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PhD Proposal: Ankur Padia, Dealing with Dubious Facts in Knowledge Graphs

November 29th, 2016, by Tim Finin, posted in KR, Machine Learning, NLP, NLP, Semantic Web

the skeptic

Dissertation Proposal

Dealing with Dubious Facts
in Knowledge Graphs

Ankur Padia

1:00-3:00pm Wednesday, 30 November 2016, ITE 325b, UMBC

Knowledge graphs are structured representations of facts where nodes are real-world entities or events and edges are the associations among the pair of entities. Knowledge graphs can be constructed using automatic or manual techniques. Manual techniques construct high quality knowledge graphs but are expensive, time consuming and not scalable. Hence, automatic information extraction techniques are used to create scalable knowledge graphs but the extracted information can be of poor quality due to the presence of dubious facts.

An extracted fact is dubious if it is incorrect, inexact or correct but lacks evidence. A fact might be dubious because of the errors made by NLP extraction techniques, improper design consideration of the internal components of the system, choice of learning techniques (semi-supervised or unsupervised), relatively poor quality of heuristics or the syntactic complexity of underlying text. A preliminary analysis of several knowledge extraction systems (CMU’s NELL and JHU’s KELVIN) and observations from the literature suggest that dubious facts can be identified, diagnosed and managed. In this dissertation, I will explore approaches to identify and repair such dubious facts from a knowledge graph using several complementary approaches, including linguistic analysis, common sense reasoning, and entity linking.

Committee: Drs. Tim Finin (Chair), Anupam Joshi, Tim Oates, Paul McNamee (JHU), Partha Talukdar (IISc, India)

Managing Cloud Storage Obliviously

May 24th, 2016, by Tim Finin, posted in cloud computing, cybersecurity, Privacy, Security, Semantic Web

Vaishali Narkhede, Karuna Pande Joshi, Tim Finin, Seung Geol Choi, Adam Aviv and Daniel S. Roche, Managing Cloud Storage Obliviously, International Conference on Cloud Computing, IEEE Computer Society, June 2016.

Consumers want to ensure that their enterprise data is stored securely and obliviously on the cloud, such that the data objects or their access patterns are not revealed to anyone, including the cloud provider, in the public cloud environment. We have created a detailed ontology describing the oblivious cloud storage models and role based access controls that should be in place to manage this risk. We have developed an algorithm to store cloud data using oblivious data structure defined in this paper. We have also implemented the ObliviCloudManager application that allows users to manage their cloud data by validating it before storing it in an oblivious data structure. Our application uses role-based access control model and collection based document management to store and retrieve data efficiently. Cloud consumers can use our system to define policies for storing data obliviously and manage storage on untrusted cloud platforms even if they are unfamiliar with the underlying technology and concepts of oblivious data structures.

Streamlining Management of Multiple Cloud Services

May 22nd, 2016, by Tim Finin, posted in cloud computing, KR, Ontologies, Semantic Web

cloudhandshake

Aditi Gupta, Sudip Mittal, Karuna Pande Joshi, Claudia Pearce and Anupam Joshi, Streamlining Management of Multiple Cloud Services, IEEE International Conference on Cloud Computing, June 2016.

With the increase in the number of cloud services and service providers, manual analysis of Service Level Agreements (SLA), comparison between different service offerings and conformance regulation has become a difficult task for customers. Cloud SLAs are policy documents describing the legal agreement between cloud providers and customers. SLA specifies the commitment of availability, performance of services, penalties associated with violations and procedure for customers to receive compensations in case of service disruptions. The aim of our research is to develop technology solutions for automated cloud service management using Semantic Web and Text Mining techniques. In this paper we discuss in detail the challenges in automating cloud services management and present our preliminary work in extraction of knowledge from SLAs of different cloud services. We extracted two types of information from the SLA documents which can be useful for end users. First, the relationship between the service commitment and financial credit. We represented this information by enhancing the existing Cloud service ontology proposed by us in our previous research. Second, we extracted rules in the form of obligations and permissions from SLAs using modal and deontic logic formalizations. For our analysis, we considered six publicly available SLA documents from different cloud computing service providers.

chmod 000 Freebase

May 2nd, 2016, by Tim Finin, posted in KR, Ontologies, Semantic Web

rip freebase

He’s dead, Jim.

Google recently shut down the query interface to Freebase. All that is left of this innovative service is the ability to download a few final data dumps.

Freebase was launched nine years ago by Metaweb as an online source of structured data collected from Wikipedia and many other sources, including individual, user-submitted uploads and edits. Metaweb was acquired by Google in July  2010 and Freebase subsequently grew to have more than 2.4 billion facts about 44 million subjects. In December 2014, Google announced that it was closing Freebase and four months later it became read-only. Sometime this week the query interface was shut down.

