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User(-to-Device) Authentication* Nitesh Saxena NYU-Poly *Adopted from a previous lecture by Vitaly Shmatikov Recall: Basic Problem Recall: Many Ways to Authenticate ... – PowerPoint PPT presentation

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Title: Nitesh Saxena


1
User(-to-Device) Authentication
  • Nitesh Saxena
  • NYU-Poly
  • Adopted from a previous lecture by Vitaly
    Shmatikov

2
Recall Basic Problem
?
How do you prove to someone that you are
who you claim to be?
Any system with access control must solve this
problem
3
Recall Many Ways to Authenticate
  • Something you know
  • Passwords/PINs
  • Something you have
  • Secure tokens
  • Something you are
  • Biometrics
  • What is the best method to authenticate secure
    as well as usable and universal? Is there any?

4
(Textual) Passwords
  • User has a secret password.
  • System checks it to authenticate the user.
  • How is the password communicated?
  • Eavesdropping risk
  • How is the password stored?
  • In the clear? Encrypted? Hashed?
  • How does the system check the password?
  • How easy is it to guess the password?
  • Easy-to-remember passwords tend to be easy to
    guess
  • Password file is difficult to keep secret

5
Passwords in the Real World
PasswordResearch.com
  • From high school pranks
  • Student in Tyler changes school attendance
    records
  • Students in California change grades
  • Different authentication for network login and
    grade system, but teachers were using the same
    password (very common)
  • to serious cash
  • English accountant uses co-workers password to
    steal 17 million for gambling
  • to identity theft
  • Helpdesk employee uses passwords of a credit card
    database to sell credit reports to Nigerian
    scammers

6
Passwords and Computer Security
  • First step after any successful intrusion
    install
  • sniffer or keylogger to steal more passwords
  • Second step run cracking tools on password files
  • Usually on other hijacked computers
  • In Mitnicks Art of Intrusion, 8 out of 9
    exploits involve password stealing and/or
    cracking
  • Excite_at_Home usernames and passwords stored in
    the clear in troubleshooting tickets
  • Dixie bank hack use default router password to
    change firewall rules to enable incoming
    connections

7
UNIX-Style Passwords
cypherpunk
user
system password file
t4h97t4m43 fa6326b1c2 N53uhjr438 Hgg658n53
hash function
8
Password Hashing
  • Instead of user password, store H(password)
  • When user enters password, compute its hash and
    compare with entry in password file
  • System does not store actual passwords!
  • Difficult to go from hash from password!
  • Hash function H must have some properties
  • One-way given H(password), hard to find password
  • No known algorithm better than trial and error
  • Is collision resistance needed?

9
UNIX Password System
  • Uses DES encryption as if it were a hash function
  • Encrypt NULL string using password as the key
  • Truncates passwords to 8 characters!
  • Can instruct modern UNIXes to use MD5 hash
    function
  • Problem passwords are not truly random
  • With 52 upper- and lower-case letters, 10 digits
    and 32 punctuation symbols, there are 948 ? 6
    quadrillion possible 8-character passwords
  • Humans like to use dictionary words, human and
    pet names ? 1 million common passwords

10
Dictionary Attack
  • Password file /etc/passwd is world-readable
  • Contains user IDs and group IDs which are used by
    many system programs
  • Dictionary attack is possible because many
    passwords come from a small dictionary
  • Attacker can pre-compute H(word) for every word
    in the dictionary this only needs to be done
    once!!
  • This is an offline attack
  • Once password file is obtained, cracking is
    instantaneous
  • With 1,000,000-word dictionary and assuming 10
    guesses per second, brute-force online attack
    takes 50,000 seconds (14 hours) on average

11
Salt
shmatfURxfg,4hLBX1451030Vitaly/u/shmat/bin/c
sh
/etc/passwd entry
salt (chosen randomly when password is first set)
hash(salt,pwd)
Password
  • Users with the same password have different
    entries in the password file
  • Offline dictionary attack becomes much harder

12
Advantages of Salting
  • Without salt, attacker can pre-compute hashes of
    all dictionary words once for all password
    entries
  • Same hash function on all UNIX machines
    identical passwords hash to identical values
  • One table of hash values works for all password
    files
  • With salt, attacker must compute hashes of all
    dictionary words once for each combination of
    salt value and password
  • With 12-bit random salt, same password can hash
    to 4096 different hash values

13
Shadow Passwords
shmatx1451030Vitaly/u/shmat/bin/csh
/etc/passwd entry
Hashed password is not stored in a world-readable
file
  • Store hashed passwords in /etc/shadow file which
    is only readable by system administrator (root)
  • Add expiration dates for passwords
  • Early Shadow implementations on Linux called the
    login program which had a buffer overflow!

14
Password Security Risks
  • Keystroke loggers
  • Hardware
  • KeyGhost, KeyShark, others
  • Software (spyware)
  • Acoustic emanations
  • Electromagnetic emanations
  • Online attacks
  • Lock account after few attempts
  • CAPTCHAs
  • Offline attacks
  • These can be dealt with somewhat (how?), but.

