adityakankriya
Enthusiastic developer with a passion for creating elegant and efficient solutions. Dedicated to learning and exploring new technologies, and always eager to co
Pinned Repositories
DNS-Crypt
DNS Security Project: 1. DNS CRYPT: Python-based encryption to safeguard hostnames in packets. Responds with fake data to mislead attackers and ensure security. 2. DNS OVER HTTPS: Trained ML model classifies data as DoH or non-DoH and identifies malicious or benign elements to prevent DNS tunneling attacks.
Escaping-The-Caves
This GitHub repo features my CS641 Modern Cryptology course projects, exploring cryptosystems like Substitution cipher, PlayFair cipher, EAEAE, and DES. Employing techniques such as frequency analysis and differential cryptanalysis.
Machine-Learning-MiniProjects
Advanced Explorations in Machine Learning: Unveiling XOR-PUFs, Automated Program Repair, and Character Recognition.
Publisher-Subscriber-Blockchain-Project
Discover a dynamic blockchain employing the publisher-subscriber model for efficient data sharing. Real-time updates, decentralization, and smart contracts enhance secure information dissemination.
CO2-Emission-Predictor
adityakankriya's Repositories
adityakankriya/Escaping-The-Caves
This GitHub repo features my CS641 Modern Cryptology course projects, exploring cryptosystems like Substitution cipher, PlayFair cipher, EAEAE, and DES. Employing techniques such as frequency analysis and differential cryptanalysis.
adityakankriya/Machine-Learning-MiniProjects
Advanced Explorations in Machine Learning: Unveiling XOR-PUFs, Automated Program Repair, and Character Recognition.
adityakankriya/Publisher-Subscriber-Blockchain-Project
Discover a dynamic blockchain employing the publisher-subscriber model for efficient data sharing. Real-time updates, decentralization, and smart contracts enhance secure information dissemination.
adityakankriya/DNS-Crypt
DNS Security Project: 1. DNS CRYPT: Python-based encryption to safeguard hostnames in packets. Responds with fake data to mislead attackers and ensure security. 2. DNS OVER HTTPS: Trained ML model classifies data as DoH or non-DoH and identifies malicious or benign elements to prevent DNS tunneling attacks.