Abstract
Deep Packet Inspection (DPI) provides full visibility into network traffic by performing detailed analysis on both packet header and packet payload. Accordingly, DPI has critical importance as it can be used in applications i.e network security or government surveillance. In this paper, we provide an extensive survey on DPI. Different from the previous studies, we try to efficiently integrate DPI techniques into network analysis mechanisms by identifying performance-limiting parameters in the analysis of modern network traffic. Analysis of the network traffic model with complex behaviors is carried out with powerful hybrid systems by combining more than one technique. Therefore, DPI methods are studied together with other techniques used in the analysis of network traffic. Security applications of DPI on Internet of Things (IoT) and Software-Defined Networking (SDN) architectures are discussed and Intrusion Detection Systems (IDS) mechanisms, in which the DPI is applied as a component of the hybrid system, are examined. In addition, methods that perform inspection of encrypted network traffic are emphasized and these methods are evaluated from the point of security, performance and functionality. Future research issues are also discussed taking into account the implementation challenges for all DPI processes.
Publisher
Omer Halisdemir Universitesi
Subject
General Economics, Econometrics and Finance
Reference203 articles.
1. M. Abbasi, A. Shahraki, A. Taherkordi, Deep learning for network traffic monitoring and analysis (ntma): A survey, Computer Communications 170 (10), 19–41, 2021. https://doi.org/10.1016/j.comcom.2021.01.021.
2. G. A. Pimenta Rodrigues, R. de Oliveira Albuquerque, F. E. Gomes de Deus, G. A. De Oliveira J´unior, L. J. Garc´ıa Villalba, T.-H. Kim, et al., Cybersecurity and network forensics: Analysis of malicious traffic towards a honeynet with deep packet inspection, Applied Sciences 7 (10), 1082, 2017.
https://doi.org/10.3390/app7101082.
3. C. Parsons, Deep Packet Inspection in Perspective: Tracing its lineage and surveillance potentials, Citeseer, 2011.
4. C. Parsons, The politics of deep packet inspection: What drives surveillance by internet service providers?, Ph.D. thesis, 2013.
5. C. Xu, S. Chen, J. Su, S.-M. Yiu, L. C. Hui, A survey on regular expression matching for deep packet inspection: Applications, algorithms, and hardware platforms, IEEE Communications Surveys & Tutorials 18 (4), 2991–3029, 2016. https://doi.org/10.1109/COMST.2016.2566669.