mining for Security Applications Dr. Bhavani Thuraisingham Dr. Doug Harris The University of Texas at Dallas bhavani.thuraisingham@utdallas.edu March

1804/20/23 18:19

Are general data/web mining techniques sufficient?

0 Does one size fit all?

- Non real-time, real-time, cyber, bio?

0 What are the major differences

- e.g., develop models ahead of time for real-time data mining?

- What happens in a very dynamic environment?

0 Data mining tasks/outcomes

- Classification, clustering, associations, anomaly detection, prediction - - - -?

0 Data mining techniques

- Which techniques are good for which problems?

Page 19: Data Mining for Security Applications Dr. Bhavani Thuraisingham Dr. Doug Harris The University of Texas at Dallas bhavani.thuraisingham@utdallas.edu March

1904/20/23 18:19

Where are we now?

0 We have some tools for

- building data warehouses from structured data

- integrating structured heterogeneous databases

- mining structured data

- forming some links and associations

- information retrieval tools

- image processing and analysis

- video information processing

- visualizing data

- managing metadata

- intrusion detection and forensics

Page 20: Data Mining for Security Applications Dr. Bhavani Thuraisingham Dr. Doug Harris The University of Texas at Dallas bhavani.thuraisingham@utdallas.edu March

2004/20/23 18:19

What are our challenges?

0 Do the tools scale for large heterogeneous databases and petabyte sized databases?

0 Integrating structured data with unstructured data

0 Extracting metadata from unstructured data

0 Mining unstructured data

0 Extracting useful patterns from knowledge-directed data mining

0 Rapidly forming links and associations; get the big picture for real-time data mining

0 Mining the web

0 Evaluating data mining algorithms

0 Building testbeds

Page 21: Data Mining for Security Applications Dr. Bhavani Thuraisingham Dr. Doug Harris The University of Texas at Dallas bhavani.thuraisingham@utdallas.edu March

2104/20/23 18:19

Some other data mining applications for National Security

0 Insider Threat analysis

0 Preventing/Detecting Money laundering, Drug trafficking, Tax violations

0 Protecting children from inappropriate content on the Internet

- National Academy of Science Panel 2000-2001 Chair: Richard Thornburgh (former U.S. Attorney General)

0 Protecting infrastructures, national databases, -.-.-.-

Page 22: Data Mining for Security Applications Dr. Bhavani Thuraisingham Dr. Doug Harris The University of Texas at Dallas bhavani.thuraisingham@utdallas.edu March

2204/20/23 18:19

Form a Research Agenda0 Immediate action (0 - 1 year)

- We’ve got to know what our current capabilities are

- Do the commercial tools scale? Do they work only on special data and limited cases? Do they deliver what they promise?

- Need an unbiased objective study with demonstrations

0 At the same time, work on the big picture

- What do we want? What are our end results for the foreseeable future? What are the criteria for success? How do we evaluate the data mining algorithms? What testbeds do we build?

0 Near-term (1 - 3 years)

- Leverage current research

- Fill the gaps in a goal-directed way

0 Long-term research (3 - 5 years and beyond)

- 5-year basic research plan for data mining for counterterrorism

Page 23: Data Mining for Security Applications Dr. Bhavani Thuraisingham Dr. Doug Harris The University of Texas at Dallas bhavani.thuraisingham@utdallas.edu March

2304/20/23 18:19

IN SUMMARY:

0 Data Mining is very useful to solve 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.

BUT CONCERNS FOR PRIVACY

Page 24: Data Mining for Security Applications Dr. Bhavani Thuraisingham Dr. Doug Harris The University of Texas at Dallas bhavani.thuraisingham@utdallas.edu March

2404/20/23 18:19

Some Privacy concerns

0 Medical and Healthcare

- Employers, marketers, or others knowing of private medical concerns

0 Security

- Allowing access to individual’s travel and spending data

- Allowing access to web surfing behavior

0 Marketing, Sales, and Finance

- Allowing access to individual’s purchases

Page 25: Data Mining for Security Applications Dr. Bhavani Thuraisingham Dr. Doug Harris The University of Texas at Dallas bhavani.thuraisingham@utdallas.edu March

2504/20/23 18:19

Data Mining as a Threat to Privacy

0 Data mining gives us “facts” that are not obvious to human analysts of the data

0 Can general trends across individuals be determined without revealing information about individuals?

0 Possible threats:- Combine collections of data and infer information that is private

=Disease information from prescription data=Military Action from Pizza delivery to pentagon

0 Need to protect the associations and correlations between the data that are sensitive or private- Privacy preserving data mining

Page 26: Data Mining for Security Applications Dr. Bhavani Thuraisingham Dr. Doug Harris The University of Texas at Dallas bhavani.thuraisingham@utdallas.edu March

2604/20/23 18:19

Data Mining and Privacy: Friends or Foes?

0 They are neither friends nor foes

0 Need advances in both data mining and privacy

0 Need to design flexible systems

- For some applications one may have to focus entirely on “pure” data mining while for some others there may be a need for “privacy-preserving” data mining

- Need flexible data mining techniques that can adapt to the changing environments

0 Technologists, legal specialists, social scientists, policy makers and privacy advocates MUST work together

Page 27: Data Mining for Security Applications Dr. Bhavani Thuraisingham Dr. Doug Harris The University of Texas at Dallas bhavani.thuraisingham@utdallas.edu March

2704/20/23 18:19

Some Projects at UTD:Privacy Preserving Data Mining

0 Randomization- Introduce random values into the data and/or results- Challenge is to introduce random values without

significantly affecting the data mining results- Give range of values for results instead of exact values

0 Secure Multi-party Computation- Each party knows its own inputs; encryption techniques

used to compute final results0 Privacy preserving link analysis

Page 28: Data Mining for Security Applications Dr. Bhavani Thuraisingham Dr. Doug Harris The University of Texas at Dallas bhavani.thuraisingham@utdallas.edu March

2804/20/23 18:19

Some Projects at UTD: Suspicious Event Detection

0 Determine normal events0 Determine suspicious events0 Analyze video and image data and determine whether events

are suspicious

Page 29: Data Mining for Security Applications Dr. Bhavani Thuraisingham Dr. Doug Harris The University of Texas at Dallas bhavani.thuraisingham@utdallas.edu March

2904/20/23 18:19

Some Projects at UTD: Secure Semantic Web

Policies

Ontologies

Rules

Semantic Web Engine

XML, RDF DocumentsWeb Pages, Databases

Inference Engine/Rules Processor

Interface to the Semantic WebTechnologyBy W3C