First, the attack instances are frequently being modified to avoid detection. Big data is slowly but surely gaining its popularity in healthcare. Androulaki, E., Barger, A., Bortnikov, V., Cachin, C., Christidis, K., De Caro, A., et al. Available online at: https://www.europol.europa.eu/activities-services/main-reports/internet-organised-crime-threat-assessment-iocta-2017. (2016). Moser, M., Bohme, R., and Breuker, D. (2013). Big data addresses speed and measurability, quality and security, flexibility and stability. (2017). Since the amount of data collected is ever increasing, it became impossible to analyze all the collected data manually to detect and prevent attacks. “Privacy preserving keyword searches on remote encrypted data,” in Proceedings of ACNS'05 (New York, NY), 442–455. Zhou, Y., Kantarcioglu, M., Thuraisingham, B., and Xi, B. Ohrimenko, O., Schuster, F., Fournet, C., Mehta, A., Nowozin, S., Vaswani, K., et al. “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. �YR����. Springer Publishing Company, Incorporated. Secondly, when a previously unknown attack appears, data analytics techniques need to respond to the new attack quickly and cheaply. (Accessed on 10/17/2016), Shaon, F., and Kantarcioglu, M. (2016). Introduction. The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. 17, 603–619. doi: 10.1073/pnas.1218772110, Kuzu, M., Kantarcioglu, M., Durham, E. A., Tóth, C., and Malin, B. Big Data PhD Thesis Topics. 4, 28–34. Social Media . Working with big data has enough challenges and concerns as … At the same time, it is not clear whether the organizations who collect the privacy sensitive data always process the data according to user consent. doi: 10.1145/2714576.2714624, Ulusoy, H., Kantarcioglu, M., Pattuk, E., and Kagal, L. (2015b). Although differential privacy techniques have shown some promise to prevent such attacks, recent results have shown that it may not be effective against many attack while providing acceptable data utility (Fredrikson et al., 2014). The Big Data: The Next Frontier for Innovation, Competition, and Productivity. Mckinsey & Company. This paper introduces the functions of big data, and the security threat faced by big data, then proposes the (2017). 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. Therefore, data analytics are being applied to large volumes of security monitoring data to detect cyber security incidents (see discussion in Kantarcioglu and Xi, 2016). As another example, passenger data coming from airlines may need to be linked to governmental terrorist watch lists to detect suspicious activity. “Access control enforcement within mqtt-based internet of things ecosystems,” in Proceedings of the 23nd ACM on Symposium on Access Control Models and Technologies, SACMAT 2018 (Indianapolis, IN), 223–234. Heatherly, R., Kantarcioglu, M., and Thuraisingham, B. M. (2013). “Multi-dimensional range query over encrypted data,” in SP '07: Proceedings of the 2007 IEEE Symposium on Security and Privacy (Washington, DC: IEEE Computer Society), 350–364. Furthermore, these results suggest that most of the privacy-preserving distributed machine learning tasks could be securely implemented by using few basic “secure building blocks” such as secure matrix operations, secure comparison, etc. Section 3 reviews the impact of Big Data analytics on security and Section 4 provides examples of Big Data usage in security contexts. Still, the scalability of these techniques for multiple data sources with different privacy and security requirements have not been explored. Thirdly, adversaries can be well-funded and make big investments to camouflage the attack instances. 2 Definition and main features of Big Data 6 2-1 Big data in general sense 6 2-2 Maritime big data 12 3 Cutting edge institutions of maritime big data 21 3-1 DNV-GL 21 3-2 Lloyd’s Register Foundation (LRF) 28 3-3 E-navigation 34 4 Analysis of challenges and solutions 45 4-1 Sound competitive conditions 46 4-2 Human resources 56 4-3 Technology 64 For example, a report from Gartner claims (MacDonald, 2012) that “Information security is becoming a big data analytics problem, where massive amounts of data will be correlated, analyzed and mined for meaningful patterns.” There are many companies that already offer data analytics solutions for this important problem. doi: 10.1109/BigData.2015.7363786. Vulnerability to fake data generation 2. Cheng, R., Zhang, F., Kos, J., He, W., Hynes, N., Johnson, N. M., et al. 4 0 obj Then it concentrates on the technical side of the tool, examining ... thesis. Other data security methods focus on the database’s hard drive. “Hyperledger fabric: a distributed operating system for permissioned blockchains,” in Proceedings of the Thirteenth EuroSys Conference (New York, NY: ACM), 30. Blockchain Data Analytics tools (Akcora et al., 2017) and big data analysis algorithms can be used by law agencies to detect such misuse (for Law Enforcement Cooperation, 2017). Once data is encrypted, if the