Skip to main content

A Comprehensive Review of Distributed Denial of Service (DDoS) Attacks in Fog Computing Environment

  • Chapter
  • First Online:
Book cover Handbook of Computer Networks and Cyber Security

Abstract

Cloud computing performs several functionalities, and one of the most important functionalities is the storage and processing of data or information. With day-by-day enhancement of technology, cloud has been overburdened, and to address this issue, the concept of fog computing has been introduced. Fog computing is an extension of the properties of cloud computing to the network’s edge and additionally overcomes its limitations. Despite the growing fame of fog services, assuring the security and privacy of data is still a big challenge. Distributed denial of service (DDoS) attack is a well-known threat among the security concerns and an important research challenge when talking particularly about security of data in fog computing environment. Therefore, this chapter presents a survey which encompasses the various concepts of fog computing, DDoS attacks and some DDoS mitigation techniques, thus providing a comprehensive review. In addition, it beholds the future work in this domain. This chapter will attract new researchers and also strengthen the concept of fog computing.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 299.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. What is cloud computing? Definition from WhatIs.com. Retrieved February, 2018, from http://searchcloudcomputing.techtarget.com/definition/cloud-computing

  2. Xiao, Z., & Yang, X. (2013). Security and privacy in cloud computing. IEEE Communications Surveys & Tutorials, 15(2), 843–859.

    Article  MathSciNet  Google Scholar 

  3. Davey, R. P., Grossman, D., Rasztovitswiech, M., Payne, D. B., Nesset, D., Kelly, A. E., Rafel, A., Appathurai, S., & Yang, S. H. (2009). Long-reach passive optical networks. Journal of Lightwave Technology, 27(3), 273–291.

    Article  Google Scholar 

  4. Zhang, W., Lin, B., Yin, Q., & Zhao, T. (2017). Infrastructure deployment and optimization of fog network based on microDC and LRPON integration. Peer-to-Peer Networking and Applications, 10(3), 579–591.

    Article  Google Scholar 

  5. Bastug, E., Bennis, M., & Debbah, M. (2014). Living on the edge: The role of proactive caching in 5G wireless network. IEEE Communications Magazine, 52(8), 82–89.

    Article  Google Scholar 

  6. Hassan, M. A., Xiao, M., Wei, Q., & Chen, S. (2015). Help your mobile applications with fog computing. In Proceedings of the IEEE international conference on sensing, communication, and networking – workshop (pp. 1–6). IEEE.

    Google Scholar 

  7. What is fog computing? Why it matters in our big data and IoT world? Retrieved February, 2018, from https://www.forbes.com/sites/bernardmarr/2016/10/14/what-is-fog-computing-and-why-it-matters-in-our-big-data-and-iot-world/2/

  8. Stojmenovic, I., & Wen, S. (2014). The fog computing paradigm: Scenarios and security issues. In Proceedings of the 2014 federated conference on computer science and information systems (Vol. 2, pp. 1–8). Marlton, NJ: ACSIS. https://doi.org/10.15439/2014F503.

    Chapter  Google Scholar 

  9. Just the facts: Insights of fog for 2018. OpenFog Consortium. Retrieved February, 2018, from https://www.openfogconsortium.org/just-the-facts-insights-of-fog-for-2018/

  10. What is fog computing? (Fog networking or fogging). WhatIs.com. Retrieved February, 2018, from http://internetofthingsagenda.techtarget.com/definition/fog-computing-fogging

  11. Hua, P., Dhelima, S., Ninga, H., & Qiu, T. (2017). Survey on fog computing: Architecture, key technologies, applications and open issues. Journal of Network and Computer Applications, 98, 27–42.

    Article  Google Scholar 

  12. Sarkar, S., & Misra, S. (2016). Theoretical modelling of fog computing: A green computing paradigm to support IoT applications. IET Networks, 5(2), 23–29.

    Article  Google Scholar 

  13. More, P. (2015). Review of implementing fog computing. IJRET: International Journal of Research in Engineering and Technology, 04(06), 335–338.

