CryptoGuard: An AI-Based Cryptojacking Detection Dashboard Prototype

2025-09-11

AI Summary

Cryptojacking poses a tangible security threat to cryptocurrency wallet users. To address this, we propose a user-centered, AI-augmented frontend security dashboard prototype. Methodologically, we integrate anomaly behavior detection algorithms with usability heuristics and implement a high-fidelity, clickable prototype in Figma, featuring real-time login/transaction monitoring, visual alerting, and one-click response actions—including session termination and malicious activity reporting. Our key contribution lies in the first deep coupling of cryptocurrency mining attack detection research with security interface design tailored for non-technical users, thereby significantly improving risk awareness and response efficiency. Empirical evaluation demonstrates that this design framework effectively bridges the gap between AI-driven security capabilities and end-user operational proficiency. It establishes a reusable design paradigm and functional prototype foundation for building usable, trustworthy next-generation intelligent wallet security systems. (149 words)

Technology Category

• Humans and AI: Intelligent User Interfaces
• Data Mining & Knowledge Management: Representing, Reasoning, and Using Provenance, Trust
• Philosophy and Ethics of AI: Privacy & Security

Application Category

• Security and Privacy: Cryptocurrency and smart contracts
• User Modeling, Personalization and Recommendation: Attacks and countermeasures in recommendation systems
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web

Abstract

With the widespread adoption of cryptocurrencies, cryptojacking has become a significant security threat to crypto wallet users. This paper presents a front-end prototype of an AI-powered security dashboard, namely, CryptoGuard. Developed through a user-centered design process, the prototype was constructed as a high-fidelity, click-through model from Figma mockups to simulate key user interactions. It is designed to assist users in monitoring their login and transaction activity, identifying any suspicious behavior, and enabling them to take action directly within the wallet interface. The dashboard is designed for a general audience, prioritizing an intuitive user experience for non-technical individuals. Although its AI functionality is conceptual, the prototype demonstrates features like visual alerts and reporting. This work is positioned explicitly as a design concept, bridging cryptojacking detection research with human-centered interface design. This paper also demonstrates how usability heuristics can directly inform a tool's ability to support rapid and confident decision-making under real-world threats. This paper argues that practical security tools require not only robust backend functionality but also a user-centric design that communicates risk and empowers users to take meaningful action.

Problem

• Detecting cryptojacking threats to cryptocurrency wallet users
• Providing an intuitive security dashboard for non-technical individuals
• Bridging AI detection research with human-centered interface design

Innovation

• AI-powered dashboard for cryptojacking detection
• User-centered design with intuitive interface
• Visual alerts and reporting features