امن‌سازی رایانش مرزی از طریق زنجیره بلوکی

نوع مقاله : مقاله ترویجی

نویسندگان

1 دانشجوی دکتری مدیریت فناوری اطلاعات، دانشکدۀ مدیریت و حسابداری، دانشگاه علامه طباطبائی

2 دانشیار دانشکدۀ مدیریت و حسابداری، دانشگاه علامه طباطبائی

چکیده

فناوری های دفتر کل توزیع شده اخیرا توجه بسیاری را به خود جلب کرده است و زنجیرۀ بلوکی، به منزلۀ فناوری زیربنایی رمزارزها، کانون این توجهات است. از زنجیرۀ بلوکی در حوزه های گوناگونی استفاده شده است، ازجمله رایانش ابری، رایانش مهوارهای، رایانش مرزی و اینترنت اشیا (IOT). بااین حال، این فناوری با محدودیت هایی مواجه است و قابلیت پشتیبانی از تراکنش های مکرر را ندارد. از سوی دیگر، پس از رایانش ابری و رایانش مهوارهای، رایانش مرزی نیز به منزلۀ توانمندساز کلیدی برای بسیاری از فناوری های آتی مانند 5G، اینترنت اشیا و ارتباطات وسائط نقلیه با یکدیگر از راه اتصال منابع و همچنین خدمات رایانش ابری به کاربران نهایی ایفای نقش می کند و این منابع و خدمات را تا مرز شبکه گسترش می دهد. اما این فناوری اکنون با چالش هایی در حوزۀ مدیریت نامتمرکز و امنیت روبه روست. ترکیب زنجیرۀ بلوکی و رایانش مرزی در قالب یک سیستم دسترسی و کنترل مطمئن شبکه، ذخیره سازی و محاسبات توزیع شده در مرزهای شبکه و درنتیجه، مقیاس بزرگی از رورهای شبکه، فضای ذخیره سازی داده ها و محاسبۀ اعتبار را در نزدیکی مرز شبکه و از راهی امن فراهم می آورد. با وجود مزایای سیستم های حاصل از یکپارچه سازی زنجیرۀ بلوکی و رایانش مرزی، پیش از پیاده سازی گسترده باید ارتقای مقیاس پذیری، خودسازماندهی، مدیریت منابع، یکپارچگی کارکردها و مسائل امنیتی آن ها مدنظر قرار گیرد. در این مقاله، برخی از پژوهش های صورت گرفته در حوزۀ سیستم یکپارچه متشکل از زنجیرۀ بلوکی و رایانش مرزی بررسی می شود. همچنین، برخی جنبه های حیاتی یکپارچه سازی زنجیرۀ بلوکی و رایانش مرزی شناسایی می شود. درنهایت، تأثیرات این یکپارچه سازی در کسب و کار بررسی خواهد شد.

کلیدواژه‌ها


عنوان مقاله [English]

Securing Edge Computing via Blockchain

نویسندگان [English]

  • Saeed Kazem Pourian 1
  • Mohammad Shahbazi 1
  • Mohammad reza Taghva 2
1 Ph.D. Candidate in IT Management, Faculty of Management & Accounting, Allameh Tabataba’i University
2 Associate Professor, Faculty of Management & Accounting, Allameh Tabataba’i University
چکیده [English]

Distributed ledger technologies have recently attracted much attention, and blockchain, as the underlying technology of cryptocurrencies, is the focal point of this attention. Blockchain has been used in various domains, such as cloud, fog, and edge computing and Internet of Things (IoT). However, it is faced with some limitations and cannot support frequent transactions. Besides, edge computing, after cloud and fog computing, serves as the key enabler for many future technologies like 5G, IoT, and vehicle-to-vehicle communications by connecting cloud computing resources and services to the end-users and extends them at the edge of the network. At the same time, it is currently confronted with challenges in decentralized management and security. Incorporating blockchain and edge computing in one system can provide reliable access and control of the network, storage, and computation distributed at the edges. It provides a large scale of network servers, data storage, and validity computation near the end in a secure manner. Notwithstanding the benefits of integrated blockchain and edge computing systems, their scalability enhancement, self-organization, resource management, functions integration, and security issues need to be addressed before widespread implementation. This paper reviews recent studies about enabling the integrated blockchain and edge computing system. Several critical aspects of the integration of blockchain and edge computing are identified. Finally, some of the effects of this integration on the business are discussed.

