• Kong Z, Hu N, Hu Y, Meng J and Koral Y. High-Fidelity Cellular Network Control-Plane Traffic Generation without Domain Knowledge. Proceedings of the 2024 ACM on Internet Measurement Conference. (530-544).

    https://doi.org/10.1145/3646547.3688422

  • Zhang S, Li T, Jin D and Li Y. (2024). NetDiff: A Service-Guided Hierarchical Diffusion Model for Network Flow Trace Generation. Proceedings of the ACM on Networking. 2:CoNEXT3. (1-21). Online publication date: 18-Aug-2024.

    https://doi.org/10.1145/3676870

  • Chu A, Jiang X, Liu S, Bhagoji A, Bronzino F, Schmitt P and Feamster N. Feasibility of State Space Models for Network Traffic Generation. Proceedings of the 2024 SIGCOMM Workshop on Networks for AI Computing. (9-17).

    https://doi.org/10.1145/3672198.3673792

  • Jiang X, Liu S, Gember-Jacobson A, Bhagoji A, Schmitt P, Bronzino F and Feamster N. (2024). NetDiffusion: Network Data Augmentation Through Protocol-Constrained Traffic Generation. Proceedings of the ACM on Measurement and Analysis of Computing Systems. 8:1. (1-32). Online publication date: 16-Feb-2024.

    https://doi.org/10.1145/3639037

  • Kfoury E, Crichigno J and Bou-Harb E. (2024). P4BS: Leveraging Passive Measurements From P4 Switches to Dynamically Modify a Router’s Buffer Size. IEEE Transactions on Network and Service Management. 21:1. (1082-1099). Online publication date: 1-Feb-2024.

    https://doi.org/10.1109/TNSM.2023.3306335

  • Zeynali D, Weyulu E, Fathalli S, Chandrasekaran B and Feldmann A. (2024). Promises and Potential of BBRv3. Passive and Active Measurement. 10.1007/978-3-031-56252-5_12. (249-272).

    https://link.springer.com/10.1007/978-3-031-56252-5_12

  • Liu C, Maeda K, Takai J, Murota K and Shin K. (2024). Synthetic Data Generation Without Real Data: Uncovering Insights in Malware Detection. Advances in Information and Communication. 10.1007/978-3-031-53963-3_17. (235-255).

    https://link.springer.com/10.1007/978-3-031-53963-3_17

  • Jiang X, Liu S, Gember-Jacobson A, Schmitt P, Bronzino F and Feamster N. Generative, High-Fidelity Network Traces. Proceedings of the 22nd ACM Workshop on Hot Topics in Networks. (131-138).

    https://doi.org/10.1145/3626111.3628196

  • De Keersmaeker F, Cao Y, Ndonda G and Sadre R. (2023). A Survey of Public IoT Datasets for Network Security Research. IEEE Communications Surveys & Tutorials. 25:3. (1808-1840). Online publication date: 1-Jul-2023.

    https://doi.org/10.1109/COMST.2023.3288942

  • Adeleke O, Bastin N and Gurkan D. (2022). Network Traffic Generation: A Survey and Methodology. ACM Computing Surveys. 55:2. (1-23). Online publication date: 28-Feb-2023.

    https://doi.org/10.1145/3488375

  • Ardi C, Hussain A, Collins M and Schwab S. Improving fidelity in video streaming experimentation on testbeds with a CDN. Proceedings of the 2nd International Workshop on Design, Deployment, and Evaluation of Network-Assisted Video Streaming. (1-7).

    https://doi.org/10.1145/3565476.3569097

  • Meslet-Millet F, Mouysset S and Chaput E. (2022). NeCSTGen: An approach for realistic network traffic generation using Deep Learning GLOBECOM 2022 - 2022 IEEE Global Communications Conference. 10.1109/GLOBECOM48099.2022.10000731. 978-1-6654-3540-6. (3108-3113).

    https://ieeexplore.ieee.org/document/10000731/

  • Yin Y, Lin Z, Jin M, Fanti G and Sekar V. Practical GAN-based synthetic IP header trace generation using NetShare. Proceedings of the ACM SIGCOMM 2022 Conference. (458-472).

