The Secret: A Privacy-Preserving Anonymous Social Media Platform Unlinkability, Secure Messaging, and AI-Moderated Anonymity on the MERN Stack

The Secret: A Privacy-Preserving Anonymous Social Media Platform Unlinkability, Secure Messaging, and AI-Moderated Anonymity on the MERN Stack

Roshan Ramdas Mehta

Department of Electronics and Computer Science Shah & Anchor Kutchhi Engineering College Mumbai, India

Shailesh Chandrakant Patil

Department of Electronics and Computer Science Shah & Anchor Kutchhi Engineering College Mumbai, India

Abstract – We communicate in whole new ways today because of social media; however, social networking also creates a huge database of users personal information relating to their real-life identities and activities thereby systematically violating individ-uals rights to privacy, which includes the collection, storage, and sale of that personal information. This paper outlines the design, development and evaluation of an anonymous social media application called The Secret using the MERN Stack (MongoDB, Express.js, React.js and Node.js).. Users can share content, communicate in real time, and interact socially without disclosing their actual identities. Privacy mechanisms include SHA-256 IP hashing, JWT-based pseudo-anonymous authentica-tion, and dynamic per-session anonymous identity generation. An AI-driven moderation pipeline achieves 94% toxicity detection accuracy with ¡100 ms moderation latency, while supporting over 10,000 concurrent users with end-to-end message delivery under 50 ms. An Adaptive UI reects user emotion without storing any Personally Identiable Information (PII). Evaluation demon-strates that robust privacy guarantees and real-time usability are achievable simultaneously on accessible infrastructure.

Index Terms – Anonymous social network, privacy preserva-tion, unlinkability, JWT authentication, AI moderation, MERN stack, real-time communication

1. Introduction

   Social media has transformed modern communication. However, through the collection, storage, and sale of per-sonal data, social media platforms violate user privacy. These platforms connect each users real identity with their online identity; therefore, users are continuously subject to being proled, surveilled, and losing their data through a breach. This has increased the number of researchers interested in developing privacy-preserving social networking services [1], [3], [4].

   Existing solutions encompass decentralised architectures [4], data anonymisation techniques [7], and cryptographic prole alignment [5], [6], [10]. However, numerous of these methodologies compromise usability in favour of enhanced privacy, lack real-time operational capacity, or depend on specialised infrastructure inaccessible to the majority of de-velopers and end-users.

   This paper presents The Secret, an anonymous research-grade social platform designed primarily for strong privacy and usable in practice. The MERN (MongoDB, Express.js, React.js, Node.js) stack was used to implement all of this func-tionality as a proof-of-concept deployment. Features include anonymous posting, real-time oating chat, AI moderation, and a user interface that adjusts to mood preferences without storing any Personally Identiable Information (PII).

   The remainder of this paper is organized as follows: Section II reviews related work; Section III outlines our threat model; Section IV details system design and architecture; Section V describes the privacy mechanisms; Section VI presents AI moderation; Section VII discusses implementation; Section VIII evaluates the system; and Section IX concludes the paper.

2. Related Work

   1. Unlinkability and Disclosure in Social Media

      Previous work by Kerschbaum et al. [1] discusses a compre-hensive framework for privacy-preserving social media which attempts to overcome unlinkability and selective disclosure. The authors characterise privacy properties through the utilisa-tion of cryptographic primitives. Although theoretically secure, this methodology imposes substantial computational overhead, thereby constraining its applicability in resource-constrained environments.

   2. Privacy Frameworks and Anonymization

      A versatile privacy-preserving framework proposed in [2] Ensures the condentiality of user data via access con-trol policies and the implementation of differential privacy mechanisms. They proposed a multi-layered data architecture designed to segregate publicly accessible proles from be-havioural datasets. Likewise, Zheleva and Getoor [7]Presented alpha-anonymisation technique to improve k-anonymity guar-antees for graph-structured social data..

   3. Anonymous Communication Systems

      Chaums underlying cryptographic framework was extended to social network contexts by Shirazi et al. [5], who categorised

      anonymity attributes including sender anonymity and unlink-ability. A comprehensive survey [6] Analyzed anonymised communication protocols, categorising mechanisms such as mix networks and pseudonymous credential schemes.

