BlockBallot
BlockBallot is a next-generation blockchain-based electronic voting system developed to revolutionize Sri Lanka’s electoral process. Traditional elections in Sri Lanka rely heavily on manual, paper-based procedures, resulting in high costs, significant logistical challenges, security vulnerabilities, and delays in result announcements. BlockBallot directly addresses these issues by harnessing the power of blockchain technology, QR-based voter verification, and real-time digital vote counting to ensure a transparent, secure, and efficient voting experience for all citizens.
The system enables each registered voter to be authenticated through a unique QR code, eliminating manual errors and reducing the potential for fraud or duplicate voting. Votes are cast electronically on tablets at polling stations, instantly encrypted and immutably stored on the Ethereum blockchain. This automated process delivers real-time vote counting, immediate results, and comprehensive audit trails—removing the delays and inaccuracies of manual counting. Voters receive a printed receipt as confirmation, enhancing trust and transparency.
Accessibility and inclusivity are central to BlockBallot’s design, featuring a multilingual interface (Sinhala, Tamil, and English) and alternative voter identification options to accommodate all demographics, including those without traditional ID cards. The solution’s robust security measures, such as end-to-end encryption and role-based access controls, ensure compliance with both local and international data protection standards.
By digitizing the voting process, BlockBallot significantly reduces costs, environmental impact, and barriers to participation, while enabling rapid, reliable, and tamper-proof elections. Ultimately, BlockBallot empowers every Sri Lankan to participate confidently in a secure, transparent, and modern democratic process.
CeyLand – Blockchain Based Land Document Management System
CeyLand is a blockchain-powered land document management platform designed to modernize and secure property ownership processes in Sri Lanka. Traditional land registration systems rely heavily on paper documentation, making them vulnerable to fraud, loss, and manipulation. CeyLand addresses these challenges by offering a secure, transparent, and immutable digital solution. The platform begins with a KYC verification process, ensuring that only verified users connected through their MetaMask wallets can access the system. Once verified, users can upload their land deeds, which are then reviewed by certified legal professionals to confirm their authenticity. Verified deeds are permanently stored on a decentralized blockchain ledger, ensuring they are tamper-proof and resistant to data loss or natural disasters. CeyLand also enables effortless land ownership transfers, where users can initiate transfer requests directly to buyers. These transactions are verified by trusted notaries and recorded on the blockchain for full transparency. Additionally, the system allows users to track the complete ownership history of any property, promoting informed decision-making and reducing disputes. CeyLand also provides access to legal professionals and a user-friendly resource center to help navigate Sri Lanka’s land registry regulations. Overall, CeyLand delivers a secure, efficient, and legally robust solution for property management.
ZKSafe: Enhancing Crypto Wallet Usability and Security Through Zero-Knowledge Proof-Based Authentication
Security and cryptocurrency wallet use are still at the center of the issues with blockchain adoption. Seed phrase-based physical wallets and private key management can result in loss, theft, and user mistake and provide entry points for mainstream use. Centralized key storage is convenient but exposes access vulnerabilities to breaches and unauthorized viewing. This study suggests a non-custodial crypto wallet with Zero-Knowledge Succinct Non-Interactive Argument of Knowledge (zk-SNARK) verification for improved security and convenience. The system offers ownership proof of the wallet without the disclosure of the private key, which maintains confidentiality and avoids utilization of the classic seed phrase recovery. The wallet uses modular design with backend features written in Node.js and Express.js, frontend in Angular, and MongoDB for safe storage of users’ data. The wallet transactions are processed by ethers.js, directly on the Ethereum blockchain. The private keys are encrypted by AES too, thus reducing exposure risk. The architecture is client-server with zk-SNARK proofs created and checked to verify the users and grant them access to their wallets. Future work will move proof creation to the client side so that private keys are never exported from the user device, giving additional security. The system was tested using functional testing, confirming key operations like wallet generation, verification, transaction handling, and secure key storage. The system was validated structured functional, integration and system level tests. The test scenarios included the core functionality of the wallet with the ZKP integration. Edge case testing was also conducted to ensure robustness against invalid inputs and unauthorized access attempts. All core features passed the validation tests under expected and abnormal scenarios. Although, performance and usability metrics were not captured due to lack of deployment the successful integration of wallet operation and ZKP shows the feasibility of the project.
Omnify – Blockchain-Based Smart Contract System for Game Tournament Management
Omnify is a blockchain-based system to improve game tournament management, addressing transparency, security, and fairness issues. Using Ethereum and Solidity smart contracts, it automates prize distribution and result verification with a tamper-proof ledger. Its React Next.js frontend with Web3 integration offers an intuitive interface, boosting trust and efficiency in eSports and online gaming tournaments.
Learning State Machines for Adaptive Authentication
Traditional authentication systems using only the username-password method are increasingly inadequate in addressing modern security threats, as they fail to adapt to dynamic risks. This project focuses on developing an adaptive authentication system using the learning state machines concept, which adjusts security protocols based on user behaviour, device type, and contextual factors, offering a more secure and adaptable approach to user authentication with a lesser usage of computational power. An adaptive authentication system was developed based on a probabilistic finite learning state machine that considers user behaviour and contextual factors to analyse the risk associated with the login attempt. Depending on the analysis, the system proceeds with the adaptive authentication to ensure a secure and user-friendly authentication process. The state machine was implemented using FlexFringe; a framework for learning automata.
A Hybrid VAE and GNN-Enhanced Few-Shot Learning Approach for Network Intrusion Detection and Adaptation to Novel Attack Classes
Advanced Network Detection Systems are important to detect established and unknown network attacks, as traditional signature-based methods fail against novel threats and supervised machine learning requires extensive labeled data for new attacks. This study proposes a hybrid deep learning approach: an unsupervised Variational Autoencoder (VAE) for anomaly detection, coupled with a GNN-enhanced Few-Shot Learning (FSL) classifier. The VAE, trained solely on ‘Normal’ data from the UNSW-NB15 dataset, identifies anomalies using a high-percentile reconstruction error threshold. Subsequently, a Prototypical Network (ProtoNet), as the FSL classifier, is episodically trained on ‘Normal’ data and a select subset of previously seen attack types to classify these anomalies. Using these, the malware through network traffic is prioritized for newer variants using the few shot component, after the VAE detects the first stage.