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Phishing

Phishing . markus.jakobsson@parc.com. Conventional Aspects of Security. Computational assumptions E.g., existence of a one-way function, RSA assumption, Decision Diffie-Hellman Adversarial model E.g., access to data/hardware, ability to corrupt, communication assumptions, goals

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Phishing

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  1. Phishing markus.jakobsson@parc.com

  2. Conventional Aspects of Security • Computational assumptions • E.g., existence of a one-way function, RSA assumption, Decision Diffie-Hellman • Adversarial model • E.g., access to data/hardware, ability to corrupt, communication assumptions, goals • Verification methods • Cryptographic reductions to assumptions, BAN logic • Implementation aspects • E.g., will the communication protocol leak information that is considered secret in the application layer?

  3. The human factor of security Successful Neglect Deceit attack Configuration

  4. The human factor: configuration Weak passwords With Tsow, Yang, Wetzel: “Warkitting: the Drive-by Subversion of Wireless Home Routers” (Journal of Digital Forensic Practice, Volume 1, Special Issue 3, November 2006) Wireless firmware update wardriving rootkitting Shows that more than 50% of APs are vulnerable

  5. The human factor: configuration Weak passwords With Stamm, Ramzan: “Drive-By Pharming” (Symantec press release, Feb 15, 2007; top story on Google Tech news on Feb 17; Cisco warns their 77 APs are vulnerable, Feb 21; we think all APs but Apple’s are at risk. Firmware update tested on only a few. Paper in submission) Wireless nvram value setting “Use DNS server x.x.x.x” And worse: geographic spread!

  6. The human factor: neglect

  7. The human factor: deceit (Threaten/disguise - image credit to Ben Edelman)

  8. The human factor: deceit Self: “Modeling and Preventing Phishing Attacks” (Panel, Financial Crypto, 2005 - notion of spear phishing) With Jagatic, Johnson, Menczer: “Social Phishing” (Communications of the ACM, Oct 2007) With Finn, Johnson: “Why and How to Perform Fraud Experiments” (IEEE Security and Privacy,March/April 2008)

  9. Experiment Design

  10. Gender Effects

  11. eBay Ethical and accurate assessments With Ratkiewicz “Designing Ethical Phishing Experiments: A study of (ROT13) rOnl auction query features” (WWW, 2006) Reality: 2 1 B A 3 credentials 4

  12. Ethical and accurate assessments With Ratkiewicz “Designing Ethical Phishing Experiments: A study of (ROT13) rOnl auction query features” (WWW, 2006) Attack: B 1 (spoof) A 2 credentials

  13. eBay Ethical and accurate assessments With Ratkiewicz “Designing Ethical Phishing Experiments: A study of (ROT13) rOnl auction query features” (WWW, 2006) A 2 Experiment: 3 (spoof) 2 1 B A 1 5 4 credentials Yield (incl spam filtering loss): 11% + 3% …“eBay greeting” removed: same -

  14. starting with 4901 Mutual authenticationin the “real world” With Tsow,Shah,Blevis,Lim, “What Instills Trust? A Qualitative Study of Phishing” (Abstract at Usable Security, 2007)

  15. How does the typical Internet user identify phishing?

  16. Spear Phishing and Data Mining Current attack style: Approx 3% of adult Americans report to have been victimized.

  17. Spear Phishing and Data Mining More sophisticated attack style: “context aware attack”

  18. Jane Garcia, Jose Garcia … and little Jimmy Garcia How can information be derived? Jose Garcia Jane Smith

  19. their marriage license his parents and Jimmy’s mother’s maiden name: Smith Let’s start from the end! “Little” Jimmy More reading: Griffith and Jakobsson, "Messin' with Texas: Deriving Mother's Maiden Names Using Public Records."

  20. www.browser-recon.info

  21. Approximate price list: PayPal user id + password $1 + challenge questions $15 Why?

  22. Password Reset:Typical Questions • Make of your first car • Mother’s maiden name • City of your birth • Date of birth • High school you graduated from • First name of your / your sister’s best friend • Name of your pet • How much wood would a woodchuck …

  23. Problem 1: Data Mining • Make of your first car? • Until 1998, Ford has >25% market share • First name of your best friend? • 10% of males named James (Jim), John, or Robert (Bob or Rob) + Facebook does not help • Name of your first / favorite pet? • Top pet names are online

  24. Problem 2: People Forget • Name of the street you grew up on? • There may have been more than one • First name of your best friend / sisters best friend? • Friends change, what if you have no sister? • City in which you were born? • NYC? New York? New York City? Manhattan? The Big Apple? • People lie to increase security … then forget!

  25. Intuition Preference-based authentication: • preferences are more stable than long-term memory (confirmed by psychology research) • preferences are rarely documented (in contrast to city of birth, brand of first car, etc.) … especially dislikes!

  26. Our Approach (1) Demo at Blue-Moon-Authentication.com, info at I-forgot-my-password.com

  27. Our Approach (2)

  28. And next? http://www. democratic-party.us/LiveEarth http://www. democratic-party.us/LiveEarth

  29. Countermeasures? • Technical • Better filters • CardSpace • OpenId • Educational • SecurityCartoon • Suitable user interfaces • Legal

  30. Interesting? Internships at PARC / meet over coffee / etc. markus.jakobsson@parc.com

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