کلیدواژه‌ها [English]

  • Edge Computing
  • Blockchain
  • Fog computing
  • Internet of things
  • Data security
  • Ahmed, E., Ahmed, A., Yaqoob, I., Shuja, J., Gani, A., Imran, M., & Shoaib, M. (2017). Bringing computation closer toward the user network: Is edge computing the solution? IEEE Communications Magazine, 55 (11), pp. 138–144.
  • Ahmed, E., Yaqoob, I., Hashem, I. A. T., Khan, I., Ahmed, A. I. A., Imran, M., and Vasilakos, A. V. (2017). The role of big data analytics in internet of things. Computer Networks, 129, pp. 459–471.
  • Al-Qamash, A., Soliman, I., Abulibdeh, R., & Saleh, M. (2018). Cloud, Fog, and edge Computing: A Software Engineering Perspective. International Conference on Computer and Applications (ICCA).
  • Asharaf, S. & Adarsh, S. (2017). Decentralized Computing Using Blockchain Technologies and Smart Contracts: Emerging Research and Opportunities. IGI Global.
  • Back, A., Corallo, M., Dashjr, L., Friedenbach M., & Maxwell, G. (2014). Enabling blockchain innovations with pegged sidechains. Available: https://blockstream.com/sidechains.pdf.
  • Bartoletti, M., & Pompianu, L. (2017). An empirical analysis of smart contracts: platforms, applications, and design patterns. In: Brenner M. et al. (eds) Financial Cryptography and Data Security, Lecture Notes in Computer Science, Vol 10323, Springer, Cham.
  • Bhattacharya, P., Tanwar, S., Shah, R., & Ladha, A. (2019). Mobile edge computing-enabled blockchain framework-A survey. In Proceedings of ICRIC 2019, Springer International Publishing, Cham, 2020, pp. 797–809.
  • Bonomi, F., Milito, R., Zhu, J., & Addepalli, S. (2012). Fog computing and its role in the internet of things. The first edition of the MCC workshop on Mobile cloud computing, ACM, pp. 13–16.
  • Brouwer, W. D., & Borda, M. (2017). NeuRoN: Decentralized artificial intelligence, distributing deep learning to the edge of the network. Available: https://s3-us-west-1.amazonaws.com/ai.doc.static/pdf/whitepaper.pdf.
  • Buterin, V. (2014). A next generation smart contract and decentralized application platform. Available: https://github.com/ethereum/wiki/wiki/White-Paper.
  • Cachin, C. (2016). Architecture of the hyperledger blockchain fabric. Available: pdfs.semanticscholar.org.
  • Chen, W., Xu, Z., Shi, S., Zhao, Y., & Zhao, J. (2018). A Survey of Blockchain Applications in Different Domains. International Conference on Blockchain technology and Applications (ICBTA) 2018, December 10–12, Xi’an, China.
  • (2015). Cisco fog computing solutions: Unleash the power of the internet of things. Available at: https://www.cisco.com/c/dam/en_us/solutions/trends/iot/docs/computing-solutions.pdf (Accessed on 23 July 2018).
  • Conti, M., Kumar, S., Lal, C., & Ruj, S. (2018). A survey on security and privacy issues of bitcoin. IEEE Communications Surveys & Tutorials, pp. 1–39, May 2018.
  • Correia, M., Veronese, G. S., Neves, N. F., & Verissimo, P. (2011). Byzantine consensus in asynchronous message-passing systems: a survey. International Journal of Critical Computer-Based Systems, vol. 2, no. 2, pp. 141–161.
  • Croman, K., Decker, C., Eyal, I., Gencer, A. E., & Juels E. A. A., (2016). On scaling decentralized blockchains. ICFCDS’16, Christ Church, Barbados, pp. 106–125.
