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SRS Common Architecture. Bob Balzer Neil Goldman Dave Wile Teknowledge Corp. Prevention. Proactive Prevention. Reactive Prevention. Self-Regeneration. Sensor. Recovery. Health Monitoring. Repair. Diagnosis. Inner Regenerative Layer: Repair (and prevent) unblocked attacks.
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SRS Common Architecture Bob Balzer Neil Goldman Dave Wile Teknowledge Corp.
Prevention Proactive Prevention Reactive Prevention Self-Regeneration Sensor Recovery Health Monitoring Repair Diagnosis • Inner Regenerative Layer: Repair (and prevent) unblocked attacks • Defense In Depth • Outer Prevention Layer: Block most attacks SRS Integration Architecture Component Diagnosis, Attack Recognition, Malicious Intent Determiner Architecture Diffferencer, Harm Detector Corruption Extent Determiner, Reconstitution Planner Software Dynamic Translation, Generated Network Filter, Dynamic Method Dispatch Memory Layout Diversity, Network Filter, Scalable Redundant Storage, Robust Scalable Comm.
Technical Goals • Include as many SRS program elements as possible • Minimal intrusion into existing tools, primarily • by announcing system status incrementally • And dynamically responding to other tools’ results • Integrate capabilities for seamless interoperation • Stimulate the production of new capabilities to further integration goals
Project Abbreviations • AWDRAT: MIT: Shrobe and Teknowledge:Balzer • Cortex: Honeywell: Musliner • Daikon: MIT: Ernst and Rinard • Dawson: Global Infotek: Just • JHU: Johns Hopkins U.: Amir and Purdue U.: Nita-Rotaru • MBE (model-based executive): MIT: Williams and Sullivan • PMOP: Teknowledge: Balzer and MIT: Shrobe • SensorNet: Telcordia: Van Den Berg and Rutgers: Rajagopalan • Strata (Genesis): UVA: Knight, Davidson, Evans, Nguyen-Tuong and CMU: Wang
SRS Component AWDRAT Cortex MBE JHU Choose response Strata Dawson PMOP SensorNet Daikon Effect response Shared System Architecture Announce and analyze system status
Technical Approach • Parallel monitoring and analysis by SRS components of a single target system • Components communicate via a global blackboard • Blackboard organized by a shared ontology for describing system and heartbeat states • Subscriptions provide access to others’ sensors, analysis, and response choice
Pervasive Self-Regeneration PMOP SensorNet Cortex AWDRAT Dawson Genesys Learning&Repair SRS Organizational Architecture
Setup Install Learning Harness (Cortex, Daikon, MBE, PMOP) Determine Method / Class Equivalents (PMOP, Strata) Install Wrappers and Obfuscate DLLs (AWDRAT, Dawson, PMOP) Detect Data Error (Daikon) Attack Indicator (Dawson) Program Error (AWDRAT, Cortex, Dawson, JHU, MBE, Strata) Heartbeat (Cortex) Operator Induced Error (PMOP, SensorNet) Analyze Collateral Damage Assessment (AWDRAT, Daikon, JHU, MBE) Trust and Risk (AWDRAT, Cortex, MBE, PMOP, SensorNet) Assess Learning Data (Cortex, Daikon, MBE, PMOP) Propose Repair Program Error: Execute a component in the virtual machine (Strata) Select from method alternatives & regenerate from scratch (AWDRAT, Dawson, MBE) Select from method alternatives & backtrack (JHU) Operator Induced Error: Automated surrogate or backup operator Omit the affected component Data Error: Data Repair (Daikon) Restore Data / DB (Cortex) Overview of Potential Scenarios
Make Repair Data Error: Data Repair (Daikon) Restore Compromised DB (Cortex) Program Error: Execute a component in the virtual machine (Strata) Select from method alternatives & regenerate from scratch (AWDRAT, Dawson, MBE) Select from method alternatives & backtrack (JHU) Operator Induced Error: Prevent bad effects (PMOP, SensorNet) Ignore or encapsulate the error (New Work) Choose Repair (New Work to choose among additional proposed repairs) Scenarios Continued
Blackboard Organization Blackboard layers correspond to scenario layers • S (setup) • D (detect) • A (analyze) • PR (propose repair) • CR (choose repair) • MR (make repair
Messages Passed • Setup and Status SRS Agents • S:Environment attribute or input A has value V • S:Program mode for Sys is M • S:System components for Sys are { ci } • S:Variants for CID are { ci } • S:Variant generator for CID is SRSAgent [ mode, CID] • S:Checkpoint Sys in D • S:GUI checkpoint E in D • Detection SRS Agents • D:Program Sys had fault F at L in ci [where L is contained in Sys](Fault is supertype of DataError, OperatorInducedError, ProgramError) • D:Missed heartbeat Sys at time T fault F • D:Attack of Sys indicator I for CID at L in ci • Analysis SRS Agents • A:Program Sys has vulnerability V at L { to risk R } • A:Program Sys has collateral damage V at L • A:Component ci would incur risk R with certainty P • A:End of Positive {or Negative} learning example trial for Sys
Messages Passed • Propose Repair, Choose Repair & Make Repair SRS Agents – Same messages used in each layer for different purposes: • Detectors and analyzers populate PR layer with these assertions (see following Messages). • Choose Repair agent asserts these same facts into CR, triggering repair. • Effectors assert these facts into MR to indicate repair completion. • Messages • [layer] :Replay component ci from checkpoint D in history H • [layer] :Substitute ci in Sys at L [used for Data repair, database substitution, and program regeneration] • [layer] :Remove component ci in Sys at L • [layer] :Revert Sys to checkpoint D in history H
Ontology for Blackboard • All blackboard objects part of ontologically described database • Historical and Metadata – facts as objects • May need special assertions • And special queries
Blackboard Design Issues • System representation • Identity • Versions (especially with learning) • Historical data • Specific types • Programs • GUI actions • States • Environment • Control Modes • Conflict resolution • Control resolution • Metadata • Layered blackboard • Agent relationships • Activities and Results to be communicated among SRS agents
Traditional Conflict Resolution Solutions • “First” rule by some criterion • Highest “priority” rule • Most “specific” rule • Rule that refers to the element most “recently” added • New rule • Arbitrary • All rules in parallel • Compartmentalized knowledge
Race Conditions • Blackboards lose their elegance when agents cannot freely access them, e.g. when agents don’t know whether to wait for more information to arrive. • E.g. Good: agents A and B both analyze message M and report their results independently • E.g. Bad: agents A, B, and C all analyze message M but B and C need A to have “passed” message M before they can work • Bad solution: B waits for A to “bless” M or “fail M” before proceeding • Good solution: when A can respond to M in a blackboard layer not examined by B and C, subsequently asserting M into a blackboard layer that both B and C look at. • If they’re all in the same layer, a possible solution is lattice-based access within a layer: • Register B and C as higher in the layer’s lattice relating all agents’ access • When a message M arrives that A is interested in, it is sent to A first. • If A reasserts M, both B and C can act on it. Otherwise, it has been “consumed” and must be removed from the blackboard. • Multiple, simultaneous messages: prefer complex message groups to simpler ones. • Use to introduce fault analyzers and repairchoice between layers. B C A