Intelligent Environments

1. Intelligent Environments Computer Science and Engineering University of Texas at Arlington Intelligent Environments

2. Security and Privacy • Motivation • Techniques • Issues Intelligent Environments

3. Motivation • Physical security • Data security • Protect sensory data • Wireless eavesdropping • e-Intrusion • Levels within environment • Degree of autonomy Intelligent Environments

4. Techniques • Physical security • Law enforcement • Encryption • Firewalls • Intrusion detection • Biometrics • Software safety Intelligent Environments

5. Physical Security • Intrusion detection • Video surveillance • Metal detectors, X-ray scanners • Motion detectors, infrared nets • GPS tracking • Access control (key, card, RFbadge, biometrics) Intelligent Environments

6. Law Enforcement and Privacy • Conflict between an individual’s right to privacy and the government’s need to invade privacy to uphold the law • Complicated by digital data, encryption and wireless communications Intelligent Environments

7. U.S. Constitution • Fourth Amendment (abridged) • The right of the people to be secure in their persons, houses, papers, and effects, against unreasonable searches and seizures, shall not be violated. • Fifth Amendment (abridged) • No person shall be compelled in any criminal case to be a witness against himself. Intelligent Environments

8. Computer Crime Laws • Texas computer crimes law • www.capitol.state.tx.us/statutes/pe/pe0003300toc.html Intelligent Environments

9. Privacy and Cyber-Utopia • Global, seamless and secure e-commerce • New encryption standard required • Individual privacy preserved • Law enforcement surveillance possible • U.S. computer industry globally competitive • Ability of national governments to regulate the nation preserved Intelligent Environments

10. Wiretapping • Law enforcement eavesdropping on communication without informing the people who are communicating • U.S. Supreme Court Olmstead v. U.S. (1928): wiretaps did not require special authorization if no trespassing necessary • U.S. Supreme Court (1967): wiretaps, even of public phone booths, require prior judicial authorization Intelligent Environments

11. Effectiveness of Wiretapping • Activity since 1968 (EPIC) • Each wiretap actually enabled monitoring many conversations • Computerization complicates wiretapping • Digital data • Computer switching • Optical fiber transmission • Need to know data structures, formats and algorithms used in communication systems Intelligent Environments

12. Digital Telephony Standards • 1994 mandate that communications systems equipment be designed to allow practical wiretapping by law enforcement • Isolate the communications stream of an individual • $500M allocated for conversion • Communications Assistance for Law Enforcement Act (CALEA) Intelligent Environments

13. Digital Telephony Standards: Issues • Most effective way to fight crime? • Increase government’s “big brother” power? • Security problems? • Hindering technological advance? • Who pays for the cost? • Effect on U.S. industry competitiveness? • Mandated capabilities useful? Intelligent Environments

14. Encryption • Wiretapping encrypted digital communication of no use • Solutions • Break encryption scheme • Legislate encryption Intelligent Environments

15. Private-Key Encryption • Also called secret key or symmetric • Algorithm public; key private • Easy to break if number of possible keys is small • Problems • How to securely distribute private key • Ensuring authenticity of messages Intelligent Environments

16. Data Encryption Standard (DES) • Developed at IBM in 1977 • Private-key encryption • 56-bit key (256 = 72 x 1015 keys) • Key chosen randomly for each message • Applies 56-bit key to each 64-bit block of data • Multiple passes for stronger encryption • Triple DES still in use (256+56+56 keys) Intelligent Environments

17. Public-key Encryption • Also called asymmetric • Each person generates a public and private key • Everybody knows public keys • Only individual A need know their own private key • privateA(publicA(M)) = M • publicA(privateA(M)) = M Intelligent Environments

18. Public-key Encryption • Digital signatures • Person A encrypts message M with their private key to get M’ • Person A encrypts M’ with B’s public key to get M’’, which is sent to B • Person B decrypts M’’ with private key to get M’ • Person B decrypts M’ with A’s public key to get M, but only if from A • publicA(privateB(publicB(privateA(M))) = M Intelligent Environments

19. Generating Public/Private Key Pairs • RSA algorithm (patented) • encryptA(M) = Me modulo n • decryptA(M) = Md modulo n • Public key = (e,n) • Private key = (d,n) • n = p*q, where p and q are large random primes • e and d chosen based on p and q • Security rests on difficulty to factor product n of two large primes Intelligent Environments

