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Sec-Lib: Protecting Scholarly Digital Libraries From Infected Papers Using Active Machine Learning Framework, Nir Nissim, Aviad Cohen, Jian Wu, Andrea Lanzi, Lior Rokach, Yuval Elovici, Lee Giles Jan 2019

Sec-Lib: Protecting Scholarly Digital Libraries From Infected Papers Using Active Machine Learning Framework, Nir Nissim, Aviad Cohen, Jian Wu, Andrea Lanzi, Lior Rokach, Yuval Elovici, Lee Giles

Computer Science Faculty Publications

Researchers from academia and the corporate-sector rely on scholarly digital libraries to access articles. Attackers take advantage of innocent users who consider the articles' files safe and thus open PDF-files with little concern. In addition, researchers consider scholarly libraries a reliable, trusted, and untainted corpus of papers. For these reasons, scholarly digital libraries are an attractive-target and inadvertently support the proliferation of cyber-attacks launched via malicious PDF-files. In this study, we present related vulnerabilities and malware distribution approaches that exploit the vulnerabilities of scholarly digital libraries. We evaluated over two-million scholarly papers in the CiteSeerX library and found the library …


Final Report For The Development Of The Nasa Technical Report Server (Ntrs), Michael L. Nelson Jan 2005

Final Report For The Development Of The Nasa Technical Report Server (Ntrs), Michael L. Nelson

Computer Science Faculty Publications

The author performed a variety of research, development and consulting tasks for NASA Langley Research Center in the area of digital libraries (DLs) and supporting technologies, such as the Open Archives Initiative Protocol for Metadata Harvesting (OAI-PMH). In particular, the development focused on the NASA Technical Report Server (NTRS) and its transition from a distributed searching model to one that uses the OAI-PMH. The Open Archives Initiative (OAI) is an international consortium focused on furthering the interoperability of DLs through the use of "metadata harvesting". The OAI-PMH version of NTRS went into public production on April 28, 2003. Since that …


Metadata And Buckets In The Smart Object, Dumb Archive (Soda) Model, Michael L. Nelson, Kurt Maly, Delwin R. Croom Jr., Steven W. Robbins Jan 2004

Metadata And Buckets In The Smart Object, Dumb Archive (Soda) Model, Michael L. Nelson, Kurt Maly, Delwin R. Croom Jr., Steven W. Robbins

Computer Science Faculty Publications

We present the Smart Object, Dumb Archive (SODA) model for digital libraries (DLs), and discuss the role of metadata in SODA. The premise of the SODA model is to "push down" many of the functionalities generally associated with archives into the data objects themselves. Thus the data objects become "smarter", and the archives "dumber". In the SODA model, archives become primarily set managers, and the objects themselves negotiate and handle presentation, enforce terms and conditions, and perform data content management. Buckets are our implementation of smart objects, and da is our reference implementation for dumb archives. We also present our …


Buckets: Aggregative, Intelligent Agents For Publishing, Michael L. Nelson, Kurt Maly, Stewart N. T. Shen, Mohammad Zubair Jan 1998

Buckets: Aggregative, Intelligent Agents For Publishing, Michael L. Nelson, Kurt Maly, Stewart N. T. Shen, Mohammad Zubair

Computer Science Faculty Publications

Buckets are an aggregative, intelligent construct for publishing in digital libraries. The goal of research projects is to produce information. This information is often instantiated in several forms, differentiated by semantic types (report, software, video, datasets, etc.). A given semantic type can be further differentiated by syntactic representations as well (PostScript version, PDF version, Word version, etc.). Although the information was created together and subtle relationships can exist between them, different semantic instantiations are generally segregated along currently obsolete media boundaries. Reports are placed in report archives, software might go into a software archive, but most of the data and …