This project seeks to create trustworthy peer-to-peer overlay systems through fundamental advances to the state-of-the-art in the design of Internet-scale, overlay networks for performance-demanding applications in the presence of adversaries. Design limitations in popular peer-to-peer systems today may be exploited to cause large-scale denial of service attacks on nodes not even part of the overlay system. Further, adversaries may control the overlay construction to create a crippling impact on application performance. To tackle this, the project will (i) Design robust and attacker resilient adaptation protocols contributing to an emerging science of trustworthy adaptability that defines a new shift in building distributed systems; (ii) Obtain fundamental insights into the interplay between the design of group management algorithms and their vulnerability to being exploited to launch distributed denial of service attacks on the Internet; (iii) Explore the interactions between peer-to-peer design, resulting traffic characteristics, and implications for distinguishing normal peer-to-peer traffic patterns from anomalous ones; and (iv) Design mechanisms for reliable, scalable and adversary-resilient key dissemination to help ensure confidentiality and integrity of application-specific data.

The project will demonstrate and validate the novel proposed mechanisms in the context of mature and widely deployed peer-to-peer systems. Peer-to-peer video broadcasting will be used to promote online education in the Lafayette area, and to broadcast a security-related seminar series. The project will benefit the design of large-scale testbeds such as GENI. The PIs will communicate with developers of popular peer-to-peer systems to alert them to critical design vulnerabilities in their systems.

Despite the rapid growth of distributed shared infrastructures such as PlanetLab and the Grid, a gap exists between the current practice and their full potential. Especially, many users wish to obtain their “own space” with full privilege in a shared infrastructure to run arbitrary distributed applications. This research introduces the concept of “virtual distributed environments” (VDEs) as a new sharing paradigm for distributed infrastructures. Based on virtualization technologies, VDEs are autonomic, mutually isolated entities, providing individual users with privileged, customized, and confined distributed environments. To realize this vision, the following new research challenges are being addressed: (1) distributed environment virtualization and logistics, (2) shepherded self-adaptation of virtual distributed environments, and (3) trusted monitoring and logging of virtual distributed environments. Solutions to these challenges are evaluated in a number of real-world application scenarios, including computer system emulation for education, e-Science service for the nanotechnology research community, and virtual playgrounds for Internet worm observation, investigation, and defense. In particular, the research and education activities of this work are closely related. Leveraging the research results, an education platform is being developed for distributed and network systems emulation. It provides students with hands-on system experience that would otherwise require expensive, dedicated equipment. This research will open the door to new opportunities for application/service deployment and distributed system experimentation. The realization of VDE will encourage public use of the emerging cyberinfrastructure by accommodating a wide range of science and engineering activities including education and research portals, virtual collaboratories, and cyber-defense testing grounds.

Analysts need mechanisms to disambiguate regulations so they may be clearly specified as software requirements. Additionally, those responsible for certifying compliance within relevant systems need controls and assurances that measure conformance with policies and regulations. Our goal is to develop methods, tools, and procedures to help software designers and policy makers achieve transparency and consistency by bringing regulations, policies and system requirements into better alignment.

Results: There are three main expected results of this work. First, we will produce tools to assist software designers in determining a clear set of actionable requirements for system design and access control from regulations and legislation. Second, we will produce methods to develop audit mechanisms and procedures that may be used to verify that a functioning system meets its requirements. This will aid organizations as they conduct policy and legal compliance. Third, we will develop a realistic corpus of synthetic electronic patient record data that can be used to test any such experimental system. We will make this available so that other researchers can use it.

In December of 2004 a US Marine is severely wounded during combat operations in Iraq. After receiving world class treatment at Bethesda Naval Hospital and the Indianapolis VA medical center, the patient is able to carry on a normal civilian life in Indianapolis. Several months later the veteran gets in an accident and is transported via medi-vac to a non-VA facility trauma center in Indianapolis for care. The provider looks up the patient’s data using the Indiana Health Information Exchange and the patient has a highly positive outcome. This outcome is only because critically important medical data was made available to the provider at the right time via a collaborative database between local hospitals. This scenario is only possible if VA hospitals can securely manage sharing of data between non VA health care facilities and themselves. The security schema the VA needs to meet this is a highly secure, manageable, portable, scalable, granular to the record & field level and most importantly cost effective security architecture.

It is with great enthusiasm we present the VISTALOCK security schema to the Department of Veterans Affairs. The scientists who have invented this technology are offering the Department of Veterans Affairs the opportunity to collaborate with them by implementing the already developed and proven technology across the VA Health Care domain. The VISTALOCK security architecture, using TEGO technology, is designed to be flexible and adaptable to support the security needs of VA and ALL of its national, regional and local affiliates.

VISTALOCK addresses four major security functions needed in collaborative data exchange and sharing, that is, Hierarchical Access Control (HAC), Secure Group Communication (SGC); Differential Access Control (DAC); Secure Dynamic Conferencing (SDC), enforces confidentiality, integrity, authentication, and fine tuned authorized access of patient records with granularity to the field and record level based on Cryptography and Key Management, and provides the capabilities of scalability, efficiency, dynamics, flexibility, and transparence.

The VISTALOCK security system is a bolt on security architecture that works in addition to the existing system(s) for which it protects, it will require no changes to the VISTA database repository and will act as a security gateway for all VISTA data traffic between the client and host. The VA will be able to apply best of breed technology to its security architecture, by providing modular and portable security services to the Vista/HealtheVET system. This enables the VA to continue full speed ahead with HealtheVET development as planned while still enabling secured collaborative data sharing capabilities to its architecture with external local health care facilities and practices.

This project is investigating linguistic extensions to map/reduce abstractions for programming large-scale distributed systems, with special focus on applications that manipulate large, unstructured graphs. It targets real-world graph analysis tasks found in comparative analysis of biological networks as an important case study.

The project is investigating the following specific questions: (i) how can highly unstructured graph-based formalisms be cast in the map/reduce framework? (ii) how effectively can these specifications leverage existing map/reduce infrastructure? (iii) how can these abstractions and their execution environments be enhanced to provide the semantic expressiveness necessary for programmability and scalable performance? (iv) how can these analysis tasks be integrated into comprehensive scientific resources usable by the wider applications community? Answers to these questions entails exploring linguistic extensions to existing map/reduce abstractions, defining new implementations on wide-area multicore/SMP platforms, and crafting an expressive graph analysis toolkit suitable for realistic deployment in important domains such as systems biology.

Results that arise from this project advance the state-of-the-art in analysis of large sparse unstructured graphs and directly impact a very broad class of scientific applications. Beyond specific target applications in biology, graph-based formalisms find direct applications in social sciences (social networks), recommender systems, and commerce (networks of transactions).