20. Government Encryption Policy • Government’s position • Public-key encryption too difficult to wiretap • Limit export of encryption • Design own tap-able encryption scheme • Industry’s position • Use widely-accepted, strong encryption standard • Freely export standard Intelligent Environments

21. Escrowed Encryption Standard • EES developed by U.S. government in 1993 • Skipjack algorithm implemented on the Clipper and Capstone chips • Private-key encryption • Each chip has an 80-bit unit key U, which is escrowed in two parts to two different agencies • Chip also includes a 30-bit serial number and an 80-bit family key F common to all Clipper chips Intelligent Environments

22. Escrowed Encryption Standard • Two devices agree on an 80-bit session key K to communicate • Message is encrypted with key K and sent • Law-Enforcement Access Field (LEAF) appended to message, including • Session key K encrypted with unit key U • Serial number of sender • All encrypted with family key F Intelligent Environments

23. ESS Wiretapping • Use family key to obtain LEAF • Now have serial number of sending device and encrypted session key • Upon authorization, two agencies present their two escrowed portions of the unit key U • Use unit key U to decrypt session key K • Use K to decrypt message Intelligent Environments

24. EES Issues • Circumvention • Security • Skipjack algorithm • Escrowed keys • Both escrow agents governmental • U.S. industry competitiveness • “Forgetting” unit keys • EES dropped due to public opposition Intelligent Environments

25. Advanced Encryption Standard • AES is U.S. government’s encryption standard as of 2001 • Rijndael algorithm selected from among several candidates • Efficient block cipher • Variable block and key length • AES supports 128, 192 and 256 bits • See http://www.nist.gov/aes Intelligent Environments

26. Current Issues • Encryption export limitations • Relaxed January 2000 • Key recovery (escrowed) encryption • Any encrypted message must be decryptable by law enforcement with proper authorization • Encrypter must provide means to decrypt message • Fifth amendment issues • Wireless communications Intelligent Environments

27. Points to Remember • Law enforcement using new wiretap legislation to monitor email • Escrowed key approaches likely to never catch on • AES holds promise • Law enforcement needs mechanism to decrypt information pertinent to criminal activity • There is no specific “right to privacy” in the U.S. Constitution Intelligent Environments

28. Privacy Law Resources • Electronic Privacy Information Center • www.epic.org • Electronic Frontier Foundation • www.eff.org Intelligent Environments

29. Firewalls • Filter packets not meeting specified constraints • IP number constraints • Port constraints • Connection-type constraints • IETF IP Security Standard (IPSEC) • Secure Shell (www.ssh.com) • Good countermeasure, but complicated to administrate Intelligent Environments

30. Intrusion Detection • Tripwire • Firewall programming • Pattern recognition • Behavioral outliers Intelligent Environments

31. Biometrics • Biometrics • Automatically recognizing a person using distinguishing traits • Modes • Face • Iris, retinal • Vein • Fingerprint, hand and finger geometry • Handwriting • Voice Intelligent Environments

32. Face Recognition • Controlled background • By color (skin) • By motion (e.g., blinks) • Mixture of above • Unconstrained scenes • Neural networks • Model-based • CMU: www.ri.cmu.edu/labs/lab_51.html Intelligent Environments

33. Iris and Retinal Biometrics • Identify iris • Encode wavelet patterns • 100,000 comparisons per second on 300MHz machine • Vein mapping Intelligent Environments

34. Vein ID • Grayscale image from back of hand • Image segmentation and edge detection • Generate unique vein map • www.veinid.com Intelligent Environments

35. Fingerprint and Hand • Approaches • Transform image • Transforms • Fourier transform • Time to frequency • Wavelet transform • Time to frequency/occurrence Intelligent Environments

36. Handwriting • Hidden Markov models • Neural networks Intelligent Environments

37. Voice • Markov models Intelligent Environments

38. Software Safety • Risk analysis is a difficult task that has a subjective component • A software model of a real physical system can never perfectly represent all relevant aspects of the system • Over-reliance on computer models that are not properly validated invites disaster Intelligent Environments

39. Software Safety • No widely accepted standard for developing safety-critical software • Resources • The Risks Digest • http://catless.ncl.ac.uk/Risks/ • CMU Software Engineering Institute • http://www.sei.cmu.edu/ Intelligent Environments

40. Degree of Autonomy “2001: A Space Odyssey” Turner Entertainment, 1968 Intelligent Environments

41. Security and Privacy • Law enforcement • Individual counter measures • Encryption • Firewalling • Biometrics • Degree of autonomy Intelligent Environments