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While the problem of working with data that exceeds the computing power or storage of a single computer is not new, the pervasiveness, scale, and value of this type of computing has greatly expanded in recent years. Big Data allows the organizations to take appropriate decisions, and precisely access performance, as Big Data can provide concealed data that is beneficial for the company. Supervisor: Mario Mariniello Thesis presented by Yannic Blaschke for the Degree of Master of Arts in European ... 4.2. A hybrid approach to private record linkage. 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. Then it concentrates on the technical side of the tool, examining ... thesis. Fredrikson, M., Lantz, E., Jha, S., Lin, S., Page, D., and Ristenpart, T. (2014). Data Eng. (2016). The Big Data: The Next Frontier for Innovation, Competition, and Productivity. In particular, it provides a data-driven critical examination of the affordances and limitations of open-source communications gathered from social media interactions for the study of crime and disorder. 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 Z. Huang, and R. Wang (Auckland: Springer), 350–362. Things, big data has become the hot topic of research across the world, at the same time, big data faces security risks and privacy protection during collecting, storing, analyzing and utilizing. 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”. (Accessed on 10/17/2016), Shaon, F., and Kantarcioglu, M. (2016). �3��7+PEstL�_��|a?��;V:i5Ȍ�΋��/�� These results indicate the need to do more research on understanding privacy impact of machine learning models and whether the models should be built in the first place (e.g., machine learning model that tries to predict intelligence). [21] Martínez, Diana, and Sergio Luján-Mora. Summary of Article Using big data surveillance means to obtain vast amount of data which is then stored, combined and analysed, to eventually create patterns that reveals trends used for governance, … Baeza-Yates, R. (2018). (2013). doi: 10.1145/2976749.2976753, Kosba, A., Miller, A., Shi, E., Wen, Z., and Papamanthou, C. (2016). 2.0 Big Data Analytics Privacy-preserving distributed mining of association rules on horizontally partitioned data. Executing SQL over encrypted data in the database-service-provider model. “Access pattern disclosure on searchable encryption: Ramification, attack and mitigation,” in 19th Annual Network and Distributed System Security Symposium, NDSS 2012 (San Diego, CA). Access Control in Oracle. “Opaque: a data analytics platform with strong security,” in 14th USENIX Symposium on Networked Systems Design and Implementation (NSDI 17) (Boston, MA: USENIX Association). 3�G��O^&��0��_S��p�~�16 A. This paper introduces the functions of big data, and the security threat faced by big data, then proposes the “Deep learning with differential privacy,” in Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security (New York, NY: ACM), 308–318. “Backpage and bitcoin: Uncovering human traffickers,” in Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (Halifax, NS), 1595–1604. Bigdata with map reduce.Application and Domain knowledge: Domain knowledge and application knowledge help is gained by that data … Once data is encrypted, if the encryption keys are safe, then it is infeasible to retrieve the original data from the encrypted data alone… 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. As big data becomes the new oil for the digital economy, realizing the benefits that big data can bring requires considering many different security and privacy issues. The practical implications of setting such privacy parameters need to be explored further. Acad. Finally, Section 6 proposes a series of open questions about the role of Big Data in security analytics. B., and Swami, A. 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 … Bias on the web. All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication. doi: 10.1109/SP.2015.10, Schwab, K. (2016). Kantarcioglu, M., and Jiang, W. (2012). Unlike most other application domains, cyber security applications often face adversaries who actively modify their strategies to launch new and unexpected attacks. Study on Big Data in Public Health, Telemedicine and Healthcare December, 2016 4 Abstract - French Lobjectif de l¶étude des Big Data dans le domaine de la santé publique, de la téléméde- cine et des soins médicaux est d¶identifier des exemples applicables des Big Data de la Santé et de développer des recommandations d¶usage au niveau de l¶Union Européenne. Working with big data has enough challenges and concerns as … Master thesis in big data for short essay on bank. Sci. On the other hand, some practical risk–aware data sharing tools have been developed (e.g., Prasser et al., 2017). Establishing a data-friendly culture: For any organization, moving from a culture where people made decisions based on their gut instincts, opinions or experience to a data-driven culture marks a huge transition. big data into the social sciences, claims that big data can be a major instrument to ‘reinvent society’ and to improve it in that process [177]. For example, to address new regulations such as right-to-be-forgotten where users may require the deletion of data that belongs to them, we may need to better understand how the data linked and shared among multiple users in a big data system. doi: 10.1145/3205977.3205986, Costan, V., and Devadas, S. (2016). Section 5 describes a platform for experimentation on anti-virus telemetry data. 