Authentication CS 461ECE 422 Spring 2012 Readings Chapter

Authentication CS 461/ECE 422 Spring 2012

Readings • Chapter 3 from text • Rainbow tables – http: //kestas. kuliukas. com/Rainbow. Tables/ • Chapter 10 from Handbook of Applied Cryptography http: //www. cacr. math. uwaterloo. ca/hac/abo ut/chap 10. pdf

Overview • • Basic elements of Authentication Password Systems Token Based Systems Biometrics

Ivanhoe, Sir Walter Scott • Paraphrased: (Wamba gains entry to the castle dressed as a friar) Wamba: Take my disguise and escape, I will stay and die in your place. Cedric: I can’t possibly impersonate a friar, I only speak English. Wamba: If anyone says anything to you, just say “Pax vobiscum. ” Cedric: What does that mean? Wamba: I don’t know, but it works like a charm! 4

Basics • Authentication: binding of identity to subject – Identity is that of external entity (my identity, the Illini Union Bookstore, etc. ) – Subject is computer entity (process, network connection, etc. ) – Two steps – Identification step: present identifier to security system. Registration – Verification step: Present or generate authentication information that corroborates the binding between entity and identifier 5

Establishing Identity • One or more of the following What entity knows (e. g. password, private key) What entity has (e. g. badge, smart card) What entity is (e. g. fingerprints, retinal characteristics) What entity does (e. g. , voice pattern, handwriting, typing rhythm) – Where entity is (e. g. In front of a particular terminal) – – • Example: scene from Ivanhoe • Example: Credit card transaction • Multi-factor authentication • Use multiple elements to prove identity 6

Complementation Information • User provides information to verify identity • System stores a processed version of this information as the complementation information • The complementation function maps from the user provided data to the system stored data

Password-based Authentication • External entity is bound to system ID (user account) • Authentication Step – External entity presents password – System compares with previously stored password – If password matches, system starts process with bound ID • Later access control decisions made against ID • Privilege decisions made against ID

Password Vulnerabilities • Password systems widely used, but very vulnerable – Offline dictionary attack – Specific account attack – Workstation hijacking – Sticky notes – Password reuse – Social engineering – Electronic monitoring

Password Storage • Store as cleartext – If password file compromised, all passwords revealed • Encipher file – Need to have decipherment, encipherment keys in memory – Reduces to previous problem • Store one-way hash of password – If file read, attacker must still guess passwords or invert the hash 10

Unix Password Hash Example • Original UNIX system standard hash function – Hashes password into 13 char string – As authentication system: – Authentication information is strings of 8 characters or less – System stores hash with user’s identity in password file – Hash is complementation information – Verification function is hash on password and comparison with stored hash 11

Salting • Have a set of n hash functions – Randomly select one function when registering new authentication info – Store ID of function with registered info • Attacker must try all n functions to see if his guess matches any password • When does this help? When does it not? 12

Examples • Vanilla UNIX method – Use DES to encipher 0 message with password as key; iterate 25 times – Perturb E table in DES in one of 4096 ways • 12 bit salt flips entries 0– 11 with entries 24– 35 • E Table is per round expansion table • Alternate methods – Use salt as first part of input to hash function 13

Dictionary Attacks • Trial-and-error from a list of potential passwords – Off-line (type 1): know functions and registered information, and repeatedly try different guesses g A until the list is done or passwords guessed • Examples: crack, john-the-ripper – On-line (type 2): have access to verification functions. Try guesses until one succeeds. – Examples: trying to log in by guessing a password 14

Preventing Attacks • How to prevent this: – Hide information so that either authentication input, authentication functions, or stored verification information cannot be found. Prevents obvious attack from above • Example: UNIX/Linux shadow password files – Hides c’s – Block access to all verification methods • Prevents attacker from knowing if guess succeeded • Example: preventing any logins to an account from a network – Prevents knowing results of verification function or accessing verification function. 15

Rainbow Tables • Rather than keeping dictionary list, could pre-compute the hashes of the dictionary values – For large dictionaries, still a lot of space – Particularly if using a smart lookup table • Trade off space for time with hash chain – p 1 ->H(p 1)->R(H(p 1))->H(R(H(p 1))) – aaaaaa –h-> 281 DAF 40 –r-> sgfnyd –h-> 920 ECF 10 – Reduction function, r, picks another plaintext from the hash. It is not the inverse hash – Only store start and end of hash – Given hash to break, look for it in the end of the chains. – Apply reduction and hash if not found – Continue until found

Rainbow Tables • Collisions are the problems with rainbow tables – Two passwords may hash to the same value – One of those values will be lost in the hash chain • Could use many small tables with different reduction functions • Could use a different reduction function for each column – Thus a “Rainbow” table

Rainbow tables • Very effective against Lan Manager Hashes – Calculated by XP and up to Windows 2008 by default for “backwards compatibility” – Can download huge tables from a number of free sites • Decent sized hashes make the rainbow table pre-computation space infeasible

Using Time Anderson’s formula: • P probability of guessing a password in specified period of time • G number of guesses tested in 1 time unit • T number of time units • N number of possible passwords (|A|) • Then 19

Example • Goal – – Passwords drawn from a 96 -char alphabet Can test 104 guesses per second Probability of a success to be 0. 5 over a 365 day period What is minimum password length? • Solution – N ≥ TG/P = (365 24 60 60) 104/0. 5 = 6. 31 1011 – Choose s such that – So s ≥ 6, meaning passwords must be at least 6 chars long – What exactly does that equation mean? 20

