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Network Information Hiding and Science 2.0 : Can it be a Match?

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Science 2.0 aims at using the information sharing and collaborative features of the Internet to offer new features to the research community. Science 2.0 has been already applied to computer sciences, especially bioinformatics. For network information hiding, a field studying the possibility of concealing a communication in networks, the application of Science 2.0 is still a rather uncovered territory. To foster the discussion of potential benefits for network information hiding, we provide a disquisition for six different Science 2.0 aspects when applied to this domain.
Twórcy
autor
  • Worms University of Applied Sciences, Worms, Germany
  • Institute for Intelligent Systems for Automation (ISSIA), Genova, Italy
autor
  • Warsaw University of Technology, Institute of Telecommunications, Warsaw, Poland
  • INSA Centre Val de Loire - Inria, Bourges, France
Bibliografia
  • [1] D. D. Roure, C. Goble, and R. Stevens, “The design and realisation of the virtual research environment for social sharing of workflows,” Future Generation Computer Systems, vol. 25, no. 5, pp. 561–567, 2009.
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  • [4] W. Mazurczyk and L. Caviglione, “Information hiding as a challenge for malware detection,” IEEE Security & Privacy, vol. 13, no. 2, pp. 89–93, 2015.
  • [5] J. Priem and B. M. Hemminger, “Scientometrics 2.0: Toward new metrics of scholarly impact on the social web,” First Monday, vol. 15, no. 7, July 2010.
  • [6] T. Lin, “Cracking open the scientific process,” January 2012, http://www.nytimes.com/2012/01/17/science/open-science-challengesjournal-tradition-with-web-collaboration.html.
  • [7] T. W. Nattkemper, “Are we ready for science 2.0?” in International Conference on Knowledge Management and Information Sharing, K. Liu and J. Filipe, Eds., Barcelona, Spain, 2012, pp. 302–306.
  • [8] T. Bcheler and J. H. Sieg, “Understanding science 2.0: Crowdsourcing and open innovation in the scientific method,” Procedia Computer Science, vol. 7, no. 0, pp. 327–329, 2011.
  • [9] J. West, A. Salter, W. Vanhaverbeke, and H. Chesbrough, “Open innovation: The next decade,” Research Policy, vol. 43, no. 5, pp. 805–811, 2014, open Innovation: New Insights and Evidence.
  • [10] C. Franzoni and H. Sauermann, “Crowd science: The organization of scientific research in open collaborative projects,” Research Policy, vol. 43, no. 1, pp. 1–20, 2014.
  • [11] K. Laursen and A. J. Salter, “The paradox of openness: Appropriability, external search and collaboration,” Research Policy, vol. 43, no. 5, pp. 867-878, 2014, open Innovation: New Insights and Evidence.
  • [12] T. Anderson, “Conference reviewing considered harmful,” ACM SIGOPS Operating Systems Review, vol. 43, no. 2, pp. 108–116, 2009.
  • [13] A. Avizienis, J.-C. Laprie, B. Randell, and C. Landwehr, “Basic concepts and taxonomy of depandable and secure computing,” IEEE Trans. Depandable and Secure Computing, vol. 1, no. 1, pp. 11–33, 2004.
  • [14] D. K. Simonton, Creativity in science: Chance, logic, genius, and zeitgeist. Cambridge University Press, 2004.
  • [15] S. Wendzel, S. Zander, B. Fechner, and C. Herdin, “Pattern-based survey and categorization of network covert channel techniques,” ACM Computing Surveys (CSUR), vol. 47, no. 3, 2015.
  • [16] W. Mazurczyk and L. Caviglione, “Steganography in modern smartphones and mitigation techniques,” Communications Surveys Tutorials, IEEE, vol. 17, no. 1, pp. 334–357, Firstquarter 2015.
  • [17] “User interface design patterns,” 2015, http://ui-patterns.com/patterns.
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  • [19] M. McLennan and R. Kennell, “Hubzero: A platform for dissemination and collaboration in computational science and engineering,” Computing in Science Engineering, vol. 12, no. 2, pp. 48–53, March 2010.
  • [20] S. Wendzel and W. Mazurczyk, “Poster: An educational network protocol for covert channel analysis using patterns,” in Proc. 23rd ACM Conference on Computer and Communications Security (CCS). ACM, 2016, pp. 1739–1741.
  • [21] F. Bertolotti, E. Mattarelli, M. Vignoli, and D. M. Macr, “Exploring the relationship between multiple team membership and team performance: The role of social networks and collaborative technology,” Research Policy, vol. 44, pp. 911–924, 2015.
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  • [23] Google Inc., “Google scholar website,” 2015, http://scholar.google.de/.
  • [24] ResearchGate GmbH, “ResearchGate website,” 2015, http://www.researchgate.net/.
  • [25] “Overleaf website,” 2015, https://www.overleaf.com/.
  • [26] “Authorea website,” 2015, https://www.authorea.com.
  • [27] Mendeley Ltd., “Mendeley website,” 2015, https://www.mendeley.com.
  • [28] K. A. Khor and L.-G. Yu, “Influence of international co-authorship on the research citation impact of young unviersities,” Scientometrics, vol. 107, pp. 1095–1110, 2016.
  • [29] J. Kosten, “A classification of the use of research indicators,” Scientometrics, vol. 108, pp. 457–464, 2016.
  • [30] J. C. Mogul, “Towards more constructive reviewing of CS papers,” ACM SIGCOMM Computer Communication Review, vol. 43, no. 3, pp. 90–94, Jul. 2013.
  • [31] B. Meyer, “The nastiness problem in computer science,” BLOG@CACM, August 2011, http://cacm.acm.org/blogs/blog-cacm/123611-thenastiness-problem-in-computer-science/fulltext.
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Uwagi
PL
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).
Typ dokumentu
Bibliografia
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