TRUST:Team for Research in Ubiquitous Secure Technologies

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Presentation transcript:

TRUST:Team for Research in Ubiquitous Secure Technologies Systems Science Challenge Area Douglas C. Schmidt Area Coordinator NSF STC Review September 13th 2004

Systems R&D Accomplishments TRUST Systems R&D Accomplishments Productivity & quality gains from higher-level abstraction mechanisms & tools Partially automated solutions for limited domains Analysis Simulation Generation 2 NSF STC Review September 13th 2004

New Systems Research Challenges TRUST New Systems Research Challenges Complex Interdependency Modeling & Analysis Model- based Integration of Secure Systems Secure Networked Embedded Systems 3 Software Tools for Design & Information Management NSF STC Review September 13th 2004

Complex Interdependency Modeling & Analysis Challenges & Goals TRUST Complex Interdependency Modeling & Analysis Challenges & Goals Characterize critical dependencies between interconnected networks e.g., what information should be transferred between the networks? Devising control architecture of networks to ease the computational burden in each network e.g., time scale of convergence of state estimation algorithms critically influences the severity of impact of failures Interdependent Critical Infrastructure 4 Finding the right trade offs e.g., privacy, dependability, security, performance, predictability NSF STC Review September 13th 2004

TRUST Complex Interdependency Modeling & Analysis Solution Approaches: Robustness from Scale Although the emerging generation of networks is locally fragile (node failures, channel impairments), the large-scale allows for global robustness 5 Sensor Networks Ad Hoc Wireless Networks NSF STC Review September 13th 2004

Model-based Integration of Secure Systems Challenges & Goals TRUST Model-based Integration of Secure Systems Challenges & Goals Domain-Specific Modeling Languages Multiple-aspect modeling languages for systems/security co- design Understanding and modeling inter- dependence between security aspects and core systems aspects Analysis tools for co- verifying security, performance and safety properties Matlab Code-Gen. Matlab Code-Gen. Config. Generator Model-Driven Generator Technology Modeling of generators Generating generators Provably correct generators Embeddable generators if (inactiveInterval != -1) { if (thisInterval > inactiveInterval) { (int)(System.currentTimeMillis() - lastAccessed) / 1000; int thisInterval = invalidate(); } ssm.removeSession(this); ServerSessionManager ssm = ServerSessionManager.getManager(); private long lastAccessedTime = creationTime; * session, as the number of milliseconds since midnight, January 1, 1970 /** * Return the last time the client sent a request associated with this */ public long getLastAccessedTime() { * a value associated with the session, do not affect the access time. * GMT. Actions that your application takes, such as getting or setting return (this.lastAccessedTime); this.lastAccessedTime = time; * should be called by the context when a request comes in for a particular * Update the accessed time information for this session. This method this.lastAccessedTime = this.thisAccessedTime; this.thisAccessedTime = System.currentTimeMillis(); public void access() { * session, even if the application does not reference it. lastAccessedTime = ((Long) stream.readObject()).longValue(); lastAccessedTime = 0L; this.isNew=false; isNew = ((Boolean) stream.readObject()).booleanValue(); maxInactiveInterval = ((Integer) stream.readObject()).intValue(); 6 Configuration Specification Code Analysis Tool NSF STC Review September 13th 2004

Model-based Integration of Secure Systems Solution Approaches TRUST Model-based Integration of Secure Systems Solution Approaches Access Control Meta-Model Composition Meta-Models GME Meta-Modeling Multiple-aspect modeling languages are defined by formal meta-models Security models are built independently from platforms and expressed as design patterns Model Weaving technology is used to generate integrated security/systems models Model-based generators are used to generate systems on Secure Platforms. built by generated from Security Models Composition Models GME S-ESML Modeling built by generated from Integrated Model Model Weaver weaved by generated from 7 Secure Platform NSF STC Review September 13th 2004

Secure Networked Embedded Systems Challenges & Goals TRUST Secure Networked Embedded Systems Challenges & Goals Automated design, verification, & validation: Support simultaneous design & propagation of constraints among different domain-specific design teams Verified design, in a mathematical or formal sense Validated design, in an engineering sense Certifiable design, to allow regulatory agencies to certify the production software Applications Applications Applications Sensors Controllers Actuators 8 Operating System Operating System Operating System Endsystem Networks Endsystem Networks Endsystem NSF STC Review September 13th 2004

Secure Networked Embedded Systems Challenges & Goals TRUST Secure Networked Embedded Systems Challenges & Goals Secure, composable, & adaptive software: Build modular middleware services that support secure embedded systems Support for a variety of performance tradeoffs In-network processing Autonomous adaptation to system conditions Assurance of a high level of security Differentiate between malicious intrusion & system failures Applications Applications Applications Sensors Controllers Actuators 9 Operating System Operating System Operating System Endsystem Networks Endsystem Networks Endsystem NSF STC Review September 13th 2004

TRUST Secure Networked Embedded Systems Solution Approaches: Integrated Research Tools Software technology Middleware & generative techniques to automatically manufacture highly optimized software using high-level design models & domain-specific configuration knowledge Hardware architectures for embedded sensor networks Berkeley motes as sensor network devices & asynchronous hardware architectures: Cornell Sensor Network Asynchronous Processor (SNAP) System support Integrated system architecture for sensor networks building from extensive work on TinyOS & MagnetOS to support secure, reliable, self-configuring sensor networks Applications Applications Applications Sensors Controllers Actuators Integrated Middleware, Operating Systems, Protocols, & Hardware Integrated Middleware, Operating Systems, Protocols, & Hardware Integrated Middleware, Operating Systems, Protocols, & Hardware 10 Endsystem Networks Endsystem Networks Endsystem NSF STC Review September 13th 2004

Software Tools for Design & Information Management Challenges & Goals TRUST Software Tools for Design & Information Management Challenges & Goals Software developers depend on complex platforms, & increasingly work by extending or customizing with extra code Web Services, J2EE, CORBA, .NET The quality of these platforms and “tools” is a direct determinant of the quality of their applications and solutions We need technologies to overcome limitations with existing platforms: Scale poorly & can “melt down” under stress Are insecure - easy to disrupt or intrude Are human intensive to deploy, configure Are hard to repair when disruption occurs Are costly to own & operate 11 NSF STC Review September 13th 2004

Software Tools for Design & Information Management Solution Approaches TRUST Software Tools for Design & Information Management Solution Approaches Astrolabe captures system state hierarchically, using P2P protocol that “assembles a puzzle” without any servers Develop new technologies based on peer-to-peer interaction styles that substitute probabilistic objectives for classic deterministic ones Apply these technologies to overcome limitations with prevailing reliable client/server model, which imposes O(N) delays & O(N2) performance degradation Name Avg Load WL contact SMTP contact SF 2.6 123.45.61.3 123.45.61.17 ITH 1.8 127.16.77.6 127.16.77.11 Paris 3.1 14.66.71.8 14.66.71.12 SQL query “summarizes” data Name Load Weblogic? SMTP? Word Version gazelle 1.7 4.5 zebra 3.2 1 6.2 gnu .5 Ithaca 12 Name Load Weblogic? SMTP? Word Version swift 2.0 1 6.2 falcon 1.5 4.1 cardinal 4.5 6.0 San Francisco NSF STC Review September 13th 2004