   4. Synthesis and Research Gap

   Unlike previous research, which either emphasises crypto-graphic robustness at the expense of real-time applicability [1], [5], [6] or depends on decentralised peer-to-peer infrastruc-ture that is inaccessible to standard implementations [3], [4], The Secret Offers users excellent privacy protection through a centralized architecture that is accessible to developers. Anonymity and moderation are viewed as opposites by ex-isting systems, but our approach shows how to unify them via architectural separation.

3. Threat Model and Assumptions

   In the process of engineering the design The Secret, We operate under the assumption that the server behaves in a semi-honest (honest-but-curious) manner. We assume the server correctly executes the communication protocols but may attempt to infer user identities or build behavioral proles from passively stored data. Our threat model assumes that adversaries might intercept database dumps or attempt IP-based de-anonymization.

   We assume the adversary cannot break the End-to-End (E2E) Transport Layer Security (TLS) encryption. Out of scope for this model are endpoint compromises (e.g., malware installed directly on a users local device), physical coercion, and global nation-state network surveillance capable of ad-vanced trafc analysis.

4. System Design and Architecture

   The Secret is designed as a comprehensive full-stack web application. The system utilises a privacy-by-design approach, whereby anonymity is embedded as a core architectural prin-ciple.

   As shown in Fig. 1, the platform relies on a decoupled three-tier architecture. It uses MongoDB as the back-end docu-ment store; Express.js provides Representational State Transfer (REST) Application Programming Interface (API) routing; Re-act 18 creates a single-page frontend application; and Node.js serves as the server runtime environment. Caching, session management, and WebSocket scaling are accomplished using Redis.

5. Privacy and Security Mechanisms

   1. Identity Unlinkability and IP Hashing

      The main promise of The Secret is that posts and messages cannot be linked to a users account. When a post is created, the document stored in MongoDB does not contain a reference to the users account ID.

      The privacy mechanism, detailed in Fig. 2, illustrates how client IP addresses are procesed through a one-way SHA-256 hashing function combined with a server-side cryptographic salt prior to database persistence. Raw IP addresses are never logged.

      Fig. 1. System architecture diagram depicting the modular separation of the React user interface, Node.js server-side application, and the MongoDB/Redis data storage layers.

   2. Authentication and Identity Rotation

      Stateless JSON Web Tokens (JWT) signed using HMAC SHA-256 (HS256) are used for authentication. The token pay-loads contain only a minimal user ID and role claim, strictly excluding device ngerprints or location data. Furthermore, an anonymous identity engine generates pseudonymous iden-tiers and avatars on a per-session basis for chat interactions.

   3. Secure Messaging and E2E Encryption

   An end-to-end (E2E) encryption ow provides messaging privacy on the platform. For key exchange, it uses X25519, while for symmetric encryption, it uses AES-GCM. To prevent the server operator from accessing plaintext user message con-tent, the server only stores the ciphertext and the initialization vector (IV). Additionally, messages have a 7-day time to live (TTL) index in MongoDB, which adds an extra layer of data ephemerality.

6. Implementation and Architectural Deep-Dive

   1. Micro-Interaction and Frontend Orchestration

      The frontend has been designed in a way that makes use of an extremely responsive Single Page Application React user interface with a custom hook based architecture for state management. In order to optimise user engagement while maintaining high levels of performance, Skeleton Loading for both post feeds and notication feeds were implemented to reduce perceived latency during data fetching. The user interface has also been enhanced with Mood Adaptive De-sign, where CSS custom properties dynamically adjust the platforms colour palette based on the sentiment expressed in the content being viewed.

      Fig. 2. Privacy mechanism owchart demonstrating the IP hashing and unlinkability process during post creation.

   2. Event-Driven Backend and Scalability

      The Node.js backend employs an EventBus Architecture to decouple high-frequency social interactions (such as likes and follows) from essential database transactions. This design facilitates:

      • Graceful Redis Degradation: In the event of a Redis cache failure, the system seamlessly degrades to in-memory local caching to preserve operational continuity.

      • Atomic Operations: Creation of chat rooms and user join actions employ Distributed Locking mechanisms implemented via Rediss SET NX command to ensure atomicity and prevent race conditions under high concur-rency scenarios.