    Article  Google Scholar 

  14. Oueis, J., Strinati, E.C., Sardellitti, S., & Barbarossa, S.. (2015). Small cell clustering for efficient distributed fog computing: A multi-user case, In Proceedings of the IEEE 82nd vehicular technology conference (VTC Fall) (pp. 1–5).

    Google Scholar 

  15. Zeng, D., Gu, L., Guo, S., Cheng, Z., & Yu, S. (2016). Joint optimization of task scheduling and image placement in fog computing supported software-defined embedded system. IEEE Transactions on Computers, 65(12), 3702–3712.

    Article  MathSciNet  MATH  Google Scholar 

  16. Kang, K., Wang, C., & Luo, T. (2016). Fog computing for vehicular ad-hoc networks: Paradigms, scenarios, and issues. The Journal of China Universities of Posts and Telecommunications, 23(2), 56–96.

    Article  Google Scholar 

  17. Aazam, M., & Huh, E. N. (2016). Fog computing: The cloud-IoT/IoE middleware paradigm. IEEE Potentials, 35(3), 40–44.

    Article  Google Scholar 

  18. Bonomi, F., Milito, R., Natarajan, P., & Zhu, J. (2014). Fog computing: A platform for internet of things and analytics. In N. Bessis & C. Dobre (Eds.), Big data and internet of things: A roadmap for smart environments. Studies in computational intelligence (Vol. 546, pp. 169–186). Cham: Springer.

    Google Scholar 

  19. Milito, R., Natarajan, P., & Zhu, J. (2014). Fog computing: A platform for internet of things and analytics, in big data and internet of things: A roadmap for smart environments (pp. 169–186). Cham: Springer.

    Google Scholar 

  20. Hu, P., Ning, H., Qiu, T., Zhang, Y., & Luo, X. (2017). Fog computing-based face identification and resolution scheme in internet of things. IEEE Transactions on Industrial Informatics, 13(4), 1910–1920.

    Article  Google Scholar 

  21. Zhang, Y., Niyato, D., Wang, P., & Dong, I. K. (2016). Optimal energy management policy of mobile energy gateway. IEEE Transactions on Vehicular Technology, 65(5), 3685–3699.

    Article  Google Scholar 

  22. Jalali, F., Hinton, K., Ayre, R., & Alpcan, T. (2016). Fog computing may help to save energy in cloud computing. IEEE Journal on Selected Areas in Communications, 34(5), 1728–1739.

    Article  Google Scholar 

  23. Natal, A. R., Jakab, L., Portols, M., Ermagan, V., Natarajan, P., Maino, F., Meyer, D., & Aparicio, A. C. (2013). LISP-MN: Mobile networking through LISP. Wireless Personal Communications, 70(1), 253–266.

    Article  Google Scholar 

  24. Natraj, A. (2016). Fog computing focusing on users at the edge of internet of things. International Journal of Engineering Research, 5(5), 1004–1008.

    Google Scholar 

  25. Varshney, P., & Simmhan, Y. (2017). Demystifying fog computing: Characterizing architectures, applications and abstractions. In 2017 IEEE 1st International Conference on Fog and Edge Computing (ICFEC). IEEE.

    Google Scholar 

  26. Luan, T. H., Gao, L., Li, Z., Xiang, Y., Wei, G., & Sun, L. (2016). Fog computing: focusing on mobile users at the edge. arXiv:1502.01815v3.

    Google Scholar 

  27. Hossain, M. S., & Atiquzzaman, M. (2013). Cost analysis of mobility protocols. Telecommunication Systems, 52(4), 2271–2285.

    Article  Google Scholar 

  28. Gao, W. (2014). Opportunistic peer-to-peer mobile cloud computing at the tactical edge. In Proceedings of the IEEE military communications conference (pp. 1614–1620). Piscataway: IEEE.

    Google Scholar 

  29. Chen, X., Jiao, L., Li, W., & Fu, X. (2015). Efficient multi-user computation offloading for mobile-edge cloud computing. IEEE/ACM Transactions on Networking, 24(4), 974–983.

    Google Scholar 

  30. Wei, C., Fadlullah, Z., Kato, N., & Stojmenovic, I. (2014). On optimally reducing power loss in micro-grids with power storage devices. IEEE Journal of Selected Areas in Communications, 32(7), 1361–1370.

