Halkla İlişkiler Ajansları için Bulut Tabanlı Güvenli Çok Taraflı Hesaplama ve İşbirliği Servisi - SMPCCaaS

Year 2021, , 783 - 790, 31.12.2021

Şaha Baygül Özpınar , Alper Özpınar

https://doi.org/10.31590/ejosat.1013962

Abstract

Günümüzde veriye erişebilmek ve bu veriyle yapılabileceklerin farkında olmak sektör farketmeksizin bütün kurumlar için büyük önem taşımaktadır. Halkla ilişkiler alanında da veri kavramı merkezi konumdadır. Halkla ilişkiler uzmanları, bir kurum, marka, ürün, kavram veya birey hakkında genel halkın ya da hedef kitlelerin algısını etkilemek için gerçek verileri kullanmaktadır. Uzmanlar farklı kaynaklardan elde edilen verilerle bilgilere ulaşabilmekte ve bunları analiz ederek daha doğru kararlar alabilmektedir. Kaliteli verilerin kullanılması sadece kurumsal imaja değil, uzmanların hizmetine de değer katmaktadır. Bu nedenle halkla ilişkiler ajansları ve uzmanları bu konudaki teknolojileri takip etmek ve hızla benimsemek durumundadır. Veriye ulaşmanın tek yolu birincil ya da ikincil araştırmalar değildir. Bu çalışmada son yıllarda büyük ilgi görmeye başlayan güvenli veri paylaşımı konusunun halkla ilişkiler alanındaki yansımaları ele alınmaktadır. Bilginin değerinin giderek arttığı bir çağda halkla ilişkiler ajanslarının güvenli veri işleyebilmesi için için bulut tabanlı, güvenli ve çok taraflı bir hesaplama ve iş birliği servisinin kullanılabilirliği tartışılmakta ve bir sistem önerisi sunulmaktadır. Bu makale böyle bir sistemin halkla ilişkilerde kullanımını içeren ilk çalışma olarak alana ve alanyazına katkıda bulunmayı hedeflemektedir. Güvenli çok taraflı hesaplama ve gizliliği koruyan hesaplama yaklaşımları halkla ilişkiler faaliyetleri için önemli bir potansiyel sunmaktadır.

Keywords

Halkla İlişkiler, Veri Yönetişimi, Bulut Bilişim, Güvenli Çok Taraflı Hesaplama, Homomorfik Şifreleme, Veri Paylaşımı, Veri Gizliliği

Cloud Based Secure Multi Party Computing and Collaboration Service for Public Relations Agencies - SMPCCaaS

Abstract

Today, access to data and being aware of what can be done with this data is of great importance for all institutions, regardless of the sector. Data is also central in the field of public relations. Public relations professionals use real data to influence the perception of the public or target audiences about an institution, brand, product, concept or individual. Experts can access information with data obtained from different sources and can make more accurate decisions by analyzing them. The use of quality data adds value not only to the corporate image, but also to the service of experts who use it. For this reason, public relations agencies and experts must follow and rapidly adopt the technologies in this field. Primary or secondary research is not the only way to access data. This study deals with the reflections of secure data processing in the field of public relations. In an era where the value of information is increasing, this study discusses the availability of a cloud-based, secure, and multilateral computing and collaboration service, and proposes a system for public relations agencies to share data securely. This article aims to contribute to the field and the literature as the first study involving the use of such a system in public relations. Secure multilateral computing and private computing approaches offer significant potential for public relations activities.