  • Dai, H., Zheng, Z., & Zhang, Y. (2019). Blockchain for Internet of Things: A Survey. IEEE Internet of Things Journal, no. 6, pp. 8076–8094.
  • Dimbean-Creta, O. (2017). Fintech - already new fashion in finance, but what about the future? Access Success, 18, pp. 25–29.
  • Dinh, T. T. A., Wang, J., Chen, G., Liu, R., Ooi, B. C., & Tan, K.-L. (2017). BLOCKBENCH: a framework for analyzing private blockchains. In Proc. of the ACM International Conf. on Management of Data, pp. 1085–1100.
  • Dorri, A., Kanhere, S. S., Jurdak, R. & Gauravaram, P. (2017). Blockchain for IoT security and privacy: The case study of a smart home. In Proc. IEEE PerCom Workshops’17, pp. 13–17, Kona, USA.
  • Dubovitskaya, A., Xu, Z., Ryu, S., Schumacher, M., & Wang, F. (2017). How blockchain could empower ehealth: an application for radiation oncology: (Extended abstract). Lecture Notes in Computer Science (including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10494, pp. 3–6.
  • Dütsch, G., & Steinecke, N. (2017). Use cases for blockchain technology in energy and commodity trading. Snapshot of current developments of blockchain in the energy and commodity sector, pwc.
  • Eyal, I., Gencer, A. E., Sirer, E. G., & Renesse, R. V. (2016). Bitcoin-NG: A scalable blockchain protocol. in Proc. Usenix Conference on NSDI’16, Santa Clara, CA, Mar. 2016, pp. 45–59.
  • Ferdowsi, A., Challita, U., & Saad, W. (2019). Deep learning for reliable mobile edge analytics in intelligent transportation systems: An overview. IEEE Vehicular Technology Magazine, 14 (1), pp. 62–70.
  • Fernandez-Carames, T. M. & Fraga-Lamas, P. (2018). A review on the use of blockchain for the internet of things. IEEE Access.
  • Florian, T., & Bjorn, S. (2016). Bitcoin and beyond: a technical survey on decentralized digital currencies. IEEE Communications Surveys & Tutorials, vol. 18, no. 3, pp. 2084–2123.
  • Fuentes, D., Laza, R., & Pereira, A. (2013). Intelligent devices in rural wireless networks. Advanced Distributed Computing Artificial Intelligence Journal, 2 (4), pp. 23–30.
  • Gazafroudi, A. S., Rodríguez, J. M. C., Keane, A. & Soroudi, A. (2019). Decentralised flexibility management for EVs. IET Renewable Power Generation, 13 (6):952.
  • Geranio, M. (2017). Fintech in the exchange industry: potential for disruption? Masaryk Univ. J. Law Technol., 11 (2), pp. 245–266.
  • Gubbi, J., Buyya, R., Marusic, S., & Palaniswami, M. (2013). Internet of things (iot): A vision, architectural elements, and future directions. Future Generation Computer Systems, 29 (7), pp. 1645–1660.
  • Guo, Y., & Liang, C. (2016). Blockchain application and outlook in the banking industry. Financial Innovation, 2 (1), 24.
  • Ha, K., Chen, Z., Hu, W., Richter, W., Pillai, P., & Satyanarayanan, M. (2014). Towards wearable cognitive assistance. In Proc. 12th Annual. International Conference Mobile System Application Services, Bretton Woods, NH, USA, pp. 68-81.
  • Hadžic, I., Abe, Y., & Woithe, H. (2017). Edge computing in the ePC. Proceedings of the Second ACM/IEEE Symposium on edge computing - SEC '17.
  • Hammerschmidt, C. (2018). Consensus in Blockchain Systems. Available on: https://medium.com/@chrshmmmr/consensus-in-blockchain-systems-in-short-691fc7d1fefe (Accessed on 5th of February, 2018).
  • Han, B., Wong, S., Mannweiler, C., Crippa, M. R. & Schotten, H. D. (2019). Context-awareness enhances 5g multi-access edge computing reliability. In press, IEEE Access.