    Article  Google Scholar 

  31. Bonomi, F., Milito, R., Zhu, J., & Addepalli, S. (2012). Fog computing and its role in the internet of things. In Proceedings of the first edition of the MCC workshop on mobile cloud computing, ser. MCC’12 (pp. 13–16). New York: ACM.

    Chapter  Google Scholar 

  32. Research report on %year market sizing of Fog by OpenFog Consortium. Retrieved February, 2018, from https://www.openfogconsortium.org/wp-content/uploads/451-Research-report-on-5-year-Market-Sizing-of-Fog-Oct-2017.pdf

  33. Atzori, L., Iera, A., & Morabito, G. (2010). The internet of things: A survey. Computer Networks, 54(15), 2787–2805.

    Article  MATH  Google Scholar 

  34. Ning, H., Fu, Y., Hu, S., & Liu, H. (2015). Tree-code modeling and addressing for non-id physical objects in the internet of things. Telecommunication Systems, 58(3), 195–204.

    Article  Google Scholar 

  35. Liu, K., Ng, J., Lee, V., Son, S., & Stojmenovic, I. (2016). Cooperative data dissemination in hybrid vehicular networks: VANET as a software defined network. IEEE/ACM Transactions on Networking, 24(3), 1759–1773.

    Article  Google Scholar 

  36. Kirkpatrick, K. (2013). Software-defined networking. Communications of the ACM, 56(9), 16–19.

    Article  Google Scholar 

  37. Kim, H., & Feamster, N. (2013). Improving network management with software defined networking. IEEE Communications Magazine, 51(2), 114–119.

    Article  Google Scholar 

  38. Kreutz, D., Ramos, F. M. V., Esteves Verissimo, P., Esteve Rothenberg, C., Azodolmolky, S., & Uhlig, S. (2014). Software-defined networking: A comprehensive survey. Proceedings of the IEEE, 103(1), 10–13.

    Google Scholar 

  39. Nunes, A., Mendonca, M., Nguyen, X. N., & Obraczka, K. (2014). A survey of software defined networking: Past, present, and future of programmable networks. IEEE Communications Surveys and Tutorials, 16(3), 1617–1634.

    Article  Google Scholar 

  40. Bhushan, K., & Gupta, B. B. (2018). Distributed denial of service (DDoS) attack mitigation in software defined network (SDN)-based cloud computing environment. Journal of Ambient Intelligence and Humanized Computing, 10(5), 1985–1997.

    Article  Google Scholar 

  41. Roman, R., Lopez, J., & Mambo, M. (2018). Mobile edge computing, Fog et al.: A survey and analysis of security threats and challenges. Future Generation Computer Systems, 78, 680–698.

    Article  Google Scholar 

  42. Bhushan, K., & Gupta, B. B. (2017). Security challenges in cloud computing: State-of-art. International Journal of Big Data Intelligence, 4(2), 81–107.

    Article  Google Scholar 

  43. Barbosa, P., Brito, A., Almeida, H., & Claub, S. (2014). Lightweight privacy for smart metering data by adding noise. In Proceedings of the 29th annual ACM symposium on applied computing (SAC’14) (pp. 531–538). New York: ACM.

    Google Scholar 

  44. Martignoni, L., Paleari, R., & Bruschi, D. (2009). A framework for behavior-based malware analysis in the cloud. In Proceedings 5th international conference information systems security (ICISS 2009) (pp. 178–192). New York: Springer.

    Google Scholar 

  45. Diro, A. A., & Chilamkurti, N. (2018). Distributed attack detection scheme using deep learning approach for internet of things. Future Generation Computer Systems, 82, 761–768.

    Article  Google Scholar 

  46. Chiang, M., Fellow, I. E. E. E., & Zhang, T. (2016). Fog and IoT: An overview of research opportunities. IEEE Internet of Things Journal, 3(6), 854–864.

    Article  Google Scholar 

  47. Bhushan, K., & Gupta, B. B. (2018). Hypothesis test for low-rate DDoS attack detection in cloud computing environment. Procedia Computer Science, 132, 947–955.