Keywords

Public Relations, Data Governance, Cloud Computing, Secure Multi Party Computation, Homomorphic Encyrption, Data Sharing, Data Collaboration

References

• Abascal, J., Faghihi Sereshgi, M. H., Hazay, C., Ishai, Y., ve Venkitasubramaniam, M. (2020). Is the Classical GMW Paradigm Practical? The Case of Non-Interactive Actively Secure 2PC. Proceedings of the 2020 ACM SIGSAC Conference on Computer and Communications Security, 1591–1605.
• Abraham, R., Schneider, J., ve vom Brocke, J. (2019). Data governance: A conceptual framework, structured review, and research agenda. International Journal of Information Management, 49, 424–438. https://doi.org/10.1016/J.IJINFOMGT.2019.07.008
• Alawaad, H. A. (2021). The role of Artificial Intelligence (AI) in Public Relations and Product Marketing in Modern Organizations. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 12(14), 3180–3187. Alhassan, I., Sammon, D., ve Daly, M. (2016). Data governance activities: an analysis of the literature. Journal of Decision Systems, 25(sup1), 64–75.
• Amazon. (2021). Amazon EC2. In Amazon Web Services, Inc. https://aws.amazon.com/ec2/
• Baars, H., ve Kemper, H.-G. (2008). Management support with structured and unstructured data—an integrated business intelligence framework. Information Systems Management, 25(2), 132–148.
• Barnett, M. L., Jermier, J. M., ve Lafferty, B. A. (2006). Corporate reputation: The definitional landscape. Corporate Reputation Review, 9(1), 26–38.
• Baygül Özpınar, Ş. B. (2021). “Yeni” Teknolojiler ve Kurumsal İletişimin Yeni Araçları. Etkileşim, 7, 150–168. Baygül Özpınar, Ş. B. (2018). Kurumsal itibarın ölçümü: Türkiye’ye yönelik ölçek geliştirme çalışması. Ed. Metin Reyhaoğlu, Araştırmalar Işığıda Yönetimde Güncel Konular, 474-464. Nobel.
• Benaissa, A., Retiat, B., Cebere, B., ve Belfedhal, A. E. (2021). TenSEAL: A Library for Encrypted Tensor Operations Using Homomorphic Encryption. ArXiv Preprint ArXiv:2104.03152.
• Bendlin, R., Damgård, I., Orlandi, C., ve Zakarias, S. (2011). Semi-homomorphic encryption and multiparty computation. Annual International Conference on the Theory and Applications of Cryptographic Techniques, 169–188.
• Biham, E., ve Shamir, A. (1991). Differential cryptanalysis of DES-like cryptosystems. Journal of CRYPTOLOGY, 4(1), 3–72.
• Biswal, S. K. (2020). The Space of Artificial Intelligence in Public Relations: The Way Forward. In Optimization in Machine Learning and Applications (pp. 169–176). Springer.
• Bozduman, H. Ç., ve Afacan, E. (2020). Simulation of a Homomorphic Encryption System. Applied Mathematics and Nonlinear Sciences, 5(1), 479–484. https://doi.org/10.2478/amns.2020.1.00046
• Brown, R. E. (2010). Symmetry and its critics: Antecedents, prospects and implications for symmetry in a postsymmetry era. The SAGE Handbook of Public Relations, 277-92.
• Bulao, J. (2021). How Much Data Is Created Every Day in 2021? In TechJury. https://techjury.net/blog/how-much-data-is-created-every-day/
• Chen, H., Laine, K., ve Player, R. (2017). Simple encrypted arithmetic library-SEAL v2. 1. International Conference on Financial Cryptography and Data Security, 3–18.
• Chen, L., Chen, L., Jordan, S., Liu, Y.-K., Moody, D., Peralta, R., Perlner, R., ve Smith-Tone, D. (2016). Report on post-quantum cryptography (Vol. 12). US Department of Commerce, National Institute of Standards and Technology.
• Cheon, J. H., Kim, A., Kim, M., ve Song, Y. (2017). Homomorphic encryption for arithmetic of approximate numbers. International Conference on the Theory and Application of Cryptology and Information Security, 409–437. Chun, R. (2005). Corporate reputation: Meaning and measurement. International Journal of Management Reviews, 7(2), 91–109.
