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Towards A User-Centric Identity-Usage Monitoring S ystem - ICIMP 2008 -. Daisuke Mashima and Mustaque Ahamad College of Computing Georgia Institute of Technology Georgia, USA Partly Supported by I3P. Outline. Background and motivation
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Towards A User-CentricIdentity-Usage Monitoring System- ICIMP 2008 - Daisuke Mashima and Mustaque Ahamad College of Computing Georgia Institute of Technology Georgia, USA Partly Supported by I3P
Outline • Background and motivation • Limitations of existing approaches • Design goals for user-centric monitoring • Proof of concept in OpenID setting • Conclusion
Background and Motivation • Increasing threat of online identity theft and misuse • Ranked in the first place for the 7th year in a row in FTC report • Prevention is not perfect • Insufficient attention to Site Authentication Image or SSL icon • Physical theft of a device and removable storage • Malwares • Social engineering • And more… • Monitoring and detection mechanisms are also required.
Existing Schemes: Fraud Detection Systems • Aim to detect fraudulent activities • Misuse of stolen credit card information • Cellular cloning, theft of calling card or cellular phone
Limitations of Existing Schemes • Limited or no user control • Users do not have option to enable or disable monitoring • Privacy concern • Users have no choice about what kind of information is captured and stored on SP • Lack of generality • System is designed in service-specific way • A dedicated system is required for each site
Design Goals • Users must be able to trust the monitoring system • Users should be able to choose an entity that they can trust • Preferably resides on a networked trusted party • Identity usage must be reliably captured and made available to monitoring system • Users should have flexible control over the monitoring system • Legitimate users should be able to turn on/off the monitoring system • Users should have choice about what information is captured and used for monitoring purpose
Design Goals Contd. • Monitoring system must offer generality without lowering effectiveness • By using context information, the monitoring system can handle identity credentials used for accessing general services • Engaging users closely in the anomaly detection process is important. • Make users attentive • Push alert or periodic reports • Provide interface to obtain feedback from user
Context Information for Monitoring • Who? • What platform a user commonly uses to access online services • OS fingerprinting (nmap, p0f, etc.) • User-Agent in web setting • To whom? • Identifier of a service provider that a user is talking to • Where? • IP Geolocation (MaxMind, Delay-based schemes, etc.) • Whois record • When? • Timestamp of usage • Day of week, week of month, hour of day etc.
Context-based Anomaly Detection • Time • Significant change in frequency of access • Anomalous access pattern • Location • Deviation of geographic location in normal usage pattern • Light-speed contradiction • Device Fingerprint • Unseen device type in the past
Basic OpenID Architecture • Authentication credential for OpenID provider could be stolen by phishing • An adversary could imitate service provider site to retrieve identity credential from legitimate OpenID provider
Evaluation: Generality • Can support any kind of services that rely on OpenID • No change is required at user side • Can be modified and applied to other types of systems
Evaluation: Performance • Increase of response time is acceptable even when multi-user setting.
Evaluation: Security • Context-based monitoring makes identity misuse more difficult • Risk of phishing attack can be mitigated • Periodic reports help shorten the window of vulnerability • Authentication to control monitoring system must be isolated from OpenID authentication
Evaluation: Usability • Pushing usage summary periodically reduces users’ burden • Context information makes reports or alerts easy to understand
Conclusion • Proposed requirements for user-centric monitoring and identified design goals • Showed a proof of concept in OpenID setting and evaluated it • Future work • Implementation in other types of architecture • Other identity management systems • GUIDE-ME • Email-based system • Explore more sophisticated mechanism for context-based anomalous usage detection