A Survey on Mitigation of Cache Pollution Attacks in NDN

Authors

  • Najam U Saqib Department of Computer Science, COMSATS University Islamabad, 45550, Pakistan
  • Sani Isnain Konya Technical University, Konya, 42250, Turkey

DOI:

https://doi.org/10.14513/actatechjaur.00760

Keywords:

Information Centric Networking, Cache Pollution Attack (CPA), False-locality Pollution Attack (FLA), Locality Disruption Attack (LDA)

Abstract

Named Data Networking (NDN) improves data retrieval by using in-network caching, but this advantage makes it susceptible to cache pollution attacks, where malicious or irrelevant content fills caches and reduces network efficiency. This paper reviews several mitigation techniques for these attacks, grouping them into proactive, reactive, and collaborative approaches. Each strategy is assessed based on its scalability, detection accuracy, and overall impact on network performance. While some progress has been made, existing methods often struggle in large, dynamic environments, where they tend to be computationally expensive and lack adaptability. The survey identifies key research gaps, such as the need for real-time, adaptive solutions that can operate without compromising network performance. It also highlights the potential for using AI and machine learning to enhance detection accuracy and reduce false positives. Future research should focus on developing scalable, decentralized systems to strengthen the security and efficiency of NDN’s caching mechanisms.

Downloads

Download data is not yet available.

References

Gao, Y., Deng, L., Kuzmanovic, A., & Chen, Y. (2006). Internet cache pollution attacks and countermeasures. In Proceedings of the 2006 IEEE International Conference on Network Protocols (pp. 54–64). IEEE. https://doi.org/10.1109/ICNP.2006.320197

AbdAllah, E. G., Hassanein, H. S., & Zulkernine, M. (2015). A survey of security attacks in information-centric networking. IEEE Communications Surveys & Tutorials, 17(3),1441–1454. https://doi.org/10.1109/COMST.2015.2412973

Guo, H., Wang, X., Chang, K., & Tian, Y. (2016). Exploiting path diversity for thwarting pollution attacks in named data networking. IEEE Transactions on Information Forensics and Security, 11(9), 2077–2090. https://doi.org/10.1109/TIFS.2016.2570746.

Jacobson, V., Smetters, D. K., Thornton, J. D., Plass, M. F., Briggs, N. H., & Braynard, R. (2009). Networking named content. In Proceedings of the 5th International Conference on Emerging Networking Experiments and Technologies (CoNEXT '09). https://doi.org/10.1145/1658939.1658941.

Ahlgren, B., Dannewitz, C., Imbrenda, C., Kutscher, D., & Ohlman, B. (2012). A survey of information-centric networking. IEEE Communications Magazine, 50(7), 26–36. https://doi.org/10.1109/MCOM.2012.6231276

Tsilopoulos, C., Vasilakos, X., Katsaros, K., Xylomenos, G., & Polyzos, G. C. (2014). A survey of information-centric networking research. IEEE Communications Surveys & Tutorials, 16(2), 1024–1049. https://doi.org/10.1109/SURV.2013.101613.00124

Eze, E. C., Zhang, S. J., & Liu, E. J. (2016). Advances in vehicular ad-hoc networks (VANETs): Challenges and roadmap for future development. International Journal of Automation and Computing, 13(1), 1–18. https://doi.org/10.1007/s11633-015-0911-3

Fang, C., Yao, H., Wang, Z., Wu, W., Jin, X., & Yu, F. R. (2018). A survey of mobile information-centric networking: Research issues and challenges. IEEE Communications Surveys & Tutorials, 20(3), 2353–2371. https://doi.org/10.1109/COMST.2018.2817685

Khelifi, H., Luo, S., Nour, B., Atiquzzaman, M., & Ben-Othman, J. (2020). Named data networking in vehicular ad hoc networks: State-of-the-art and challenges. IEEE Communications Surveys & Tutorials, 22(1), 320–351. https://doi.org/10.1109/COMST.2019.2894816

Lee, E., Lee, E., Gerla, M., & Oh, S. Y. (2014). Vehicular cloud networking: Architecture and design principles. IEEE Communications Magazine, 52(2), 148–155. https://doi.org/10.1109/MCOM.2014.6736756

Villarreal-Vasquez, M., Bhargava, B., & Angin, P. (2017). Adaptable safety and security in V2X systems. In 2017 IEEE International Congress on Internet of Things (ICIOT) (pp. 17–24). IEEE. https://doi.org/10.1109/IEEE.ICIOT.2017.12

Guo, H., Wang, X., Chang, K., & Tian, Y. (2016). Exploiting path diversity for thwarting pollution attacks in named data networking. IEEE Transactions on Information Forensics and Security, 11(9), 2077–2090. https://doi.org/10.1109/TIFS.2016.2570746

Deng, L., Gao, Y., Chen, Y., & Kuzmanovic, A. (2008). Pollution attacks and defenses for Internet caching systems. Computer Networks, 52(5), 935–956. https://doi.org/10.1016/j.comnet.2007.11.010.

