-بهبود حفظ حریم خصوصی داده‌گان در اینترنت اشیا با در نظر گرفتن محدودیت اینترنت به کمک سیستم ایمنی مصنوعی

نویسندگان

1 پردیس دانشگاهی احرار رشت، گروه کامپیوتر و فناوری اطلاعات، رشت ، گیلان

2 استادیار دانشکده کامپیوتر، دانشگاه آزاد اسلامی واحد تهران مرکز، تهران، ایران

3 دانشگاه آزاد اسلامی واحد الکترونیکی

چکیده

امروزه حفاظت از حریم خصوصی داده‌گان به‌ عنوان مهم‌ترین چالش در شبکه‌های اینترنت اشیا تلقی می‏شود. این شبکه‌ها حاوی اطلاعات مهمی می‌باشند که در شبکه میان نودها منتقل می‌گردد. به همین دلیل توجه به مسئله حریم خصوصی داده‌گان در اینترنت اشیاء بسیار حائز اهمیت است. تحقیقات نشان می‌دهد که نبود یک مدل کامل، کارا و استاندارد موجب شده تا بسیاری از نقص‌های امنیتی در این شبکه‌ها پدیدار گردد. در این پژوهش با در نظر گرفتن محدودیت اینترنت، چگونگی تشکیل تابع هدف جهت حریم خصوصی داده‏گان در اینترنت اشیاء مطرح شده و هدف از روش پیشنهادی، یافتن یک مسیر بهینه است که از میزان شایستگی خوبی برخوردار باشد. این روش در نرم‌افزار متلب پیاده‌سازی شده است و نتایج حاصل از آزمایشات نشان می‌دهد که  الگوریتم سیستم ایمنی مصنوعی برای حل مسائل بهینه‌سازی، هرچند جواب قطعی نمی‌دهد اما جوابی نزدیک به بهینه را پیدا می‌کند. همچنین، زمان پاسخگویی الگوریتم سیستم ایمنی مصنوعی در مقایسه با الگوریتم‌های مورد مقایسه کمتر است و با توجه به نمودارهای همگرایی، مشاهده می‌شود که الگوریتم سیستم ایمنی مصنوعی از همگرایی خوبی برخوردار است. 

کلیدواژه‌ها


عنوان مقاله [English]

Improving Data Privacy in the Internet of Things by Using Artificial Immune System, in Regard with the Internet Limitations

نویسندگان [English]

  • Marzieh Faridi Masouleh 1
  • ali harounabadi 2
  • asal sayyad 3
1 Ahrar Institute of Technology and Higher Education, Rasht, Guilan
2 Associate Prof., Faculty of Computer, Islamic Azad University Tehran Branch, Tehran, Iran
3 IAUEC
چکیده [English]

Today, protecting data privacy is considered as the most important challenge in the Internet of Things networks. These networks contain important data which is transmitted among the nodes. For this reason, it is very important to pay attention to the concern of data privacy in the Internet of Things. Studies show that the lack of a complete, efficient and standard model has caused many security flaws in these networks. By using the Internet limitations, this study discusses how to create a target function to protect data privacy in the Internet of Things. The proposed approach aims to find an optimal path with high competence. This method has been implemented in MATLAB software and the results of experiments show that although the Artificial Immune System (AIS) algorithm has no certain solution for optimization problems, it finds a near optimal answer. In addition, the response time of AIS algorithm is lower compared with the examined algorithms. According to the convergence diagrams, the AIS algorithm has good convergence.

کلیدواژه‌ها [English]

  • Artificial Immune System (AIS) algorithm
  • data privacy
  • Internet limitations
  • the Internet of Things
  1. Akhtari, M., (1394). Analyzing Security Concerns in IoT. IOT First International Conference on Accounting and Management in the Third Millennium, Rasht, Pioneer of Modern Research. DOI:10.1109/ICITST.2015.7412116

    Aloudat, A., Katina, M., Chen, X., & Al-Debei, M. M. (2014). Social acceptance of location-based mobile government services for emergency management. Telematics and Informatics, 31, 153e171. DOI:10.1016/j.tele.2013.02.002

    Alvarado, C., Teevan, J., Ackerman, M. S., & Karger, D. (2003). Surviving the information explosion: How people find their electronic information. doi:10.1145/3143699.3143739

    Angst, C. M., & Agarwal, R. (2009). Adoption of electronic health records in the presence of privacy concerns: the elaboration likelihood model and individual persuasion. MIS Quarterly, 33(2), 339e370. DOI:10.2307/20650295

    Atzori, L., Iera, A., & Morabito, G. (2010). The internet of things: A survey. Computer networks, 54(15), 2787-2805. DOI:10.1016/j.comnet.2010.05.010

    Bandyopadhyay, D., & Sen, J. (2011). Internet of things: Applications and challenges in technology and standardization. Wireless personal communications, 58(1), 49-69. DOI:10.1007/s11277-011-0288-5

