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Tim Finin

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14 papers
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14

AAAI Conference 2020 Conference Paper

CASIE: Extracting Cybersecurity Event Information from Text

  • Taneeya Satyapanich
  • Francis Ferraro
  • Tim Finin

We present CASIE, a system that extracts information about cybersecurity events from text and populates a semantic model, with the ultimate goal of integration into a knowledge graph of cybersecurity data. It was trained on a new corpus of 1, 000 English news articles from 2017–2019 that are labeled with rich, event-based annotations and that covers both cyberattack and vulnerability-related events. Our model defines five event subtypes along with their semantic roles and 20 event-relevant argument types (e. g. , file, device, software, money). CASIE uses different deep neural networks approaches with attention and can incorporate rich linguistic features and word embeddings. We have conducted experiments on each component in the event detection pipeline and the results show that each subsystem performs well.

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AAAI Conference 2006 Conference Paper

Detecting Spam Blogs: A Machine Learning Approach

  • Pranam Kolari
  • Tim Finin

Weblogs or blogs are an important new way to publish information, engage in discussions, and form communities on the Internet. The Blogosphere has unfortunately been infected by several varieties of spam-like content. Blog search engines, for example, are inundated by posts from splogs – false blogs with machine generated or hijacked content whose sole purpose is to host ads or raise the PageRank of target sites. We discuss how SVM models based on local and link-based features can be used to detect splogs. We present an evaluation of learned models and their utility to blog search engines; systems that employ techniques differing from those of conventional web search engines.

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JAAMAS Journal 2006 Journal Article

Modeling conversation policies using permissions and obligations

  • Lalana Kagal
  • Tim Finin

Abstract Both conversation specifications and policies are required to facilitate effective agent communication. Specifications provide the order in which speech acts can occur in a meaningful conversation, whereas policies restrict the specifications that can be used in a certain conversation based on the sender, receiver, messages exchanged thus far, content, and other context. We propose that positive/negative permissions and obligations be used to model conversation specifications and policies. We also propose the use of ontologies to categorize speech acts such that high level policies can be defined without going into specifics of the speech acts. This approach is independent of the syntax and semantics of the communication language and can be used for different agent communication languages. Our policy based framework can help in agent communication in three ways: (i) to filter inappropriate messages, (ii) to help an agent to decide which speech act to use next, and (iii) to prevent an agent from sending inappropriate messages. Our work differs from most existing research on communication policies because it is not tightly coupled to any domain information such as the mental states of agents or specific communicative acts. Contributions of this work include: (i) an extensible framework that is applicable to varied domain knowledge and different agent communication languages, and (ii) the declarative representation of conversation specifications and policies in terms of permitted and obligated speech acts.

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AAAI Conference 2006 System Paper

Using the Semantic Web to Integrate Ecoinformatics Resources

  • Cynthia Parr
  • Joel Sachs
  • Lushan Han
  • Tim Finin

We demonstrate an end-to-end use case of the semantic web’s utility for synthesizing ecological and environmental data. ELVIS (the Ecosystem Location Visualization and Information System) is a suite of tools for constructing food webs for a given location. ELVIS functionality is exposed as a collection of web services, and all input and output data is expressed in OWL, thereby enabling its integration with other semantic web resources. In particular, we describe using a Triple Shop application to answer SPARQL queries from a collection of semantic web documents.

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AAAI Conference 2005 System Paper

Swoogle: Searching for Knowledge on the Semantic Web

  • Tim Finin
  • Rong Pan
  • Pranam Kolari

The Semantic Web’s distributed nature raises significant data access problems — how can an agent discover, index, search and navigate knowledge on the Semantic Web? Swoogle was developed to facilitate webscale semantic web data access by providing these services to both human and software agents. It focuses on two levels of knowledge granularity: URI based semantic web vocabulary and semantic web documents (SWDs), i.e., RDF and OWL documents encoded in XML, NTriples or N3.

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KER Journal 2003 Journal Article

An ontology for context-aware pervasive computing environments

  • HARRY CHEN
  • Tim Finin
  • ANUPAM JOSHI

This document describes COBRA-ONT, an ontology for supporting pervasive context-aware systems. COBRA-ONT, expressed in the Web Ontology Language OWL, is a collection of ontologies for describing places, agents and events and their associated properties in an intelligent meeting-room domain. This ontology is developed as a part of the Context Broker Architecture (CoBrA), a broker-centric agent architecture that provides knowledge sharing, context reasoning and privacy protection supports for pervasive context-aware systems. We also describe an inference engine for reasoning with information expressed using the COBRA-ONT ontology and the ongoing research in using the DAML-Time ontology for context reasoning.

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KER Journal 2003 Journal Article

Using DAML+OIL to classify intrusive behaviours

  • JEFFREY UNDERCOFFER
  • ANUPAM JOSHI
  • Tim Finin
  • JOHN PINKSTON

We have produced an ontology specifying a model of computer attack. Our ontology is based upon an analysis of over 4000 classes of computer intrusions and their corresponding attack strategies and is categorised according to system component targeted, means of attack, consequence of attack and location of attacker. We argue that any taxonomic characteristics used to define a computer attack be limited in scope to those features that are observable and measurable at the target of the attack. We present our model as a target-centric ontology that is to be refined and expanded over time. We state the benefits of forgoing dependence upon taxonomies in favour of ontologies for the classification of computer attacks and intrusions. We have specified our ontology using the DARPA Agent Markup Language+Ontology Inference Layer and have prototyped it using DAMLJessKB. We present our model as a target-centric ontology and illustrate the benefits of utilising an ontology in lieu of a taxonomy, by presenting a use-case scenario of a distributed intrusion detection system.

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KER Journal 2002 Journal Article

Introduction to the special issue on ontologies in agent systems

  • Stephen Cranefield
  • STEVEN WILLMOTT
  • Tim Finin

It is now more than ten years since researchers in the US Knowledge Sharing Effort envisaged a future where complex systems could be built by combining knowledge and services from multiple knowledge bases and the first agent communication language, KQML, was proposed (Neches et al., 1991). This model of communication, based on speech acts, a declarative message content representation language and the use of explicit ontologies defining the domains of discourse (Genesereth & Ketchpel, 1994), has become widely recognised as having great benefits for the integration of disparate and distributed information sources to form an open, extensible and loosely coupled system. In particular, this idea has become a key tenet in the multi-agent systems research community.

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AAAI Conference 1990 Conference Paper

Integrating Natural Language Processing and Knowledge Based Processing

  • Rebecca Passonneau
  • Tim Finin

A central problem in text-understanding research is the indeterminacy of natural language. Two related issues that arise in confronting this problem are the need to make complex interactions possible among the system components that search for cues, and the need to control the amount of reasoning that is done once cues have been discovered. We identify a key d. ifEculty iu enabling true interaction among system components and we propose an architectural framework that minimizes this difficulty. A concrete example of a reasoning task encountered iu an actual text+mderstanding application is used to motivate the design principles of our framework.

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