  • Huckle, S., Bhattacharya, R., White, M., & Beloff, N. (2016). Internet of things, blockchain and shared economy applications. Procedia Computer Science, 98, pp. 461–466.
  • (2018). Huawei’s Blockchain Whitepaper. https://static.huaweicloud.com/upload/files/pdf/20180411/ 20180411144924_27164.pdf (Accessed on 28 December 2019).
  • (2015). Empowering the edge: Practical insights on a decentralized Internet of Things. Available: https://www01.ibm.com/common/ssi/cgi-bin/ssialias?htmlfid=GBE03662USEN.
  • Jayasinghe, U., Lee, G. M., MacDermott, Á., & Rhee, W. S. (2019). TrustChain: A Privacy Preserving Blockchain with Edge. Wireless Communications and Mobile Computing.Lemieux, V. L., (2016). Trusting records: is Blockchain technology the answer? Audit. Account. Journal. 2 (2), pp. 72–92.
  • Jiao, Y., Wang, P., Niyato, D., & Xiong, Z. (2017). Social welfare maximization auction in edge computing resource allocation for mobile blockchain. Available on: https://arxiv.org/abs/1711.02844.
  • Jo˚A¡ilo, S., & DA¡n, G. (2019). Selfish decentralized computation offloading for mobile cloud computing in dense wireless networks. IEEE Transactions on Mobile computing, 18 (1), pp. 207–220.
  • Khan, W. Z., Ahmed, E., Hakak, S., Yaqoob, I., & Ahmed, A. (2019). Edge Computing: A Survey. Future Generation Computer Systems, Volume 97, pp. 219-235.
  • Khelifi, H., Luo, S., Nour, B., Sellami, A., Moungla, H., Ahmed, S. H., & Guizani, M. (2019). Bringing deep learning at the edge of information-centric internet of things. IEEE Communications Letters, 23 (1), pp. 52–55.
  • King, S., & Nadal, S. (2012). Ppcoin: peer-to-peer crypto-currency with proof-of-stake. Available: http://peercoin:net/assets/paper/peercoin-paper.pdf.
  • Lei, A., Cruickshank, H., Cao, Y., Asuquo, P., Ogah, C. P. A., & Sun, Z. (2017). Blockchain-based dynamic key management for heterogeneous intelligent transportation systems. IEEE Internet of Things Journal, vol. 4, no. 6, pp. 1832 – 1843.
  • Li, C., & Zhang, L. (2017). A blockchain based new secure multi-layer network model for Internet of Things. In Proc. IEEE ICIOT’17, pp. 33–41, Honolulu, USA.
  • Li, Z., Kang, J., Yu, R., Ye, D., Deng, Q., & Zhang, Y. (2017). Consortium blockchain for secure energy trading in industrial internet of things. IEEE Trans. Ind. Informatics, 1.
  • Liu, B., Yu, X., Chen, S., Xu, X., & Zhu, L. (2017). Blockchain based data integrity service framework for IoT data. IEEE ICWS’17, Honolulu, USA.
  • Luong, N. C., Xiong, Z., Wang, P., & Niyato, D. (2017). Optimal auction for edge computing resource management in mobile blockchain networks: A deep learning approach. Available on: https://arxiv.org/abs/1711.02844.
  • Merz, M. (2016). Potential of the blockchain technology in energy trading. Burgwinkel, Daniel, Blockchain technology Introduction for Business and IT Managers, de Gruyter.
  • Nakamoto, S. (2008). Bitcoin: a peer-to-peer electronic cash system. Available: https://bitcoin.org.
  • Ning, Z., Kong, X., Xia, F., Hou, W., & Wang, X. (2019). Green and sustainable cloud of things: Enabling collaborative edge computing. IEEE Communications Magazine, 57 (1), pp. 72–78.
  • Novo, O. (2018). Blockchain meets IoT: An architecture for scalable access management in IoT. IEEE Internet of Things Journal, no. 5, pp. 1184–1195.