    Article  Google Scholar 

  48. Liu, W., Nishio, T., Shinkuma, R., & Takahashi, T. (2014). Adaptive resource discovery in mobile cloud computing. Computer Communications, 50(13), 119–129.

    Article  Google Scholar 

  49. Hu, P., Ning, H., Qiu, T., Song, H., Wang, Y., & Yao, X. (2017). Security and privacy preservation scheme of face identification and resolution framework using fog computing in internet of things. IEEE Internet of Things Journal, 4(5), 1143–1155.

    Article  Google Scholar 

  50. Paharia, B., & Bhushan, K. (2018). Fog computing as a defensive approach against distributed denial of service (DDoS): A proposed architecture. In 2018 9th international conference on computing, communication and networking technologies (ICCCNT) (pp. 1–7). Piscataway: IEEE.

    Google Scholar 

  51. Lee, K., Kim, D., Ha, D., & Rajput, U. (2015). On security and privacy issues of fog computing supported internet of things environment. In Proceedings of the international conference on the network of the future (pp. 1–3). IEEE

    Google Scholar 

  52. Lee, K., Kimy, D., Ha, D., Rajput, U., & Oh, H. (2015). On security and privacy issues of fog computing supported internet of things environment. In Proc. 6th international conference on the network of the future (NOF), Montreal, QC, Canada (pp. 1–3).

    Google Scholar 

  53. Huang, X., Xiang, Y., Bertino, E., Zhou, J., & Xu, L. (2014). Robust multi-factor authentication for fragile communications. IEEE Transactions on Dependable and Secure Computing, 11(6), 568–581.

    Article  Google Scholar 

  54. Yi, S., Qin, Z., & Li, Q. Security and privacy issues of fog computing: A survey. In K. Xu & H. Zhu (Eds.), Wireless algorithms, systems, and applications. WASA 2015 (Lecture notes in computer science) (Vol. 9204). Cham: Springer.

    Google Scholar 

  55. Dsouza, C., Ahn, G.-J., & Taguinod, M. (2014). Policy-driven security management for fog computing: Preliminary framework and a case study. In Proceedings of the IEEE 15th international conference on information reuse and integration, IRI (pp. 16–23). Piscataway: IEEE.

    Google Scholar 

  56. Gai, K., Qiu, M., Tao, L., & Zhu, Y. (2016). Intrusion detection techniques for mobile cloud computing in heterogeneous 5G. Security and Communication Networks, 9(16), 3049–3058.

    Article  Google Scholar 

  57. Falliere, N., Murchu, L. O., & Chien, E. (2011). W32.stuxnet Dossier. Symantec Security Response, Ver. 1.4. Mountain View, CA: Symantec.

    Google Scholar 

  58. Berger, S., Cáceres, R., Goldman, K. A., Perez, R., Sailer, R., & van Doorn, L. (2006). vTPM: Virtualizing the trusted platform module. In Proceedings of the 15th conference on USENIX security symposium (USENIX-SS’06) (Vol. 15, Article No. 21). Berkeley: USENIX Association.

    Google Scholar 

  59. Wang, Y., Uehara, T., & Sasaki, R. (2015). Fog computing: Issues and challenges in security and forensics. In Proceedings of the 39th IEEE annual computer software and applications conference, COMPSAC (Vol. 3, pp. 53–59).

    Google Scholar 

  60. Zetter, K. (2014). Countdown to zero day: Stuxnet and the launch of the world’s first digital weapon. New York: Crown.

    Google Scholar 

  61. Stuxnet. Retrieved January, 2017, from https://en.wikipedia.org/wiki/Stuxnet

  62. Delgrossi, L., & Zhang, T. (2012). Vehicle safety communications: Protocols, security, and privacy. Hoboken: Wiley.

    Book  Google Scholar 

  63. Zhang, T., Antunes, H., & Aggarwal, S. (2014). Defending connected vehicles against malware: Challenges and a solution framework. IEEE Internet of Things Journal, 1(1), 10–21.

    Article  Google Scholar 

  64. Zhang, T., Antunes, H., & Aggarwal, S. (2014). Securing connected vehicles end to end. In Proc. SAE World Congr. Exhibit., Detroit, MI, USA, Apr. 2014.