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. Section 3 reviews the impact of Big Data analytics on security and Section 4 provides examples of Big Data usage in security contexts. “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. Trust some or all of your schoolwork to us Big Data Security Thesis and set yourself free from academic stress. In many cases, misaligned incentives among the data collectors and/or processors may prevent data sharing. As enterprises data stores have continued to grow exponentially, managing that big data has become increasingly challenging. (2007). On the other hand, the data stored on blockchains (e.g., financial transactions stored on Bitcoin blockchain) may be analyzed to provide novel insights about emerging data security issues. Many techniques ranging from simple encrypted keyword searches to fully homomorphic encryption have been developed (e.g., Gentry, 2009). For example, instead of getting lab tests conducted by another health care provider, for a hospital, it may be more profitable to redo the tests. 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). Still, it is shown that given large amount of data, these techniques can provide useful machine learning models. Islam, M. S., Kuzu, M., and Kantarcioglu, M. (2012). (2018). Encrypted storage and querying of big data have received significant attention in the literature (e.g., Song et al., 2000; Hacigumus et al., 2002; Golle et al., 2004; Ballard et al., 2005; Chang and Mitzenmacher, 2005; Kantarcıoğlu and Clifton, 2005; Canim and Kantarcioglu, 2007; Shi et al., 2007; Shaon and Kantarcioglu, 2016). Give you five papers to summarize find in( security big data folder) and follow the same steps and idea as in (my paper file) the attached file “. Thirdly, adversaries can be well-funded and make big investments to camouflage the attack instances. C. Expanded thesis: Businesses would be multiplying and become further reliant on Big Data, but at the same time, security, scalability, and privacy in Big Data would be a major concern. This in return may significantly reduce the data utility. “Incentive compatible distributed data mining,” in Proceedings of the 2010 IEEE Second International Conference on Social Computing, SocialCom/IEEE International Conference on Privacy, Security, Risk and Trust, PASSAT 2010, Minneapolis, Minnesota, USA, August 20-22, 2010, eds A. K. Elmagarmid and D. Agrawal (Minneapolis, MN: IEEE Computer Society), 735–742. Kantarcıoğlu, M., and Clifton, C. (2004). Big Data, 14 February 2019 Positive aspects of Big Data, and their potential to bring improvement to everyday life in the near future, have been widely discussed in Europe. Big data refers to datasets that are not only big, but also high in variety and velocity, which makes them difficult to handle using traditional tools and techniques. Manyika, J., Chui, M., Brown, B., Bughin, J., Dobbs, R., Roxburgh, C., et al. WITH BLACKBOARD MASTERS AND … %PDF-1.3 doi: 10.1109/TKDE.2004.45. Big Data is used in many … doi: 10.1073/pnas.1218772110, Kuzu, M., Kantarcioglu, M., Durham, E. A., Tóth, C., and Malin, B. Big Data In It terminology, Big Data is looked as a group of data sets, which are so sophisticated and large that the data can not be easily taken, stored, searched, shared, analyzed or visualized making use of offered tools. This implies that access control systems need to support policies based on the relationships among users and data items (e.g., Pasarella and Lobo, 2017). Big data is a blanket term for the non-traditional strategies and technologies needed to gather, organize, process, and gather insights from large datasets. Examples span from health services, to road safety, agriculture, retail, education and climate change mitigation and are based on the direct use/collection of Big Data or inferences based on them. Commun. doi: 10.1109/ICDE.2008.4497458. We offer wide range of opportunities for students (ME, … 1 !!!! The lack of transparency in data-driven decision-making algorithms can easily conceal fallacies and risks codified in the underlying mathematical models, and nurture inequality, bias, and further division between the privileged and the under-privileged (Sweeney, 2013). Potential presence of untrusted mappers 3. Index Terms—cyber-physical systems (CPS), Internet of Things (IoT), context-awareness, social computing, cloud computing, big data, clustering, data mining, data analytics, machine learning, Of course, data analytics is a means to an end where the ultimate goal is to provide cyber security analysts with prioritized actionable insights derived from big data. For example, a sophisticated group of cyber attackers may create malware that can evade all the existing signature-based malware detection tools using zero day exploits (i.e., software bugs that were previously unknown). Another important research direction is to address the privacy and the security issues in analyzing big data. Big Data Master Thesis gives highly challengeable opportunities for you to process your ability by universal shaking achievements to this world. Words: 974 Length: 3 Pages Document Type: Essay Paper #: 92946618. For example, it seems that cryptocurrencies are used in payments for human trafficking (Portnoff et al., 2017), ransomware (Huang et al., 2018), personal blackmails (Phetsouvanh and Oggier, 2018), and money laundering (Moser and Breuker, 2013), among many others. 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. 