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An Adaptive Intrusion-Tolerant Architecture. Alfonso Valdes, Tomas Uribe, Magnus Almgren, Steven Cheung, Yves Deswarte, Bruno Dutertre, Josh Levy, Hassen Saïdi. Acknowledgements
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An Adaptive Intrusion-Tolerant Architecture Alfonso Valdes, Tomas Uribe, Magnus Almgren, Steven Cheung, Yves Deswarte, Bruno Dutertre, Josh Levy, Hassen Saïdi Acknowledgements Research sponsored under DARPA Contract N66001-00-C-8058. Views presented are those of the authors and do not represent the views of DARPA or the Space and Naval Warfare Systems Center
Outline • Assumptions • Background • System Components • The Single Proxy • Mechanisms • Validation and Future Work
Dependable Intrusion Tolerance New Ideas Contain • Detect cyber system deviation resulting from attacks, • Contain the attacked resource, • Adapt system resources, and • Recover lost functionality over time Adapt Recover Hacked Schedule Impact • Assures integrity and availability of mission critical content provision services such as plan distribution • Critical service providers function even when under attack • Distributed content is accurate, despite hacker’s malicious changes • Automatic recovery lets operators focus on primary mission
Assumptions • Attacker does not have physical access • Flood/overrun attacks are not addressed • Not all replicates are vulnerable to the same attack • No attack can simultaneously compromise more than a critical fraction of the COTS Servers • Correct servers all give the same answer to a given request • Focus is on integrity and availability, but system is compatible with mechanisms for confidentiality
Background • Intrusion Tolerant Server
Background • Intrusion Tolerant Server • Redundancy & Diversity
Background • Intrusion Tolerant Server • Redundancy & Diversity • Hardened Proxy • StackGuard • Online Verification ensures operation conforms to spec • Small Code Base
Background • Intrusion Tolerant Server • Redundancy & Diversity • Hardened Proxy • StackGuard • Online Verifiers • Small Code Base • HIDS/NIDS/app-IDS • EMERALD/Snort
Proxy Limits access to app servers Sanitizes some suspicious requests IDS Detect attacks, anomalous traffic Trigger response mechanism Adaptive agreement policy Corroborates response to client Identifies malfunctioning servers Challenge-response Integrity and liveness Triggers response mechanism On-line verification Ensures correct proxy functionality Triggers response mechanism Periodic reboot Mechanism Summary
System Components • Application Servers • Solaris, Win2k, RedHat, FreeBSD • IDS • Proxy • RedHat-6.2 • Our own code base RedHat 6.2 Proxy eAggregator C-R eXpert-Net eBayes-TCP eBayes-Blue Snort MS Win2k IIS Solaris 8(Sparc5) Apache eXpert-BSM RedHat 7.1 iPlanet FreeBSD 4.2 Apache App-IDS
1,1 2,2 3,3 4,4 Agreement Policies • Benign - Each request dealt to one app server • Duplex (default regime at system start) - Each request sent to two app servers • Triplex - Each request sent to three app servers • Quad - Each request sent to four app servers • Transition to a more permissive regime after some time of normal activity Policy/Regime 4,3 Policy regime is specified as (N, K), N servers are polled, K must agree. (3,3) is the regime obtained if (4, 3) is in effect and one server is diagnosed faulty. While it is repaired, full agreement is required of the rest.
e-Aggregator RegimeManager AlertManager ChallengeResponse Proxy Server RepairManager Policy/Regime 1,1 2,2 3,3 4,4 4,3 Proxy in Detail
Response • Temporarily blocking the address from where attack seems to originate • Increasing agreement regime • Increasing frequency and coverage of challenge-response protocol • Disconnecting and rebooting a server • Refusing service and alerting the sys admin
Publications and Presentations • “Dependable Intrusion Tolerance”, Tenth Annual Conference on Security Protocols, Cambridge, UK, April 02 • “An Adaptive Intrusion Tolerant Server Architecture”Workshop on Intrusion Tolerant Systems, DSN02, June 02 • “Combining Monitors for Run-Time System Verification”, Workshop on Runtime Verification (RV'02) International Conference on Computer Aided Verification, Copenhagen, Denmark, July 02Electronic Notes in Theoretical Computer Science, vol. 70, number 4
Validation • Diversity • Direct detection on external network (IDS sensors) • Symptom detection on the private network (proxy) • Agreement • Challenge response protocols • Performance • Preliminary Results • Resistance to attacks • Compiling a list of existing Web exploits to run them against the implementation • Formal verification of appropriate components • Red teaming
Plans • Address dynamic content • Refine alert, detection, response mechanisms • Validation and experimentation • Transition