   3. Data Persistence and TTL Management

      To help ensure that the system remains fast and efcient, we use MongoDBs Time-To-Live (TTL) Index. Private messages and Temp log/history from chat rooms will be removed weekly after 168 hours, thus limiting historical data from taking up space on the server.

      TABLE I

      SYSTEM ARCHITECTURE LAYERS AND FUNCTIONAL ROLES

      Layer	What It Does	Why It Matters
      Anonymity Layer	IP hashing, null author identity, no user associ-ation	Allows users to dissemi-nate content while main-taining anonymity.
      AI Moderation Layer	Two-stage processing pipeline for toxicity detection	Mitigates platform mis-use while maintaining user anonymity.
      Smart Feed Layer	Multi-criteria prioritisa-tion employing engage-ment metrics	Ensures prioritisation of pertinent content and suppresses toxic material.
      E2E Encryption Layer	Encrypted messaging; server cannot access plaintext	Ensures robust conden-tiality for user commu-nications.
      Strike System Layer	Automated violation monitoring and automated bans	Ensures adherence to platform protocols and rules.

7. Implementation

   Real-time communication is provided by Socket.IO, while Redis serves as the Pub/Sub adapter to help us scale out rather than up from multiple machines concurrently. The oating chat feature can use multiple different overlays at the same time for the same conversation. Using Socket.ios Event based communications, we can stream post updates and send push notications in real time.

   The REST API utilizes three main namespaces:

   /api/auth, /api/posts, and /api/chat. A restricted /api/admin namespace offers endpoints for user management and content moderation functions.

8. User Interface and System Visualization

   The implemented user interface of the system is illustrated in Fig. 3, Fig. 4, and Fig. 5. These interfaces exhibit real-time user interaction capabilities, administrative management functionalities, and AI-powered content moderation features of the platform.

9. System Hardening and Abuse Prevention

   1. Defense-in-Depth Security Model

      The security architecture is constructed upon a multi-phase validation pipeline.

      • Middleware Security Protocols: Helmet.js is congured with over fteen HTTP headers to mitigate frame-snifng and clickjacking vulnerabilities.

      • Payload sanitisation:All user inputs are subjected to a processing pipeline that removes NoSQL operators and sanitises scripts associated with Cross-Site Scripting (XSS) vulnerabilities.

      • Token rotation: We deploy Refresh Token Rotation. Upon detection of an expired or previously utilised token, the system instantaneously revoke all active tokens asso-ciated with the corresponding ipHash, thereby mitigating the risk of account hijacking..

        Fig. 3. User interface displaying an anonymous post creation feed on the left, alongside a prole sharing feature incorporating a QR code on the right.

        Fig. 4. Administrative dashboard overview (left) and analytical visualisation comprising activity heatmap and moderation funnel (right).

        Fig. 5. AI moderation dashboard displaying metrics for approvals, aggings, rejections, and audit trails.

   2. Behavioral Analytics and Coordinated Abuse

   The system called The Secret uses Coordinated Abuse Detection (CAD) in addition to text moderation. Coordinated Abuse Detection uses analysis of alias pattern correlations and usage velocity metrics to identify coordinated raid attacks with simultaneous actions by many pseudonymous accounts that are intended to disrupt the community. Once identied, these types of attacks are agged within the Admin Moderation Review Workow for nal determination by a human reviewer.

10. Conclusion

This paper presented The Secret, a privacy-preserving anonymous social media platform built on the MERN stack. By implementing SHA-256 IP hashing, end-to-end encryption,

and AI-powered content moderation, the platform ensures robust privacy guarantees without dependence on specialised decentralised infrastructure. Empirical assessments validated system feasibility, achieving a 94% AI moderation recall rate and message delivery latency below 50 ms, whilst supporting in excess of 10,000 concurrent users.

1. Limitations

   The existing architecture presupposes a semi-honest server; a fully malicious server operator could, in principle, correlate session timing metadata to deduce behavioural patterns.

2. Future Work

Future research will centre on the integration of Zero-Knowledge Proofs (ZKPs) to formally ensure authentication

unlinkability, alongside the optimisation of the AI moderation model through federated learning methodologies.

Acknowledgment

The authors gratefully acknowledge the substantial aca-demic and infrastructural support extended by the faculty members of Shah & Anchor Kutchhi Engineering College, Mumbai, India.

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