ocatak

6g-channel-estimation-dataset

6G Wireless Communication Security - Deep Learning Based Channel Estimation Dataset

6g_security

6G and Security repository for telecommunications and AI research. We will share our implementations and publications in 5G and beyond technology, 6G, Security, Machine learning on 6G, Massive MIMO, THz communication and communication networks.

adversarial-ml-training

apache-http-logs

to detect vulnerability scans, XSS and SQLI attacks, examine access log files for detections.

devsecops-tutorial

DevSecOps best practices with a vulnerable Flask based web application

Homomorphic-Neural-Cryptography

Master thesis, Asymmetric Neural Cryptography with Homomorphic Properties

lstm_malware_detection

malware_api_class

Malware dataset for security researchers, data scientists. Public malware dataset generated by Cuckoo Sandbox based on Windows OS API calls analysis for cyber security researchers

TradeRES-BC-Portal

TradeRES EU Project: A pioneering Ethereum-based blockchain framework for facilitating secure and efficient energy trading. This repository houses the smart contracts for the EnergyToken and EnergyExchange platforms, enabling the production, consumption, and trading of renewable energy tokens. Explore the future of decentralized energy markets.

trustworthyai

Trustworthy AI: From Theory to Practice book. Explore the intersection of ethics and technology with 'Trustworthy AI: From Theory to Practice.' This comprehensive guide delves into creating AI models that prioritize privacy, security, and robustness. Featuring practical examples in Python, it covers uncertainty quantification, adversarial ML

ocatak/malware_api_class

Malware dataset for security researchers, data scientists. Public malware dataset generated by Cuckoo Sandbox based on Windows OS API calls analysis for cyber security researchers

ocatak/6g-channel-estimation-dataset

6G Wireless Communication Security - Deep Learning Based Channel Estimation Dataset

ocatak/6g_security

6G and Security repository for telecommunications and AI research. We will share our implementations and publications in 5G and beyond technology, 6G, Security, Machine learning on 6G, Massive MIMO, THz communication and communication networks.

ocatak/apache-http-logs

to detect vulnerability scans, XSS and SQLI attacks, examine access log files for detections.

ocatak/devsecops-tutorial

DevSecOps best practices with a vulnerable Flask based web application

ocatak/trustworthyai

Trustworthy AI: From Theory to Practice book. Explore the intersection of ethics and technology with 'Trustworthy AI: From Theory to Practice.' This comprehensive guide delves into creating AI models that prioritize privacy, security, and robustness. Featuring practical examples in Python, it covers uncertainty quantification, adversarial ML

ocatak/Homomorphic-Neural-Cryptography

Master thesis, Asymmetric Neural Cryptography with Homomorphic Properties

ocatak/TradeRES-BC-Portal

TradeRES EU Project: A pioneering Ethereum-based blockchain framework for facilitating secure and efficient energy trading. This repository houses the smart contracts for the EnergyToken and EnergyExchange platforms, enabling the production, consumption, and trading of renewable energy tokens. Explore the future of decentralized energy markets.

ocatak/5g-rng

5G Spectrogram-based Random Number Generation for Devices with Low Entropy Sources

ocatak/adversarial-detection

ocatak/book-projects

ocatak/ocatak.github.io

ocatak/PMU-Anomaly-Detection

Trustworthy Cyber-physical Power Systems using AI: Dueling Algorithms for PMU Anomaly Detection and Cybersecurity

ocatak/social-insecurity

ocatak/uncertainty_in_llm

Code and experiments for the research paper "Uncertainty Quantification in Large Language Models Through Convex Hull Analysis" published in Discover Artificial Intelligence (2024).

ocatak/VLM_Uncertainty

ocatak/6G-Homomorphic-Enc-Federated-Learning

ocatak/6g_MIMO_security_distillation

ocatak/boosted-elm-with-map-reduce

ocatak/Homomorphic-Encryption-and-Federated-Learning-based-Privacy-Preserving-CNN-Training-

Medical data is often highly sensitive in terms of data privacy and security concerns. Federated learning, one type of machine learn- ing techniques, has been started to use for the improvement of the privacy and security of medical data. In the federated learning, the training data is distributed across multiple machines, and the learning process

ocatak/Homomorphic-Encryption-Based-Privacy-Preserving-ELM

ocatak/multikey-homomorphic-encryption

ocatak/Neural-Cryptography

ocatak/ocatak

ocatak/programming-dp

ocatak/RadarSpectrumSensing-FL-AML

ocatak/rec_dlt

ocatak/SonarQube

Setting up sonarqube using docker

ocatak/uncertainty-based-attack-defense

ocatak/xai_covid19