The Experts below are selected from a list of 17547 Experts worldwide ranked by ideXlab platform

A Min Tjoa - One of the best experts on this subject based on the ideXlab platform.

  • ICT-EurAsia - Using semantic web to enhance user understandability for online shopping License Agreement
    Lecture Notes in Computer Science, 2013
    Co-Authors: Muhammad Asfand-e-yar, A Min Tjoa
    Abstract:

    Normally, a common user sign License Agreement without understanding the Agreement. License Agreements are a form of information, which describes product's usage and its terms and conditions. Habitually, users agree with it but without understanding. In the today's information age, there is no integration of License Agreements with any current technology. The contents of License Agreements are out of scope for search engines. Management of License Agreements using Semantic Web is a multi-disciplinary challenge, involving categorization of common features and structuring the required information in such semantics that is easily extendable and fulfilling the requirements of common user. In this paper construction of Semantic Web model for Online Shopping License Agreement is discussed. The user requirements facilitate the construction of License Ontological model. Moreover, rules are used to capture the complex statements of "terms and conditions". Finally, an explicit semantic model for Agreements is constructed that facilitates users' queries.

  • Towards an ontology-based solution for managing License Agreement using semantic desktop
    ARES 2010 - 5th International Conference on Availability Reliability and Security, 2010
    Co-Authors: Mansoor Ahmed, Muhammad Asfandeyar, Amin Anjomshoaa, A Min Tjoa, Abid Khan
    Abstract:

    Whenever software is installed on a computer system, one has to agree to the end-user License Agreement. The software License Agreement grants Licensee certain rights in software usage, but usually the ownership rights of the software stays with licensor. The licensor may also hold the right to restrict the usage of the software and can revoke the Agreement if the Licensee violates the License terms. Without agreeing with the License terms and conditions, the end-user is not authorized to use the software and could face penalties as described in the law. The main problem is that the percentage of the users who actually read the end-user License Agreement which are almost incomprehensible for the average software user is very low. Mostly the end-user does not pay much attention to reading the License Agreement because they believe that nearly all the end-user License Agreements are practically the same. This misunderstanding makes them not fully read the Agreement and just scroll the Agreement and accept the terms and conditions. What they do not realize is that by breaking the License Agreement they could be confronted with some penalties as described in the law. To overcome the problem of human inefficiency of understanding the License Agreement, we have introduced a machine readable representation of the License Agreement based on Semantic Web Technologies.

  • ARES - Towards an Ontology-Based Solution for Managing License Agreement Using Semantic Desktop
    2010 International Conference on Availability Reliability and Security, 2010
    Co-Authors: Mansoor Ahmed, Amin Anjomshoaa, A Min Tjoa, Muhammad Asfand-e-yar, Abid Khan
    Abstract:

    Whenever software is installed on a computer system, one has to agree to the end-user License Agreement. The software License Agreement grants Licensee certain rights in software usage, but usually the ownership rights of the software stays with licensor. The licensor may also hold the right to restrict the usage of the software and can revoke the Agreement if the Licensee violates the License terms. Without agreeing with the License terms and conditions, the end-user is not authorized to use the software and could face penalties as described in the law. The main problem is that the percentage of the users who actually read the end-user License Agreement which are almost incomprehensible for the average software user is very low. Mostly the end-user does not pay much attention to reading the License Agreement because they believe that nearly all the end-user License Agreements are practically the same. This misunderstanding makes them not fully read the Agreement and just scroll the Agreement and accept the terms and conditions. What they do not realize is that by breaking the License Agreement they could be confronted with some penalties as described in the law. To overcome the problem of human inefficiency of understanding the License Agreement, we have introduced a machine readable representation of the License Agreement based on Semantic Web Technologies.

Olivier Bodenreider - One of the best experts on this subject based on the ideXlab platform.

