Pinned Repositories
Directed-Acyclic-Graph-for-Peer-to-Peer-Distributed-Communication-in-Vehicular-Network
Internet of things(IoT) and Internet of Vehicles(IoV) are the buzz words today. Building a smart vehicle running on a smart road that could respond to the very urgent requests such as reporting an accident ahead or basic requests such as down- loading a song at the blink of an eye is the hottest topic researchers and computer scientists are working on. The latest testing and later the rolling out of 5G technology will prove to be a boon in providing the required speed, which will further enhance safety as well as Quality-of-service(QoS) concerns. Hashgraphs, a superior distributed ledger technology, is used to create a communication network between various ve- hicles and other essential parameters. The decentral- ized system will check any delay in responses through the inherent consensus process, which is the USP of hashgraph. Scheduling the requests is done according to the priorities to provide a better Quality-of-Service. We have also compared why hashgraph surpasses other counter-parts such as generic blockchain or ethereum. The proposed model is simulated using Omnetpp simulation by making proper design and network description files. Messages can be seen getting transferred between the vehicles, and hashgraph is implemented for prioritizing the messages
Energy-efficient-data-detection-for-uplink-multiuser-massive-mimo-systems
Insider-Threat-and-Anomaly-Detection-from-User-Activities
Anomaly detection in network traffic and event logs using deep learning (w/ Pytorch)
Intern-work
compare the performance of the model in deep learning and svm to find the best way to use with sdn classify DDoS attack
link-level-performance-evaluation-of-mimo
Evaluate the capacity and error rate performance of basic MIMO transmission and reception schemes.
mimo-detect-and-decode
mininet-wifi-projects
mininet-wifi-projects
Network-Traffic-Classification-2
Uses Neural Net for Classification
ns2-leach
leach ns2.35
SDUWN
Software-Defined Underwater Wireless Networks
rubiruchi's Repositories
rubiruchi/5G-Flow-RAN
rubiruchi/5GIIK-testbed
rubiruchi/Amazing-Python-Scripts
🚀 Curated collection of Amazing Python scripts from Basics to Advance with automation task scripts.
rubiruchi/awesome-chatgpt-prompts
This repo includes ChatGPT prompt curation to use ChatGPT better.
rubiruchi/awesome-ml-for-cybersecurity
:octocat: Machine Learning for Cyber Security
rubiruchi/BAMSDN
rubiruchi/CFR-RL
CFR-RL: Traffic Engineering with Reinforcement Learning in SDN
rubiruchi/CICI-SAFE
rubiruchi/Classifier-methods-on-IRIS-Dataset---Deep-Learning-Included
rubiruchi/DA-SDN
Python implementation of "A Clustering Approach to Edge Controller Placement in Software Defined Networks with Cost Balancing"
rubiruchi/DCLNet
rubiruchi/DeepLearning_irisdataset_beginnner
This repository contains a simple sequential model which I have used for the classification problem for the Iris_dataset. CSV file is also inculded. This repository should be used as a guide/tutorial to train an introductory deep learning project.
rubiruchi/ECGR4090-ML-IoT
Template repository for assignments for ECGR 4090/5090 ML for IoT
rubiruchi/IoT-Network-Intrusion-Detection-and-Classification-using-Explainable-XAI-Machine-Learning
The continuing increase of Internet of Things (IoT) based networks have increased the need for Computer networks intrusion detection systems (IDSs). Over the last few years, IDSs for IoT networks have been increasing reliant on machine learning (ML) techniques, algorithms, and models as traditional cybersecurity approaches become less viable for IoT. IDSs that have developed and implemented using machine learning approaches are effective, and accurate in detecting networks attacks with high-performance capabilities. However, the acceptability and trust of these systems may have been hindered due to many of the ML implementations being ‘black boxes’ where human interpretability, transparency, explainability, and logic in prediction outputs is significantly unavailable. The UNSW-NB15 is an IoT-based network traffic data set with classifying normal activities and malicious attack behaviors. Using this dataset, three ML classifiers: Decision Trees, Multi-Layer Perceptrons, and XGBoost, were trained. The ML classifiers and corresponding algorithm for developing a network forensic system based on network flow identifiers and features that can track suspicious activities of botnets proved to be very high-performing based on model performance accuracies. Thereafter, established Explainable AI (XAI) techniques using Scikit-Learn, LIME, ELI5, and SHAP libraries allowed for visualizations of the decision-making frameworks for the three classifiers to increase explainability in classification prediction. The results determined XAI is both feasible and viable as cybersecurity experts and professionals have much to gain with the implementation of traditional ML systems paired with Explainable AI (XAI) techniques.
rubiruchi/Iris.DeepLearning
rubiruchi/iris_predictor_web_app
Iris Predictor with Deep Learning | Web App
rubiruchi/jplag
JPlag - Detecting Software Plagiarism
rubiruchi/LogiTraffic-
Deep Learning || IOT || Web Development
rubiruchi/network-traffic-analysis-
rubiruchi/neurobionicspi
Builds a custom Raspberry Pi image for robotics
rubiruchi/ofsoftswitch13
OpenFlow 1.3 switch.
rubiruchi/p4-macsec
P4-MACsec
rubiruchi/Prompt-Engineering-Guide
🐙 Guides, papers, lecture, notebooks and resources for prompt engineering
rubiruchi/sdn-nfv-papers
This is a paper list about Resource Allocation in Network Functions Virtualization (NFV) and Software-Defined Networking (SDN).
rubiruchi/sdn-pcap-simulator
This is a sdn based pcap simulator
rubiruchi/sdwannewhope
SD-WAN security and insecurity
rubiruchi/Smart-Traffic-Predictor
A Deep Learning model predicts traffic patterns using LSTM neural network and Time Series Analysis at every junction within a city.
rubiruchi/stress-ng
This is the stress-ng upstream project git repository. stress-ng will stress test a computer system in various selectable ways. It was designed to exercise various physical subsystems of a computer as well as the various operating system kernel interfaces.
rubiruchi/webinterface
The web interface for the tool Adam (AdamMC and AdamSYNT) providing an intuitive, visual definition of Petri nets with transits and Petri games, and an interactive interface to the algorithms of AdamMC and AdamSYNT. Contains the repos (as submodules): libs, framework, logics, modelchecking, examples, synthesizer, high-level, webinterface-backend.
rubiruchi/Zero-Time-Waste