    https://doi.org/10.1145/3544216.3544251

  • DeAngelis D, Hussain A, Kocoloski B, Ardi C and Schwab S. Generating Representative Video Teleconferencing Traffic. Proceedings of the 15th Workshop on Cyber Security Experimentation and Test. (100-104).

    https://doi.org/10.1145/3546096.3546107

  • Ardi C, Hussain A and Schwab S. Building Reproducible Video Streaming Traffic Generators. Proceedings of the 14th Cyber Security Experimentation and Test Workshop. (91-95).

    https://doi.org/10.1145/3474718.3474721

  • Campazas-Vega A, Crespo-Martínez I, Guerrero-Higueras Á and Fernández-Llamas C. (2020). Flow-Data Gathering Using NetFlow Sensors for Fitting Malicious-Traffic Detection Models. Sensors. 10.3390/s20247294. 20:24. (7294).

    https://www.mdpi.com/1424-8220/20/24/7294

  • Shukla A, Fathalli S, Zinner T, Hecker A and Schmid S. P4Consist: Toward Consistent P4 SDNs. IEEE Journal on Selected Areas in Communications. 10.1109/JSAC.2020.2999653. 38:7. (1293-1307).

    https://ieeexplore.ieee.org/document/9109655/

  • Ghoshal D, Wu K, Pouyoul E and Strohmaier E. (2019). Analysis and Prediction of Data Transfer Throughput for Data-Intensive Workloads 2019 IEEE International Conference on Big Data (Big Data). 10.1109/BigData47090.2019.9005543. 978-1-7281-0858-2. (3648-3657).

    https://ieeexplore.ieee.org/document/9005543/

  • Enghardt T, Tiesel P, Zinner T and Feldmann A. (2019). Informed Access Network Selection: The Benefits of Socket Intents for Web Performance 2019 15th International Conference on Network and Service Management (CNSM). 10.23919/CNSM46954.2019.9012714. 978-3-903176-24-9. (1-9).

    https://ieeexplore.ieee.org/document/9012714/

  • Cao L, Fahmy S, Sharma P and Zhe S. Data-driven resource flexing for network functions visualization. Proceedings of the 2018 Symposium on Architectures for Networking and Communications Systems. (111-124).

    https://doi.org/10.1145/3230718.3230725

  • Yuan D, Yi W, Hu H and Shi X. (2017). A fast, affordable and extensible FPGA-based synthetic Ethernet traffic generator for network evaluation 2017 3rd IEEE International Conference on Computer and Communications (ICCC). 10.1109/CompComm.2017.8322700. 978-1-5090-6352-9. (1036-1040).

    http://ieeexplore.ieee.org/document/8322700/

  • Zhang X, Gu N and Su J. (2016). DCUDP: scalable data transfer for high‐speed long‐distance networks. Concurrency and Computation: Practice and Experience. 10.1002/cpe.3846. 29:4. Online publication date: 25-Feb-2017.

    https://onlinelibrary.wiley.com/doi/10.1002/cpe.3846

  • Zhang X, Gu N, Su J and Ren K. (2016). DFTCP: A TCP-friendly delay-based high-speed TCP variant 2016 International Conference on Networking and Network Applications (NaNA). 10.1109/NaNA.2016.33. 978-1-4673-9803-9. (273-278).

    http://ieeexplore.ieee.org/document/7564153/

  • Xue L, Kumar S, Cui C, Kondikoppa P, Chiu C and Park S. (2016). Towards fair and low latency next generation high speed networks. Journal of Network and Computer Applications. 70:C. (183-193). Online publication date: 1-Jul-2016.

    https://doi.org/10.1016/j.jnca.2016.03.021

  • Bartlett G and Mirkovic J. Expressing Different Traffic Models Using the LegoTG Framework. Proceedings of the 2015 IEEE 35th International Conference on Distributed Computing Systems Workshops. (56-63).