  • The Unified Medical Language System (UMLS): integrating biomedical terminology
    Nucleic Acids Research, 2004
    Co-Authors: Olivier Bodenreider
    Abstract:

    The Unified Medical Language System (http://umlsks.nlm.nih.gov) is a repository of biomedical vocabularies developed by the US National Library of Medicine. The UMLS integrates over 2 million names for some 900 000 concepts from more than 60 families of biomedical vocabularies, as well as 12 million relations among these concepts. Vocabularies integrated in the UMLS Metathesaurus include the NCBI taxonomy, Gene Ontology, the Medical Subject Headings (MeSH), OMIM and the Digital Anatomist Symbolic Knowledge Base. UMLS concepts are not only inter‐related, but may also be linked to external resources such as GenBank. In addition to data, the UMLS includes tools for customizing the Metathesaurus (MetamorphoSys), for generating lexical variants of concept names (lvg) and for extracting UMLS concepts from text (MetaMap). The UMLS knowledge sources are updated quarterly. All vocabularies are available at no fee for research purposes within an institution, but UMLS users are required to sign a License Agreement. The UMLS knowledge sources are distributed on CD‐ROM and by FTP.

Muhammad Asfand-e-yar - One of the best experts on this subject based on the ideXlab platform.

  • Using Semantic Web to Enhance User Understandability for Online Shopping License Agreement
    2013
    Co-Authors: Muhammad Asfand-e-yar, A Tjoa
    Abstract:

    Normally, a common user sign License Agreement without understanding the Agreement. License Agreements are a form of information, which describes product’s usage and its terms and conditions. Habitually, users agree with it but without understanding. In the today’s information age, there is no integration of License Agreements with any current technology. The contents of License Agreements are out of scope for search engines. Management of License Agreements using Semantic Web is a multi-disciplinary challenge, involving categorization of common features and structuring the required information in such semantics that is easily extendable and fulfilling the requirements of common user.In this paper construction of Semantic Web model for Online Shopping License Agreement is discussed. The user requirements facilitate the construction of License Ontological model. Moreover, rules are used to capture the complex statements of “terms and conditions”. Finally, an explicit semantic model for Agreements is constructed that facilitates users’ queries.

  • ICT-EurAsia - Using semantic web to enhance user understandability for online shopping License Agreement
    Lecture Notes in Computer Science, 2013
    Co-Authors: Muhammad Asfand-e-yar, A Min Tjoa
    Abstract:

    Normally, a common user sign License Agreement without understanding the Agreement. License Agreements are a form of information, which describes product's usage and its terms and conditions. Habitually, users agree with it but without understanding. In the today's information age, there is no integration of License Agreements with any current technology. The contents of License Agreements are out of scope for search engines. Management of License Agreements using Semantic Web is a multi-disciplinary challenge, involving categorization of common features and structuring the required information in such semantics that is easily extendable and fulfilling the requirements of common user. In this paper construction of Semantic Web model for Online Shopping License Agreement is discussed. The user requirements facilitate the construction of License Ontological model. Moreover, rules are used to capture the complex statements of "terms and conditions". Finally, an explicit semantic model for Agreements is constructed that facilitates users' queries.

  • ARES - Towards an Ontology-Based Solution for Managing License Agreement Using Semantic Desktop
    2010 International Conference on Availability Reliability and Security, 2010
    Co-Authors: Mansoor Ahmed, Amin Anjomshoaa, A Min Tjoa, Muhammad Asfand-e-yar, Abid Khan
    Abstract:

    Whenever software is installed on a computer system, one has to agree to the end-user License Agreement. The software License Agreement grants Licensee certain rights in software usage, but usually the ownership rights of the software stays with licensor. The licensor may also hold the right to restrict the usage of the software and can revoke the Agreement if the Licensee violates the License terms. Without agreeing with the License terms and conditions, the end-user is not authorized to use the software and could face penalties as described in the law. The main problem is that the percentage of the users who actually read the end-user License Agreement which are almost incomprehensible for the average software user is very low. Mostly the end-user does not pay much attention to reading the License Agreement because they believe that nearly all the end-user License Agreements are practically the same. This misunderstanding makes them not fully read the Agreement and just scroll the Agreement and accept the terms and conditions. What they do not realize is that by breaking the License Agreement they could be confronted with some penalties as described in the law. To overcome the problem of human inefficiency of understanding the License Agreement, we have introduced a machine readable representation of the License Agreement based on Semantic Web Technologies.

