Geneva, Switzerland, November 01, 2024 -- WISeKey International Holding, a global leader in cybersecurity digital identity and Internet of Things (IoT) innovations operating as a holding company, today unveiled a new phase in e-voting technology, which integrates post-quantum cryptography and artificial intelligence (AI) to address the increasing complexity of cybersecurity threats in digital voting. This advancement positions WISeKey and its subsidiary, SEALSQ Corp, as pioneers in secure e-voting, providing a robust solution for governments and institutions committed to a secure, transparent, and efficient electoral process.

WISeKey first entered the e-voting space with a proof of concept in the early 2000s, collaborating with local authorities in Geneva to design an e-voting system that maintained the security, integrity, and accessibility of traditional voting methods while leveraging digital innovation (see article here).

Since then, WISeKey has continuously evolved its e-voting platform, incorporating blockchain, Web 3.0, post-quantum technologies, and now AI.

The integration of post-quantum cryptography through SEALSQ’s state-of-the-art chips provides long-term resistance against quantum attacks, while AI brings enhanced security features, automating detection and response processes to mitigate threats as they arise. Key technologies in this enhanced e-voting system include:

1. Post-Quantum Cryptography for Long-Term Security

With the anticipated arrival of quantum computers capable of breaking conventional encryption, WISeKey’s collaboration with SEALSQ brings critical advancements in post-quantum cryptographic algorithms. These algorithms provide resilience against quantum-powered attacks, using advanced encryption techniques such as the Quantum-Resistant Algorithm CRYSTALS-Kyber. This algorithm, developed in partnership with Mines Saint-Etienne, ensures the security of sensitive voter data, making it computationally infeasible for quantum systems to decrypt or alter voting information.

Post-quantum cryptography in e-voting protects every stage of the voting process, from voter authentication to ballot submission and data storage, ensuring that sensitive information remains secure, private, and immutable even in the face of future quantum threats.

2. Blockchain-Enabled Transparency and Decentralized Verification

Blockchain technology is integral to WISeKey’s e-voting solution, as it provides an immutable ledger that records each vote securely and transparently. By using blockchain’s distributed ledger system, WISeKey ensures that each vote cast is verifiable from start to finish without compromising voter anonymity. This transparency allows stakeholders to monitor the electoral process in real-time, verifying the integrity of each ballot without risk of tampering or altering.

Moreover, smart contracts embedded in the blockchain framework automate election procedures, guaranteeing compliance with election rules and reducing human errors. Blockchain also supports decentralized identity (DID) solutions, ensuring voter authentication is private and secure.

3. Artificial Intelligence for Real-Time Threat Detection and Anomaly Response

AI plays a central role in monitoring and safeguarding e-voting platforms. By deploying machine learning algorithms, WISeKey’s e-voting system continuously monitors and detects any suspicious behavior patterns, such as unusual login attempts or unauthorized access, flagging potential threats in real-time. AI-powered threat detection allows the system to react dynamically to cybersecurity threats as they arise, adjusting security protocols and, if necessary, blocking suspicious activity before it impacts the voting process.

Machine learning-based fraud detection algorithms can identify and differentiate between typical user behavior and irregular voting patterns, ensuring the validity of each ballot cast. This capability provides election administrators with invaluable insights into voting trends and potential threats.

4. Advanced Biometric Voter Authentication

WISeKey’s e-voting platform includes enhanced biometric security options, such as facial recognition, voice recognition, and behavioral biometrics. AI-driven biometric verification strengthens voter authentication, providing an extra layer of security by verifying voter identity with high accuracy. The system continually improves its recognition accuracy by learning from new data, ensuring robust, adaptive, and scalable security measures.
By integrating behavioral biometrics, such as typing patterns or touch behavior on mobile devices, WISeKey enhances security against spoofing and fraudulent voting attempts.

5. Adaptive Encryption for Data Privacy and Access Control

To safeguard voter data and privacy, AI dynamically adapts encryption levels based on perceived threat levels. This adaptive encryption approach ensures that sensitive voter data is accessible only to authorized individuals and systems, preventing unauthorized access and enhancing overall data protection. In the face of potential security threats, adaptive encryption mechanisms reinforce security, preventing data breaches or leaks.

6. Predictive Analytics for Anticipating Cybersecurity Threats

AI-powered predictive analytics add a proactive layer to e-voting security. By analyzing historical data and past security incidents, the system forecasts potential vulnerabilities and points of attack, allowing election administrators to reinforce defenses before threats arise. This foresight is particularly critical for identifying weak points within voting infrastructures and implementing preventive measures to ensure election integrity.

7. Automated Vote Integrity Verification with AI Algorithms

WISeKey’s platform utilizes AI to track each vote from the point of casting through to tallying, ensuring that no manipulation or tampering occurs throughout the process. Automated vote integrity verification cross-references the ballot data against exit polls and historical trends, flagging any anomalies that could indicate tampering.

8. Social Engineering Threat Detection Using Natural Language Processing (NLP)

NLP enables real-time monitoring of social media and communication channels to detect disinformation or social engineering campaigns aimed at manipulating voter perceptions. NLP algorithms identify and analyze keywords, sentiment, and other indicators that suggest attempts to misinform voters. By alerting officials, WISeKey’s AI-driven NLP tools enable a rapid response to any disinformation campaigns, ensuring that voters make informed decisions.

9. Continuous Security Enhancement through Machine Learning

Machine learning algorithms embedded in WISeKey’s e-voting system evolve as they encounter new threats, adapt to emerging attack strategies and continuously enhance security resilience. This continuous improvement process is key to staying ahead of cyber threats, ensuring that the platform remains robust and capable of defending against even the most advanced attacks.

10. Transparent AI for Accountability and Public Trust

To foster public trust, WISeKey’s e-voting AI models are designed with transparency in mind, providing clear explanations for their security decisions. This transparency enables independent auditors and the public to understand how the AI safeguards voting processes, ensuring AI remains an accountable, reliable component of the e-voting system.

11. Advancing Democracy with Technology

By integrating post-quantum cryptography, blockchain, and AI, WISeKey and SEALSQ deliver a secure, reliable, and accessible e-voting platform that advances democratic engagement. This suite of technologies provides election administrators with the tools needed to maintain the integrity, privacy, and transparency of elections in an increasingly digital world, ensuring citizens can vote confidently and securely.