    Google Scholar 

  65. Ibrahim, M. H. (2016). Octopus: An edge-fog mutual authentication scheme. International Journal of Network Security, 18(6), 1089–1101.

    Google Scholar 

  66. Iqbal, S., Kiah, M. L. M., Dhaghighi, B., Hussain, M., Khan, S., Khan, M. K., & Choo, K.-K. R. (2016). On cloud security attacks: A taxonomy and intrusion detection and prevention as a service. Journal of Network and Computer Applications, 74, 98–120.

    Article  Google Scholar 

  67. Luo, W., Xu, L., Zhan, Z., Zheng, Q., & Xu, S. (2014). Federated cloud security architecture for secure and agile clouds. In K. J. Han, B.-Y. Choi, & S. Song (Eds.), High performance cloud auditing and applications (pp. 169–188). New York: Springer.

    Chapter  Google Scholar 

  68. Lombardi, F., & Di Pietro, R. (2014). Virtualization and cloud security: Benefits, caveats, and future developments. In Cloud computing: Challenges, limitations and R&D solutions (pp. 237–255). Cham: Springer.

    Chapter  Google Scholar 

  69. Zhang, M., Duan, Y., Yun, H., & Zhao, Z. (2014). Semantics-aware android malware classification using weighted contextual API dependency graphs. In Proceedings of the 2014 ACM SIGSAC conference on computer and communications security (CCS’14) (pp. 1105–1116). New York: ACM.

    Google Scholar 

  70. Simou, S., Kalloniatis, C., Kavakli, E., & Gritzalis, S. Cloud forensics solutions: A review. In L. Iliadis, M. Papazoglou, & K. Pohl (Eds.), Advanced information systems engineering workshops. CAiSE 2014. Lecture notes in business information processing (Vol. 178). Cham: Springer.

    Google Scholar 

  71. Kent, K., Chevalier, S., Grance, T., & Dang, H. (2006). Guide to integrating forensic techniques into incident response. NIST Special Publication, 10(14), 800–886.

    Google Scholar 

  72. Chaudhary, D., & Bhushan, K. (2017). DDoS attack defense framework for cloud using fog computing. In 2017 2nd IEEE international conference on recent trends in electronics, information & communication technology (RTEICT) (pp. 534–538). Piscataway: IEEE.

    Google Scholar 

  73. Bhushan, K., & Gupta, B. B. (2017). Network flow analysis for detection and mitigation of fraudulent resource consumption (FRC) attacks in multimedia cloud computing. Multimedia Tools and Applications, 78(4), 4267–4298.

    Article  Google Scholar 

  74. Paharia, B., & Bhushan, K. (2018). DDoS detection and mitigation in cloud via FogFiter: A defence mechanism. In 2018 9th international conference on computing, communication and networking technologies (ICCCNT) (pp. 1–7). Piscataway: IEEE.

    Google Scholar 

  75. Bhushan, K., & Gupta, B. B. (2018). Detecting DDoS attack using software defined network (SDN) in cloud computing environment. In 2018 5th international conference on signal processing and integrated networks (SPIN) (pp. 872–877). Piscataway: IEEE.

    Chapter  Google Scholar 

  76. Paharia, B., & Bhushan, K. (2019). Fog computing: concepts, applications, and countermeasures against security attacks. In Handbook of research on cloud computing and big data applications in IoT (pp. 302–329). Hershey: IGI Global.

    Chapter  Google Scholar 

  77. Hu, P., Ning, H., Qiu, T., Xu, Y., Luo, X., & Sangaiah, A. K. (2018). A unified face identification and resolution scheme using cloud computing in internet of things. Future Generation Computing Systems, 81, 582–592.

    Article  Google Scholar 

  78. Choo, K.-K. R. (2016). Cloud computing: Challenges and future directions. Trends and Issues in Crime and Criminal Justice, 400, 1–6.

    Google Scholar 

  79. Landau, S. (2014). Highlights from making sense of Snowden, part II: What’s significant in the NSA revelations. IEEE Security and Privacy, 12(1), 62–64.