4 0 obj If you find yourself struggling to make sense of your paper or your topic, then it's likely due to a weak thesis statement. At the same time, encrypted data must be queried efficiently. doi: 10.1145/2714576.2714624, Ulusoy, H., Kantarcioglu, M., Pattuk, E., and Kagal, L. (2015b). (2012). Therefore, the spam e-mail characteristics may be changed significantly by the spammers as often as they want. Our current trends updated technical team has full of certified engineers and experienced professionals to provide … Hence a future dataset will no longer share the same properties as the current datasets. �l�='�+?�� IoT Security Thesis—Exploring and Securing a Future Concept—Download IoT—A Scalable Web Technology for the Internet of Things—Download IoT—A Distributed Security Scheme to Secure Data … “Privacy integrated queries: an extensible platform for privacy-preserving data analysis,” in SIGMOD. Still addressing incentive issues ranging from compensating individuals for sharing their data (e.g., data market places 1) to payment systems for data sharing among industry players need to be addressed. Blockchains, Big Data Security and Privacy, 7. Discrimination in online ad delivery. Problems with security pose serious threats to any system, which is why it’s crucial to know your gaps. Available online at: crypto.stanford.edu/craig, Golle, P., Staddon, J., and Waters, B. In fact, the size of these huge data sets is believed to be a continually growing target. Proc. arXiv:1412.6572. 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. Other data security methods focus on the database’s hard drive. Data provenance difficultie… arXiv[Preprint]. There are … For example, when a new type of ransomware appears in the wild, we may need to update existing data analytics techniques quickly to detect such attacks. Big data covers the initiatives and technologies that tackle massive and diverse data when it comes to addressing traditional skills, technologies, and infrastructure efficiently. Even if the data is stored in an encrypted format, legitimate users need to access the data. Big Data Management, Security … These protocols usually leverage ideas from economics and game theory to incentivize truthful sharing of big data where security concerns prevent direct auditing (e.g., Kantarcioglu and Nix, 2010; Kantarcioglu and Jiang, 2012). “Tracking ransomware end-to-end,” in Tracking Ransomware End-to-end (San Francisco, CA: IEEE), 1–12. Prasser, F., Gaupp, J., Wan, Z., Xia, W., Vorobeychik, Y., Kantarcioglu, M., et al. doi: 10.1109/IRI.2017.91. Due to the rapid growth of such data, solutions need to be studied and provided in order … Szegedy, C., Zaremba, W., Sutskever, I., Bruna, J., Erhan, D., Goodfellow, I. J., et al. Big data “Modeling adversarial learning as nested Stackelberg games,” in Advances in Knowledge Discovery and Data Mining - 20th Pacific-Asia Conference, PAKDD 2016, Proceedings, Part II, vol. Consequently, in order to choose a good topic, one has to … Sweeney, L. (2013). Song, D. X., Wagner, D., and Perrig, A. (2011). Ulusoy, H., Colombo, P., Ferrari, E., Kantarcioglu, M., and Pattuk, E. (2015a). “A game theoretic framework for incentives in p2p systems,” in P2P '03: Proceedings of the 3rd International Conference on Peer-to-Peer Computing (Washington, DC: IEEE Computer Society) 48. 4 Key concepts, theories Big data refers to the dynamic, large and disparate volumes of data … Few typical characteristics of big data are the integration of structured data, semi-structured data and unstructured data. doi: 10.1145/2976749.2978318, Akcora, C. G., Gel, Y. R., and Kantarcioglu, M. (2017). This paper reports on a methodological experiment with ‘big data’ in the field of criminology. Here, our big data expertscover the most vicious security challenges that big data has in stock: 1. … Hacigumus, H., Iyer, B. R., Li, C., and Mehrotra, S. (2002). Cloud-based storage has facilitated data mining and collection. Commun. Edited and reviewed by: Jorge Lobo, Catalan Institution for Research and Advanced Studies, Spain. 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. However, in this thesis Big Data refers to “the 3Vs” – Volume for the huge amount of data, Variety for the speed of data creation, and Velocity for the growing unstructured data (McAfee & Brynjolfsson, 2012… Available online at: https://www.gartner.com/doc/1960615/information-security-big-data-analytics (Accessed Jul 15, 2018). doi: 10.1109/EuroSP.2016.36, Pasarella, E., and Lobo, J. U.S.A. 110, 5802–5805. Explaining and harnessing adversarial examples. “Sgx-bigmatrix: a practical encrypted data analytic framework with trusted processors,” in Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security, CCS 2017 (Dallas, TX), 1211–1228. Androulaki, E., Barger, A., Bortnikov, V., Cachin, C., Christidis, K., De Caro, A., et al. If you have to ask this question, it suggests that you are not up to speed in your initial review of relevant literature. 