Bibliography on Secure Big Data    

 

Maintained by

Rongxing LU and Ximeng LIU and Hui ZHU

 

Faculty of Computer Science

University of New Brunswick

ITC Building, 550 Windsor Street Fredericton, NB, Canada E3B 5A3
   Big Data, as it is regarded as a key basis of future competition and innovation, has attracted considerable attentions from both the market and academia in recent years. In general, Big Data is the term for a collection of data sets so large and complex that it becomes difficult to process with traditional database management and processing tools. In specific, Big Data is defined as high volume, high velocity, and high variety information assets that require new forms of processing to enable enhanced decision making, insight discovery and process optimization. In addition to "3V" characteristics, a new V "Veracity" has also been paid great attention in Big Data, as security and privacy issues are magnified by velocity, volume, and variety of big data. Obviously, traditional security mechanisms, which are tailored to securing small-scale static data, are inadequate. Therefore, how to develop new tools to solve the security and privacy challenges become crucial for the success of big data.
   It would be useful to create an up-to-date bibliography on secure big data and make it available on the Internet. So we try our best to maintain a complete list of all secure big data.
   In general, we are including literatures in English, which are published in conference proceedings, journals, and some unpublished technical reports or dissertations. We would appreciate knowing of any errors in this list, as well as any literatures that should be added. Please e-mail to us.
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  Bibliography on Secure Big Data
  • [BJC16] Bello-Orgaz, G., Jung, J. J., & Camacho, D. (2016). Social big data: Recent achievements and new challenges. Information Fusion, 28, 45-59.
  • [H16] Hilbert, M. (2016). Big Data for Development: A Review of Promises and Challenges. Development Policy Review, 34(1), 135-174.
  • [I16] Ilo, A. (2016). “Link”—The smart grid paradigm for a secure decentralized operation architecture. Electric Power Systems Research, 131, 116-125.
  • [JS16] Jeong, Y. S., & Shin, S. S. (2016). An efficient authentication scheme to protect user privacy in seamless big data services. Wireless Personal Communications, 86(1), 7-19.
  • [RB16] Raja, H., & Bajwa, W. U. (2016). Cloud K-SVD: A collaborative dictionary learning algorithm for big, distributed data. Signal Processing, IEEE Transactions on, 64(1), 173-188.
  • [SZZCZ16] Shi, R., Zhang, Y., Zhong, H., Cui, J., & Zhang, S. (2016). Data Integrity Checking Protocol Based on Secure Multiparty Computation. In Wireless Communications, Networking and Applications (pp. 873-882). Springer India.
  • [XWZW16] Xiao, C., Wang, L., Zhu, M., & Wang, W. (2016). A resource-efficient multimedia encryption scheme for embedded video sensing system based on unmanned aircraft. Journal of Network and Computer Applications, 59, 117-125.
  • [XZWZ16] Xu, X., Zhou, J., Wang, X., & Zhang, Y. (2016). Multi-authority proxy re-encryption based on CPABE for cloud storage systems. Journal of Systems Engineering and Electronics, 27(1), 211-223.
  • [ABCY15] Ajiboye, S. O., Birch, P., Chatwin, C., & Young, R. (2015, March). Hierarchical video surveillance architecture: a chassis for video big data analytics and exploration. In IS&T/SPIE Electronic Imaging (pp. 94070K-94070K). International Society for Optics and Photonics.
  • [BDBC15] Baro, E., Degoul, S., Beuscart, R., & Chazard, E. (2015). Toward a Literature-Driven Definition of Big Data in Healthcare. BioMed Research International.
  • [BN15] Babaguchi, N., & Nakashima, Y. (2015). Protection and Utilization of Privacy Information via Sensing. IEICE TRANSACTIONS on Information and Systems, 98(1), 2-9.
  • [C15] Cates, S. (2015). The evolution of security intelligence. Network Security, 2015(3), 8-10.
  • [C15] Chang, V. (2015). Towards a Big Data system disaster recovery in a Private Cloud. Ad Hoc Networks, 35, 65-82.
  • [CRHWL15] Cheng, H., Rong, C., Hwang, K., Wang, W., & Li, Y. (2015). Secure big data storage and sharing scheme for cloud tenants. Communications, China, 12(6), 106-115.