Abid Khan - One of the best experts on this subject based on the ideXlab platform.

  • Towards an ontology-based solution for managing License Agreement using semantic desktop
    ARES 2010 - 5th International Conference on Availability Reliability and Security, 2010
    Co-Authors: Mansoor Ahmed, Muhammad Asfandeyar, Amin Anjomshoaa, A Min Tjoa, Abid Khan
    Abstract:

    Whenever software is installed on a computer system, one has to agree to the end-user License Agreement. The software License Agreement grants Licensee certain rights in software usage, but usually the ownership rights of the software stays with licensor. The licensor may also hold the right to restrict the usage of the software and can revoke the Agreement if the Licensee violates the License terms. Without agreeing with the License terms and conditions, the end-user is not authorized to use the software and could face penalties as described in the law. The main problem is that the percentage of the users who actually read the end-user License Agreement which are almost incomprehensible for the average software user is very low. Mostly the end-user does not pay much attention to reading the License Agreement because they believe that nearly all the end-user License Agreements are practically the same. This misunderstanding makes them not fully read the Agreement and just scroll the Agreement and accept the terms and conditions. What they do not realize is that by breaking the License Agreement they could be confronted with some penalties as described in the law. To overcome the problem of human inefficiency of understanding the License Agreement, we have introduced a machine readable representation of the License Agreement based on Semantic Web Technologies.

  • ARES - Towards an Ontology-Based Solution for Managing License Agreement Using Semantic Desktop
    2010 International Conference on Availability Reliability and Security, 2010
    Co-Authors: Mansoor Ahmed, Amin Anjomshoaa, A Min Tjoa, Muhammad Asfand-e-yar, Abid Khan
    Abstract:

    Whenever software is installed on a computer system, one has to agree to the end-user License Agreement. The software License Agreement grants Licensee certain rights in software usage, but usually the ownership rights of the software stays with licensor. The licensor may also hold the right to restrict the usage of the software and can revoke the Agreement if the Licensee violates the License terms. Without agreeing with the License terms and conditions, the end-user is not authorized to use the software and could face penalties as described in the law. The main problem is that the percentage of the users who actually read the end-user License Agreement which are almost incomprehensible for the average software user is very low. Mostly the end-user does not pay much attention to reading the License Agreement because they believe that nearly all the end-user License Agreements are practically the same. This misunderstanding makes them not fully read the Agreement and just scroll the Agreement and accept the terms and conditions. What they do not realize is that by breaking the License Agreement they could be confronted with some penalties as described in the law. To overcome the problem of human inefficiency of understanding the License Agreement, we have introduced a machine readable representation of the License Agreement based on Semantic Web Technologies.

Martin Boldt - One of the best experts on this subject based on the ideXlab platform.

  • Informed software installation through License Agreement categorization
    2011 Information Security for South Africa - Proceedings of the ISSA 2011 Conference, 2011
    Co-Authors: Anton Borg, Martin Boldt, Niklas Lavesson
    Abstract:

    Spyware detection can be achieved by using machine learning techniques that identify patterns in the End User License Agreements (EULAs) presented by application installers. However, solutions have required manual input from the user with varying degrees of accuracy. We have implemented an automatic prototype for extraction and classification and used it to generate a large data set of EULAs. This data set is used to compare four different machine learning algorithms when classifying EULAs. Furthermore, the effect of feature selection is investigated and for the top two algorithms, we investigate optimizing the performance using parameter tuning. Our conclusion is that feature selection and performance tuning are of limited use in this context, providing limited performance gains. However, both the Bagging and the Random Forest algorithms show promising results, with Bagging reaching an AUC measure of 0.997 and a False Negative Rate of 0.062. This shows the applicability of License Agreement Categorization for realizing informed software installation.

