Title:
Enhancing Privacy-Preserving Authentication through NIST, PCI, IETF, and ICANN Compliant Encryption and Zero-Knowledge Proofs
Abstract:
This proposal aims to develop an advanced mathematical framework for a third-party service provider to authenticate device users' activities while preserving privacy. The framework will utilize encrypted GPS coordinates and multi-factor authentication in compliance with NIST, PCI, IETF, and ICANN standards. It will focus on Zero-Knowledge Proofs (ZKPs) to maintain user privacy, exploring three distinct models: the plain model, the common random string model, and the random oracle model.
Introduction:
- Background: As digital interactions increase, the need for robust, privacy-preserving authentication mechanisms becomes crucial.
- Objective: To create a mathematical model for third-party verification that adheres to international standards and utilizes ZKPs to ensure user privacy during various digital interactions.
Standards and Compliance:
- NIST (National Institute of Standards and Technology): Explore encryption standards and guidelines for secure cryptographic practices.
- PCI (Payment Card Industry): Incorporate data security standards for handling GPS and transaction-related data.
- IETF (Internet Engineering Task Force): Follow protocols and standards for internet security, including SSL/TLS for sessions and RDP connections.
- ICANN (Internet Consortium for Assigned Names and Numbers): Ensure compliance with domain name and IP address standards for device authentication.
Methodology:
Expected Outcomes:
Significance:
- For Users: Ensures privacy and security in digital transactions and interactions.
- For Service Providers: Provides a reliable and compliant way to authenticate user activities.
- For Regulatory Bodies: Sets a new standard for privacy-preserving, compliant authentication systems.
It is essential to research the advancement of authentication systems that prioritise privacy by employing encryption, zero-knowledge proofs, and complying with industry standards (Jo, 2020; LogicMonitor, n.d.; Microsoft, 2022). In order for a technical solution to be successful, it must carefully manage the authentication process, maximise efficiency, improve user experience, and protect user privacy (CyberArk, n.d.; Influencer Marketing Hub, n.d.).
Multiple factors necessitate resolution:
1. Which user activities necessitate authentication, and what degree of certainty is required? The sources above (FreeCodeCamp, 2022; Influencer Marketing Hub, n.d.; LogicMonitor, n.d.; Microsoft, 2022) provide the primary impetus for developing and implementing authentication factors and techniques.
2. Zero-knowledge proofs can demonstrate significant computational intricacy. An evaluation is necessary to analyse the compromises in performance between privacy and efficiency (Goldwasser et al., 1988; Jo, 2020; Vadhan, 2022).
3. Over a period of time, encrypted GPS coordinates can still provide approximate locations. Assessing the necessary level of hiding one's location (FPf, 2020; IRJET, 2019; Stack Exchange, 2022).
4. Mapping and implementing the required NIST, PCI, IETF, and ICANN standards and ensuring compliance with encryption, protocols, and other requirements is a complex task (NIST, 2022a, 2022b, 2022c; IETF, n.d.).
5. Conducting a comprehensive analysis of the privacy guarantees provided by zero-knowledge proofs and other components (Aimultiple, 2023; Identity.com, n.d.; MakeUseOf, 2022).
6. Performing tests to detect vulnerabilities, such as side-channel attacks, that could possibly compromise user privacy (Goodwill et al., 2021; MIT News, 2022a, 2022b; Springer, 2021).
Given the supplementary contextual details, I am now able to formulate a more comprehensive technological proposal and a compelling call to action:
Directive:
Privacy-preserving authentication solutions are urgently required to verify user identities and actions securely in an increasingly digitalised world. With the rapid increase in cyber dangers, individual privacy and security protection are becoming more vulnerable without adequate measures. I urge the cryptography, security, and standards community to prioritise the investigation and advancement of authentication protocols that utilise encryption, zero-knowledge proofs, and rigorous adherence to industry standards to strengthen privacy safeguards. I specifically propose the promotion of collaborative endeavours among academic researchers, technology providers, government agencies, regulatory bodies, and advocacy groups. The aim is to develop and establish standardised privacy-focused authentication methods for various applications such as financial transactions, border security, and online communications. It is imperative to prioritise the implementation of user privacy by fostering collaboration in both scientific and social domains.
Proposal for Technical Solution:
Objective: Create a mathematical system for multi-factor authentication that incorporates encrypted GPS coordinates, zero-knowledge proofs (ZKPs), and strict compliance with standards set by NIST, PCI DSS, IETF, and ICANN. The primary goals are to uphold privacy, provide security, and sustain efficiency.
Cryptographic Standards: Utilize Hybrid Encryption by creating a symmetric Data Encryption Key (DEK) using ECC or RSA Asymmetric Encryption according to NIST rules. Utilise the Data Encryption Key (DEK) to secure Global Positioning System (GPS) data by employing a symmetric cypher, such as AES-256, that has been authorised by the National Institute of Standards and Technology (NIST). Apply the SHA-256 algorithm to the ciphertext. Every key must possess an ample amount of randomness and flawless protection against future compromise.