  • [DPVPC15] Douzgou, S., Pollalis, Y. A., Vozikis, A., Patrinos, G. P., & Clayton-Smith, J. (2015). Collaborative Crowdsourcing for the Diagnosis of Rare Genetic Syndromes: The DYSCERNE Experience. Public health genomics, 19(1), 19-24.
  • [DZLC15] Dou, W., Zhang, X., Liu, J., & Chen, J. (2015). Hiresome-ii: towards privacy-aware cross-cloud service composition for big data applications. IEEE Transactions on Parallel & Distributed Systems, 26(2), 455-466.
  • [FEJ15] Fabian, B., Ermakova, T., & Junghanns, P. (2015). Collaborative and secure sharing of healthcare data in multi-clouds. Information Systems, 132–150.
  • [HHLLX15] Hou, S., Huang, X., Liu, J. K., Li, J., & Xu, L. (2015). Universal designated verifier transitive signatures for graph-based big data. Information Sciences.
  • [HRLO15] Hussain, R., Rezaeifar, Z., Lee, Y. H., & Oh, H. (2015). Secure and privacy-aware traffic information as a service in VANET-based clouds. Pervasive and Mobile Computing, 24, 194-209.
  • [HWQLL15] He, S., Wu, Q., Qin, B., Liu, J., & Li, Y. (2015). Efficient group key management for secure big data in predictable large‐scale networks. Concurrency and Computation: Practice and Experience.
  • [KKS15] Kang, J., Kim, K., & Suk, S. (2015). Personal Information Access Control Scheme for Secure NFC Integrated Payment. In Computer Science and its Applications (pp. 263-268). Springer Berlin Heidelberg.
  • [LY15] Li, X., & Yang, T(2015). Signal Processing Oriented Approach for Big Data Privacy. In 16th International Symposium on High Assurance Systems Engineering on (pp. 1149 - 1176)
  • [M15] Montgomery, K. C. (2015). Youth and surveillance in the Facebook era: Policy interventions and social implications. Telecommunications Policy.
  • [MH15] Müller, H., & Hanbury, A. (2015). [Research applications in digital radiology: Big data and co]. Der Radiologe.
  • [MJBM15] Megrhi, S., Jmal, M., Beghdadi, A., & Mseddi, W. (2015, March). Spatio-temporal action localization for human action recognition in large dataset. In IS&T/SPIE Electronic Imaging (pp. 94070O-94070O). International Society for Optics and Photonics.
  • [PRLKZ15] Perera, C. , Ranjan, R. , Lizhe Wang, Khan, S.U. , Zomaya, A.Y.(2015). IT Professional, 17(3), 32 - 39
  • [RCP15] Ratha, N. K., Connell, J. H., & Pankanti, S. (2015). Big Data approach to biometric-based identity analytics. IBM Journal of Research and Development, 59(2/3), 4-1.
  • [SC15] Shin, D. H., & Choi, M. J. (2015). Ecological views of big data: Perspectives and issues. Telematics and Informatics, 32(2), 311-320.
  • [SEHM15] Samanthula, B. K., Elmehdwi, Y., Howser, G., & Madria, S. (2015). A secure data sharing and query processing framework via federation of cloud computing. Information Systems, 48, 196-212.
  • [SM15] Shin, D. H., & Min, J. C. (2015). Ecological views of big data: perspectives and issues. Telematics & Informatics, 32, 311–320.
  • [SSMCVMF15] Suciu, G., Suciu, V., Martian, A., Craciunescu, R., Vulpe, A., Marcu, I., & Fratu, O. (2015). Big Data, Internet of Things and Cloud Convergence–An Architecture for Secure E-Health Applications. Journal of medical systems, 39(11), 1-8.
  • [SZDLKT15] Shuang, W., Zhang, Y., Dai, W., Lauter, K., Kim, M., & Tang, Y., et al. (2015). Healer: homomorphic computation of exact logistic regression for secure rare disease variants analysis in gwas. Bioinformatics.
  • [TZL15] Tan, X., Zhang, X., & Li, J. (2015). Big data quantum private comparison with the intelligent third party. Journal of Ambient Intelligence and Humanized Computing, 6(6), 797-806.
