eSIM security with Generative AI
Addressing challenges, innovations & measures
Industry is undergoing a major transformation driven by the rise of generative AI technologies. The telecoms sector is no different, as intelligent algorithms and data-driven approaches redefine operations and security measures, especially for eSIMs, are being reimagined to adapt to new standards, such as eSIM IoT's SGP.32 specifications. This article examines how Generative AI can improve the security of eSIMs, highlighting Trasna's development of innovative identity verification systems based on Zero Knowledge Proof (ZKP) algorithms.
The importance of identity
For centuries, identity has been a central theme in philosophy and psychology. In the telecom world, identity is critical to ensure customer verification, fraud prevention, and regulatory compliance, such as KYC (Know Your Customer). However, the move from traditional KYC to eKYC (electronic KYC) in telecoms is where AI shines, providing an autonomous, adaptive, and intelligent system for identity validation.
The challenge for telecom providers is to minimise the distribution of sensitive data across cloud platforms and third-party systems while simultaneously speeding up identity verification processes. Generative AI, alongside TRASNA's implementation of an intelligent Zero Knowledge Proof (i-ZKP) algorithm, can streamline this process and address these security challenges.
Zero-Knowledge Proof: The core of eSIM security
At the heart of eSIM security lies the concept of Zero Knowledge Proofs (zkProofs). A zkProof allows one party (the prover) to demonstrate the truth of a statement to another party (the verifier) without revealing the underlying information. This is a key requirement in security-sensitive environments such as eSIM management.
Three key properties define zkProofs:
- Completeness: The verifier will always be convinced if the statement is true.
- Soundness: A deceptive prover cannot convince an honest verifier of a false statement.
- Zero Knowledge: No information other than the validity of the statement is shared with the verifier.
An advanced form of this, called zk-SNARKs (Succinct Non-Interactive Argument of Knowledge), is widely used in blockchain technology. However, in the context of eSIM security, zkProofs can ensure secure, private transactions, validating identity and network access without exposing sensitive data.
Generative AI: A new frontier for security
Generative AI refers to AI models that create new content (such as text, images, or data models) based on existing data. It relies on unsupervised and self-supervised learning techniques, enabling machines to learn patterns without explicit labels. TRASNA's i-ZKP protocol integrates Generative AI to make ZKP algorithms more efficient and intelligent.
How does Trasna’s intelligent ZKP (i-ZKP) work?
TRASNA is pioneering the integration of Generative AI with Zero-Knowledge cryptography to authenticate identities and secure eSIM usage. Here's how it works: Generative AI can validate specific instances of data, such as identity information, while zkProofs hide parts of the process to ensure privacy. This approach enables eSIM providers to verify identity securely and quickly without exposing sensitive data.
It is important to note that whilst i-ZKP can be a game changer for eSIM security as it can add significant value in authentication and fraud prevention any proposed implementations must align strictly with SGP.22 and SGP.32 GSMA specification standards rather than conventional crypto methods to ensure interoperability, security, and regulatory compliance.
Use cases for AI and ZKP in eSIM security
1. Automated threat detection with AI-enhanced anomaly detection
Innovation: Generative AI can detect anomalies in network usage, identifying potential security threats in eSIM operations. ZKP ensures the detection methods remain private.
Impact: Faster detection of fraud and unauthorised access while protecting sensitive network data.
2. AI-driven contextual security levels
Innovation: AI adapts security measures based on the user's location or network conditions, while ZKP verifies security enforcement without exposing location data.
Impact: Enhanced protection, especially for users in high-risk environments, without compromising privacy.
3. eSIM profile generation with Generative AI
Innovation: Generative AI can generate customised eSIM profiles for users, ensuring they adhere to security standards with the help of ZKP.
Impact: Simplifies the management of multiple eSIM profiles while maintaining security and compliance.
4. AI-driven eSIM activation via secure remote protocols
Innovation: AI optimises eSIM activation based on user data, and ZKP verifies the process without revealing sensitive information.
Impact: Streamlines the eSIM activation process, making it more secure and user-friendly.
Conclusion
TRASNA's innovative approach demonstrates the potential for Zero Knowledge Proof (ZKP) protocols to drive eSIM security. By combining Generative AI with ZKP, security processes become more intelligent, adaptive, and secure. In these use cases, AI supports ZKP as a security enabler, moving beyond traditional applications.
For a deeper understanding of TRASNA's intelligent Zero Knowledge Proof (i-ZKP), readers are encouraged to explore further.
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