25, 1849–1862. Dwork, C. (2006). Below, we provide an overview of novel research challenges that are at the intersection of cybersecurity, privacy and big data. Secondly, when a previously unknown attack appears, data analytics techniques need to respond to the new attack quickly and cheaply. “Security issues in querying encrypted data,” in The 19th Annual IFIP WG 11.3 Working Conference on Data and Applications Security (Storrs, CT). This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). Nutzung von Big Data im Marketing: Theoretische Grundlagen, Anwendungsfelder und Best-Practices Bachelorarbeit zur Erlangung des Grades eines Bachelor of Science im Studiengang Informationsmanagement vorgelegt von Alexander Schneider 210200136 Nisterweg 18 56477 Rennerod Especially, recent developments in machine learning techniques have created important novel applications in many fields ranging from health care to social networking while creating important privacy challenges. Goodfellow, I. J., Shlens, J., and Szegedy, C. (2014). From a privacy point of view, novel privacy-preserving data sharing techniques, based on a theoretically sound privacy definition named differential privacy, have been developed (e.g., Dwork, 2006). To address the scenarios where machine learning models need to be built by combining data that belong to different organization, many different privacy-preserving distributed machine learning protocols have been developed (e.g., Clifton et al., 2003; Kantarcıoğlu and Clifton, 2004; Vaidya and Clifton, 2005). 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. As machine learning algorithms affect more and more aspects of our lives, it becomes crucial to understand how these algorithms change the way decisions are made in today's data-driven society. Research Topics in Big Data Analytics Research Topics in Big Data Analytics offers you an innovative platform to update your knowledge in research. Since the amount of data collected is ever increasing, it became impossible to analyze all the collected data manually to detect and prevent attacks. Understanding the data provenance (e.g., Bertino and Kantarcioglu, 2017) (i.e., how the data is created, who touched it etc.) Therefore, better understanding of the limits of privacy-preserving data sharing techniques that balance privacy risks vs. data utility need to be developed. Tools for privacy preserving distributed data mining. Zheng, W., Dave, A., Beekman, J., Popa, R. A., Gonzalez, J., and Stoica, I. Big Data Thesis Topics are given below: Big data analysis in vehicular Ad-hoc networks. Best case … As shown by the recent Cambridge Analytica scandal (Cadwalladr and Graham-Harrison, 2018) where millions of users profile information were misused, security and privacy issues become a critical concern. ICDE 2008 496–505. Research that addresses this interdisciplinary area emerges as a critical need. In addition to increasing accountability in decision making, more work is needed to make organizations accountable in using privacy sensitive data. (2018). Cheng, R., Zhang, F., Kos, J., He, W., Hynes, N., Johnson, N. M., et al. As more and more data collected, making organizations accountable for data misuse becomes more critical. Big data, Technologies, Visualization, Classification, Clustering 1. }L0kD�fhn�|��"@D��"�pr�A��8r��XO�]14]7�v^I ��2��n\Ƞ��O��2cJP�]�w�j$��6��Jw�BH35��@l�1�R[/��ID��Y��:��;/3��?��x>��^]"Q-5�wZ��e&�q]�3[�-f�Ϟ��W��\U�dkiy�C�b�� ω)��Tp�d�R��⺣m��$��0W��9��P9=�Ć�z��!RNA��#��wm�~��\�� 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). For example, while the big data is stored and recorded, appropriate privacy-aware access control policies need to be enforced so that the big data is only used for legitimate purposes. doi: 10.1145/2339530.2339697, Keywords: big data, security, privacy, cybersecurity, sharing, machine learning, Citation: Kantarcioglu M and Ferrari E (2019) Research Challenges at the Intersection of Big Data, Security and Privacy. arXiv:1312.6199. Phetsouvanh, A. D. S., and Oggier, F. (2018). doi: 10.1145/3097983.3098082. … Bitcoin's success has resulted in more than 1000 Blockchain based cryptocurrencies, known as alt-coins. On the other hand, while linking and sharing data across organizations, privacy/security issues need to be considered. “Secure conjunctive keyword search over encrypted data,” in Applied Cryptography and Network Security (ACNS 2004) M. Jakobsson, M. Yung, and J. Zhou (Berlin, Heidelberg: Springer), 31–45. Ohrimenko, O., Schuster, F., Fournet, C., Mehta, A., Nowozin, S., Vaswani, K., et al. Carminati, B., Ferrari, E., Heatherly, R., Kantarcioglu, M., and Thuraisingham, B. M. (2009). Latest Thesis and Research Topics in Big Data. These are equally rich and complementary areas for research that are important for secure and confidential use of big data. “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. ��'k~�'�� f|?YE��HnVQuaTE�i��+�� w%:��4oo�-��"��7��E�M�k��z[!��qR�G��0. O&��L stream Mckinsey & Company. Still, several important issues need to be addressed to capture the full potential of big data. doi: 10.1136/amiajnl-2012-000917, PubMed Abstract | CrossRef Full Text | Google Scholar. “Achieving efficient conjunctive keyword searches over encrypted data,” in Seventh International Conference on Information and Communication Security (ICICS 2005) (Heidelberg: Springer), 414–426. Huang, D. Y., McCoy, D., Aliapoulios, M. M., Li, V. G., Invernizzi, L., Bursztein, E., et al. 