  • [YJR15] Yang, K., Jia, X., & Ren, K. (2015). Secure and Verifiable Policy Update Outsourcing for Big Data Access Control in the Cloud. Parallel and Distributed Systems, IEEE Transactions on, 26(12), 3461-3470.
  • [YLN15] Yang, J. J., Li, J. Q., & Niu, Y. (2015). A hybrid solution for privacy preserving medical data sharing in the cloud environment. Future Generation Computer Systems, 43, 74-86.
  • [YXXH15] Yongan, Z., Xiaofeng, W., Xiaoqian, J., Lucila, O. M., & Haixu, T. (2015). Choosing blindly but wisely: differentially private solicitation of dna datasets for disease marker discovery. Journal of the American Medical Informatics Association, 22(1), 100-108.
  • [ZQD15] Zhang, Y., Qin, J., & Du, L. (2015). A secure biometric authentication based on peks. Concurrency & Computation Practice & Experience, 11.
  • [AS14] Akin, I. H., & Sunar, B. (2014, December). On the Difficulty of Securing Web Applications using CryptDB. In Big Data and Cloud Computing (BdCloud), 2014 IEEE Fourth International Conference on (pp. 745-752). IEEE.
  • [ASB14] Abdellatif, M., Saleh, I., & Blake, M. B. (2014, October). JPrivacy: A java privacy profiling framework for Big Data applications. In Collaborative Computing: Networking, Applications and Worksharing (CollaborateCom), 2014 International Conference on (pp. 501-502). IEEE.
  • [CML14] Chen, M., Mao, S., & Liu, Y. (2014). Big Data: A Survey. Mobile Networks and Applications, 1-39.
  • [CTF14] Chard, K., Tuecke, S., & Foster, I. (2014). Efficient and Secure Transfer, Synchronization, and Sharing of Big Data. Cloud Computing, IEEE, 1(3), 46-55.
  • [CZSH14] Chen, C., Zhu, X., Shen, P., & Hu, J. (2014, April). A hierarchical clustering method for big data oriented ciphertext search. In Computer Communications Workshops (INFOCOM WKSHPS), 2014 IEEE Conference on (pp. 559-564). IEEE.
  • [CZW14] Cai, C., Zhu, Y., & Wang, B. (2014, December). A Novel Mutual Authentication Scheme for Smart Card without Information Leakage. In Computational Science and Engineering (CSE), 2014 IEEE 17th International Conference on (pp. 599-604). IEEE.
  • [ES14] Eckhoff, D., & Sommer, C. (2014). Driving for Big Data? Privacy Concerns in Vehicular Networking. Security & Privacy, IEEE, 12(1), 77-79.
  • [G14] Gathegi, J. N. (2014). Clouding Big Data: Information Privacy Considerations. In Challenges of Information Management Beyond the Cloud on (pp. 64-69). Springer Berlin Heidelberg.
  • [HD14] Huang, X., & Du, X. (2014, April). Achieving big data privacy via hybrid cloud. In Computer Communications Workshops (INFOCOM WKSHPS), 2014 IEEE Conference on (pp. 512-517). IEEE.
  • [HGFK14] Hu, V. C., Grance, T., Ferraiolo, D. F., & Kuhn, D. R. (2014, October). An Access Control scheme for Big Data processing. In Collaborative Computing: Networking, Applications and Worksharing (CollaborateCom), 2014 International Conference on (pp. 1-7). IEEE.
  • [HLZ14] Huang, M. L., Lu, L. F., & Zhang, X. (2014). Using arced axes in parallel coordinates geometry for high dimensional BigData visual analytics in cloud computing. Computing, 1-13. IEEE.
  • [HZZ14] Hsu, C., Zeng, B., & Zhang, M. (2014). A novel group key transfer for big data security. Applied Mathematics & Computation, 249, 436–443.
  • [JLWW14] Jung, T., Li, X., Wan, Z., & Wan, M. (2014). Control cloud data access privilege and anonymity with fully anonymous attribute based encryption. Information Forensics and Security, IEEE Transactions , 10(1), 190-199.
  • [JZWMWO14] Jiang, X., Zhao, Y., Wang, X., Malin, B., Wang, S., & Ohno-Machado, L., et al. (2014). A community assessment of privacy preserving techniques for human genomes. Bmc Medical Informatics & Decision Making, 14(Suppl 1), S1-S1.
