Presentation Transcript
Users Are Not DependableHow to make security indicators that protect them better : Users Are Not Dependable How to make security indicators that protect them better Min Wu, Simson Garfinkel, Robert Miller
MIT Computer Science and Artificial Intelligence Lab
User Is Part Of System : User Is Part Of System “Weakest link” in operational security systems
If attackers can easily trick users into compromising their security, they do not have to try hard to directly attack the system.
A typical attack: Phishing
Security Indicators : Security Indicators “Look for the lock at the bottom of your browser and ‘https’ in front of the website address.”
Security Indicators : Security Indicators “Look for the lock at the bottom of your browser and ‘https’ in front of the website address.”
More Security Indicators : More Security Indicators
More Security Indicators : More Security Indicators Spoofstick
More Security Indicators : More Security Indicators Netcraft
Toolbar
More Security Indicators : More Security Indicators Trustbar
More Security Indicators : More Security Indicators eBay
Account
Guard
More Security Indicators : More Security Indicators Spoofguard
Outline : Outline Introduction of security indicators
Anti-phishing user study
Web authentication using cell phones
Conclusions
Security Toolbar Abstractions : Security Toolbar Abstractions SpoofStick Netcraft Toolbar eBay Account Guard SpoofGuard Neutral-Information Toolbar System-Decision Toolbar Positive-Information Toolbar TrustBar
Study Scenario : Study Scenario We set up dummy accounts as John Smith at various websites
“You are the personal assistant of John Smith. John is on vacation now. During his vacation, he sometimes sends you emails asking you to do some tasks for him online.”
“Here is John Smith’s profile.”
Study Scenario : Study Scenario Users dealt with 20 emails forwarded by John Smith.
5 emails were phishing emails.
Most of the emails were about managing John’s wish lists at various sites
Slide16 : Main Frame
Slide17 : Address bar frame http://tigermail.co.kr/cgi-bin/webscrcmd_login.php
Slide18 : Toolbar frame Status bar frame
Attack Types : Attack Types 1. Similar-name attack
2. IP-address attack
3. Hijacked-server attack
4. Popup-window attack
5. Paypal attack bestbuy.com www.bestbuy.com.ww2.us bestbuy.com 212.85.153.6 bestbuy.com www.btinternet.com
Security Toolbar Display : Security Toolbar Display Legitimate Site Phishing Site vs.
Attack Pattern : Attack Pattern
Recruitment : Recruitment 30 users
Recruited at MIT, paid $15 for one hour
10 for each toolbar
Average age 27 [18-50]
14 females and 16 males
20 MIT students, 10 not Neutral-Information
Toolbar System-Decision Toolbar Positive-Information Toolbar
Spoof Rates With Different Toolbars : Spoof Rates With Different Toolbars
Spoof Rates With Different Attacks : Spoof Rates With Different Attacks p = 0.052 (ANOVA)
Why Did Users Get Fooled? : Why Did Users Get Fooled? 20 out of 30 got fooled by at least one attack. Among the 20 users
17 (85%) claimed web content is professional or familiar; 7 (35%) depended on security-related content
12 (60%) explained away odd behaviors
“I have been to sites that use plain IP addresses.”
“Sometimes I go to a website, and it directs me to another site with a different address.”
“Yahoo may have just opened a branch in Brazil and thus registered there.”
“I must have mistakenly triggered the popup window.”
Results : Results Users did not rely on security indicators
Depended on web content instead
Cannot distinguish poorly designed websites from malicious phishing attacks
Outline : Outline Introduction of security indicators
Anti-phishing user study
Web authentication using cell phones
Authentication protocol
User study
An improved protocol
Conclusions
Authentication Using Cell Phones : Authentication Using Cell Phones Prevent people’s passwords from being captured by public computers
Use trusted cell phone to authenticate login sessions from untrusted public computers
Checking security indicator is part of the authentication protocol
Authentication Protocol : Authentication Protocol
Authentication Protocol : Authentication Protocol Login attempt
Authentication Protocol : Authentication Protocol Login attempt “This login session is named ‘FAITH’.” “FAITH” “Do you approve login session
named ‘FAITH’?” “FAITH”
Authentication Protocol : Authentication Protocol Login attempt “This login session is named ‘FAITH’.” “FAITH” “Do you approve login session
named ‘FAITH’?” “FAITH”
Authentication Protocol : Authentication Protocol Login attempt “This login session is named ‘FAITH’.” “FAITH” “Do you approve login session
named ‘FAITH’?” “FAITH” “I approve ‘FAITH’.”
Authentication Protocol : Authentication Protocol Login attempt “This login session is named ‘FAITH’.” “FAITH” “Do you approve login session
named ‘FAITH’?” “FAITH” Log in “I approve ‘FAITH’.”
User Interface : User Interface
Attack Types : Attack Types Duplicated attack Blocking attack
User Study : User Study Log in to Amazon.com with a personal computer and a cell phone
6 logins in a row
Attacks were randomly selected and assigned to the 5th or the 6th login
20 users
Recruited at MIT, paid $10 for one hour
Average age 25 [18 - 43]
9 females and 11 males
16 MIT students, 4 not
Results : Results Duplicated attack: 36% (4 successful out of 11 attacks)
“There must be a bug in the proxy since the session name displayed in the computer does not match the one in the cell phone.”
Blocking attack: 22% (2 successful out of 9 attacks)
“The network connection must be really slow since the session name has not been displayed.”
Users failed to follow the protocol
Cannot distinguish system failures from malicious attacks
An Improved Protocol : An Improved Protocol Thanks to Steve Strassman
from Orange™
Under Attacks : Under Attacks Duplicated Attack Blocking attack
Results : Results Login by choosing a correct session name has zero spoof rate!
9 duplicated attacks and 11 blocking attacks
There was little chance that the attacker’s list included the user’s session name in the browser
Users were forced to attend to the security indicator
Conclusions : Conclusions Security indicator checking scheme fails
Users ignore advice (34% spoof rate)
Users do not follow instructions (30% spoof rate)
Users cannot distinguish “bugs” from “attacks”
Security indicator is not part of the user’s “critical action sequence”
Lesson Learned : Lesson Learned Moving the security indicator into the critical action sequence can better protect users
Users Cared About Security : Users Cared About Security 18 out of 30 uncheck “remember me”
13 out of 30 logged out (or tried to) after at least one task
Slide45 : Legitimate Site Phishing Site
Catch the
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