Cache performance in NDN networks with ADMM algorithm to deal with pollution attacks and traffic load changes
محورهای موضوعی : journal of Artificial Intelligence in Electrical Engineering
عاطفه واعظ شهرستانی
1
,
محمدرضا خیام باشی
2
,
faramarz safi
3
1 - دانشکده مهندسي کامپیوتر، واحد نجف¬آباد، دانشگاه آزاد اسلامی، نجف¬آباد، ایران
2 - دانشکده کامپیوتر- دانشگاه اصفهان
3 - Faculty of Computer Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran
کلید واژه: Named data, ADMM algorithm, cache pollution, cache hit rate, dynamic networks,
چکیده مقاله :
As data-driven networks like Named Data Networks (NDN) continue to grow, securing cache systems has become an increasingly critical issue, especially in defending against cache pollution attacks (CPA). This paper introduces a novel algorithm based on the Alternating Direction Method of Multipliers (ADMM) method for adaptively tuning the β parameter in the PFP-β-DA cache policy. The algorithm works by decomposing the optimization problem into manageable subproblems and updating the parameters in a distributed fashion. This approach enhances the cache CHR and reduces cache pollution (CPR). The algorithm was tested in three network topologies—simple, hierarchical, and advanced—and evaluated under stable conditions, attack scenarios, and dynamic traffic. Simulation results demonstrate that ADMM outperforms traditional methods like LRU, LFU-DA, and PFP-β-DA, providing better stability, adaptability, and precision. Particularly, in high-attack scenarios, the proposed algorithm reduces cache pollution by as much as 5% and increases the cache hit rate by up to 4% over the baseline methods. These results confirm the effectiveness of ADMM as a scalable and intelligent solution for improving cache security and efficiency in NDN networks.
1-1- Refrences
[1] R. Alubady, M. Salman, and A. S. Mohamed, “A review of modern caching strategies in named data network: Overview, classification, and research directions,” Telecommunication Systems, vol. 84, no. 4, pp. 581-626, 2023.
[2] H. Khelifi, S. Luo, B. Nour, H. Moungla, Y. Faheem, R. Hussain, and A. Ksentini, “Named data networking in vehicular ad hoc networks: State-of-the-art and challenges,” IEEE Communications Surveys & Tutorials, vol. 22, no. 1, pp. 320-351, 2019.
[3] N. Sadat, and R. Dai, “A Survey of Quality-of-Service and Quality-of-Experience Provisioning in Information-Centric Networks,” Network, vol. 5, no. 2, pp. 10, 2025.
[4] S. Yassine, N. Najib, and J. Abdellah, “Routing approaches in named data network: a survey and emerging research challenges,” International Journal of Computers and Applications, vol. 46, no. 1, pp. 32-45, 2024.
[5] X. Zhang, Y. Zhou, D. Wu, Q. Z. Sheng, S. Riaz, M. Hu, and L. Xiao, “A Survey on Privacy-Preserving Caching at Network Edge: Classification, Solutions, and Challenges,” ACM Computing Surveys, vol. 57, no. 5, pp. 1-38, 2025.
[6] L. V. Yovita, and N. R. Syambas, “Caching on Named Data Network: a Survey and Future Research,” International Journal of Electrical & Computer Engineering (2088-8708), vol. 8, no. 6, 2018.
[7] N. U. Saqib, and S. Isnain, “A Survey on Mitigation of Cache Pollution Attacks in NDN,” Acta Technica Jaurinensis, 2025.
[8] P. Kar, L. Chen, W. Sheng, C. F. Kwong, and D. Chieng, “Advancing NDN security: Efficient identification of cache pollution attacks through rank comparison,” Internet of Things, vol. 26, pp. 101142, 2024.
[9] P. Chaudhary, and N. Hubballi, “PeNCache: Popularity based cooperative caching in Named Data Networks,” Computer Networks, vol. 257, pp. 110995, 2025.
[10] A. Karami, and M. Guerrero-Zapata, “An anfis-based cache replacement method for mitigating cache pollution attacks in named data networking,” Computer Networks, vol. 80, pp. 51-65, 2015.
[11] A. Hidouri, N. Hajlaoui, H. Touati, M. Hadded, and P. Muhlethaler, “A survey on security attacks and intrusion detection mechanisms in named data networking,” Computers, vol. 11, no. 12, pp. 186, 2022.
[12] J. Baugh, and J. Guo, “Enhancing Cache Robustness in Information-Centric Networks: Per-Face Popularity Approaches,” Network, vol. 3, no. 4, pp. 502-521, 2023.
[13] N. Kumar, and S. Srivastava, “IBPC: An Approach for Mitigation of Cache Pollution Attack in NDN using Interface-Based Popularity,” Arabian Journal for Science and Engineering, vol. 49, no. 3, pp. 3241-3251, 2024.
[14] T. Lauinger, N. Laoutaris, P. Rodriguez, T. Strufe, E. Biersack, and E. Kirda, “Privacy risks in named data networking: What is the cost of performance?,” ACM SIGCOMM Computer Communication Review, vol. 42, no. 5, pp. 54-57, 2012.
[15] Z. N. S. ALMUDAYNI, “Improving Energy Efficiency and Network Lifetime in IoT Systems: A Novel Theoretical Framework and Experimental Validation,” La Trobe, 2025.
[16] D. Han, and X. Yuan, “A note on the alternating direction method of multipliers,” Journal of Optimization Theory and Applications, vol. 155, pp. 227-238, 2012.
[17] S. G. Mandapati, C. Ranaweera, and R. Doss, "Early Detection and Mitigation of Cache-Based Attacks in IoT-NDN," Deakin University, 2025.
[18] H. Wang, D. Man, S. Han, H. Wang, and W. Yang, "Detection and Defense of Cache Pollution Attack Using State Transfer Matrix in Named Data Networks." pp. 545-556.
[19] L. Liu, and S. Peng, "Detection of A Novel Dual Attack in Named Data Networking." pp. 1-8.
[20] 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,” IEEE Transactions on Dependable and Secure Computing, vol. 18, no. 6, pp. 2848-2860, 2020.
[21] J. P. Baugh, “Enhancing Cache Robustness in Named Data Networks,” 2018.
[22] J. B. Gouge, “A targeted denial of service attack on data caching networks,” 2015.