  • [KKKG14] Kambatla, K., Kollias, G., Kumar, V., & Grama, A. (2014). Trends in big data analytics. Journal of Parallel & Distributed Computing, 74(7), 2561-2573.
    • [KOMK14] Khan, A. R., Othman, M., Madani, S. A., & Khan, S. U. (2014). A survey of mobile cloud computing application models. Communications Surveys & Tutorials, IEEE, 16(1), 393-413.
    [LAHSZY14] Liu, J. K., Au, M. H., Huang, X., Susilo, W., Zhou, J., & Yu, Y. (2014). New insight to preserve online survey accuracy and privacy in big data era. In Computer Security-ESORICS 2014 on(pp. 182-199). Springer International Publishing.
  • [LBYZC14] Liu, C., Beaugeard, N., Yang, C., Zhang, X., & Chen, J. (2014). HKE‐BC: hierarchical key exchange for secure scheduling and auditing of big data in cloud computing. Concurrency and Computation: Practice and Experience.
  • [LG14] Li, P., & Guo, S. (2014, April). Load balancing for privacy-preserving access to big data in cloud. In Computer Communications Workshops (INFOCOM WKSHPS), 2014 IEEE Conference on (pp. 524-528). IEEE.
  • [LNB14] Lauter, K., Naehrig, M., & Bos, J. W. (2014). Private predictive analysis on encrypted medical data. JOURNAL OF BIOMEDICAL INFORMATICS, 50, 8, 234-243.
  • [LP14] Lindell, Y., & Pinkas, B. (2014). An efficient protocol for secure two-party computation in the presence of malicious adversaries. Journal of Cryptology, 28,2,312-350.
  • [LPZ14] Lu, Y., Phoungphol, P., & Zhang, Y. (2014, September). Privacy Aware Non-linear Support Vector Machine for Multi-source Big Data. In Trust, Security and Privacy in Computing and Communications (TrustCom), 2014 IEEE 13th International Conference on (pp. 783-789). IEEE.
  • [LUB14] Liu, W., Uluagac, A. S., & Beyah, R. (2014, April). MACA: A privacy-preserving multi-factor cloud authentication system utilizing big data. In Computer Communications Workshops (INFOCOM WKSHPS), 2014 IEEE Conference on (pp. 518-523). IEEE.
  • [LZLLS14] Lu, R., Zhu, H., Liu, X., Liu, J. K., & Shao, J. (2014). Toward efficient and privacy-preserving computing in big data era. Network, IEEE, 28(4), 46-50.
  • [LYZC14] Liu, C., Yang, C., Zhang, X., & Chen, J. (2014). External integrity verification for outsourced big data in cloud and iot: a big picture. Future Generation Computer Systems, 49.
  • [PC14] Payton, T. M., & Claypoole, T. (2014). Privacy in the Age of Big Data: Recognizing Threats, Defending Your Rights, and Protecting Your Family. Rowman & Littlefield.
  • [PHD14] Paul, R., Hamilton, M., & D'Souza, D. (2014, December). A Cloud Model for Distributed Transport System Integration. In Big Data and Cloud Computing (BdCloud), 2014 IEEE Fourth International Conference on (pp. 77-84). IEEE.
  • [PPD14] Potnis, A. A., Pandit, H. V., & Deshpande, S. S. (2014, December). Vehicular Travel Initiated Sustainable USB Mobile Charging and Travel Analytics System. In Big Data and Cloud Computing (BdCloud), 2014 IEEE Fourth International Conference on (pp. 620-624). IEEE.
  • [PS14] Patil, H. K., & Seshadri, R. (2014, June). Big data security and privacy issues in healthcare. In Big Data (BigData Congress), 2014 IEEE International Congress on (pp. 762-765). IEEE.
  • [RAH14] Rahmani, A., Amine, A., & Hamou, R. M. A Multilayer Evolutionary Homomorphic Encryption Approach for Privacy Preserving over Big Data(2014). In Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC), 2014 International Conference on (pp. 19 - 26). IEEE.
  • [SBG14] Sedayao, J., Bhardwaj, R., & Gorade, N. (2014, June). Making Big Data, Privacy, and Anonymization Work Together in the Enterprise: Experiences and Issues. In Big Data (BigData Congress), 2014 IEEE International Congress on (pp. 601-607). IEEE.