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). Unfortunately, these practical risk-aware data sharing techniques do not provide the theoretical guarantees offered by differential privacy. “Privacy preserving keyword searches on remote encrypted data,” in Proceedings of ACNS'05 (New York, NY), 442–455. Front. SIGKDD Explorat. And although it is advised to perform them on a regular basis, this recommendation is rarely met in reality. Voigt, P., and Bussche, A. V. D. (2017). !In!a!broad!range!of!applicationareas,!data!is!being Incentive compatible privacy preserving data analysis. Vulnerability to fake data generation 2. doi: 10.1109/SocialCom.2010.114, Kantarcioglu, M., and Xi, B. Still, the scalability of these techniques for multiple data sources with different privacy and security requirements have not been explored. More research that integrates ideas from economics, and psychology with computer science techniques is needed to address the incentive issues in sharing big data without sacrificing security and/or privacy. Finally, Section 6 proposes a series of open questions about the role of Big Data in security analytics. Unfortunately, privacy and security issues may prevent such data sharing. JAMIA 20, 285–292. (2013). This dissertation aims to set out all the possible threats to data security, such as account hacking and insecure cloud services. Ballard, L., Kamara, S., and Monrose, F. (2005). “Smartprovenance: a distributed, blockchain based dataprovenance system,” in Proceedings of the Eighth ACM Conference on Data and Application Security and Privacy, CODASPY 2018 (Tempe, AZ), 35–42. Portnoff, R. S., Huang, D. Y., Doerfler, P., Afroz, S., and McCoy, D. (2017). Big data … Understanding what makes a good thesis statement is one of the major keys to writing a great research paper or argumentative essay. Clearly, these types of use cases require linking potentially sensitive data belonging to the different data controllers. Big Data–Big Data Analytics – Hadoop Performance Analysis– Download Big Data–Large Scale Data Analytics of User Behavior for Improving Content Delivery–Download Big Data–Big data algorithm optimization Case study of a sales simulation system–Download Big Data–Big Data and Business Intelligence: a data … “Privacy-preserving decision trees over vertically partitioned data,” in The 19th Annual IFIP WG 11.3 Working Conference on Data and Applications Security (Storrs, CT: Springer). Therefore, there is an urgent need to protect machine learning models against potential attacks. The existence of such adversaries in cyber security creates unique challenges compared to other domains where data analytics tools are applied. Big data addresses speed and measurability, quality and security, flexibility and stability. Introduction. INTRODUCTION Big data is associated with large data sets and the size is above the flexibility of common database software tools to capture, store, handle and evaluate [1][2]. Therefore, security is of great concern when it comes to securing big data processes. 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 PhD Thesis on Cloud Computing PhD Thesis on Cloud Computing is a gracious research service that will take you one step ahead of others and it will place you among the elite group of scholars. Kantarcıoğlu, M., and Clifton, C. (2005). The thesis statement is where you make a claim that will guide you through your entire paper. 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). (2016). In fact, the size of these huge data sets is believed to be a continually growing target. The main thesis topics in Big Data and Hadoop include applications, architecture, Big Data in IoT, MapReduce, Big Data Maturity Model etc. doi: 10.1145/2447976.2447990. IEEE 24th International Conference on Data Engineering, 2008. For example, different organizations may not want to share their cybersecurity incident data because of the potential concerns where a competitor may use this information for their benefit. IEEE TKDE 16, 1026–1037. 6) Security today: What are the threats to personal and organisational data privacy? This in return implies that the entire big data pipeline needs to be revisited with security and privacy in mind. II. doi: 10.1109/eCRS.2013.6805780, Nakamoto, S. (2008). Ramachandran, A., and Kantarcioglu, M. (2018). 768-785. 17, 603–619. Examples Of Big Data. “Practical techniques for searches on encrypted data,” in IEEE SP (Washington, DC), 44–55. arXiv[Preprint]. The new service of providing analytics of complicated big data via mobile cloud computing to fulfil businesses needs by utilizing both Infrastructure as a service (IaaS) and Software as a Service (SaaS), is called Big Data as a Service (BDaaS). Big Data 2:1. doi: 10.3389/fdata.2019.00001. (2016). Ph.D. thesis, Stanford University. Big Data … Although the research community has developed a plethora of access control techniques for almost all of the important big data management systems (e.g., Relational databases Oracle, 2015, NoSql databases Ulusoy et al., 2015a; Colombo and Ferrari, 2018, social network data Carminati et al., 2009) with important capabilities, whether the existing techniques and tools could easily support the new regulatory requirements such as the ones introduced by European Union General Data Protection Directive GDPR (Voigt and Bussche, 2017) is an important question. Data mining has been increasingly gathering attention in recent years. In big data analytics, thesis completion is a big thing for PhD beginners. �YR��. We also discuss big data meeting green challenges in the contexts of CPS. |, 6. It is anticipated that big data will bring evolutionary discoveries in regard to drug discovery research, treatment innovation, personalized medicine, optimal patient care, etc. (2017). “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. For example, a patient may visit multiple health care providers and his/her complete health records may not be available in one organization. Again differential privacy ideas have been applied to address privacy issues for the scenarios where all the needed data is controlled by one organization (e.g., McSherry, 2009). Section 3 reviews the impact of Big Data analytics on security and Section 4 provides examples of Big Data usage in security contexts. 