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Emerging trends around big data analytics and security: panel

Published: 20 June 2012 Publication History

Abstract

This panel will discuss the interplay between key emerging security trends centered around big data analytics and security. With the explosion of big data and advent of cloud computing, data analytics has not only become prevalent but also a critical business need. Internet applications today consume vast amounts of data collected from heterogeneous big data repositories and provide meaningful insights from it. These include applications for business forecasting, investment and finance, healthcare and well-being, science and hi-tech, to name a few. Security and operational intelligence is one of the critical areas where big data analytics is expected to play a crucial role. Security analytics in a big data environment presents a unique set of challenges, not properly addressed by the existing security incident and event monitoring (or SIEM) systems that typically work with a limited set of traditional data sources (firewall, IDS, etc.) in an enterprise network. A big data environment presents both a great opportunity and a challenge due to the explosion and heterogeneity of the potential data sources that extend the boundary of analytics to social networks, real time streams and other forms of highly contextual data that is characterized by high volume and speed. In addition to meeting infrastructure challenges, there remain additional unaddressed issues, including but not limited to development of self-evolving threat ontologies, integrated network and application layer analytics, and detection of "low and slow" attacks. At the same time, security analytics requires a high degree of data assurance, where assurance implies that the data be trustworthy as well as managed in a privacy preserving manner. Our panelists represent individuals from industry, academia, and government who are at the forefront of big data security analytics. They will provide insights into these unique challenges, survey the emerging trends, and lay out a vision for future.

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  • (2024)Navigating Industry 5.0: A Survey of Key Enabling Technologies, Trends, Challenges, and OpportunitiesIEEE Communications Surveys & Tutorials10.1109/COMST.2023.332947226:2(1080-1126)Online publication date: Oct-2025
  • (2017)Designing a Pragmatic Graphical Grammar2017 IEEE Conference on Cognitive and Computational Aspects of Situation Management (CogSIMA)10.1109/COGSIMA.2017.7929599(1-5)Online publication date: Mar-2017
  • (2016)A Hierarchical Security Model for Multimedia Big DataBig Data10.4018/978-1-4666-9840-6.ch022(441-453)Online publication date: 2016
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Published In

cover image ACM Conferences
SACMAT '12: Proceedings of the 17th ACM symposium on Access Control Models and Technologies
June 2012
242 pages
ISBN:9781450312950
DOI:10.1145/2295136

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 20 June 2012

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Author Tags

  1. analytics
  2. big data
  3. privacy
  4. security

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  • Panel

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SACMAT '12
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SACMAT '12 Paper Acceptance Rate 19 of 73 submissions, 26%;
Overall Acceptance Rate 177 of 597 submissions, 30%

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Cited By

View all
  • (2024)Navigating Industry 5.0: A Survey of Key Enabling Technologies, Trends, Challenges, and OpportunitiesIEEE Communications Surveys & Tutorials10.1109/COMST.2023.332947226:2(1080-1126)Online publication date: Oct-2025
  • (2017)Designing a Pragmatic Graphical Grammar2017 IEEE Conference on Cognitive and Computational Aspects of Situation Management (CogSIMA)10.1109/COGSIMA.2017.7929599(1-5)Online publication date: Mar-2017
  • (2016)A Hierarchical Security Model for Multimedia Big DataBig Data10.4018/978-1-4666-9840-6.ch022(441-453)Online publication date: 2016
  • (2016)Closing the loopIBM Journal of Research and Development10.1147/JRD.2016.257158060:4(10:1-10:12)Online publication date: 1-Jul-2016
  • (2016)Lateral Movement Detection Using Distributed Data Fusion2016 IEEE 35th Symposium on Reliable Distributed Systems (SRDS)10.1109/SRDS.2016.014(21-30)Online publication date: Sep-2016
  • (2016)Big Data for supply chain management in the service and manufacturing sectorsComputers and Industrial Engineering10.1016/j.cie.2016.07.013101:C(572-591)Online publication date: 1-Nov-2016
  • (2015)Intrusion detection and Big Heterogeneous Data: a SurveyJournal of Big Data10.1186/s40537-015-0013-42:1Online publication date: 27-Feb-2015
  • (2014)A Hierarchical Security Model for Multimedia Big DataInternational Journal of Multimedia Data Engineering & Management10.4018/ijmdem.20140101015:1(1-13)Online publication date: 1-Jan-2014
  • (2013)Enabling trustworthy spaces via orchestrated analytical securityProceedings of the Eighth Annual Cyber Security and Information Intelligence Research Workshop10.1145/2459976.2459991(1-4)Online publication date: 8-Jan-2013

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