  • Pahl, C., EL Ioini, N., & Helmer S. (2018). A Decision Framework for Blockchain Platforms for IoT and Edge Computing. In Proceedings of the 3rd International Conference on Internet of Things, Big Data and Security, Volume 1: IoTBDS, pp. 105-113.
  • Panikkar, S., Nair, S., Brody, P., & Pureswaran, V. (2015). ADEPT: An IoT practitioner perspective. DRAFT COPY FOR ADVANCE REVIEW, IBM.
  • Patel, M., Hu, Y., & Hédé, P. (2010). Mobile edge computing. Available at: https://portal.etsi.org/Portals/0/TBpages/MEC/Docs/Mobile-edge_Computing_-_Introductory_Technical_ White_Paper_V1%2018-09-14.pdf (Accessed on 23 July 2018).
  • Poon, J., & Buterin, V. (2017). Plasma: Scalable autonomous smart contracts. Available: https://plasma.io/plasma.pdf.
  • Poon, J., & Dryja, T. (2016). The bitcoin lightning network: Scalable off-chain instant payments. Available: https://lightning.network/lightning-network-paper.pdf.
  • Prazeres C., & Serrano, M. (2016). SOFT-IoT: Self-organizing fog of things. In Proc. WAINA’ 16, Crans-Montana, Switzerland, May. 2016, pp. 803–808.
  • Preden, J. S., Tammemae, K., Jantsch, A., Leier, M., Riid, A., & Calis, E. (2015). The benefits of self-awareness and attention in fog and mist computing. Computer, vol. 48, no. 7, pp. 37–45.
  • Ren, J., He, Y., Huang, G., Yu, G., Cai, Y., & Zhang, Z. (2019). An edge-computing based architecture for mobile augmented reality. In press, IEEE Network, pp. 12–19.
  • Romano, D., & Schmid, G. (2017). Beyond Bitcoin: A Critical Look at blockchain-Based Systems. Cryptography, 1 (2), 15.
  • Sahni, Y., Cao, J., & Yang, L. (2019). Data-aware task allocation for achieving low latency in collaborative edge computing. In press, IEEE Internet of Things Journal.
  • Samaniego, M., & Deters, R. (2017). Virtual resources & blockchain for configuration management in IoT. Journal of Ubiquitous Systems & Pervasive Networks, vol. 9, no. 2, pp. 1–13.
  • Samaniego, M., & Deters, R. (2016). Hosting virtual IoT resources on edgehosts with blockchain. In Proc. IEEE CIT’16, Nadi, Fiji, pp. 116–119.
  • Satyanarayanan, M. (2017). The emergence of edge computing. Computer, vol. 50, no. 1, pp. 30–39.
  • Satyanarayanan, M. (2019). How we created edge computing. Nature Electronics, 2 (1), 42.
  • Satyanarayanan, M., Bahl, P., Caceres R., & Davies, N. (2009). The case for VM-based cloudlets in mobile computing. IEEE Pervasive computing, 8 (4), pp. 14–23. Doi: 10.1109/mprv.2009.82.
  • Seijas, P. L., Thompson, S., & McAdams, D. (2016). Scripting smart contracts for distributed ledger technology. Available: http://eprint.iacr.org/2016/1156.
  • Sharma, P. K., Chen, M.-Y., & Park, J. H. (2017). A software defined fog node based distributed blockchain cloud architecture for IoT. IEEE Access, vol. PP, no. 99, pp. 2169–3536.
  • Shi, W., Cao, J., Zhang, Q., Li, Y., & Xu, L. (2016). Edge Computing: Vision and Challenges. IEEE Internet of Things Journal, vol. 3, no. 5, pp. 637-646.
  • Sikorski, J. J., Haughton, J., & Kraft, M. (2017). Blockchain technology in the chemical industry: machine-to-machine electricity market. Applied Energy, 195, pp. 234–246.
  • Sittón, I., & Rodríguez, S. (2017). Pattern Extraction for the Design of Predictive Models in Industry 4.0. International Conference on Practical Applications of Agents and Multi-Agent Systems (PAAMS), pp. 258–261.