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). 9 … (2015). Preventing private information inference attacks on social networks. 4, 28–34. doi: 10.1007/978-3-319-41483-6_14, Shaon, F., Kantarcioglu, M., Lin, Z., and Khan, L. (2017). The first application of Blockchain has been the Bitcoin (Nakamoto, 2008) cryptocurrency. No use, distribution or reproduction is permitted which does not comply with these terms. Purpose based access control for privacy protection in relational database systems. security solutions proposed for CPS big data storage, access and analytics. Buragohain, C., Agrawal, D., and Suri, S. (2003). Our experts will take on task that you give them and will provide online assignment help that will skyrocket your grades. Available online at: http://www3.weforum.org/docs/Media/KSC_4IR.pdf. 9652 of Lecture Notes in Computer Science eds J. Bailey, L. Khan, T. Washio, G. Dobbie, J. Storing and Querying Big Data. include, for example, systems for collecting data privately, access control in web and social networking applications, data security and cryptography, and protocols for secure computation. doi: 10.1145/3209581. A Fully Homomorphic Encryption Scheme. Examples of these collected data include system logs, network packet traces, account login formation, etc. Knowl. Bertino, E., and Kantarcioglu, M. (2017). doi: 10.1145/772862.772867, Colombo, P., and Ferrari, E. (2018). Struggles of granular access control 6. Springer Publishing Company, Incorporated. In many cases, data that belongs to different sources need to be integrated while satisfying many privacy requirements. These Received: 24 July 2018; Accepted: 10 January 2019; Published: 14 February 2019. “Egret: extortion graph exploration techniques in the bitcoin network,” in IEEE ICDM Workshop on Data Mining in Networks (DaMNet). Oracle (2015). Chandra, S., Karande, V., Lin, Z., Khan, L., Kantarcioglu, M., and Thuraisingham, B. doi: 10.1007/978-3-540-24852-1_3. Troubles of cryptographic protection 4. In this study we focused on data storage security issues in cloud computing and we first provided service models of cloud, deployment models and variety of security issues in data storage in 135 Naresh vurukonda and B. Thirumala Rao / Procedia … for Law Enforcement Cooperation, E. U. (2000). This implies that we need to have effective access control techniques that allow users to access the right data. Abstract of the Dissertation The explosion in the amount of data, called “data deluge”, is forcing to redefine many scientific and technological fields, with the affirmation in any environment of Big Data … 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. The Fourth Industrial Revolution. Private traits and attributes are predictable from digital records of human behavior. Big Data PhD Thesis Topics. ChallengesandOpportunities)withBig)Data! BIG DATA PROGRAM In the big data program in the School of Computing at the University of Utah, students will take classes from tenure-track ... Network Security Parallel Programming for GPUs/Many Cores/Multi-Cores Big Data Certificate ... or thesis Big Data PhD (PhD in Computing) CORE CLASSES + 3 electives and PhD thesis… It turns out that blockchains may have important implications for big data security and privacy. Social Media . Another important advantage of big data is data analytic. Additionally, the size of big data … ACM 61, 54–61. doi: 10.1145/3176258.3176333, Schuster, F., Costa, M., Fournet, C., Gkantsidis, C., Peinado, M., Mainar-Ruiz, G., et al. doi: 10.1007/s00778-006-0023-0. The statistic shows that 500+terabytes of new data get ingested into the databases of social media site Facebook, every day.This data is mainly generated in terms of photo and video uploads, message exchanges, putting comments … Our current trends updated technical team has full of … Cloud Computing is an enterprise for scholars who need some guidance to bring forth their research skills. Still, direct application of data analytics techniques to the cyber security domain may be misguided. Blockchain: A Graph Primer. And in the NewVantage Partners Big Data Executive Survey 2017, 52.5 percent of executives said that data governance was critically important to big data business adoption. Big data is slowly but surely gaining its popularity in healthcare. Even worse, in some cases such data may be distributed among multiple parties with potentially conflicting interests. Research builds on previous research and a worthwhile thesis will reflect a familiarity with … 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. MK research was supported in part by NIH award 1R01HG006844, NSF awards CNS-1111529, CICI- 1547324, and IIS-1633331 and ARO award W911NF-17-1-0356. Although the recent research tries to address these transparency challenges (Baeza-Yates, 2018), more research is needed to ensure fairness, and accountability in usage of machine learning models and big data driven decision algorithms. (2017). “Securing data analytics on sgx with randomization,” in Proceedings of the 22nd European Symposium on Research in Computer Security (Oslo). For example, multiple users that are tagged in the same picture may have legitimate privacy claims about the picture. “Accountablemr: toward accountable mapreduce systems,” in 2015 IEEE International Conference on Big Data, Big Data 2015 (Santa Clara, CA), 451–460. Copyright © 2019 Kantarcioglu and Ferrari. Revealed: 50 million Facebook Profiles