    https://doi.org/10.1109/ICDCSW.2015.21

  • Han Y, Yoo J and Hong J. (2015). Poisson shot-noise process based flow-level traffic matrix generation for data center networks 2015 IFIP/IEEE International Symposium on Integrated Network Management (IM). 10.1109/INM.2015.7140322. 978-1-4799-8241-7. (450-457).

    http://ieeexplore.ieee.org/document/7140322/

  • Huang C, Lin Y, Liao P and Lai Y. (2015). Stateful traffic replay for web application proxies. Security and Communication Networks. 8:6. (970-981). Online publication date: 1-Apr-2015.

    https://doi.org/10.1002/sec.1053

  • Hohlfeld O, Pujol E, Ciucu F, Feldmann A and Barford P. A QoE Perspective on Sizing Network Buffers. Proceedings of the 2014 Conference on Internet Measurement Conference. (333-346).

    https://doi.org/10.1145/2663716.2663730

  • ElSheikh M, Gadelrab M, Ghoneim M and Rashwan M. (2014). BoTGen: A new approach for in-lab generation of botnet datasets 2014 9th International Conference on Malicious and Unwanted Software: "The Americas" (MALWARE). 10.1109/MALWARE.2014.6999406. 978-1-4799-7329-3. (76-84).

    http://ieeexplore.ieee.org/document/6999406/

  • Xue L, Kumar S, Cui C and Park S. (2014). A study of fairness among heterogeneous TCP variants over 10Gbps high-speed optical networks. Optical Switching and Networking. 10.1016/j.osn.2014.03.003. 13. (124-134). Online publication date: 1-Jul-2014.

    https://linkinghub.elsevier.com/retrieve/pii/S1573427714000319

  • Han Y, Seo S, Hwang C, Yoo J and Hong J. (2014). Flow-level traffic matrix generation for various data center networks NOMS 2014 - 2014 IEEE/IFIP Network Operations and Management Symposium. 10.1109/NOMS.2014.6838394. 978-1-4799-0913-1. (1-6).

    http://ieeexplore.ieee.org/document/6838394/

  • Xue L, Kumar S, Cui C, Kondikoppa P, Chiu C and Park S. (2013). AFCD: An Approximated-Fair and Controlled-Delay Queuing for High Speed Networks 2013 22nd International Conference on Computer Communication and Networks (ICCCN 2013). 10.1109/ICCCN.2013.6614103. 978-1-4673-5775-3. (1-7).

    http://ieeexplore.ieee.org/document/6614103/

  • Groléat T, Arzel M, Vaton S, Bourge A, Le Balch Y, Bougdal H and Aranaz Padron M. Flexible, extensible, open-source and affordable FPGA-based traffic generator. Proceedings of the first edition workshop on High performance and programmable networking. (23-30).

    https://doi.org/10.1145/2465839.2465843

  • Gondor S, Kupper A, Uzun A, Bayer N and Kollecker L. A Traffic Injection Framework to Support the Evaluation of Effects of Reconfigurations on Energy Consumption in Multi-RAT Networks. Proceedings of the 2012 IEEE International Conference on Green Computing and Communications. (595-598).

    https://doi.org/10.1109/GreenCom.2012.90

  • Botta A, Dainotti A and Pescapé A. (2012). A tool for the generation of realistic network workload for emerging networking scenarios. Computer Networks: The International Journal of Computer and Telecommunications Networking. 56:15. (3531-3547). Online publication date: 1-Oct-2012.

    https://doi.org/10.1016/j.comnet.2012.02.019

  • Qardaji W and Li N. Anonymizing Network Traces with Temporal Pseudonym Consistency. Proceedings of the 2012 32nd International Conference on Distributed Computing Systems Workshops. (622-633).

    https://doi.org/10.1109/ICDCSW.2012.11

  • Benno S, Esteban J and Rimac I. (2011). Adaptive streaming: The network HAS to help. Bell Labs Technical Journal. 16:2. (101-114). Online publication date: 1-Sep-2011.

    https://doi.org/10.1002/bltj.20505

  • Wu Y, Tseng H, Yang W and Jan R. DDoS Detection and Traceback with Decision Tree and Grey Relational Analysis. Proceedings of the 2009 Third International Conference on Multimedia and Ubiquitous Engineering. (306-314).

    https://doi.org/10.1109/MUE.2009.60

  • Dales M and Glick M. (2006). Networking Challenges in High-Capacity, Low-Latency, Optically-Switched Interconnects 2006 International Conference on Photonics in Switching. 10.1109/PS.2006.4350143. 978-0-7803-9789-7. (1-3).

    http://ieeexplore.ieee.org/document/4350143/

  • Simpson C, Reddy D and Riley G. Empirical Models of TCP and UDP End-User Network Traffic from NETI@home Data Analysis. Proceedings of the 20th Workshop on Principles of Advanced and Distributed Simulation. (166-174).

    https://doi.org/10.1109/PADS.2006.17

  • Tsang Y, Yildiz M, Barford P and Nowak R. Network radar. Proceedings of the 4th ACM SIGCOMM conference on Internet measurement. (175-180).

    https://doi.org/10.1145/1028788.1028809

  • Li R, Li Q, Zou Q, Zhao D, Zeng X, Huang Y, Jiang Y, Lyu F, Ormazabal G, Singh A and Schulzrinne H. IoTGemini: Modeling IoT Network Behaviors for Synthetic Traffic Generation. IEEE Transactions on Mobile Computing. 10.1109/TMC.2024.3426600. 23:12. (13240-13257).

    https://ieeexplore.ieee.org/document/10595132/

  • Amich A, Eshete B, Yegneswaran V and Hoang N. DeResistor. Proceedings of the 32nd USENIX Conference on Security Symposium. (2617-2633).

    /doi/10.5555/3620237.3620384

  • Le F, Srivatsa M, Ganti R and Sekar V. Rethinking data-driven networking with foundation models. Proceedings of the 21st ACM Workshop on Hot Topics in Networks. (188-197).

    https://doi.org/10.1145/3563766.3564109

  • Mi Y, Mohaisen D and Wang A. (2022). AutoDefense: Reinforcement Learning Based Autoreactive Defense Against Network Attacks 2022 IEEE Conference on Communications and Network Security (CNS). 10.1109/CNS56114.2022.9947232. 978-1-6654-6255-6. (163-171).

    https://ieeexplore.ieee.org/document/9947232/

  • Palmer M, Appel M, Spiteri K, Chandrasekaran B, Feldmann A and Sitaraman R. VOXEL. Proceedings of the 17th International Conference on emerging Networking EXperiments and Technologies. (359-374).

    https://doi.org/10.1145/3485983.3494864

  • Severini J, Mysore R, Sekar V, Banerjee S and Reiter M. (2021). The Netivus Manifesto. ACM SIGCOMM Computer Communication Review. 51:2. (10-17). Online publication date: 11-Apr-2021.

    https://doi.org/10.1145/3464994.3464997

  • Enghardt T, Zinner T and Feldmann A. Using informed access network selection to improve HTTP adaptive streaming performance. Proceedings of the 11th ACM Multimedia Systems Conference. (126-140).

    https://doi.org/10.1145/3339825.3391865

  • Javali C and Revadigar G. (2019). Network Web Traffic Generator for Cyber Range Exercises 2019 IEEE 44th Conference on Local Computer Networks (LCN). 10.1109/LCN44214.2019.8990880. 978-1-7281-1028-8. (308-315).

    https://ieeexplore.ieee.org/document/8990880/

  • Fernandes S. (2017). Internet Traffic Profiling. Performance Evaluation for Network Services, Systems and Protocols. 10.1007/978-3-319-54521-9_4. (113-152).

    http://link.springer.com/10.1007/978-3-319-54521-9_4

  • Ricciato F, Strohmeier F, Dorfinger P and Coluccia A. (2011). One-way loss measurements from IPFIX records 2011 IEEE International Workshop on Measurements and Networking Proceedings. 10.1109/IWMN.2011.6088499. 978-1-4577-0457-4. (158-163).

    http://ieeexplore.ieee.org/document/6088499/

  • Wu Y, Tseng H, Yang W and Jan R. (2011). DDoS detection and traceback with decision tree and grey relational analysis. International Journal of Ad Hoc and Ubiquitous Computing. 7:2. (121-136). Online publication date: 1-Mar-2011.

    https://doi.org/10.1504/IJAHUC.2011.038998

  • Lombardo A, Reforgiato D and Schembra G. An accelerated and energy-efficient traffic monitor using the NetFPGA (abstract only). Proceedings of the 19th ACM/SIGDA international symposium on Field programmable gate arrays. (277-277).

    https://doi.org/10.1145/1950413.1950464

  • Shin K, Kim J, Sohn K, Park C and Choi S. Online gaming traffic generator for reproducing gamer behavior. Proceedings of the 9th international conference on Entertainment computing. (160-170).

    /doi/10.5555/1881673.1881692

  • Siska P, Stoecklin M, Kind A and Braun T. A flow trace generator using graph-based traffic classification techniques. Proceedings of the 6th International Wireless Communications and Mobile Computing Conference. (457-462).

    https://doi.org/10.1145/1815396.1815503

  • Shin K, Kim J, Sohn K, Park C and Choi S. (2010). Online Gaming Traffic Generator for Reproducing Gamer Behavior. Entertainment Computing - ICEC 2010. 10.1007/978-3-642-15399-0_15. (160-170).

    http://link.springer.com/10.1007/978-3-642-15399-0_15

  • Shuo Z, Rongcai Z and Ke A. On Generating Self-Similar Network Traffic Using Multi-core Processors. Proceedings of the 2008 International Symposium on Computer Science and Computational Technology - Volume 01. (667-672).

    https://doi.org/10.1109/ISCSCT.2008.162

  • Simpson C, Reddy D and Riley G. (2008). Empirical Models of End-User Network Behavior from NETI@home Data Analysis. Simulation. 84:10-11. (557-571). Online publication date: 1-Oct-2008.

    https://doi.org/10.1177/0037549708099041

  • Li W, Zeng B, Zhang D and Yang J. Performance evaluation of end-to-end path capacity measurement tools in a controlled environment. Proceedings of the 3rd international conference on Advances in grid and pervasive computing. (222-231).

    /doi/10.5555/1788754.1788781

  • Seongjin Lee , Youjip Won and Dong-Joon Shin . (2008). On the multi-scale behavior of packet size distribution in Internet backbone network NOMS 2008 - 2008 IEEE Network Operations and Management Symposium - Pervasive Management for Ubiquitous Networks and Services. 10.1109/NOMS.2008.4575217. 978-1-4244-2065-0. (799-802).

    http://ieeexplore.ieee.org/document/4575217/

  • Li W, Zeng B, Zhang D and Yang J. Performance Evaluation of End-to-End Path Capacity Measurement Tools in a Controlled Environment. Advances in Grid and Pervasive Computing. 10.1007/978-3-540-68083-3_23. (222-231).

    http://link.springer.com/10.1007/978-3-540-68083-3_23

  • Ying-Jun H, Zhang-Jun , Fan-Jiang X and Li-Lei . (2006). FSNDP based aggregated traffic generating in constellation networks emulating Multiconference on "Computational Engineering in Systems Applications. 10.1109/CESA.2006.4281889. 7-302-13922-9. (1588-1591).

    http://ieeexplore.ieee.org/document/4281889/

  • Simpson C, Reddy D and Riley G. Empirical Models of TCP and UDP End-User Network Traffic from NETI@home Data Analysis. Proceedings of the 20th Workshop on Principles of Advanced and Distributed Simulation. (166-174).

    https://doi.org/10.1109/PADS.2006.17

  • Appenzeller G, Keslassy I and McKeown N. (2004). Sizing router buffers. ACM SIGCOMM Computer Communication Review. 34:4. (281-292). Online publication date: 30-Aug-2004.

    https://doi.org/10.1145/1030194.1015499

  • Appenzeller G, Keslassy I and McKeown N. Sizing router buffers. Proceedings of the 2004 conference on Applications, technologies, architectures, and protocols for computer communications. (281-292).

    https://doi.org/10.1145/1015467.1015499