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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
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About me
Aristide Tanyi-Jong Akem and Edwin Mugume, "A Machine Learning Approach to Temporal Traffic-Aware Energy-Efficient Cellular Networks," 2020 11th IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON), New York, NY, USA, 2020, pp. 0628-0634, doi: 10.1109/UEMCON51285.2020.9298085.
Aristide Tanyi-Jong Akem, Beyza Bütün, Michele Gucciardo, and Marco Fiore, Henna: hierarchical machine learning inference in programmable switches, 1st International Workshop on Native Network Intelligence (NativeNi’22), Roma, Italy, pp. 1–7, doi: 10.1145/3565009.3569520
Aristide Tanyi-Jong Akem, Michele Gucciardo and Marco Fiore, "Flowrest: Practical Flow-Level Inference in Programmable Switches with Random Forests," IEEE INFOCOM 2023 - IEEE Conference on Computer Communications, New York City, NY, USA, 2023, pp. 1-10, doi: 10.1109/INFOCOM53939.2023.10229100.
Michele Gucciardo, Aristide Tanyi-Jong Akem, Beyza Bütün and Marco Fiore, "Demonstrating Flow-Level In-Switch Inference," IEEE INFOCOM 2023 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), Hoboken, NJ, USA, 2023, pp. 1-2, doi: 10.1109/INFOCOMWKSHPS57453.2023.10225967.
Aristide Tanyi-Jong Akem, Beyza Bütün, Michele Gucciardo and Marco Fiore, "Showcasing In-Switch Machine Learning Inference," 2023 IEEE 9th International Conference on Network Softwarization (NetSoft), Madrid, Spain, 2023, pp. 299-301, doi: 10.1109/NetSoft57336.2023.10175464.
Beyza Bütün, Aristide Tanyi-Jong Akem, Michele Gucciardo and Marco Fiore, "Fast Detection of Cyberattacks on the Metaverse through User-plane Inference," 2023 IEEE International Conference on Metaverse Computing, Networking and Applications (MetaCom), Kyoto, Japan, 2023, pp. 350-354, doi: 10.1109/MetaCom57706.2023.00067.
Aristide Tanyi-Jong Akem, Guillaume Fraysse and Marco Fiore, "Encrypted Traffic Classification at Line Rate in Programmable Switches with Machine Learning," NOMS 2024 - IEEE/IFIP Network Operations and Management Symposium, Seoul, South Korea, 6-10 May 2024, pp. 1-9, (Accepted for Publication).
Aristide Tanyi-Jong Akem and Marco Fiore, "Towards Data-Driven Management of Mobile Networks through User Plane Inference," NOMS 2024 - IEEE/IFIP Network Operations and Management Symposium, Seoul, South Korea, 6-10 May 2024, pp. 1-4, (Accepted for Publication).
Aristide Tanyi-Jong Akem*, Beyza Bütün*, Michele Gucciardo and Marco Fiore, "Jewel: Resource-Efficient Joint Packet and Flow Level Inference in Programmable Switches," IEEE INFOCOM 2024 - IEEE Conference on Computer Communications, Vancouver, Canada, 2024, pp. 1-10, (Accepted for Publication).
Michele Gucciardo, Beyza Bütün, Aristide Tanyi-Jong Akem and Marco Fiore, "Evaluating the Impact of Flow Length on the Performance of In-Switch Inference Solutions," IEEE INFOCOM 2024 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), Vancouver, Canada, 2024.
Aristide Tanyi-Jong Akem, Michele Gucciardo, and Marco Fiore, "Ultra-Low Latency User-Plane Cyberattack Detection in SDN-based Smart Grids," In The 15th ACM International Conference on Future and Sustainable Energy Systems (E-Energy 24), June 04--07, 2024, Singapore, Singapore. ACM, New York, NY, USA 7 Pages. doi: 10.1145/3632775.3661995(Accepted for Publication).
Aristide Tanyi-Jong Akem and Marco Fiore, "Towards Real-Time Intrusion Detection in P4-Programmable 5G User Plane Functions," 7th European P4 Workshop (EuroP4’24), co-located with ICNP, Charleroi, Belgium, 28-31 October 2024, pp. 1-6, (Accepted for Publication).
Aristide Tanyi-Jong Akem, Guillaume Fraysse, and Marco Fiore, "Real-Time Encrypted Traffic Classification in Programmable Networks with P4 and Machine Learning," International Journal of Network Management, Wiley, Volume 35, Issue 1, January 2025.
Aristide Tanyi-Jong Akem, Beyza Bütün, Michele Gucciardo and Marco Fiore, "Practical and General-Purpose Flow-Level Inference With Random Forests in Programmable Switches," in IEEE Transactions on Networking, doi: 10.1109/TON.2025.3564465.