Multi-factor Authentication: Incorporate encrypted GPS, device IDs, user passwords/biometrics, and secure timestamps into the authentication process using OCSP and OAuth2 authorisation standards. Verify the authenticity of device certificates by checking them against OCSP responders for each request. Enforce the need for reauthentication after 30 minutes of no activity.
Zero-Knowledge Proofs: Utilize zk-SNARKs to verify the location of an individual within predefined bounds, confirming traits such as age without disclosing exact GPS coordinates or other confidential data. Employ ECC scalar multiplication within the standard reference string model to enhance efficiency. Adhere to the standards set by IETF/W3C for Decentralised Identifiers.
Through thorough and rigorous testing, side channel protections involve mitigating vulnerabilities such as power analysis, electromagnetic leaks, and timing attacks. Employ masking, noise injection, and removal of deterministic patterns.
The primary objective of this framework is to prioritise user privacy while ensuring security, performance, and adherence to standards. I perceive it as a potential model for extensive implementation across several sectors. Please provide feedback about improvements, collaborations, or assessment of this project.
References:
Here are the references in APA 7th edition format:
Aimultiple. (2023). Zero-knowledge proofs: How it works & use cases in 2023. https://research.aimultiple.com/zero-knowledge-proofs/
CyberArk. (n.d.). What is authentication and authorization? https://www.cyberark.com/what-is/authentication-authorization/
FreeCodeCamp. (2022). Secure user authentication methods – 2FA, biometric, and passwordless. https://www.freecodecamp.org/news/user-authentication-methods-explained/
FPf. (2020). Policy brief: Location data under existing privacy laws. https://fpf.org/wp-content/uploads/2020/12/FPF_Guide_Location_Data_v2.2.pdf
Goldwasser, S., Micali, S., & Rackoff, C. (1988). Concurrent zero knowledge without complexity assumptions. In Proceedings of the seventeenth annual ACM symposium on Theory of computing (pp. 365-377). https://doi.org/10.1145/62212.62222
Goodwill, G., Jun, B., Jaffe, J., & Rohatgi, P. (2021). A testing methodology for side channel resistance validation. https://csrc.nist.gov/csrc/media/events/non-invasive-attack-testing-workshop/documents/08_goodwill.pdf
Identity.com. (n.d.). Securing data with zero-knowledge proofs. https://www.identity.com/zero-knowledge-proofs/
IETF. (n.d.). IETF | Security & privacy. https://www.ietf.org/topics/security/
Influencer Marketing Hub. (n.d.). What are the levels of authentication? https://influencermarketinghub.com/glossary/levels-of-authentication/
IRJET. (2019). Geo encryption using GPS co-ordinates. https://www.irjet.net/archives/V6/i1/IRJET-V6I1345.pdf
Jo, T. (2020). An exploration of zero-knowledge proofs and zk-SNARKs (Publication No. 28239) [Master's thesis, University of Pennsylvania]. Fisher Digital Publications. https://fisher.wharton.upenn.edu/wp-content/uploads/2020/09/Thesis_Terrence-Jo.pdf
LogicMonitor. (n.d.). What are the different types of authentication? https://www.logicmonitor.com/blog/what-are-the-different-types-of-authentication
MakeUseOf. (2022). What is a zero-knowledge proof in cybersecurity, and how does it work? https://www.makeuseof.com/what-is-a-zero-knowledge-proof/
Microsoft. (2022). What is authentication? Definition and methods. https://www.microsoft.com/en-us/security/business/security-101/what-is-authentication
MIT News. (2022a). Keeping web-browsing data safe from hackers. https://news.mit.edu/2022/side-channel-attacks-detection-0609
MIT News. (2022b). Thinking like a cyber-attacker to protect user data. https://news.mit.edu/2022/chip-interconnect-side-channel-attacks-0811
NIST. (2022a). Cryptographic standards and guidelines. https://csrc.nist.gov/Projects/Cryptographic-Standards-and-Guidelines
NIST. (2022b). Cybersecurity framework. https://www.nist.gov/cyberframework
NIST. (2022c). Guideline for using cryptographic standards in the federal government. https://nvlpubs.nist.gov/nistpubs/SpecialPublications/NIST.SP.800-175Br1.pdf
Springer. (2021). Security beyond cybersecurity: Side-channel attacks against embedded systems. https://link.springer.com/article/10.1007/s10207-021-00563-6
Stack Exchange. (2022). Encrypting/Salting GPS coordinates. https://crypto.stackexchange.com/questions/95418/encrypting-salting-gps-coordinates
Vadhan, S. P. (2022). The beginnings of zero-knowledge. https://blog.computationalcomplexity.org/2022/02/the-beginnings-of-zero-knowledge.html
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