Joshua Taylor

A Quantitative Framework for Moving Target Defense Effectiveness Evaluation

Static defense has proven to be a brittle mechanism for defending against cyber attack. Despite this, proactive defensive measures have not been widely deployed. This is because flexible proactive defensive measures such as Moving Target Defense (MTD) have as much potential to interfere with a networks ability to support the mission as they do to defend the network. In this paper we introduce an approach to defining and measuring MTD effects applied in a network environment to help guide MTD deployment decisions that successfully balance the potential security benefits of MTD deployment against the potential productivity costs.

A new Gödelian argument for hypercomputing minds based on the busy beaver problem

Abstract Do human persons hypercompute? Or, as the doctrine of computationalism holds, are they information processors at or below the Turing Limit? If the former, given the essence of hypercomputation, persons must in some real way be capable of infinitary information processing. Using as a springboard Godel’s little-known assertion that the human mind has a power “converging to infinity”, and as an anchoring problem Rado’s [T. Rado, On non-computable functions, Bell System Technical Journal 41 (1963) 877–884] Turing-uncomputable “busy beaver” (or Σ ) function, we present in this short paper a new argument that, in fact, human persons can hypercompute. The argument is intended to be formidable, not conclusive: it brings Godel’s intuition to a greater level of precision, and places it within a sensible case against computationalism.

Proof verification and proof discovery for relativity

The vision of machines autonomously carrying out substantive conjecture generation, theorem discovery, proof discovery, and proof verification in mathematics and the natural sciences has a long history that reaches back before the development of automatic systems designed for such processes. While there has been considerable progress in proof verification in the formal sciences, for instance the Mizar project’ and the four-color theorem, now machine verified, there has been scant such work carried out in the realm of the natural sciences—until recently. The delay in the case of the natural sciences can be attributed to both a lack of formal analysis of the so-called “theories” in such sciences, and the lack of sufficient progress in automated theorem proving. While the lack of analysis is probably due to an inclination toward informality and empiricism on the part of nearly all of the relevant scientists, the lack of progress is to be expected, given the computational hardness of automated theorem proving; after all, theoremhood in even first-order logic is Turing-undecidable. We give in the present short paper a compressed report on our building upon these formal theories using logic-based AI in order to achieve, in relativity, both machine proof discovery and proof verification, for theorems previously established by humans. Our report is intended to serve as a springboard to machine-produced results in the future that have not been obtained by humans.

Provability-based semantic interoperability via translation graphs

Provability-based semantic interoperability (PBSI) is a kind of interoperability that transcends mere syntactic translation to allow for robust, meaningful information exchange across systems employing ontologies for which mappings or matchings may not exist, and which can be evaluated by provability-based (PB) queries. We introduce a system of translation graphs to formalize the relationships between diverse ontologies and knowledge representation and reasoning systems, and to automatically generate the translation axioms governing PB information exchange and inter-system reasoning. We demonstrate the use of translation graphs on a small number of simple systems to achieve interoperability.

Automated Effectiveness Evaluation of Moving Target Defenses: Metrics for Missions and Attacks

In this paper, we describe the results of several experiments designed to test two dynamic network moving target defenses against a propagating data exfiltration attack. We designed a collection of metrics to assess the costs to mission activities and the benefits in the face of attacks and evaluated the impacts of the moving target defenses in both areas. Experiments leveraged Sieges Cyber-Quantification Framework to automatically provision the networks used in the experiment, install the two moving target defenses, collect data, and analyze the results. We identify areas in which the costs and benefits of the two moving target defenses differ, and note some of their unique performance characteristics.

Software analysis in the semantic web

Many approaches in software analysis, particularly dynamic malware analyis, benefit greatly from the use of linked data and other Semantic Web technology. In this paper, we describe AIS, Inc.’s Semantic Extractor (SemEx) component from the Malware Analysis and Attribution through Genetic Information (MAAGI) effort, funded under DARPA’s Cyber Genome program. The SemEx generates OWL-based semantic models of high and low level behaviors in malware samples from system call traces generated by AIS’s introspective hypervisor, IntroVirtTM. Within MAAGI, these semantic models were used by modules that cluster malware samples by functionality, and construct “genealogical” malware lineages. Herein, we describe the design, implementation, and use of the SemEx, as well as the C2DB, an OWL ontology used for representing software behavior and cyber-environments.

A framework for network-wide semantic event correlation

An increasing need for situational awareness within network-deployed Systems Under Test has increased desire for frameworks that facilitate system-wide data correlation and analysis. Massive event streams are generated from heterogeneous sensors which require tedious manual analysis. We present a framework for sensor data integration and event correlation based on Linked Data principles, Semantic Web reasoning technology, complex event processing, and blackboard architectures. Sensor data are encoded as RDF models, then processed by complex event processing agents (which incorporate domain specific reasoners, as well as general purpose Semantic Web reasoning techniques). Agents can publish inferences on shared blackboards and generate new semantic events that are fed back into the system. We present AIS, Inc.’s Cyber Battlefield Training and Effectiveness Environment to demonstrate use of the framework.

Creativity and conducting: handle in the CAIRA project

After providing some context via (i) earlier work on literary creativity carried out by Bringsjord et al., and (ii) an account of creativity espoused by Cope, which stands in rather direct opposition to Bringsjords account, we summarize our nascent attempt to engineer an artificial conductor: Handle. Handle is a microcosmic version of part of a larger, much more ambitious system: CAIRA. Both are under development courtesy of a three-year CreativeIT grant from the National Science Foundation (PI Braasch, Co-PIs Oliveros & Bringsjord).

Reports of the AAAI 2008 Fall Symposia

The Association for the Advancement of Artificial Intelligence was pleased to present the 2008 Fall Symposium Series, held Friday through Sunday, November 7-9, at the Westin Arlington Gateway in Arlington, Virginia. The titles of the seven symposia were (1) Adaptive Agents in Cultural Contexts, (2) AI in Eldercare: New Solutions to Old Problems, (3) Automated Scientific Discovery, (4) Biologically Inspired Cognitive Architectures, (5) Education Informatics: Steps toward the International Internet Classroom, (6) Multimedia Information Extraction, and (7) Naturally Inspired AI.