• Cutlip, Scott (1994). The Unseen Power: A History of Public Relations. Lawrence Erlbaum Associates. Demchenko, Y., De Laat, C., ve Membrey, P. (2014). Defining architecture components of the Big Data Ecosystem. 2014 International Conference on Collaboration Technologies and Systems (CTS), 104–112.
• Dinakaran, S. S. (n.d.). An Overview on Secured Multi-Party Computations (SMC).
• Dolev, D., Dwork, C., Waarts, O., ve Yung, M. (1993). Perfectly secure message transmission. Journal of the ACM (JACM), 40(1), 17–47.
• Fan, J., ve Vercauteren, F. (2012). Somewhat practical fully homomorphic encryption. IACR Cryptol. EPrint Arch., 2012, 144.
• Fox, M. (2021). Zoom overtakes Exxon Mobil in market value amid COVID-19 pandemic. In Business Insider. https://www.businessinsider.com/zoom-exxon-mobil-overtakes-market-value-stock-price-covid19-pandemic-2020-10
• Goldreich, O., Micali, S., ve Wigderson, A. (2019). How to play any mental game, or a completeness theorem for protocols with honest majority. In Providing Sound Foundations for Cryptography: On the Work of Shafi Goldwasser and Silvio Micali (pp. 307–328).
• Goldwasser, S., ve Micali, S. (1984). Probabilistic encryption. Journal of Computer and System Sciences, 28(2), 270–299.
• Google. (2021). Google Colaboratory. https://colab.research.google.com/
• Gotsi, M., ve Wilson, A. M. (2001). Corporate reputation: seeking a definition. Corporate Communications: An International Journal.
• Grunig, J. E., ve Grunig, L. A. (1992). Models of public relations and communication. Excellence in Public Relations and Communication Management, 1992, 285–325.
• Halevi, S., Polyakov, Y., ve Shoup, V. (2019). An improved RNS variant of the BFV homomorphic encryption scheme. Cryptographers’ Track at the RSA Conference, 83–105.
• Harrison, G. (1953). Public Relations. YB, 65.
• Hirsch, D. D. (2013). The glass house effect: Big Data, the new oil, and the power of analogy. Me. L. Rev., 66, 373.
• Huynh, D. (2020). Cryptotree: fast and accurate predictions on encrypted structured data. ArXiv Preprint ArXiv:2006.08299.
• Johnson, M. A. (1997). Public relations and technology: Practitioner perspectives. Journal of Public Relations Research, 9(3), 213–236.
• Jugenheimer, D. W., Kelley, L. D., Hudson, J., ve Bradley, S. (2015). Advertising and public relations research. Routledge.
• Kacen, J. J., Hess, J. D., ve Chiang, W. K. (2013). Bricks or clicks? Consumer attitudes toward traditional stores and online stores. Global Economics and Management Review, 18(1), 12–21.
• Khatri, V., ve Brown, C. V. (2010). Designing data governance. Communications of the ACM, 53(1), 148–152. Kim, Y. (2001). Measuring the economic value of public relations. Journal of Public Relations Research, 13(1), 3–26.
• Kiousis, S., Popescu, C., ve Mitrook, M. (2007). Understanding influence on corporate reputation: An examination of public relations efforts, media coverage, public opinion, and financial performance from an agenda-building and agenda-setting perspective. Journal of Public Relations Research, 19(2), 147–165.
• Ladley, J. (2019). Data governance: How to design, deploy, and sustain an effective data governance program. Academic Press.
• Laudon, K. C., ve Laudon, J. P. (2011). Essentials of management information systems.
• Ljungqvist, A., ve Wilhelm Jr, W. J. (2003). IPO pricing in the dot‐com bubble. The Journal of Finance, 58(2), 723–752.
• Manyika, J., Chui, M., Brown, B., Bughin, J., Dobbs, R., Roxburgh, C., ve Hung Byers, A. (2011). Big data: The next frontier for innovation, competition, and productivity. McKinsey Global Institute.
