2.0 Big Data … “Vc3: trustworthy data analytics in the cloud using sgx,” in 2015 IEEE Symposium on Security and Privacy (SP) (San Jose, CA: IEEE), 38–54. “An open source tool for game theoretic health data de-identification,” in AMIA 2017, American Medical Informatics Association Annual Symposium (Washington, DC). Kantarcıoğlu, M., and Clifton, C. (2005). This thesis aims to present a literature review of work on big data analytics, a pertinent contemporary topic which has been of importance since 2010 as one of the top technologies suggested to solve multiple academic, industrial, and societal problems. Connecting every smart objects inside the home to the internet and to each other results in new security and privacy problems, e.g., confidentiality, authenticity, and integrity of data sensed and exchanged by objects. %PDF-1.3 Buragohain, C., Agrawal, D., and Suri, S. (2003). arXiv preprint arXiv:1708.08749, 1–17. On the other hand, while linking and sharing data across organizations, privacy/security issues need to be considered. (2017). Natl. big-data-analytics-for-security -intelligence), focuses on big data’s role in security. 4, 28–34. Section 5 describes a platform for experimentation on anti-virus telemetry data. “Hawk: the blockchain model of cryptography and privacy-preserving smart contracts,” in 2016 IEEE Symposium on Security and Privacy (SP) (San Jose, CA: IEEE), 839–858. Understanding what makes a good thesis statement is one of the major keys to writing a great research paper or argumentative essay. … We are … As reports from McKinsey Global Institute (Mckinsey et al., 2011) and the World Economic Forum (Schwab, 2016) suggest, capturing, storing and mining “big data” may create significant value in many industries ranging from health care to government services. As more and more data collected, making organizations accountable for data misuse becomes more critical. Carminati, B., Ferrari, E., Heatherly, R., Kantarcioglu, M., and Thuraisingham, B. M. (2009). BIG DATA AND ANALYTICS: The emergence of new technologies, applications and network systems makes it hard to run the current business models and huge data types, and thus emerged various types of analytic tools like Big Data, which make this work easier by way of proper organization of data. Once data is collected and potentially linked/cleaned, it may be shared across organizations to enable novel applications and unlock potential value. Still many challenges remain in both settings. These techniques usually work by adding noise to shared data and may not be suitable in some application domains where noise free data need to be shared (e.g., health care domain). (2016). Ramachandran, A., and Kantarcioglu, M. (2018). Private traits and attributes are predictable from digital records of human behavior. For example, McKinsey estimates that capturing the value of big data can create $300 billion dollar annual value in the US health care sector and $600 billion dollar annual consumer surplus globally (Mckinsey et al., 2011). Available online at: https://bitcoin.org/bitcoin.pdf. We!are!awash!in!a!floodof!data!today. The Fourth Industrial Revolution. ACM 61, 54–61. Big Data And Analytics Analysis 1316 Words | 6 Pages. “A cyber-provenance infrastructure for sensor-based data-intensive applications,” in 2017 IEEE International Conference on Information Reuse and Integration, IRI 2017 (San Diego, CA), 108–114. 3.2 Data privacy and security 17 3.3 Big data talent 18 4 Industry Case Examples 19 4.1 Big data in agriculture 19 4.2 Big data in logistics 21 4.3 Big data in retail 23 4.3.1 Amazon’s anticipatory shipping 23 4.3.2 Recommended items 25 4.3.3 Customer loyalty programs 25 4.3.4 Big data touch points in retail 26 Ekiden: a platform for confidentiality-preserving, trustworthy, and performant smart contract execution. security solutions proposed for CPS big data storage, access and analytics. 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