15
User Issues!!
  • Make passwords easy to remember
  • password, Longhorns, Kevin123
  • Write them down
  • Use a single password at multiple sites
  • Do you use the same password for Amazon and your
    bank account? MyPoly? Do you remember them all?
  • Some services use secret questions
  • to reset passwords
  • What is your favorite pets name?
  • Paris Hiltons T-Mobile cellphone hack
  • Susceptible to Social Engineering
  • e.g., Phishing

16
Social Engineering
  • Univ. of Sydney study (1996)
  • 336 CS students emailed asking for their
    passwords
  • Pretext validate password database after
    suspected break-in
  • 138 returned their passwords 30 returned invalid
    passwords 200 reset passwords (not disjoint)
  • Treasury Dept. report (2005)
  • Auditors pose as IT personnel attempting to
    correct a network problem
  • 35 (of 100) IRS managers and employees provide
    their usernames and change passwords to a known
    value
  • Other examples Mitnicks Art of Deception

17
A recent mailat my Poly Id
  • From "Webmaster" ltcustomer.care_at_8u8.comgt
  • To ltundisclosed-recipientsgt
  • Sent Tuesday, December 08, 2009 654 PM
  • Subject Notification
  • gt gt gt Dear Mail User,gt gt Due to spam
    complaints of email users in our webmail system,
    ourgt investigation shows that your email address
    is compromised and isgt used to send out spam
    message in our webmail system.gt gt As a result,
    our network engineer will be conducting a
    maintenancegt in our webmail system, your
    Username will be disabled if you do not  gt send
    us the required information within 48hrs to the
    webmailgt Engineering Email for proper
    cerification.gt gt Informations Required
    .................gt Your Full Names...........gt
    Email address .................gt
    Password................gt Retype
    Password.................gt Maintenance
    Engineering Email Address customer.care_at_8u8.comgt
    gt NoteYou are to forward these information to
    Engineers forgt maintenance purpose.(
    customer.care_at_8u8.com )gt gt Thanks you for your
    co-operations.gt

18
A Recent Email
Images from Anti-Phishing Working Groups
Phishing Archive
19
Images from Anti-Phishing Working Groups
Phishing Archive
20
The next page requests
  • Name
  • Address
  • Telephone
  • Credit Card Number, Expiration Date, Security
    Code
  • PIN
  • Account Number
  • Personal ID
  • Password

21
Images from Anti-Phishing Working Groups
Phishing Archive
22
But wait
WHOIS 210.104.211.21 Location Korea,
Republic Of
Images from Anti-Phishing Working Groups
Phishing Archive
23
(No Transcript)
24
Phishing A Growing Problem
  • Over 16,000 unique phishing attacks reported in
    Nov. 2005, about double the number from 2004
  • Estimates suggest phishing affected 1.2 million
    US citizens and cost businesses billions of
    dollars in 2004
  • Additional losses due to consumer fears

Anti-Phishing Working Group, Phishing Activity
Trends Report, Dec. 2005
25
Basic Phishing Attack
  • Victim receives email seemingly from an
    institution
  • Often reports a problem with victims account
  • Email demands immediate action
  • Victim led to a website that mimics that of the
    institution
  • Prompted to enter account information, passwords,
    personal information, etc.
  • Two variations
  • Passive Attacker collects victims information
    for later exploitation
  • Active Attacker relays victims information to
    the real institution and plunders the account in
    real time

26
Current Phishing Techniques
  • Employ visual elements from target site
  • DNS Tricks
  • www.ebay.com.kr
  • www.ebay.com_at_192.168.0.5
  • www.gooogle.com (typosquatting)
  • Unicode attacks
  • JavaScript Attacks
  • Spoofed SSL lock
  • Certificates
  • Phishers can acquire certificates for domains
    they own
  • Certificate authorities make mistakes

27
Advanced Phishing Attacks
  • Spear-phishing Improved target selection
  • Socially aware attacks Jakobsson 2005
  • Mine social relationships from public data
  • Phishing email appears to arrive from someone
    known to the victim
  • Context-aware attacks ibid
  • Your bid on eBay has won!
  • The books on your Amazon wishlist are on sale!

28
User Issues!!
  • Users are task-focussed
  • Security is a secondary objective
  • Users choose bad passwords and readily disclose
    them
  • Users cannot parse URLs, domain names or PKI
    certificates
  • Users are inundated with warnings and pop-ups

29
Phishing Prevention Approaches
  • Heuristics
  • Spoofguard Chou et al. 2004, TrustBar HerzGbar
    2004, eBay toolbar, SpoofStick
  • Recent studies indicate users ignore toolbar
    warnings Wu et al. 2005

30
Spoofguard example
31
Other Approaches
  • Origin/Server Authentication
  • Dynamic Security Skins DhamTyga 2004, Passmark,
    and the Petname project BankofAmerica SiteKey
  • All rely on user diligence a single mistake
    will result in a compromised account (slow to
    load image!)

