Archive for the 'GENERAL' Category
November 18th, 2017, by Tim Finin, posted in GENERAL
Cybersecurity Challenges to American Local Governments
In this paper we examine data from the first ever nationwide survey of cybersecurity among American local governments. We are particularly interested in understanding the threats to local government cybersecurity, their level of preparedness to address the threats, the barriers these governments encounter when deploying cybersecurity, the policies, tools and practices that they employ to improve cybersecurity and, finally, the extent of awareness of and support for high levels of cybersecurity within their organizations. We found that local governments are under fairly constant cyberattack and are periodically breached. They are not especially well prepared to prevent cyberattacks or to recover when breached. The principal barriers to local cybersecurity are financial and organizations. Although a number of policies, tools and practices to improve cybersecurity, few local governments are making wide use of them. Last, local governments suffer from too little awareness of and support for cybersecurity within their organizations.
November 6th, 2017, by Tim Finin, posted in GENERAL, UMBC
UMBC upgrades High Performance Computing Facility with new NSF grant
The National Science Foundation recently awarded UMBC a Major Research Instrumentation (MRI) award totaling more than $550,000 to expand the university’s High Performance Computing Facility (HPCF). The funding will go toward upgraded hardware and increased computing speeds for the interdisciplinary core facility, which supports scientific computing and other complex, data-intensive research across disciplines, university-wide. As part of the NSF grant, UMBC is required to contribute 30 percent of the amount that NSF is providing to further support the project, meaning a total new investment of more than $780,000 in UMBC’s High Performance Community Facility.
Meilin Yu, assistant professor of mechanical engineering, is the principal investigator on the grant. He replaced Matthias Gobbert, professor of mathematics, who served as principal investigator on previous grants for the core facility in 2008, 2012 and 2017 on behalf of the 51 faculty investigators from academic departments and research centers across all three colleges. Co-Principal investigators on the grant are Professors Marc Olano, Jianwu Wang and Daniel Lobo.
Adapted for a UMBC news article by Megan Hanks
May 21st, 2017, by Tim Finin, posted in GENERAL
One of the key challenges faced by consumers is to efficiently manage and monitor the quality of cloud services. To manage service performance, consumers have to validate rules embedded in cloud legal contracts, such as Service Level Agreements (SLA) and Privacy Policies, that are available as text documents. Currently this analysis requires significant time and manual labor and is thus inefficient. We propose a cognitive assistant that can be used to manage cloud legal documents by automatically extracting knowledge (terms, rules, constraints) from them and reasoning over it to validate service performance. In this paper, we present this Question and Answering (Q&A) system that can be used to analyze and obtain information from the SLA documents. We have created a knowledgebase of Cloud SLAs from various providers which forms the underlying repository of our Q&A system. We utilized techniques from natural language processing and semantic web (RDF, SPARQL and Fuseki server) to build our framework. We also present sample queries on how a consumer can compute metrics such as service credit.
November 22nd, 2016, by Tim Finin, posted in GENERAL
In this week’s meeting, Ankur Padia will about about his work on the problem of identifying and managing ‘dubious facts’ extracted from text and added to a knowledge graph.
Dealing with Dubious Facts in Knowledge Graphs
Knowledge graphs are used to represent real-world facts and events with entities as nodes and relations as labeled edges. Generally, a knowledge graph is automatically constructed by extracting facts from text corpus using information extraction (IE) techniques. Such IE techniques are scalable but often extract low quality (or dubious) facts due to errors caused by NLP libraries, internal components of an extraction system, choice of learning techniques, heuristics and syntactic complexity of underlying text. We wish to explore techniques to process such dubious facts and improve the quality of a knowledge graph.
November 19th, 2016, by Tim Finin, posted in GENERAL
A common Big Data problem is the need to integrate large temporal data sets from various data sources into one comprehensive structure. Having the ability to correlate evolving facts between data sources can be especially useful in supporting a number of desired application functions such as inference and influence identification. As a real world application we use climate change publications based on the Intergovernmental Panel on Climate Change, which publishes climate change assessment reports every five years, with currently over 25 years of published content. Often these reports reference thousands of research papers. We use dynamic topic modeling as a basis for combining report and citation domains into one structure. We are able to correlate documents between the two domains to understand how the research has influenced the reports and how this influence has changed over time. In this use case, the topic report model used a total number of 410 documents and 5911 terms in the vocabulary while in the topic citations the vocabulary consisted of 25,154 terms and the number of documents was closer to 200,000 research papers.