  • [SF14] Selimi, M., & Freitag, F. (2014, December). Tahoe-LAFS Distributed Storage Service in Community Network Clouds. In Big Data and Cloud Computing (BdCloud), 2014 IEEE Fourth International Conference on (pp. 17-24). IEEE.
  • [SGDRTW14] Sen, S., Guha, S., Datta, A., Rajamani, S. K., Tsai, J., & Wing, J. M. (2014, May). Bootstrapping privacy compliance in big data systems. In Security and Privacy (SP), 2014 IEEE Symposium on (pp. 327-342). IEEE.
  • [SKHO14] Son, J., Kim, D., Hussain, R., & Oh, H. (2014, April). Conditional proxy re-encryption for secure big data group sharing in cloud environment. In Computer Communications Workshops (INFOCOM WKSHPS), 2014 IEEE Conference on (pp. 541-546). IEEE.
  • [SPR14] Sur, C., Park, Y., & Rhee, K. H. (2014). An efficient and secure navigation protocol based on vehicular cloud. International Journal of Computer Mathematics, 1-20.
  • [WMC14] Wang, S., Mohammed, N., & Chen, R. (2014). Differentially private genome data dissemination through top-down specialization.. Bmc Medical Informatics & Decision Making, 14(Suppl 1), S2-S2.
  • [XB14] Xhafa, F., & Barolli, L. (2014). Semantics, intelligent processing and services for big data. Future Generation Computer Systems.
  • [XJWYR14] Xu, L., Jiang, C., Wang, J. I. A. N., Yuan, J. I. A. N., & Ren, Y. O. N. G(2014). Information Security in Big Data: Privacy and Data Mining. In Access, IEEE, 2, 1149-1176. IEEE
  • [YJR14] Yang, K., Jia, X., & Ren, K. (2014). Secure and verifiable policy update outsourcing for big data access control in the cloud. IEEE Transactions on Parallel & Distributed Systems, 1-1.
  • [ZHWLM14] Zhang, J., Huang, M. L., Wang, W. B., Lu, L. F., & Meng, Z. P. (2014, December). Big Data Density Analytics Using Parallel Coordinate Visualization. In Computational Science and Engineering (CSE), 2014 IEEE 17th International Conference on (pp. 1115-1120). IEEE.
  • [ZLNYDC14] Zhang, X., Liu, C., Nepal, S., Yang, C., Dou, W., & Chen, J. (2014). A hybrid approach for scalable sub-tree anonymization over big data using MapReduce on cloud. Journal of Computer and System Sciences, 80(5), 1008-1020.
  • [B13] Bahrami, M. (2013). Cloud Template, a Big Data Solution. arXiv preprint arXiv:1307.4716.
  • [BHJT13] Bowers, K D., Hart C., Juels A., Triandopoulos, N. (2013) Securing the Data in Big Data Security Analytics. Cryptology ePrint Archive: Report 2013/625.
  • [CLW13] Chen, J., Liang, Q., & Wang, J. (2013). Secure transmission for big data based on nested sampling and coprime sampling with spectrum efficiency. Security & Communication Networks.
  • [CRR13] Chandrasekhar, U., Reddy, A., & Rath, R. (2013, April). A comparative study of enterprise and open source big data analytical tools. In Information & Communication Technologies (ICT), 2013 IEEE Conference on (pp. 372-377). IEEE.
  • [DCW13] Dong, C., Chen, L., Wen, Z. (2013, November). When private set intersection meets big data: An efficient and scalable protocol. In 20th ACM Conference on Computer and Communications Security. (In Press).
  • [DJLC13] Dong, X., Jiadi, Y., Luo, Y., & Chen, Y. (2013). P2E: Privacy-preserving and effective cloud data sharing service. Global Communications Conference (GLOBECOM), 2013 IEEE (pp.689 - 694). IEEE..
  • [DZLC13] Dou, W., Zhang, X., Liu, J., & Chen, J. (2013). HireSome-II: Towards privacy-aware cross-cloud service composition for big data applications. In Parallel and Distributed Systems, IEEE Transactions, 26(2) , IEEE, 455 - 466.
  • [GLN13] Graepel, T., Lauter, K., & Naehrig, M. (2013). ML confidential: Machine learning on encrypted data. In Information Security and Cryptology–ICISC 2012 (pp. 1-21). Springer Berlin Heidelberg.
