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Home » Publication » Cyber & formal methods publications

Cyber & formal methods publications

Cyber & formal methods publications November 1, 2020

Deductive Synthesis of the Unification Algorithm: The Automation of Introspection

Richard J. Waldinger

We are working to create the first automatic deductive synthesis of a unification algorithm. The program is extracted from a proof of the existence of an output substitution that satisfies a given logical specification.

Cyber & formal methods publications April 1, 2017 Tech Report

Semantic Instrumentation of Virtual Environments for Training

Grit Denker, Karen Myers

Interactive virtual environments are useful tools for hands-on learning or rehearsing of procedural tasks. However, task training applications typically provide a constrained course of action for the learner, forcing them down a single specific solution path. We discuss an approach in which the virtual environment is semantically instrumented in order to allow for the tracking of and reasoning about open-ended learner activity therein. Our approach leverages ontology-based knowledge representation which allows for a structured and meaningful description of virtual objects and of the learner actions that may be performed upon them. This is facilitated by the association of specific ontological classes with geometric components of the objects which populate a training exercise. These classes, together with their attributes, relationships and rules, characterize the environment and user actions in a readily understandable manner. As a result, a training system is able to observe the learner activity, render an assessment of that activity, and provide meaningful feedback to the learner. We also present an authoring tool which allows content developers to semantically annotate three-dimensional models for such an environment.

Cyber & formal methods publications January 1, 2016 Conference Paper

Diagnosis cloud: Sharing knowledge across cellular networks

SRI International

This paper presents a novel diagnosis cloud framework that enables the extraction and transfer of knowledge from one network to another. It also presents use cases and requirements. We present the implementation details of the diagnosis cloud framework for two specific types of models: topic models and Markov Logic Networks (MLNs).

Cyber & formal methods publications October 1, 2015

Keys Under Doormats

SRI International

In this report, a group of computer scientists and security experts, many of whom participated in a 1997 study of these same topics, has convened to explore the likely effects of imposing extraordinary access mandates.

Cyber & formal methods publications June 1, 2015

Machine Learning Models and Pathway Genome Data Base for Trypanosoma cruzi Drug Discovery

Carolyn Talcott

We have demonstrated how combining chemoinformatics and bioinformatics for T. cruzi drug discovery can bring interesting in vivo active molecules to light that may have been overlooked.

Cyber & formal methods publications May 1, 2015

Weakness in Depth: A Voting Machine’s Demise

SRI International

Virginia’s government recently examined the AVS WinVote and learned that the vulnerabilities are more serious than any other voting system, allowing complete exploitation over a Wi-Fi network.

Cyber & formal methods publications April 1, 2015 Conference Paper

Discrete Vs. Dense Times in the Analysis of Cyber-Physical Security Protocols

Carolyn Talcott

This paper investigates the foundational differences and the impacts on the analysis when using models with discrete time and models with dense time.

Speech & natural language publications November 1, 2014 Conference Paper

The SRI AVEC-2014 Evaluation System

Martin Graciarena, Dimitra Vergyri, Colleen Richey, Andreas Kathol

We explore a diverse set of features based only on spoken audio to understand which features correlate with self-reported depression scores according to the Beck depression rating scale. 

Cyber & formal methods publications April 1, 2014 Conference Paper

Safety Envelope for Security

Patrick Lincoln, John Rushby

We present an approach for detecting sensor spoofing attacks on a cyber-physical system. Our approach consists of two steps. In the first step, we construct a safety envelope of the system. Under nominal conditions (that is, when there are no attacks), the system always stays inside its safety envelope. In the second step, we build an attack detector: a monitor that executes synchronously with the system and raises an alarm whenever the system state falls outside the safety envelope. We synthesize safety envelopes using a modifed machine learning procedure applied on data collected from the system when it is not under attack. We present experimental results that show effectiveness of our approach, and also validate the several novel features that we introduced in our learning procedure.

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