I’ve enjoyed using Freebase in various projects in the past two years and found that it complemented DBpedia in many ways. Although its native semantics differed from that of RDF and OWL, it was close enough to allow all of Freebase to be exported as RDF.  Its schema was larger than DBpedia’s and the data tended to be a bit cleaner.

Google generously  decided to donate the data to the Wikidata project, which began migrating Freebase’s data to Wikidata in 2015.  The Freebase data also lives on as part of Google’s Knowledge Graph.  Google recently allowed very limited querying of its knowledge graph and my limited experimenting with it suggests that has Freebase data at its core.

Representing and Reasoning with Temporal Properties/Relations in OWL/RDF

May 1st, 2016, by Tim Finin, posted in KR, NLP, Ontologies, Semantic Web

Representing and Reasoning with Temporal
Properties/Relations in OWL/RDF

Clare Grasso

10:30-11:30 Monday, 2 May 2016, ITE346

OWL ontologies offer the means for modeling real-world domains by representing their high-level concepts, properties and interrelationships. These concepts and their properties are connected by means of binary relations. However, this assumes that the model of the domain is either a set of static objects and relationships that do not change over time, or a snapshot of these objects at a particular point in time. In general, relationships between objects that change over time (dynamic properties) are not binary relations, since they involve a temporal interval in addition to the object and the subject. Representing and querying information evolving in time requires careful consideration of how to use OWL constructs to model dynamic relationships and how the semantics and reasoning capabilities within that architecture are affected.

Context-Sensitive Policy Based Security in Internet of Things

April 18th, 2016, by Tim Finin, posted in IoT, Policy, Semantic Web

Prajit Kumar Das, Sandeep Nair, Nitin Kumar Sharma, Anupam Joshi, Karuna Pande Joshi, and Tim Finin, Context-Sensitive Policy Based Security in Internet of Things, 1st IEEE Workshop on Smart Service Systems, co-located with IEEE Int. Conf. on Smart Computing, St. Louis, 18 May 2016.

According to recent media reports, there has been a surge in the number of devices that are being connected to the Internet. The Internet of Things (IoT), also referred to as Cyber-Physical Systems, is a collection of physical entities with computational and communication capabilities. The storage and computing power of these devices is often limited and their designs currently focus on ensuring functionality and largely ignore other requirements, including security and privacy concerns. We present the design of a framework that allows IoT devices to capture, represent, reason with, and enforce information sharing policies. We use Semantic Web technologies to represent the policies, the information to be shared or protected, and the IoT device context. We discuss use-cases where our design will help in creating an “intelligent” IoT device and ensuring data security and privacy using context-sensitive information sharing policies.

Policies For Oblivious Cloud Storage Using Semantic Web Technologies

April 3rd, 2016, by Tim Finin, posted in cybersecurity, Ontologies, OWL, RDF, Security, Semantic Web

Policies For Oblivious Cloud Storage
Using Semantic Web Technologies

Vaishali Narkhede
10:30am, Monday, 4 April 2016, ITE 346, UMBC

Consumers want to ensure that their enterprise data is stored securely and obliviously on the cloud, such that the data objects or their access patterns are not revealed to anyone, including the cloud provider, in the public cloud environment. We have created a detailed ontology describing the oblivious cloud storage models and role based access controls that should be in place to manage this risk. We have also implemented the ObliviCloudManager application that allows users to manage their cloud data using oblivious data structures. This application uses role based access control model and collection based document management to store and retrieve data efficiently. Cloud consumers can use our system to define policies for storing data obliviously and manage storage on untrusted cloud platforms, even if they are not familiar with the underlying technology and concepts of the oblivious data structure.

Detecting Botnets Using a Collaborative Situational-Aware IDPS

February 17th, 2016, by Tim Finin, posted in Ontologies, Security, Semantic Web

M. Lisa Mathews, Anupam Joshi and Tim Finin, Detecting Botnets Using a Collaborative Situational-Aware IDPS, 2nd Int. Conf. on Information Systems Security and Privacy, Rome, IT, February 2016

Botnet attacks turn susceptible victim computers into bots that perform various malicious activities while under the control of a botmaster. Some examples of the damage they cause include denial of service, click fraud, spamware, and phishing. These attacks can vary in the type of architecture and communication protocol used, which might be modified during the botnet lifespan. Intrusion detection and prevention systems are one way to safeguard the cyber-physical systems we use, but they have difficulty detecting new or modified attacks, including botnets. Only known attacks whose signatures have been identified and stored in some form can be discovered by most of these systems. Also, traditional IDPSs are point-based solutions incapable of utilizing information from multiple data sources and have difficulty discovering new or more complex attacks. To address these issues, we are developing a semantic approach to intrusion detection that uses a variety of sensors collaboratively. Leveraging information from these heterogeneous sources leads to a more robust, situational-aware IDPS that is better equipped to detect complicated attacks such as botnets.