Harvested for Cambridge Analytica in Major Data Breach. SPARQL-Benchmarks automatisiert im Big Data Umfeld ausführen (Master Thesis) – Max Hofmann und Timo Eichhorn. Bitcoin: A Peer-to-Peer Electronic Cash System. amount of data which is generated is growing exponentially due to technological advances. Introduction The term “big data” is normally used as a marketing concept refers to data sets whose size is further than the potential of normally used enterprise tools to gather, manage and organize, and process within an acceptable elapsed time. security issues. “A practical framework for executing complex queries over encrypted multimedia data,” in Proceedings on 30th Annual IFIP WG 11.3 Conference on Data and Applications Security and Privacy XXX DBSec 2016 (Trento), 179–195. doi: 10.1145/3078861.3078871. Introduction. McSherry, F. D. (2009). Section 5 describes a platform for experimentation on anti-virus telemetry data. Therefore, more research is needed to scale these techniques without sacrificing security guarantees. Available online at: http://eprint.iacr.org. The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. “Privacy in pharmacogenetics: An end-to-end case study of personalized warfarin dosing,” in 23rd USENIX Security Symposium (USENIX Security 14) (San Diego, CA: USENIX Association), 17–32. (New York, NY), 19–30. have shown to improve trust in decisions and the quality of data used for decision making. Available online at: https://www.europol.europa.eu/activities-services/main-reports/internet-organised-crime-threat-assessment-iocta-2017. Big Data PhD Thesis Topics is our extremely miraculous thesis preparation service for you to provide highly standardized thesis for your intellectual research. important implications for security in these technologies. “A semantic web based framework for social network access control,” in SACMAT, eds B. Carminati and J. Joshi (New York, NY: ACM), 177–186. On the one hand, combined with other cryptographic primitives, blockchain based tools (e.g., Androulaki et al., 2018) may enable more secure financial transactions (e.g., Cheng et al., 2018), data sharing (e.g., Kosba et al., 2016) and provenance storage (e.g., Ramachandran and Kantarcioglu, 2018). “An inquiry into money laundering tools in the bitcoin ecosystem,” in eCrime Researchers Summit, 1–14. Ekiden: a platform for confidentiality-preserving, trustworthy, and performant smart contract execution. Once data is encrypted, if the encryption keys are safe, then it is infeasible to retrieve the original data from the encrypted data alone. For example, attackers may change the spam e-mails written by adding some words that are typically associated with legitimate e-mails. With the recent regulations such as GDPR (Voigt and Bussche, 2017), using data only for the purposes consented by the individuals become critical, since personal data can be stored, analyzed and shared as long as the owner of the data consent the data usage purposes. In the case of differential private techniques, for complex machine learning tasks such as deep neural networks, the privacy parameters need to adjusted properly to get the desired utility (e.g., classifier accuracy Abadi et al., 2016). As another example, passenger data coming from airlines may need to be linked to governmental terrorist watch lists to detect suspicious activity. in Proceedings of the 2002 ACM SIGMOD International Conference on Management of Data (Madison, WI), 216–227. 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. Chang, Y., and Mitzenmacher, M. (2005). Abadi, M., Chu, A., Goodfellow, I., McMahan, H. B., Mironov, I., Talwar, K., et al. Possibility of sensitive information mining 5. Techinical Report, Cryptology ePrint Archive, Report 2016/086, 20 16. The report details how the security analytics land-scape is changing with the intro-duction and widespread use of new tools to leverage large quantities of structured and unstructured data. SOX Act & Financial Data Security Business Security Breach of security is the worst thing that can happen to a business. (2017). VLDB J. Heatherly, R., Kantarcioglu, M., and Thuraisingham, B. M. (2013). doi: 10.1109/TKDE.2012.61, Kantarcioglu, M., and Nix, R. (2010). Web security and the Internet face a constant threat for both private users and organisation. Why Big Data Security Issues are Surfacing. In addition, in some cases, these techniques require adding significant amount of noise to protect privacy. B. Thesis statement: Big Data will face management, security and privacy challenges. “The limitations of deep learning in adversarial settings,” in IEEE European Symposium on Security and Privacy, EuroS&P 2016 (Saarbrücken), 372–387. One of the ways to securely store big data is using encryption. Natl. Byun, J.-W., and Li, N. (2008). 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). Canim, M., and Kantarcioglu, M. (2007). Introduction The term “big data” is normally used as a marketing concept refers to data sets whose size is further than the potential of normally used enterprise tools to gather, manage and organize, and process within an acceptable elapsed time. Datenvalidierung anhand von Ontologien in Verbindung mit der Semantic Web Rule Language (SWRL) – Münztypen außerhalb des Roman Imperial Coinage (Bachelor Thesis) … We!are!awash!in!a!floodof!data!today. IoT Security Thesis—Exploring and Securing a Future Concept—Download IoT—A Scalable Web Technology for the Internet of Things—Download IoT—A Distributed Security Scheme to Secure Data Communication between Class-0 IoT Devices and the Internet —Download IoT—Sesnsor Communication in Smart Cities and Regions: An Efficient IoT-Based Remote Health Monitoring System— Download Using cryptographic techniques, these algorithms usually provide security/privacy proofs that show nothing other than the final machine learning models are revealed. “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. “Differential privacy,” in 33rd International Colloquium on Automata, Languages and Programming- ICALP 2006 (Venice: Springer-Verlag), 1–12. 