  • [H13] Hayashi, K. (2013, September). Social Issues of Big Data and Cloud: Privacy, Confidentiality, and Public Utility. In Availability, Reliability and Security (ARES), 2013 Eighth International Conference on (pp. 506-511). IEEE.
  • [HHBBD13] Hasan, O., Habegger, B., Brunie, L., Bennani, N., Damiani, E. (2013, June). A Discussion of Privacy Challenges in User Profiling with Big Data Techniques: The EEXCESS Use Case. In Big Data (BigData Congress), 2013 IEEE International Congress on (pp. 25-30). IEEE.
  • [HLYW13] Han, X., Li, J., Yang, D., Wang, J. (2013). Efficient Skyline Computation on Big Data. IEEE Transactions on Knowledge and Data Engineering, 25(11), 2521 - 2535.
  • [J13a] Jensen, Meiko. "Challenges of Privacy Protection in Big Data Analytics." Big Data (BigData Congress), 2013 IEEE International Congress on. IEEE, 2013.
  • [J13b] Jerome, J. W. (2013). Buying and Selling Privacy: Big Data's Different Burdens and Benefits. Stanford Law Review Online, 66, 47.[Online]
  • [JBA13] Jutla, D. N., Bodorik, P., & Ali, S. (2013, June). Engineering Privacy for Big Data Apps with the Unified Modeling Language. In Big Data (BigData Congress), 2013 IEEE International Congress on (pp. 38-45). IEEE.
  • [LPMRS13] Lorch, J. R., Parno, B., Mickens, J. W., Raykova, M., & Schiffman, J. (2013, February). Shroud: Ensuring private access to large-scale data in the data center. In FAST (Vol. 2013, pp. 199-213).
  • [LLS13] Lu, R., Lin, X., & Shen, X. (2013). Spoc: a secure and privacy-preserving opportunistic computing framework for mobile-healthcare emergency. Parallel and Distributed Systems, IEEE Transactions on, 24, 3, 614 - 624.
  • [M13] Malkin, T. (2013). Secure computation for big data. In Theory of Cryptography on (pp. 355-355). Springer Berlin Heidelberg.
  • [MM13] Michael, K., & Miller, K. W. (2013). Big Data: New Opportunities and New Challenges. Editorial: IEEE Computer, 46(6), 22-24.
  • [NaM13] Nassar, M., al Bouna, B., & Malluhi, Q. (2013, June). Secure Outsourcing of Network Flow Data Analysis. In Big Data (BigData Congress), 2013 IEEE International Congress on (pp. 431-432). IEEE.
  • [O13] Oltsik, J. (2013, Jan.). White paper: The Big Data Security Analytics Era Is Here. Enterprise Strategy Group. [Online].
  • [PT13] Polonetsky, J., Tene, O. (2013, Sep.). Privacy and Big Data Making Ends Meet, Stanford Law Review. [Online].
  • [SM13] Sylla, Y., & Morizet-Mahoudeaux, P. (2013, June). Fraud Detection on Large Scale Social Networks. In Big Data (BigData Congress), 2013 IEEE International Congress on (pp. 413-414). IEEE.
  • [T13] Andy Thurai, A. (2013,Sep.). Big Data: Big Security Risk? Enterprise Executive. [Online].
  • [TBSD13] Tan, W., Blake, M. B., Saleh, I., & Dustdar, S. (2013). Social-Network-Sourced Big Data Analytics. Internet Computing, IEEE, 17(5), 62-69.
  • [TP13] Tene, O., Polonetsky, J. (2013). Big Data for All: Privacy and User Control in the Age of Analytics, Nw. J. Tech. & Intell. Prop. 11(5).
  • [USFFPM13] Urbauer, P., Sauermann, S., Frohner, M., Forjan, M., Pohn, B., & Mense, A. (2013). Applicability of IHE/Continua components for PHR systems: Learning from experiences. Computers in biology and medicine.
  • [VWC13] Vidyalakshmi, B. S., Wong, R. K., & Chi, C. H. (2013, June). Decentralized Trust Driven Access Control for Mobile Content Sharing. In Big Data (BigData Congress), 2013 IEEE International Congress on (pp. 239-246). IEEE.