  • ISSA - Informed software installation through License Agreement Categorization
    2011 Information Security for South Africa, 2011
    Co-Authors: Anton Borg, Martin Boldt, Niklas Lavesson
    Abstract:

    Spyware detection can be achieved by using machine learning techniques that identify patterns in the End User License Agreements (EULAs) presented by application installers. However, solutions have required manual input from the user with varying degrees of accuracy. We have implemented an automatic prototype for extraction and classification and used it to generate a large data set of EULAs. This data set is used to compare four different machine learning algorithms when classifying EULAs. Furthermore, the effect of feature selection is investigated and for the top two algorithms, we investigate optimizing the performance using parameter tuning. Our conclusion is that feature selection and performance tuning are of limited use in this context, providing limited performance gains. However, both the Bagging and the Random Forest algorithms show promising results, with Bagging reaching an AUC measure of 0.997 and a False Negative Rate of 0.062. This shows the applicability of License Agreement Categorization for realizing informed software installation.

  • Automated spyware detection using end user License Agreements
    Proceedings of the 2nd International Conference on Information Security and Assurance ISA 2008, 2008
    Co-Authors: Martin Boldt, Niklas Lavesson, Andreas Jacobsson, Peter Davidsson
    Abstract:

    The amount of spyware increases rapidly over the Internet and it is usually hard for the average user to know if a software application hosts spyware. This paper investigates the hypothesis that it is possible to detect from the end user License Agreement (EULA) whether its associated software hosts spyware or not. We generated a data set by collecting 100 applications with EULAs and classifying each EULA as either good or bad. An experiment was conducted, in which 15 popular default-configured mining algorithms were applied on the EULA data set. The results show that 13 algorithms are significantly better than random guessing, thus we conclude that the hypothesis can be accepted. Moreover, 2 algorithms also perform significantly better than the current state-of-the-art EULA analysis method. Based on these results, we present a novel tool that can be used to prevent the installation of spyware.

  • Preventing Privacy-Invasive Software using Online Reputations
    2008
    Co-Authors: Martin Boldt, Bengt Carlsson, Tobias Larsson, Niklas Lindén
    Abstract:

    Privacy-invasive software, loosely labeled spyware, is an increasingly common problem for today’s computer users, one to which there is no absolute cure. Most of the privacy-invasive software are positioned in a legal gray zone, as the user accepts the malicious behaviour when agreeing to the End User License Agreement. This paper proposes the use of a specialized reputation system to gather and share information regarding software behaviour between community users. A client application helps guide the user at the point of executing software on the local computer, displaying other users’ feedback about the expected behaviour of the software. We discuss important aspects to consider when constructing such a system, and propose possible solutions. Based on the observations made, we implemented a client/server based proof-of-concept tool, which allowed us to demonstrate how such a system would work. We also compare this solution to other, more conventional, protection methods such as anti-virus and anti-spyware software.

  • spyware prevention by classifying end user License Agreements
    International Conference Industrial Engineering & Other Applications Applied Intelligent Systems, 2008
    Co-Authors: Niklas Lavesson, Martin Boldt, Paul Davidsson, Andreas Jacobsson
    Abstract:

    We investigate the hypothesis that it is possible to detect from the End User License Agreement (EULA) if the associated software hosts spyware. We apply 15 learning algorithms on a data set consisting of 100 applications with classified EULAs. The results show that 13 algorithms are significantly more accurate than random guessing. Thus, we conclude that the hypothesis can be accepted. Based on the results, we present a novel tool that can be used to prevent spyware by automatically halting application installers and classifying the EULA, giving users the opportunity to make an informed choice about whether to continue with the installation. We discuss positive and negative aspects of this prevention approach and suggest a method for evaluating candidate algorithms for a future implementation.