32
Another approach
  • PwdHash
  • Instead of the password p, share the hash of the
    password (contatenated with domain name)
    H(p, domain)
  • User types in the password p, the browser
    computes H(p, domain) and send it to the server
  • Phishing site learns the hashed value for its own
    doman, which is of no direct use (except
    running a dictionary attack on the password)

33
In summary
  • Lot of problems with the passwords
  • Especially due to user behavior
  • Can we help users pick strong(er) passwords
  • Use of mnemonics Easy to remember but hard to
    guess phrases
  • Phrase to a password
  • Jack and Jill went up the hill (JaJwuth)
    (probably not good!)
  • Ive owned 4 Gateway computers so far (Io4Gcsf
    )
  • Other Directions

34
Graphical Passwords
  • Images are easy for humans to recall/recognize
  • Especially if you invent a memorable story to go
    along with the images
  • Images can not be written down

35
Recognition Based Techniques
  • Dhamija and Perrig Scheme
  • Pick several pictures out of many choices,
    identify them later
  • in authentication.
  • http//www.random-art.org/
  • Using Hash Visualization, which,
  • given a seed, automatically
  • generate a set of pictures
  • No need to store images, but
    take longer to create
    passwords
  • password space N!/K! (N-K)!
  • ( N-total number of pictures K-number of
    pictures selected as passwords)

36
Recognition Based Techniques
  • Sobrado and Birget Scheme
  • System display a number of pass-objects
    (pre-selected by user) among many other objects,
    user click inside the convex hull bounded by
    pass-objects.
  • authors suggeated using 1000
  • objects, which makes the display
  • very crowed and the objects almost
  • indistinguishable.
  • password space N!/K! (N-K)!
  • ( N-total number of picture objects K-number of
    pre-registered objects)

37
Recognition Based Techniques
  • PassFaces
  • Using human faces as password

38
User Quotes
  • I chose the images of the ladies which appealed
    the most
  • I simply picked the best lookin girl on each
    page
  • In order to remember all the pictures for my
    login (after forgetting my password 4 times in
    a row) I needed to pick pictures I could EASILY
    remember... So I chose beautiful women. The other
    option I would have chosen was handsome men, but
    the women are much more pleasing to look at

39
More User Quotes
  • I picked her because she was female and Asian
    and being female and Asian, I thought I could
    remember that
  • I started by deciding to choose faces of people
    in my own race
  • Plus he is African-American like me

40
Recall Based Techniques
  • Draw-A-Secret (DAS) Scheme
  • User draws a simple picture on a 2D grid, the
    coordinates of the
  • grids occupied by the picture are stored in the
    order of drawing
  • redrawing has to touch the
  • same grids in the same
  • sequence in authentication
  • user studies showed the
  • drawing sequences is hard to
  • Remember

41
Recall Based Techniques
  • PassPoint Scheme
  • User click on any place on an image to create a
    password. A tolerance
  • around each chosen pixel is calculated. In order
    to be authenticated,
  • user must click within the tolerances in correct
    sequence.
  • can be hard to remember the
  • sequences
  • Password Space NK
  • ( N -the number of pixels or smallest
  • units of a picture, K - the number of
  • Point to be clicked on )

42
Disadvantages
  • Graphical password schemes are perceived to be
    more vulnerable to shoulder surfing
  • A change in Infrastructure is needed
  • Need to store, transmit images

43
Biometric Authentication
  • Nothing to remember
  • Passive
  • Nothing to type, no devices to carry around
  • Cant share (usually)
  • Can be fairly unique
  • If measurements are sufficiently accurate

44
Problems with Biometrics
  • Identification vs. authentication
  • Identification associating an identity with an
    event or a piece of data
  • Example fingerprint at a crime scene
  • Authentication verifying a claimed identity
  • Example fingerprint scanner to enter a building
  • How hard are biometric readings to forge?
  • Difficulty of forgery is routinely overestimated
  • Analysis often doesnt take into account the
    possibility of computer-generated forgery
  • Revocation is difficult or impossible

45
Fake Fingers
Schuckers
  • Gelatin gummy fingers
  • Play-Doh fingers fool 90 of fingerprint scanners
  • Clarkson University study
  • Suggested perspiration measurement to test
    liveness of the finger

46
Face/off ?
47
Tokens
  • Generally used to improve security of passwords
  • Two-factor authentication Something you have
    Something you know
  • Use of one time passwords
  • Example RSA SecurID (many different forms)
  • Problem token might not be available, when
    needed also each secure site needs a different
    token

48
References
  • Use google
  • Some of these can be found here
  • http//www.cs.utexas.edu/shmat/courses/cs378_fall
    07/cs378_ref.html
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