  • Stanciu, A. (2017). Blockchain based distributed control system for edge computing. In Proc. IEEE CSCS’17, Bucharest, Romania, pp. 29–31.
  • Stojmenovic, I., & Wen, S. (2014). The fog computing paradigm: Scenarios and security issues. Computer Science and Information Systems (FedCSIS), 2014 Federated Conference on IEEE, pp. 1–8.
  • Teutsch, J., & Reitwießner, C. (2019). A scalable verification solution for blockchains. ArXiv: 1908.04756v1.
  • Tomaso, A., Paolo, T., & Matteo, T. D. (2017). Blockchain technologies: the foreseeable impact on society and industry. Computer, vol. 50, no. 9, pp. 18–28.
  • Tuli, S., Mahmud, R., Tuli, S., & Buyya, R. (2019). FogBus: A Blockchain-based Lightweight Framework for Edge and Fog Computing. The Journal of Systems and Software, 154, pp. 22-36.
  • Vaquero, L. M., & Rodero-Merino, L. (2014). Finding your way in the fog: Towards a comprehensive definition of fog computing. ACM SIGCOMM Computer Communication Review, 44 (5) pp. 27–32.
  • Viriyasitavata, W., & Hoonsopon, D. (2018). Blockchain Characteristics and Consensus in Modern Business Processes. Journal of Industrial Information Integration.
  • Vukolic, M. (2015). The quest for scalable blockchain fabric: Proof-of-work vs. BFT replication. International Workshop on Open Problems in Network Security, Zurich, Switzerland.
  • Wang, P., Yao, C., Zheng, Z., Sun, G., & Song, L. (2019). Joint task assignment, transmission and computing resource allocation in multi-layer mobile edge computing systems. In press, IEEE Internet of Things Journal.
  • Yang, R., Yu, F. R., Si, P., Yang, Z., & Zhang, Y. (2019). Integrated blockchain and edge computing Systems: A Survey, Some Research Issues and Challenges. IEEE Communications Surveys & Tutorials, vol. 21, no. 2, pp. 1508–1532.
  • Yeow, K., Gani, A., Ahmad, R. W., Rodrigues, J. J. P. C., & Ko, K. (2018). Decentralized Consensus for Edge-Centric Internet of Things: A Review, Taxonomy, and Research Issues. In IEEE Access, vol. 6, pp. 1513-1524.
  • Yi, S., Li, C., & Li, Q. (2015). A survey of fog computing: concepts, applications and issues. 2015 workshop on mobile big data, ACM, pp. 37–42.
  • Yousefpour, A., Fung, C., Nguyen, T., Kadiyala, K., Jalali, F., Niakanlahiji, A., Kong, J., & Jue, J. P. (2019). All One Needs to Know about Fog computing and related edge computing Paradigms. Journal of Systems Architecture.
  • Yu, F. R. (2019). A service-oriented blockchain system with virtualization. Transactions on blockchain technology and Applications, vol. 1, no. 1, pp. 1–10.
  • Yu, F. R., Liu, J., He, Y., Si, P., & Zhang, Y. (2018). Virtualization for distributed ledger technology (vdlt). IEEE Access, vol. 6, pp. 25019–25028.
  • Yu, W., Liang, F., He, X., Hatcher, G. W., Lu, C., Lin, J., & Yang, X. (2017). A survey on the edge computing for the Internet of Things. IEEE Access, no. 99, pp. 1–18.
  • Zhang, Y., & Wen, J. (2017). The IoT electric business model: using blockchain technology for the internet of things. Peer-to-Peer Network Applications, 10, pp. 983–994.
  • Zhang, Z., Zhang, W., & Tseng, F. (2019). Satellite mobile edge computing: Improving qos of high-speed satellite-terrestrial networks using edge computing techniques. IEEE Network, 33 (1), pp. 70–76.