Approaches: Password Selection • Random selection – Any password from A equally likely to be selected – See previous example – Make sure it’s random! • Pronounceable passwords • User selection of passwords 21

Pronounceable Passwords • Generate phonemes randomly – Phoneme is unit of sound, e. g. cv, vc, cvc, vcv – Examples: helgoret, juttelon are; przbqxdfl, zxrptglfn are not • ~ 440 possible phonemes • 4406 possible keys with 6 phonemes (12 -18 characters long), about the same as 968 • Used by GNU Mailman mailing list software (? ) 22

User Selection • Problem: people pick easy-to-guess passwords – Based on account names, user names, computer names, place names – Dictionary words (also reversed, odd capitalizations, control characters, “l 33 t-speak”, conjugations or declensions, Torah/Bible/Koran/… words) – Too short, digits only, letters only – License plates, acronyms, social security numbers – Personal characteristics or foibles (pet names, nicknames, etc. ) – Using the same password in multiple accounts 23

User Password Education • Use the first letter of each word in a phrase – “My dog’s first name is Rex. ” becomes “Mdfni. R”

Reactive Password Checking • Have a password cracking program running in the background – Shut down account of passwords it can crack – CPU intensive – Shutting down active accounts is likely to annoy someone important eventually.

Proactive password checking • Don’t let them pick a “bad” password in the first place • Need to have a fairly fast test of the “goodness” of a password

Markov Model • Reduce space requirements of bad password list • Create model that represents the bad password database • Created from trigrams (three letter segments) from words in bad password list

Bloom Filter • Another way of encoding the bad password dictionary in a small cheap to check data structure • Create N bit array • Use k independent hash functions which hash into a space of 0 to N-1 • For each bad password, – Compute every version of the hash, and set the corresponding bit in the hash table for every hash value • To check a password – Computer every version of the hash, and check the corresponding bits in the array – If all bits are 1, then the password is bad • Will allow some false positives – Passwords marked bad that weren’t in the original list • But it will not generate any false negatives.

Challenge-Response • User and system share a secret function • User proves knowledge of secret function by answering challenge request to authenticate system user random message r (the challenge) system user f(r) (the response) system user 29

One-Time Passwords • Password that can be used exactly once – After use, it is immediately invalidated • Challenge-response mechanism – Challenge is one of a number of authentications; response is password for that particular number • Problems – Synchronization of user, system – Generation of good random passwords – Password distribution problem 30

S/Key • One-time password scheme based on idea of Lamport • h one-way hash function (MD 5 or SHA-1, for example) • User chooses initial seed k • System calculates: h(k) = k 1, h(k 1) = k 2, …, h(kn– 1) = kn • Passwords are reverse order: p 1 = kn, p 2 = kn– 1, …, pn– 1 = k 2, pn = k 1 31

S/Key Protocol System stores maximum number of authentications n, number of next authentication i, last correctly supplied password pi– 1. user { name } {i} { pi } system System computes h(pi) = h(kn–i+1) = kn–i+2 = pi– 1. If match with what is stored, system replaces pi– 1 with pi and increments i. 32

Token-based Authentication • Something you have • Memory Cards – No computation on the card – Need special reader to pull data off the card – Need pin to decrypt data off of card – E. g. , ATM card or debit card • By adding PIN (something you know) you get multi-factor authentication

Token Based Authentication • Smart Card – Computation on the card – Plug in with USB or wireless communication (credit card) • Authentication options – Static – equivalent to memory card – Dynamic password generator – generates a unique password every minute. – Challenge response

Biometrics • Automated measurement of biological, behavioural features that identify a person – Fingerprints: optical or electrical techniques • Maps fingerprint into a graph, then compares with database • Measurements imprecise, so approximate matching algorithms used – Voices: speaker verification or recognition • Verification: uses statistical techniques to test hypothesis that speaker is who is claimed (speaker dependent) • Recognition: checks content of answers (speaker independent) 35

Other Characteristics • Can use several other characteristics – Eyes: patterns in irises unique • Measure patterns, determine if differences are random; or correlate images using statistical tests – Faces: image, or specific characteristics like distance from nose to chin • Lighting, view of face, other noise can hinder this – Keystroke dynamics: believed to be unique • Keystroke intervals, pressure, duration of stroke, where key is struck • Statistical tests used 36

Biometric • Physical characteristics encoded in a template – The C or complement information • User registers physical information (S) – Generally with multiple measurements • The verification function takes a measurement and tries to line up with template 37

Authentication vs Identification • Used for surveillance – Subject is motivated to avoid detection • Used for authentication – Subject is motivated to positively identify – Perhaps pick up other's characteristics • False positives vs false negatives 38

Biometric Cautions • These can be fooled! – Assumes biometric device accurate in the environment it is being used in! – Transmission of data to validator is tamperproof, correct (remember pax vobiscum) • Physical characteristics change over time • Some people may not be able to identify via specific characteristics – Albinos and iris scans 39

Biometric Cautions • Where are the biometric templates stored? • What if your biometric template data is stolen?

Key Points • Passwords are the reality for now • Multi-factor authentication is must stronger • Biometrics can help, but not a silver bullet yet