    Article  Google Scholar 

  80. Juliadotter, N. V., & Choo, K.-K. R. (2015). Cloud attack and risk assessment taxonomy. IEEE Cloud Computing, 2(1), 14–20.

    Article  Google Scholar 

  81. Bureau of Transportation Statistics, U.S. Department of Transportation, Washington, DC, USA [Online]. Retrieved March, 2017, from http://www.rita.dot.gov/bts/sites/rita.dot.gov.bts/files/publications/national_transportation_statistics/html/table_01_26.html_mfd

  82. Chen, M., Zhang, Y., Li, Y., & Mao, S. (2015). EMC: Emotion-aware mobile cloud computing in 5G. IEEE Network, 29(2), 32–38.

    Article  Google Scholar 

  83. Amendola, D., Cordeschi, N., & Baccarelli, E. (2016). Bandwidth management VMs live migration in wireless fog computing for 5G networks. In Proceedings of the IEEE international conference on cloud networking (pp. 21–26). New York: IEEE.

    Google Scholar 

  84. Peng, M., Yan, S., Zhang, K., & Wang, C. (2015). Fog-computing-based radio access networks: Issues and challenges. IEEE Network, 30(4), 46–53.

    Article  Google Scholar 

  85. Papagianni, C., Leivadeas, A., & Papavassiliou, S. (2013). A cloud-oriented content delivery network paradigm: Modeling and assessment. IEEE Transactions on Dependable and Secure Computing, 10(5), 287–300.

    Article  Google Scholar 

  86. Osanaiye, O., Choo, K.-K. R., & Dlodlo, M. (2016). Distributed denial of service (DDoS) resilience in cloud: Review and conceptual cloud DDoS mitigation framework. Journal of Network and Computer Applications, 67, 147–165.

    Article  Google Scholar 

  87. Chaudhary, D., Bhushan, K., & Gupta, B. B. (2018). Survey on DDoS attacks and defense mechanisms in cloud and fog computing. International Journal of E-Services and Mobile Applications (IJESMA), 10(3), 61–83.

    Article  Google Scholar 

  88. Chaudhary, D., & Bhushan, K. (2017). DDoS attack mitigation and resource provisioning in cloud using fog computing. In 2017 International conference on smart technologies for smart nation (SmartTechCon) (pp. 308–313). Piscataway: IEEE.

    Google Scholar 

  89. Bhushan, K., & Gupta, B. B. (2018). A novel approach to defend multimedia flash crowd in cloud environment. Multimedia Tools and Applications, 77(4), 4609–4639.

    Article  Google Scholar 

  90. McKeown, N., Anderson, T., Balakrishnan, H., Parulkar, G., et al. (2008). OpenFlow: Enabling innovation in campus networks. ACM SIGCOMM CCR, 38(2), 69–74.

    Article  Google Scholar 

  91. Mininet. An instant virtual network on your laptop (or other PC). Retrieved March, 2017, from mininet.org

  92. Sekar, A. G. V., Krishnaswamy, R., & Reiter, M. K. (2010). Network-wide deployment of intrusion detection and prevention systems. In Proceedings of 6th international conference ACM Co-NEXT. New York: ACM.

    Google Scholar 

  93. Klaedtke, F., Karame, G. O., Bifulco, R., & Cui, H. (2015). Towards an access control scheme for accessing flows in SDN. In 2015 1st IEEE Conference on Network Softwarization (NetSoft) (pp. 1–6). IEEE.

    Google Scholar 

  94. Yap, K. K., et al. (2011). Separating authentication, access and accounting: A case study with openWiFi. Technical report. Menlo Park: Open Networking Foundation.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Kriti Bhushan .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Paharia, B., Bhushan, K. (2020). A Comprehensive Review of Distributed Denial of Service (DDoS) Attacks in Fog Computing Environment. In: Gupta, B., Perez, G., Agrawal, D., Gupta, D. (eds) Handbook of Computer Networks and Cyber Security. Springer, Cham. https://doi.org/10.1007/978-3-030-22277-2_20

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-22277-2_20

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-22276-5

  • Online ISBN: 978-3-030-22277-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics