Id

Project

Description

Link

Students

1

P4 load-balancing

Demonstrate the implementation of P4 load-balancing in a configuration with 5 nodes and 3 links per node

https://github.com/p4lang/tutorials/tree/master/exercises/load_balance

Baptiste Thomas.

2

P4 in-network computing

Implement an in-network computing system based on the BMv2 software switch. Demonstrate the execution of at least 2 instructions.

Paper: Ganesh C. Sankaran, Krishna M. Sivalingam, Harsh Gondaliya, "P4 and NetFPGA based secure in-network computing architecture for AI-enabled Industrial Internet of Things"

Link: https://github.com/harshgondaliya/PSasCP/tree/master

3

P4 heavy-hitter detection

Demonstrate the implementation of a heavy hitter detection using P4, showing how the detection performance decreases as the traffic increases

https://github.com/nsg-ethz/p4-learning/tree/master/exercises/06-Heavy_Hitter_Detector

4

P4 fast-reroute

Demonstrate the implementation of fast rerouting with loop free alternative with P4, in a configuration with 6 nodes and 4 links per node.

https://github.com/nsg-ethz/p4-learning/tree/master/exercises/12-Fast-Reroute

BERGER Charles

BOIVIN Benoit

5

Container auto scaling-1

Implementation of vertical autoscaling of docker containers/pods (prepare a lab excercise)

https://www.giantswarm.io/blog/vertical-autoscaling-in-kubernetes

6

Container auto scaling-2

Implementation of horizontal autoscaling of docker containers/pods (prepare a lab excercise)

https://kubernetes.io/docs/tasks/run-application/horizontal-pod-autoscale/

Vincent Thibaut

7

Real-world Dataset de-anonymization

Exploit the analysis of crafted malicious packets in a real-world dataset (2022) to de-anonymize it. Apply it to at least one trace per week for the year 2022 (e.g., every Monday)

Paper: will be provided by email (in French)

Dataset link: https://mawi.wide.ad.jp/mawi/samplepoint-F/2022/

Gauvain CRAHE

8

Anomaly detection with ISF algorithm

Determine the performance of Isolation forest to detect anomalie/outliers in time-series data

https://neptune.ai/blog/anomaly-detection-in-time-series

9

Anomaly detection with transformers

Determine the performance of transformers to detect anomalie/outliers in time-series data

https://neptune.ai/blog/anomaly-detection-in-time-series

10

Anomaly detection with GRU

Determine the performance of Gated recurrent unit (GRU) to detect anomalie/outliers in time-series data

https://neptune.ai/blog/anomaly-detection-in-time-series

Dufort Ornecipe

11

P4-Runtime based controller for fast failure recovery

Demonstrate the application of a novel control plane from recent scientific literature to achieve network failure detection and recovery

Paper:

https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10036033

github:

https://github.com/commlab513/P4-Inband-Network/

12

OVS vs bmv2 software switches

Compare the performance of the two software switches in terms of switching latency and packets per second with different bitrates

OVS: https://docs.openvswitch.org/en/latest/

bmv2:
https://github.com/p4lang/behavioral-model

Oumar Ndongo

13

Container scaling for IoT video traffic

Assess the accuracy and the throughput of an AI model and the network utilization under varying arrival rate of networked IoT video streams. Consider for a single AI model (yolov8) 3 cases: (1) AI model deployed in a single container of medium size; (2) AI model replicated in 5 containers of small size; (3) AI model deployed in a single container of size equals 5 times the small size.

https://docs.docker.com/

https://docs.ultralytics.com/modes/

https://docs.ultralytics.com/modes/track/

VISVAL Thierry

14

Container Migration

Implement and demonstrate migration of a container between 2 servers

https://ieeexplore.ieee.org/document/9407315

Bououf Faiçal

Lavaury Yannick

15

Universal Packet Scheduling

Demonstrate the capability of Least Slack Time First (LSTF) scheduling algorithm to minimize Mean Flow Completion Time and Tail Packet Delay, as well as assuring fairness.

Paper:

https://dl.acm.org/doi/pdf/10.1145/2834050.2834085?casa_token=EzMsEjNipUwAAAAA:W5MsyydbbADTJtvcyksLKg28sPZd6GWxS_h4IVVHZvrIq20-0ZFPofcb07urcAjJeLI73EelBWv8NSE

github:
https://github.com/NetSys/ups

Gérard Delorme

16

Mirai Botnet DDoS Attack

Deploy a Mirai Botnet testbed using containers, consisting of one CnC (Command and Control), one receiver, two bots, and one target host. The objective is to showcase at least one of Mirai's fundamental functions, including scanning, infection, and DDoS attacks.

https://github.com/jgamblin/Mirai-Source-Code

17

Service Function Chain (SFC) traffic scheduling simulator

Demonstrate the use of the SFC TSS discrete event simulator

https://github.com/mblo/sfctss

18

eBPF

Demonstrate at least three eBPF applications

https://ebpf.io

Mame DIAGNE

19

Deep Learning for LDPC decoding in wireless connections

Compare a Deep Learning based solution for Low-Density Parity-Check decoding with the conventional Min-Sum decoder in terms of Bit Error Rate under different Signal-to-Noise ratio

Paper:
https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9445813

Github:

https://github.com/Leo-Chu/Deep-learning-for-LDPC-decoding

Dufort ORNECIPE

20

SniffnDetect

Demonstrate the use of the Scapy-based DDoS detector SniffnDetect 2.0 to detect at least 3 kinds of attacks and evaluate its resource usage in terms of RAM and CPU under different conditions (idle, during attacks, during attacker identification)

https://github.com/priyamharsh14/SniffnDetect

Sadki Abderrahil

21

Network attacks with Scapy

Demonstrate the use of Scapy to perform Wifi deauthentication, ARP cache poisoning and DHCP Starvation attacks. Use the code from the suggested github repos (or more) to create a single platform to launch several attacks.

https://github.com/veerendra2/wifi-deauth-attack

https://github.com/rusec/scapy-arpspoof-demo

https://github.com/peppelinux/pyDHCPStarvator

REIST Clément

22

Snort Intrusion Detection

Demonstrate the use of Snort3 as Intrusion Detection System analysing PCAP files including TCP SYS scans and DoS attacks

https://github.com/snort3/snort3_demo/tree/master

https://www.snort.org/

JOSEPH-MONDESIR Gérald

23

Labelled data vs unlabelled data

Use ISF ML algorithm and compare the ML performance metrics

https://github.com/mhdadizadeh/CICDDoS2019/blob/master/CICDDoS2019.ipynb

24

Binary neural networks

Compare the performance of BNNs to other non BNN models (choose another DL model)

https://github.com/mhdadizadeh/CICDDoS2019/blob/master/CICDDoS2019.ipynb

https://arxiv.org/abs/2110.06804

25

Rancher demo

Demo Rancher by deploying and managing a microservices-based application. The project will demonstrate how Rancher simplifies the deployment and orchestration of containerized applications.

https://ranchermanager.docs.rancher.com/pages-for-subheaders/quick-start-guides

Julien Dillenseger

26

KubeVirt

Illustrate the capacity of KubeVirt by demonstrating how it can create and manage virtual machines (VMs) within a Kubernetes environment.

https://kubevirt.io/quickstart_minikube/

Freddy PEZERON

27

Firewall  BPF/XDP

Simulate a denial of service attack and demonstrate the performance of BPF/XDP in handling and mitigating the attack by efficiently filtering and processing network traffic.

http://arthurchiao.art/blog/firewalling-with-bpf-xdp/

https://dev.to/xenbytes/simple-xdp-firewall-with-golang-1da3

Othmane Essabil 

28

eBPF exploitation

Demonstrate some security vulnerabilities in eBPF and effective mitigations to enhance the security of eBPF-enabled environments.

https://sysdig.com/blog/ebpf-offensive-capabilities/

KEFKEF Ahmed

YILDIRIM Umit