  • [WM13] Wong, K. S., & Kim, M. H. (2013). Secure Re-publication of Dynamic Big Data. In Cyberspace Safety and Security (pp. 468-477). Springer International Publishing.
  • [YS13] Yin, X., & Sun, Y. (2013). Secure and efficient integration of big data for multi‐cells based on micro images. Security and Communication Networks.
  • [ZLNYDC13] Zhang, X., Liu, C., Nepal, S., Yang, C., Dou, W., & Chen, J. (2013). SaC‐FRAPP: a scalable and cost‐effective framework for privacy preservation over big data on cloud. Concurrency and Computation: Practice and Experience, 25(18), 2561-2576.
  • [ZLNYDC13] Zhang, X., Liu, C., Nepal, S., Yang, C., Dou, W., & Chen, J. (2013, July). Combining Top-Down and Bottom-Up: Scalable Sub-tree Anonymization over Big Data Using MapReduce on Cloud. In Trust, Security and Privacy in Computing and Communications (TrustCom), 2013 12th IEEE International Conference on (pp. 501-508). IEEE.
  • [ZYNLDC13] Zhang, X., Yang, C., Nepal, S., Liu, C., Dou, W., & Chen, J. (2013, September). A MapReduce Based Approach of Scalable Multidimensional Anonymization for Big Data Privacy Preservation on Cloud. In Cloud and Green Computing (CGC), 2013 Third International Conference on (pp. 105-112). IEEE.
  • [BK12] Beck, M., & Kerschbaum, F. (2012). Approximate Two-Party Privacy-Preserving String Matching with Linear Complexity. ArXiv preprint arXiv:1209.5208 .
  • [CJ12] Cavoukian, A., Jonas J. (2012, June). Privacy by Design in the Age of Big Data. Privacy by Design(PbD), [Online].
  • [CSA12] Cloud Security Alliance (CSA). (2012, Nov). Top Ten Big Data Security and Privacy Challenges. Online.
  • [DZGW12] Demchenko, Y., Zhao, Z., Grosso, P., Wibisono, A., & de Laat, C. (2012, December). Addressing Big Data challenges for Scientific Data Infrastructure. In Cloud Computing Technology and Science (CloudCom), 2012 IEEE 4th International Conference on (pp. 614-617). IEEE.
  • [HMCK12] Hore, B., Mehrotra, S., Canim, M., & Kantarcioglu, M. (2012). Secure multidimensional range queries over outsourced data. Vldb Journal International Journal on Very Large Data Bases, 21(3), 333-358.
  • [HP12] Hewlett-Packard. (2012, Dec.). Business white paper: Big security for big data. Hewlett-Packard Development Company, L.P. [Online].
  • [L12] Lee, N. (2013). Consumer Privacy in the Age of Big Data. In Facebook Nation (pp. 61-66). Springer New York.
  • [LJ12] Labrinidis, A., & Jagadish, H. V. (2012). Challenges and opportunities with big data. Proceedings of the VLDB Endowment, 5(12), 2032-2033.
  • [LP12] Lee, J. W., & Park, N. (2012). Encryption Scheme Supporting Range Queries on Encrypted Privacy Databases in Big Data Service Era. InComputer Science and its Applications (pp. 739-746). Springer Netherlands.
  • [MR12] Machanavajjhala, A., & Reiter, J. P. (2012). Big privacy: protecting confidentiality in big data. XRDS: Crossroads, The ACM Magazine for Students, 19(1), 20-23.
  • [S12a] Schadt, E. E. (2012). The changing privacy landscape in the era of big data. Molecular Systems Biology, 8(1).
  • [S12b] Securosis, L.L.C. (2012, Oct.). Securing Big Data: Security Recommendations for Hadoop and NoSQL Environments. Securosis, L.L.C.
  • [SSHV12] Smith, M., Szongott, C., Henne, B., & von Voigt, G. (2012, June). Big data privacy issues in public social media. In Digital Ecosystems Technologies (DEST), 2012 6th IEEE International Conference on (pp. 1-6). IEEE
  • [C11a] Chuck Hollis, When Big Data Met Security: Is the New Era Beginning? [Online]
  • [C11b] Craig, T., & Ludloff, M. E. (2011). Privacy and big data. O'Reilly Media, Inc.. [Book]

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