• Mark Weiner, S. K. (2016). Irreversible: The Public Relations Big Data Revolution. Institute for Public Relations. https://instituteforpr.org/wp-content/uploads/IPR_PR-Big-Data-Revolution_3-29.pdf
• Mert, A. C., Öztürk, E., ve Savaş, E. (2019). Design and implementation of encryption/decryption architectures for bfv homomorphic encryption scheme. IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 28(2), 353–362.
• Newsom, D., Turk, J., ve Kruckeberg, D. (2012). Cengage advantage books: This is PR: The realities of public relations. Cengage Learning.
• Ofek, E., Katona, Z., ve Sarvary, M. (2011). “Bricks and clicks”: The impact of product returns on the strategies of multichannel retailers. Marketing Science, 30(1), 42–60.
• PRSSA. (n.d.). What is public relations: Learn about PR. Erişim 23 Ekim, 2021, https://www.prsa.org/reference/prssa/about-prssa/learn-about-pr.
• Özgen, E., ve Bilbil, E. (2007). Türkiye'de ulusal basın ile ilişkiler kapsamında halkla ilişkiler ve reklamcıların etik sorunları. Marmara İletişim Dergisi, 12(12), 177-185.
• Rosenbaum, S. (2010). Data governance and stewardship: designing data stewardship entities and advancing data access. Health Services Research, 45(5p2), 1442–1455.
• Schoenmakers, B. (2021). MPyC. https://www.win.tue.nl/~berry/mpyc/ Seitel, F. P. (2017). Practice of public relations. Pearson Education.
• Shamir, A., Rivest, R. L., ve Adleman, L. M. (1981). Mental poker. In The mathematical gardner (pp. 37–43). Springer.
• Shannon, C. E. (1949). Communication theory of secrecy systems. The Bell System Technical Journal, 28(4), 656–715.
• Sindermann, C., Lachmann, B., Elhai, J. D., ve Montag, C. (2021). Personality associations with WhatsApp usage and usage of alternative messaging applications to protect one’s own data. In Journal of Individual Differences (p. No Pagination Specified-No Pagination Specified). Hogrefe Publishing. https://doi.org/10.1027/1614-0001/a000343
• Stacks, D. W. (2016). Primer of public relations research. Guilford Publications.
• Turing, A. M. (2004). The essential turing. Oxford University Press.
• Wang, F. (2014). Field Study of Patent Strategies from Patent Map on Big Data: An Empirical Case of Big Data Application Platform in Taiwan.
• Whitten, D., ve Leidner, D. (2006). Bringing IT back: An analysis of the decision to backsource or switch vendors. Decision Sciences, 37(4), 605–621.
• Wiencierz, C., ve Röttger, U. (2019). Big Data in Public Relations: A Conceptual Framework. 12, 1–15.
• Wijoyo, H., Limakrisna, N., ve Suryanti, S. (2021). The effect of renewal privacy policy whatsapp to customer behavior. Insight Management Journal, 1(2), 26–31.
• Wilcox, D. L., Ault, P. H., ve Agee, W. K. (2006). Public relations: Strategies and tactics.
• Wright, D. K., ve Hinson, M. D. (2008). How blogs and social media are changing public relations and the way it is practiced. Public Relations Journal, 2(2), 1–21.
• Yao, A. C.-C. (1982). Protocols for Secure Computations (Extended Abstract) BT - 23rd Annual Symposium on Foundations of Computer Science, Chicago, Illinois, USA, 3-5 November 1982 (pp. 160–164). https://doi.org/10.1109/SFCS.1982.38
• Yao, A. C.-C. (1986). How to Generate and Exchange Secrets (Extended Abstract) BT - 27th Annual Symposium on Foundations of Computer Science, Toronto, Canada, 27-29 October 1986 (pp. 162–167). https://doi.org/10.1109/SFCS.1986.25
• Zhang, Y., Ren, J., Liu, J., Xu, C., Guo, H., ve Liu, Y. (2017). A survey on emerging computing paradigms for big data. Chinese Journal of Electronics, 26(1), 1–12.