Comprehensive digital library showcasing our extensive academic contributions across quantum-resistant cybersecurity domains and vulnerabilities.
Breakthrough studies and recent publications from our research team
Dr. Franciny Salles Rojas, Dr. Michael Rodriguez, Prof. David Kim
Published: August 2025 | Citations: 156 | Downloads: 2,847
Comprehensive analysis of migration pathways from classical to quantum-resistant cryptographic systems, addressing performance implications and security considerations...
Col. James Anderson, Dr. Franciny Salles Rojas Marin, Prof. Robert Martinez
Published: November 2024 | Citations: 89 | Downloads: 1,523
Novel application of zero-knowledge proofs in high-security military environments, ensuring authentication without revealing sensitive operational data...
Dr. Elena Petrov, Dr. Thomas Zhang, Dr. Franciny Salles Rojas Marin
Published: October 2024 | Citations: 203 | Downloads: 3,156
Comprehensive framework for assessing quantum threats to power grids, financial networks, and telecommunications infrastructure...
Research Team and Dr. Franciny Salles Rojas Marin
Published: October 2024 | Citations: 203 | Downloads: 3,156
This whitepaper presents a critical vulnerability found in the popular Node.js package form-data, where multipart boundaries are derived from Math.random(), leading to predictable values under low-entropy conditions. This design flaw allows attackers to preempt or replicate the boundary used by legitimate clients, enabling multipart forgery, parameter injection, and privilege escalation in multipart/form-data HTTP POST requests.
Research Team and Dr. Franciny Salles Rojas Marin
Published: October 2024 | Citations: 203 | Downloads: 3,156
This whitepaper documents a critical buffer overflow vulnerability in OpenSSL version 1.1.1k, discovered during an internal vulnerability audit of a Node.js-based application running on Alpine Linux. The vulnerability, CVE-2021-3711, is related to the improper handling of ciphertext padding during decryption via the EVP_DecryptFinal_ex() function, which can result in memory corruption and potentially lead to denial of service (DoS) or remote code execution (RCE).
Research Team and Dr. Franciny Salles Rojas Marin
Published: October 2024 | Citations: 203 | Downloads: 3,156
This whitepaper documents a critical SQL Injection vulnerability discovered in Sequelize version 4.44.4, a widely used Node.js ORM. The flaw stems from improper input sanitization when constructing raw queries with the replacements parameter and unsafe string concatenation practices. Our research demonstrates how this vulnerability can be exploited to bypass authentication, exfiltrate sensitive data, and execute destructive operations against the underlying database. The vulnerability was validated in controlled environments and affects multiple database engines supported by Sequelize, including SQLite, MySQL, PostgreSQL, and MSSQL. This document provides a comprehensive technical analysis, a working Proof of Concept (PoC), and remediation strategies
Research Team and Dr. Franciny Salles Rojas Marin
Published: October 2024 | Citations: 203 | Downloads: 3,156
This paper expands upon the foundational aspects of the Chaum-Pedersen protocol, providing a comprehensive and technical deep dive into its algebraic settings, protocol specifications, and security properties. We will also explore its diverse applications, offer detailed engineering guidance, and present a robust Python reference implementation
Research Team and Dr. Franciny Salles Rojas Marin
Published: October 2024 | Citations: 203 | Downloads: 3,156
This whitepaper provides a comprehensive analysis of Open-Source Intelligence (OSINT) as a critical discipline in the investigation of complex and high-stakes cybercrime. It explores the evolution of OSINT from a supplementary data collection method to a cornerstone of modern digital forensics and threat intelligence.
Research Team and Dr. Franciny Salles Rojas Marin
Published: October 2024 | Citations: 203 | Downloads: 3,156
In early September 2025, a sophisticated and large-scale supply-chain attack was identified within the Node Package Manager (NPM) ecosystem. The attack involved the compromise of a popular developer's account, "qix," leading to the publication of malicious versions of several high-impact packages, including chalk , strip-ansi , and color-convert
Research Team and Dr. Franciny Salles Rojas Marin
Published: October 2024 | Citations: 203 | Downloads: 3,156
This whitepaper presents a comprehensive, data-driven framework designed to systematically unmask and combat money laundering within cryptocurrency networks. We detail a multi-layered approach that begins with foundational heuristic-based clustering to establish a baseline of entity identification, progresses to unsupervised machine learning to discover novel and complex laundering patterns, and culminates in an advanced supervised learning model leveraging Graph Neural Networks (GNNs) for high-accuracy classification of illicit activities
Research Team and Dr. Franciny Salles Rojas Marin
Published: October 2024 | Citations: 203 | Downloads: 3,156
The advent of blockchain technology introduced a paradigm of radical transparency, yet this very feature has given rise to a powerful counter-movement towards enhanced on-chain privacy. This whitepaper delves into the escalating and technically profound conflict between privacy-enhancing technologies (PETs) and the established discipline of blockchain forensics.
Research Team and Dr. Franciny Salles Rojas Marin
Published: October 2024 | Citations: 203 | Downloads: 3,156
This paper introduces a novel mathematical framework for the forensic analysis of privacy-enhanced blockchains that utilize Zero-Knowledge Proofs (ZKPs). As ZKPbased systems like Zcash and Tornado Cash become increasingly prevalent, they present a formidable challenge to traditional blockchain forensic techniques, which rely on the transparency of the public ledger. We address this challenge by developing a rigorous, mathematically-grounded framework that combines advanced cryptographic analysis, statistical modeling, and graph-theoretic techniques to enable the probabilistic de-anonymization and forensic investigation of shielded transactions.
Research Team and Dr. Franciny Salles Rojas Marin
Published: October 2024 | Citations: 203 | Downloads: 3,156
This whitepaper presents Fikresekhel, a novel and robust framework for the advanced detection of web-based malware. As cyber threats continue to evolve in sophistication, traditional signature-based antivirus solutions are increasingly insufficient. Fikresekhel addresses this challenge by integrating a multi-layered detection strategy that combines static analysis, dynamic analysis, and machine learning-based behavioral analysis