A COMPREHENSIVE SURVEY ON MULTIPLE ATTACKS IN NAMED DATA NETWORK
DOI:
https://doi.org/10.29121/shodhkosh.v5.i6.2024.2498Keywords:
Named Data Networking (NDN), NDN Security, Countermeasures, Intrusion Detection Systems (IDS), Cache Pollution Attacks (PA), Cache Poisoning Attack (CPA), Interest Flooding Attack (IFA), Distributed Denial Of Service (DDOS) AttacksAbstract [English]
Named data network is a future architecture of internet, which acts as a data-centric model. The NDN designed as an alternative to the current IP (Internet Protocol) based architecture, which relies on addressing devices and routing packets between them. NDN, on the other hand, focuses on naming data rather than devices in the network. As like its popularity nature, NDN suffers from different types of security vulnerabilities such as are cache pollution attacks (PA), cache poisoning attack (CPA), interest flooding attack (IFA) and Distributed denial of service (DDOS) attacks, which affects the data integrity, privacy, availability and confidentiality. These attacks made impacts on developing a security framework for NDN. This paper provides a review of existing solutions against the NDN vulnerabilities in detailed manner. This finally provides the complication and drawbacks of those existing solutions and thus helps to navigate to a future mechanism generation.
References
J. Zhou, J. Luo, J. Wang and L. Deng, "Cache Pollution Prevention Mechanism Based on Deep Reinforcement Learning in NDN," in Journal of Communications and Information Networks, vol. 6, no. 1, pp. 91-100, March 2021. DOI: https://doi.org/10.23919/JCIN.2021.9387728
L. Yao, Y. Zeng, X. Wang, A. Chen and G. Wu, "Detection and Defense of Cache Pollution Based on Popularity Prediction in Named Data Networking," in IEEE Transactions on Dependable and Secure Computing, vol. 18, no. 6, pp. 2848-2860, 1 Nov.-Dec. 2021. DOI: https://doi.org/10.1109/TDSC.2020.2967724
L. Yao, Z. Fan, J. Deng, X. Fan and G. Wu, "Detection and Defense of Cache Pollution Attacks Using Clustering in Named Data Networks," in IEEE Transactions on Dependable and Secure Computing, vol. 17, no. 6, pp. 1310-1321, 1 Nov.-Dec. 2020, doi: 10.1109/TDSC.2018.2876257. DOI: https://doi.org/10.1109/TDSC.2018.2876257
T. Zhi, Y. Liu, J. Wang and H. Zhang, "Resist Interest Flooding Attacks via Entropy–SVM and Jensen–Shannon Divergence in Information-Centric Networking," in IEEE Systems Journal, vol. 14, no. 2, pp. 1776-1787, June 2020 DOI: https://doi.org/10.1109/JSYST.2019.2939371
L. Liu, W. Feng, Z. Wu, M. Yue and R. Zhang, "The Detection Method of Collusive Interest Flooding Attacks Based on Prediction Error in NDN," in IEEE Access, vol. 8, pp. 128005-128017, 2020, doi: 10.1109/ACCESS.2020.3008723 DOI: https://doi.org/10.1109/ACCESS.2020.3008723
K. Wang, D. Guo and W. Quan, "Analyzing NDN NACK on Interest Flooding Attack via SIS Epidemic Model," in IEEE Systems Journal, vol. 14, no. 2, pp. 1862-1873, June 2020 DOI: https://doi.org/10.1109/JSYST.2019.2923841
R. A. Al-Share, A. S. Shatnawi and B. Al-Duwairi, "Detecting and Mitigating Collusive Interest Flooding Attacks in Named Data Networking," in IEEE Access, vol. 10, pp. 65996-66017, 2022 DOI: https://doi.org/10.1109/ACCESS.2022.3184304
Z. Wu, S. Peng, L. Liu and M. Yue, "Detection of Improved Collusive Interest Flooding Attacks Using BO-GBM Fusion Algorithm in NDN," in IEEE Transactions on Network Science and Engineering, vol. 10, no. 1, pp. 239-252, 1 Jan.-Feb. 2023 DOI: https://doi.org/10.1109/TNSE.2022.3206581
S. S. Ullah et al., "A Lightweight Identity-Based Signature Scheme for Mitigation of Content Poisoning Attack in Named Data Networking With Internet of Things," in IEEE Access, vol. 8, pp. 98910-98928, 2020 DOI: https://doi.org/10.1109/ACCESS.2020.2995080
M. S. M. Shah, Y. -B. Leau, M. Anbar and A. A. Bin-Salem, "Security and Integrity Attacks in Named Data Networking: A Survey," in IEEE Access, vol. 11, pp. 7984-8004, 2023 DOI: https://doi.org/10.1109/ACCESS.2023.3238732
S. Hussain, S. S. Ullah, A. Gumaei, M. Al-Rakhami, I. Ahmad and S. M. Arif, "A Novel Efficient Certificateless Signature Scheme for the Prevention of Content Poisoning Attack in Named Data Networking-Based Internet of Things," in IEEE Access, vol. 9, pp. 40198-40215, 2021 DOI: https://doi.org/10.1109/ACCESS.2021.3063490
Z. Xu, X. Wang and Y. Zhang, "Towards Persistent Detection of DDoS Attacks in NDN: A Sketch-Based Approach," in IEEE Transactions on Dependable and Secure Computing, vol. 20, no. 4, pp. 3449-3465, 1 July-Aug. 2023 DOI: https://doi.org/10.1109/TDSC.2022.3196187
D. Sul, S. H. Byun, J. Lee and N. Ko, "Countering Interest flooding DDoS attacks in NDN Network," 2021 International Conference on Information and Communication Technology Convergence (ICTC), Jeju Island, Korea, Republic of, 2021, pp. 1412-1414 DOI: https://doi.org/10.1109/ICTC52510.2021.9620750
Benmoussa, Ahmed, et al. "MSIDN: Mitigation of sophisticated interest flooding-based DDoS attacks in named data networking." Future Generation Computer Systems 107 (2020): 293-306. DOI: https://doi.org/10.1016/j.future.2020.01.043
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 A. Abdul Faiz, Dr. N. A. Sheelaselvakumari

This work is licensed under a Creative Commons Attribution 4.0 International License.
With the licence CC-BY, authors retain the copyright, allowing anyone to download, reuse, re-print, modify, distribute, and/or copy their contribution. The work must be properly attributed to its author.
It is not necessary to ask for further permission from the author or journal board.
This journal provides immediate open access to its content on the principle that making research freely available to the public supports a greater global exchange of knowledge.