2.0 Big Data … Vaidya, J., and Clifton, C. (2005). Internet Organised Crime Threat Assessment (iocta). Individuals may encrypt the drive, which will establish a complicated code on the drive and make it nearly impossible for unauthorized users to access the content. (2017). “Adversarial data mining: Big data meets cyber security,” in Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security (Vienna), 1866–1867. Intel sgx Explained. “Guardmr: fine-grained security policy enforcement for mapreduce systems,” in Proceedings of the 10th ACM Symposium on Information, Computer and Communications Security, ASIA CCS (Singapore), 285–296. An example of this problem is reflected in the recent Cambridge Analytica scandal (Cadwalladr and Graham-Harrison, 2018). To protect individual privacy, only the records belonging to government watch lists may be shared. (2016). Zhou, Y., and Kantarcioglu, M. (2016). Cadwalladr, C., and Graham-Harrison, E. (2018). Although there is an active research directions for addressing adversarial attacks in machine learning (e.g., Zhou et al., 2012; Szegedy et al., 2013; Goodfellow et al., 2014; Papernot et al., 2016; Zhou and Kantarcioglu, 2016), more research that also leverages human capabilities may be needed to counter such attacks. A practical approach to achieve private medical record linkage in light of public resources. Intriguing properties of neural networks. Adversarial ML and ML for Cybersecurity, https://www.theguardian.com/news/2018/mar/17/cambridge-analytica-facebook-influence-us-election, https://www.europol.europa.eu/activities-services/main-reports/internet-organised-crime-threat-assessment-iocta-2017, https://www.gartner.com/doc/1960615/information-security-big-data-analytics, http://www3.weforum.org/docs/Media/KSC_4IR.pdf, Creative Commons Attribution License (CC BY). That is why there are plenty of relevant thesis topics in data mining. In the case of privacy-preserving distributed machine learning techniques, except few exceptions, these techniques are not efficient enough for big data. Big data is nothing new to large organizations, however, it’s also becoming popular among smaller and medium sized firms due to cost reduction and provided ease to manage data. ACM 56, 44–54. Although there have been major progress in this line of research, breakthroughs are still needed to scale encryption techniques for big data workloads in a cost effect manner. 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). Therefore, many issues ranging from security to privacy to incentives for sharing big data need to be considered. Research Topics in Big Data Analytics Research Topics in Big Data Analytics offers you an innovative platform to update your knowledge in research. 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. Information Security is Becoming a Big Data Analytics Problem. 1.)Introduction! Your research can change the worldMore on impact ›, Catalan Institution for Research and Advanced Studies (ICREA), Spain. The EU General Data Protection Regulation (GDPR): A Practical Guide. IEEE Trans. arXiv preprint arXiv:1708.08749, 1–17. Big data security audits help companies gain awareness of their security gaps. First, the attack instances are frequently being modified to avoid detection. x�\[��~篘�\�f��Ed�d�A�"i�XmQ$}��^m�D��ȉ��;CJ�p�),%rx��os��+�VUU1e'׶�{��k�OuT�>{W�W�Ti��{�w�B7��}�ՍV�o�C��I=ݫֽ�/��ԧ�}�*��Sߨ�7�1��O�?��k��F�;��Y}��_l�+�N��l��6�ru��?��e��G�GU��v�A��6e1��A:�4�v�ꆦ�u��3�?��y+R��(�w��r�"�˳�<��b��Ͻg��è�KPǿ��{��%A�1��]�'�z�:Zw��vծ/t�i�/�^Ի�˩{��`-��|��W �c|�[Xg�nvEٕ��O�sAN/�w��۲h��5_W��}e��%�Kwq��эj��:�uWu]C�=�=�� H��8��_1N7u[t}+X0�\0ڄ�FWM1tC��i�ǂ�f��Q��@�j�� Moser, M., Bohme, R., and Breuker, D. (2013). One of the ways to securely store big data is using encryption. Available online at:http://goo.gl/cnwQVv, Papernot, N., McDaniel, P. D., Jha, S., Fredrikson, M., Celik, Z. “Adversarial support vector machine learning,” in Proceedings of the 18th ACM SIGKDD international Conference on Knowledge Discovery and Data Mining, KDD '12 (New York, NY: ACM), 1059–1067. In global market segments, such “Big Data… Over the years, private record linkage research has addressed many issues ranging from handling errors (e.g., Kuzu et al., 2013) to efficient approximate schemes that leverage cryptographic solutions (e.g., Inan et al., 2008). “Data Cleaning Technique for Security Big Data Ecosystem.” Proceedings of the 2nd International Conference on Internet of Things, Big Data and Security… More research is needed to make these recent developments to be deployed in practice by addressing these scalability issues. “Hyperledger fabric: a distributed operating system for permissioned blockchains,” in Proceedings of the Thirteenth EuroSys Conference (New York, NY: ACM), 30. “Vc3: trustworthy data analytics in the cloud using sgx,” in 2015 IEEE Symposium on Security and Privacy (SP) (San Jose, CA: IEEE), 38–54. York, NY ), 442–455 other hand, while linking and sharing across. 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