UCO: A Unified Cybersecurity Ontology

December 16th, 2015, by Tim Finin, posted in cybersecurity, KR, Ontologies, Semantic Web

Unified Cybersecurity Ontology

Zareen Syed, Ankur Padia, Tim Finin, Lisa Mathews and Anupam Joshi, UCO: Unified Cybersecurity Ontology, AAAI Workshop on Artificial Intelligence for Cyber Security (AICS), February 2016.

In this paper we describe the Unified Cybersecurity Ontology (UCO) that is intended to support information integration and cyber situational awareness in cybersecurity systems. The ontology incorporates and integrates heterogeneous data and knowledge schemas from different cybersecurity systems and most commonly used cybersecurity standards for information sharing and exchange. The UCO ontology has also been mapped to a number of existing cybersecurity ontologies as well as concepts in the Linked Open Data cloud. Similar to DBpedia which serves as the core for general knowledge in Linked Open Data cloud, we envision UCO to serve as the core for cybersecurity domain, which would evolve and grow with the passage of time with additional cybersecurity data sets as they become available. We also present a prototype system and concrete use cases supported by the UCO ontology. To the best of our knowledge, this is the first cybersecurity ontology that has been mapped to general world ontologies to support broader and diverse security use cases. We compare the resulting ontology with previous efforts, discuss its strengths and limitations, and describe potential future work directions.

Alexa, get my coffee: Using the Amazon Echo in Research

December 3rd, 2015, by Tim Finin, posted in AI, NLP, NLP, Semantic Web

“Alexa, get my coffee”:
Using the Amazon Echo in Research

Megan Zimmerman

10:30am Monday, 7 December 2015, ITE 346

The Amazon Echo is a remarkable example of language-controlled, user-centric technology, but also a great example of how far such devices have to go before they will fulfill the longstanding promise of intelligent assistance. In this talk, we will describe the Interactive Robotics and Language Lab‘s work with the Echo, with an emphasis on the practical aspects of getting it set up for development and adding new capabilities. We will demonstrate adding a simple new interaction, and then lead a brainstorming session on future research applications.

Megan Zimmerman is a UMBC undergrad majoring in computer science working on interpreting language about tasks at varying levels of abstraction, with a focus on interpreting abstract statements as possible task instructions in assistive technology.

Assessing credibility of content on Twitter using automated techniques

November 29th, 2015, by Tim Finin, posted in Machine Learning, Semantic Web, Social media, Web

Aditi Gupta

10:30am, Monday 30 November 2015, ITE 346

Online social media is a powerful platform for dissemination of information during real world events. Beyond the challenges of volume, variety and velocity of content generated on online social media, veracity poses a much greater challenge for effective utilization of this content by citizens, organizations, and authorities. Veracity of information refers to the trustworthiness /credibility / accuracy / completeness of the content. This work addressed the challenge of veracity or trustworthiness of content posted on social media.  We focus our work on Twitter, which is one of the most popular microblogging web service today. We provided an in-depth analysis of misinformation spread on Twitter during real world events. We showed effectiveness of automated techniques to detect misinformation on Twitter using a combination of content, meta-data, network, user profile and temporal features. We developed and deployed a novel framework, TweetCred for providing indication of trustworthiness / credibility of tweets posted during events. TweetCred, which was available as a browser plug-in, was installed and used by real Twitter users.

Dr. Aditi Gupta is a research associate in the Computer Science and Electrical Engineering Department at UMBC.  She received her Ph.D. from the Indraprastha Institute of Information Technology, Delhi  (IIIT-Delhi) in 2105 for her dissertation on designing and evaluating techniques to mitigate misinformation spread on microblogging web services.

Semantic Interpretation of Structured Log Files

November 21st, 2015, by Tim Finin, posted in Machine Learning, Semantic Web

 

Piyush Nimbalkar, Semantic Interpretation of Structured Log Files, M.S. thesis, University of Maryland, Baltimore County, August, 2015.

Log files comprise a record of different events happening in various applications, operating systems and even in network devices. Originally they were used to record information for diagnostic and debugging purposes. Nowadays, logs are also used to track events which can be used in auditing and forensics in case of malicious activities or systems attacks. Various softwares like intrusion detection systems, web servers, anti-virus and anti-malware systems, firewalls and network devices generate logs with useful information, that can be used to protect against such system attacks. Analyzing log files can help in pro- actively avoiding attacks against the systems. While there are existing tools that do a good job when the format of log files is known, the challenge lies in cases where log files are from unknown devices and of unknown formats. We propose a framework that takes any log file and automatically gives out a semantic interpretation as a set of RDF Linked Data triples. The framework splits a log file into columns using regular expression-based or dictionary-based classifiers. Leveraging and modifying our existing work on inferring the semantics of tables, we identify every column from a log file and map it to concepts either from a general purpose KB like DBpedia or domain specific ontologies such as IDS. We also identify relationships between various columns in such log files. Converting large and verbose log files into such semantic representations will help in better search, integration and rich reasoning over the data.

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