    Bandyopadhyay, S., & Sen, J. (2011). Internet of Things: applications and challenges in technology and standardization. Journal of Wireless Personal Communications,58(1), 49e69. DOI:10.1007/s11277-011-0288-5

    Bandyopadhyay, S., Balamuralidhar, P., & Pal, A. (2013). Interoperation among IoT standards. Journal of ICT Standardization, 1(2), 253-270. DOI:10.13052/jicts2245-800X.12a9

    Bennati, S., & Pournaras, E. (2018). Privacy-enhancing aggregation of Internet of Things data via sensors grouping. Sustainable cities and society, 39, 387-400. DOI:10.1016/j.scs.2018.02.013

    Castro, L. N., De Castro, L. N., & Timmis, J. (2002). Artificial immune systems: a new computational intelligence approach. Springer Science & Business Media.  DOI:10.1016/S0893-6080(03)00058-3

    Chin-Lung Hsu a, Judy Chuan-Chuan Lin ،(2016) An empirical examination of consumer adoption of Internet of Things services: Network externalities and concern for information privacy perspectives, Computers in Human Behavior 62 516e527. DOI:10.1016/j.chb.2016.04.023

    Dzhokam, A., (1394), New Strategies for the Oil and Gas Industry in the Light of the Internet of Things. International Conference on Research in Science and Technology, Tehran, Karine Institute of Excellence.

    1. Fasolo, M. Rossi, J. Widmer, M. Zorzi, In-network aggregation techniques for wireless sensor networks: a survey, IEEE Wirel. Commun. 14 (2) (2007) 70–87, doi: 10.1109/MWC.2007.358967.

    Fesharaki Esfahani, A., and Khorsand Absolute Isfahani, R., et al. (۱۳۹۴). Investigating the challenges, classifying and comparing operating systems for IoT. First National Conference on New Ideas in Computer Engineering, Shahrekord Islamic Azad University, Shahrekord Branch. DOI:10.4108/eai.13-7-2018.160386

    Javier.L, Ruben RiosaFeng Bao Guilin Wang (2017), Evolving privacy: From sensors to the Internet of Things, Future Generation Computer Systems Volume 75, October 2017, Pages 46-57. DOI:10.1016/j.future.2017.04.045

    Kumar, P. M., & Gandhi, U. D. (2018). A novel three-tier Internet of Things architecture with machine learning algorithm for early detection of heart diseases. Computers & Electrical Engineering, 65, 222-235. DOI:10.1016/j.compeleceng.2017.09.001

    Mashayekhi, M., (1394). The future of IoT applications in intelligent transportation system management. National Conference on the Third Millennium and Humanities, Shiraz, Iran Modern Education Development Center (Methana). DOI:10.1016/j.compeleceng.2017.09.001

    Masouleh, M. F., Kazemi, M. A. A., Alborzi, M., & Eshlaghy, A. T. (2017). Identification of electrocardiogram signals using internet of things based on combinatory classification. International Journal of Modeling, Simulation, and Scientific Computing, 8(03), 1750035. DOI:10.1142/S1793962317500350

    Rebouças Filho, P. P., Gomes, S. L., e Nascimento, N. M. M., Medeiros, C. M., Outay, F., & de Albuquerque, V. H. C. (2019). Energy production predication via Internet of Thing based machine learning system. Future Generation Computer Systems. DOI:10.1016/j.future.2019.01.020

    Safari, M., (1394). Security and privacy concerns in the Internet of Things. The First National Conference on Computer, Islamic Information and Communication Technology of Iran, Qom, Soroush Hekmat Mortazavi Islamic Studies and Research Center DOI:10.1016/j.future.2019.01.020

    Sarkhosh, R., Razvani, M., & Hajjabian, M. (1394). Modern architecture for mobile RFID systems in IoT. International Conference on Applied Research in Information Technology, Computer and Telecommunication, Torbat Heydariyeh, Khorasan Razavi Telecommunication Company. DOI:10.1108/ICT-07-2015-0045

    Turkmani, S., and Shahrokhi, H. (۱۳۹۴). The Challenges and Threats of the Internet of Things. International Conference on Applied Research in Information Technology, Computer and Telecommunication, Torbat Heydariyeh, Khorasan Razavi Telecommunication Company. DOI:10.32604/iasc.2023.026115

    Yaghoubi, M., and Zoghi, M.S. (۱۳۹۴). Emergency-Based Health Care System Model of IoT. International Conference on Research in Science and Technology, Tehran, Karine Institute of Excellence. doi:10.34172/jech.2679

    Zhou, T., & Li, H. (2014). Understanding mobile SNS continuance usage in China from the perspectives of social influence and privacy concern. Computers in Human Behavior. DOI:10.1016/j.chb.2014.05.008

    Ziegeldorf, J. H., Morchon, O. G., & Wehrle, K. (2014). Privacy in the internet of things: threats and challenges. Security and Communication Networks, 7(12), 2728e2742. DOI:10.1002/sec.795

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