Karami, A., & Guerrero-Zapata, M. (2015). An ANFIS-based cache replacement method for mitigating cache pollution attacks in named data networking. Computer Networks, 80, 51–65. https://doi.org/10.1016/j.comnet.2015.01.011.

Gao, Y., Deng, L., Kuzmanovic, A., & Chen, Y. (2006, November). Internet cache pollution attacks and countermeasures. In Proceedings of the 2006 IEEE International Conference on Network Protocols (pp. 54–64). IEEE. https://doi.org/10.1109/ICNP.2006.320197

Xie, M., Widjaja, I., & Wang, H. (2012). Enhancing cache robustness for content-centric networking. In 2012 Proceedings IEEE INFOCOM (pp. 2426–2434). IEEE. https://doi.org/10.1109/INFCOM.2012.6195606

Rani, P. V., & Shalinie, S. M. (2020). FuRL: Fuzzy RBM learning framework to detect and mitigate network anomalies in information centric network. Sādhanā, 45(1), 1–13. https://doi.org/10.1007/s12046-019-1240-4

Conti, M., Gasti, P., & Teoli, M. (2013). A lightweight mechanism for detection of cache pollution attacks in Named Data Networking. Computer Networks, 57(16), 3178–3191. https://doi.org/10.1016/j.comnet.2013.07.034

Salah, H., Alfatafta, M., SayedAhmed, S., & Strufe, T. (2017). CoMon++: Preventing cache pollution in NDN efficiently and effectively. In 2017 IEEE 42nd Conference on Local Computer Networks (LCN) (pp. 43–51). IEEE. https://doi.org/10.1109/LCN.2017.14

Guo, H., Wang, X., Chang, K., & Tian, Y. (2016). Exploiting path diversity for thwarting pollution attacks in named data networking. IEEE Transactions on Information Forensics and Security, 11(9), 2077–2090. https://doi.org/10.1109/TIFS.2016.2570742

Zhang, G., Liu, J., Chang, X., & Chen, Z. (2017). Combining popularity and locality to enhance in-network caching performance and mitigate pollution attacks in content-centric networking. IEEE Access, 5, 19012–19022. https://doi.org/10.1109/ACCESS.2017.2757479

Hidouri, A., Touati, H., Elhadad, M., & Bouzefrane, S. (2023). Q-ICAN: A Q-learning based cache pollution attack mitigation approach for Named Data Networking. Computer Networks, 224, 109998. https://doi.org/10.1016/j.comnet.2023.109998

Eze, E. C., Zhang, S. J., & Liu, E. J. (2016). Advances in vehicular ad-hoc networks (VANETs): Challenges and roadmap for future development. International Journal of Automation and Computing, 13(1), 1–18. https://doi.org/10.1007/s11633-015-0913-y

Seetharam, A., Seetharam, A., & Seetharam, A. (2018). On caching and routing in information-centric networks. IEEE Communications Magazine, 56(3), 204–209. https://doi.org/10.1109/MCOM.2018.1700611

Yao, L., Fan, Z., Deng, J., Fan, X., & Wu, G. (2020). Detection and defense of cache pollution attacks using clustering in named data networks. IEEE Transactions on Dependable and Secure Computing, 17(6), 1310–1321. https://doi.org/10.1109/TDSC.2018.2876845

Park, H., Widjaja, I., & Lee, H. (2012). Detection of cache pollution attacks using randomness checks. In Proceedings of the IEEE International Conference on Communications (pp. 1096–1100). IEEE. https://doi.org/10.1109/ICC.2012.6363885.

Afanasyev, A., Mahadevan, P., Moiseenko, I., Uzun, E., & Zhang, L. (2013). Interest flooding attack and countermeasures in named data networking. In Proceedings of the IFIP Networking Conference (pp. 1–9). IEEE. https://doi.org/10.1109/IFIPNetworking.2013.6663522

Downloads

Published

2025-03-28

How to Cite

Saqib, N. U., & Sani Isnain. (2025). A Survey on Mitigation of Cache Pollution Attacks in NDN. Acta Technica Jaurinensis. https://doi.org/10.14513/actatechjaur.00760

Issue

Section

Mini reviews