November 6th, 2016, by Tim Finin, posted in GENERAL
Multi-relational data, like knowledge graphs, are generated from multiple data sources by extracting entities and their relationships. We often want to include inferred, implicit or likely relationships that are not explicitly stated, which can be viewed as link-prediction in a graph. Tensor decomposition models have been shown to produce state-of-the-art results in link-prediction tasks. We describe a simple but novel extension to an existing tensor decomposition model to predict missing links using similarity among tensor slices, as opposed to an existing tensor decomposition models which assumes each slice to contribute equally in predicting links. Our extended model performs better than the original tensor decomposition and the non-negative tensor decomposition variant of it in an evaluation on several datasets.
April 3rd, 2016, by Tim Finin, posted in GENERAL
The UMBC School of Public Policy, bwtech@UMBC Cyber Incubator, and UMBC Center for Cybersecurity are sponsoring a form on Cybersecurity Concerns in Local Governments from 8:30-11:00am on Friday, April 15, 2016 at the Columbus Center in Baltimore.
“Like their counterparts in the private sector, it is important for local government officials and managers to understand cybersecurity threats to their websites and information systems and to take actions to prevent cyber attacks. The purpose of this forum is to present research on cybersecurity initiatives in local governments in Maryland, and highlight the public policy implications of these initiatives.”
There is no charge to attend this forum, but registration is required. For questions or more information, contact email@example.com.
8:30 a.m. Coffee, light breakfast and networking
9:00 Welcome and Overview
Cybersecurity Challenges in American Local Government
Donald F. Norris, Professor and Director, UMBC School of Public Policy
Policy-driven Approaches to Security
Anupam Joshi, Professor and Director, UMBC Center for Cybersecurity
Perspectives from Maryland Local Governments
Rob O’Connor, Chief Technology Officer, Baltimore County
Jerome Mullen, Chief Technology Officer, City of Baltimore
10:15 Audience Q & A
January 6th, 2015, by Tim Finin, posted in GENERAL
Jeff Shager’s Genealogy of Eliza project has added an 1100-line Perl emulator written by James Markevitch for the 1966 version of BBN-LISP for the PDP-1 computer that can run Bernie Cosell’s original LISP version of doctor.
Markevitch writes in the comments
This is a Perl hack to implement the 1966 version of BBN-LISP for the PDP-1 computer. This was written primarily to run the 1966 LISP version of the “doctor” program (aka Eliza) written by Bernie Cosell. The intent is to be compatible with the version of LISP described in The BBN-LISP System, Daniel G. Bobrow et al, February, 1966, AFCRL-66-180 [BBN66]. However, because many of the quirks of that version of LISP are not documented, The BBN-LISP System Reference Manual April 1969, D. G. Bobrow et al [BBN69] was used as a reference. Finally, LISP 1.5 Programmer’s Manual, John McCarthy et al [LISP1.5] was also used as a reference. N.B. The 1966 version of BBN-LISP has differences from later versions and this interpreter will not properly execute programs written for those later versions.
You can download the Perl Lisp emulator, the doctor lisp code and the script file from the elizagen github repository.
December 13th, 2014, by Tim Finin, posted in GENERAL
UMBC has a total of nine open full-time positions for computing faculty including five tenure track professors, a professor of the practice and three lecturers.
UMBC’s Computer Science and Electrical Engineering department is seeking to fill five positions for the coming year. They include two tenure track positions in Computer Science, up to three full-time lecturers. See the CSEE jobs page for more information.
The College of Engineering and Information Technology has a position for a full-time lecturer or Professor of Practice to focus on the needs of incoming computing majors through teaching, advising, and helping develop programs in computing. This person will work closely with faculty in the Computer Science and Electrical Engineering Department and Information Systems Department.
UMBC’s Information Systems department is accepting applications for three tenure track faculty positions in data science, software engineering and human-centered computing.