encryption keys are safe, then it is infeasible to retrieve the original data from the encrypted data alone. And although it is advised to perform them on a regular basis, this recommendation is rarely met in reality. in Proceedings of the 2002 ACM SIGMOD International Conference on Management of Data (Madison, WI), 216–227. doi: 10.1145/3097983.3098082. Fredrikson, M., Lantz, E., Jha, S., Lin, S., Page, D., and Ristenpart, T. (2014). ACM 61, 54–61. Hence a future dataset will no longer share the same properties as the current datasets. For example, a patient may visit multiple health care providers and his/her complete health records may not be available in one organization. Prasser, F., Gaupp, J., Wan, Z., Xia, W., Vorobeychik, Y., Kantarcioglu, M., et al. 25, 1849–1862. This made it difficult for existing data mining tools, technologies, methods, and techniques to be applied directly on big data streams due to the inherent dynamic characteristics of big data. doi: 10.1145/2447976.2447990. 9 … Byun, J.-W., and Li, N. (2008). This dissertation aims to set out all the possible threats to data security, such as account hacking and insecure cloud services. The practical implications of setting such privacy parameters need to be explored further. Problems with security pose serious threats to any system, which is why it’s crucial to know your gaps. “Design and analysis of querying encrypted data in relational databases,” in The 21th Annual IFIP WG 11.3 Working Conference on Data and Applications Security (Berlin, Heidelberg: Springer-Verlag), 177–194. Following are some of the Big Data examples- The New York Stock Exchange generates about one terabyte of new trade data per day. These observations indicate that understanding how to provide scalable, secure and privacy-aware access control mechanisms for the future big data applications ranging from personalized medicine to Internet of Things systems while satisfying new regulatory requirements would be an important research direction. Although leveraging trusted execution environments showed some promising results, potential leaks due to side channels need to be considered (Schuster et al., 2015; Costan and Devadas, 2016; Shaon et al., 2017). Information Security is Becoming a Big Data Analytics Problem. Revealed: 50 million Facebook Profiles Harvested for Cambridge Analytica in Major Data Breach. It has been shown that machine learning results may be used to infer sensitive information such as sexual orientation, political affiliation (e.g., Heatherly et al., 2013), intelligence (e.g., Kosinski et al., 2013) etc. |, 6. That is why there are plenty of relevant thesis topics in data mining. This in return implies that the entire big data pipeline needs to be revisited with security and privacy in mind. B. Thesis statement: Big Data will face management, security and privacy challenges. Big data, Technologies, Visualization, Classification, Clustering 1. (2016). “The limitations of deep learning in adversarial settings,” in IEEE European Symposium on Security and Privacy, EuroS&P 2016 (Saarbrücken), 372–387. stream doi: 10.1109/EuroSP.2016.36, Pasarella, E., and Lobo, J. Big Data displays a pivotal role in Personalization of things whether in Marketing, Healthcare, Purchase, Social Networks which help in better understanding of the customer behaviors, their likes, choices and accordingly there future prediction is made by analyzing upon their present data. Data … To address this type of incentive issues, secure distributed data sharing protocols that incentivize honest sharing of data have been developed (e.g., Buragohain et al., 2003). IEEE Trans. Thus, the purpose of this thesis is to study multiple models for privacy preservation in an In-memory based real-time big data analytics solution, and to subsequently evaluate and analyze the outcome … Potential presence of untrusted mappers 3. All you need to do is go online, give us a call Big Data Security Thesis or send a chat message and say: “Do Big Data Security Thesis my assignment”. Unfortunately, these practical risk-aware data sharing techniques do not provide the theoretical guarantees offered by differential privacy. Executing SQL over encrypted data in the database-service-provider model. doi: 10.1109/TKDE.2012.61, Kantarcioglu, M., and Nix, R. (2010). (2004). Recently, big data streams have become ubiquitous due to the fact that a number of applications generate a huge amount of data at a great velocity. “A datalog framework for modeling relationship-based access control policies,” in Proceedings of the 22nd ACM on Symposium on Access Control Models and Technologies, SACMAT 2017 (Indianapolis), 91–102. ! a! floodof! data! is! have continued to grow exponentially, that... Many privacy requirements accountable for data misuse becomes more critical thirdly, can! Cps big data: the Next Frontier for Innovation, Competition, and,! N. ( 2008 ), Kosinski, M., and Li, C. ( 2005.! 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