June 23rd, 2014, by Tim Finin, posted in GENERAL
Justin Martineau, Doreen Cheng and Tim Finin, TISA: topic independence scoring algorithm. In Proc. 9th Int. Conf. on Machine Learning and Data Mining (MLDM’13), pp. 555-570, July 2013, Springer-Verlag.
Textual analysis using machine learning is in high demand for a wide range of applications including recommender systems, business intelligence tools, and electronic personal assistants. Some of these applications need to operate over a wide and unpredictable array of topic areas, but current in-domain, domain adaptation, and multi-domain approaches cannot adequately support this need, due to their low accuracy on topic areas that they are not trained for, slow adaptation speed, or high implementation and maintenance costs.
To create a true domain-independent solution, we introduce the Topic Independence Scoring Algorithm (TISA) and demonstrate how to build a domain-independent bag-of-words model for sentiment analysis. This model is the best preforming sentiment model published on the popular 25 category Amazon product reviews dataset. The model is on average 89.6% accurate as measured on 20 held-out test topic areas. This compares very favorably with the 82.28% average accuracy of the 20 baseline in-domain models. Moreover, the TISA model is highly uniformly accurate, with a variance of 5 percentage points, which provides strong assurance that the model will be just as accurate on new topic areas. Consequently, TISAs models are truly domain independent. In other words, they require no changes or human intervention to accurately classify documents in never before seen topic areas.
March 27th, 2014, by Prajit Kumar Das, posted in Ebiquity, Google, Mobile Computing, Policy, Semantic Web, Social, Wearable Computing
If you are a Google Glass user, you might have been greeted with concerned looks or raised eyebrows at public places. There has been a lot of chatter in the “interweb” regarding the loss of privacy that results from people taking your pictures with Glass without notice. Google Glass has simplified photography but as what happens with revolutionary technology people are worried about the potential misuse.
FaceBlock helps to protect the privacy of people around you by allowing them to specify whether or not to be included in your pictures. This new application developed by the joint collaboration between researchers from the Ebiquity Research Group at University of Maryland, Baltimore County and Distributed Information Systems (DIS) at University of Zaragoza (Spain), selectively obscures the face of the people in pictures taken by Google Glass.
Comfort at the cost of Privacy?
As the saying goes, “The best camera is the one that’s with you”. Google Glass suits this description as it is always available and can take a picture with a simple voice command (“Okay Glass, take a picture”). This allows users to capture spontaneous life moments effortlessly. On the flip side, this raises significant privacy concerns as pictures can taken without one’s consent. If one does not use this device responsibly, one risks being labelled a “Glasshole”. Quite recently, a Google Glass user was assaulted by the patrons who objected against her wearing the device inside the bar. The list of establishments which has banned Google Glass within their premises is growing day by day. The dos and donts for Glass users released by Google is a good first step but it doesn’t solve the problem of privacy violation.
Privacy-Aware pictures to the rescue
FaceBlock takes regular pictures taken by your smartphone or Google Glass as input and converts it into privacy-aware pictures. This output is generated by using a combination of Face Detection and Face Recognition algorithms. By using FaceBlock, a user can take a picture of herself and specify her policy/rule regarding pictures taken by others (in this case ‘obscure my face in pictures from strangers’). The application would automatically generate a face identifier for this picture. The identifier is a mathematical representation of the image. To learn more about the working on FaceBlock, you should watch the following video.
Using Bluetooth, FaceBlock can automatically detect and share this policy with Glass users near by. After receiving this face identifier from a nearby user, the following post processing steps happen on Glass as shown in the images.
What promises does it hold?
FaceBlock is a proof of concept implementation of a system that can create privacy-aware pictures using smart devices. The pervasiveness of privacy-aware pictures could be a right step towards balancing privacy needs and comfort afforded by technology. Thus, we can get the best out of Wearable Technology without being oblivious about the privacy of those around you.
FaceBlock is part of the efforts of Ebiquity and SID in building systems for preserving user privacy on mobile devices. For more details, visit http://face-block.me
October 16th, 2013, by Tim Finin, posted in GENERAL
The UMBC Computer Science and Electrical Engineering department is searching for new full-time faculty: two in Computer Science, one in Electrical and Computer Engineering, one Computer Science professor of the practice, and one Computer Science/Information Systems lecturer. See the CSEE Jobs page for detailed information on the positions, preferred specializations and the application process.
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