Computationalcoin

Free online secure password generator. Create strong random passwords ranging from 12 to 256 characters, supporting combinations of uppercase and lowercase letters, numbers, and symbols. Generated locally to ensure password security and prevent leakage.

Analysis of a research paper applying adversarial machine learning to improve password strength classification accuracy against deceptive password attacks.

A comprehensive analysis of hbACSS protocols for efficient and robust asynchronous complete secret sharing in multiparty computation systems.

Detailed specification and security analysis of AutoPass, a novel client-side password generator designed to address user and service-related password management challenges.

A comprehensive security analysis of 13 popular password managers, evaluating password generation randomness, storage security, and autofill vulnerabilities, with actionable recommendations.

Comprehensive technical documentation and resources about computationalcoin technology and applications.

Analysis of DPAR, a system that improves user passwords by suggesting specific, memorable tweaks based on a dataset of 905 million leaked passwords.

A novel approach using deep neural networks and dynamic dictionary attacks to reduce measurement bias in password security analysis, providing more accurate adversary modeling.

A novel approach using deep neural networks and dynamic dictionary attacks to reduce measurement bias in password security analysis, providing more accurate adversary modeling.

A novel approach using deep neural networks and dynamic dictionary attacks to model real-world password cracking strategies and reduce measurement bias in password security analysis.

A research paper proposing a formally verified reference implementation for random password generators in password managers, using EasyCrypt for functional correctness and security proofs.

Analysis of formal verification for password generation algorithms in password managers, covering security properties, implementation correctness, and future directions.

Analysis of deep learning models (VAEs, GANs, Attention Networks) for password guessing. Includes technical details, results, and future directions.

Analysis of human-computable hash functions for password generation, leveraging associative memory for security without password managers.

A deep learning framework for creating interpretable password strength meters that provide character-level feedback, moving beyond opaque security scores to support user education.

An in-depth analysis of long passphrase policies, their usability, security implications, and future directions in authentication systems.

Analysis of a proposed strong password generation technique for cloud computing using multiple input parameters to enhance security against brute force attacks.

Analysis of a novel password management system using multi-factor key derivation and deterministic generation to eliminate credential storage and upgrade legacy authentication.

A comprehensive analysis of password generator systems, proposing a general model, evaluating existing schemes, and introducing the novel AutoPass concept for improved security and usability.

A comprehensive security analysis of 13 popular password managers, evaluating password generation randomness, storage security, and autofill vulnerabilities.

Analysis of PassGPT, an LLM for password generation and strength estimation, outperforming GANs and enabling guided password creation with character-level constraints.

Analysis of PassGPT, an LLM for password generation and strength estimation, outperforming GANs and enabling guided password creation with character-level constraints.

Analysis of PassTSL, a novel password modeling framework using pretraining and fine-tuning inspired by NLP, demonstrating superior performance in password guessing and strength estimation.

Analysis of PESrank, a novel password strength estimator using multi-dimensional rank estimation for fast, accurate, and explainable online password security assessment.

Analysis of PESrank, a novel password strength estimator using multi-dimensional rank estimation for online, explainable, and tweakable password security assessment.

Performance analysis of BIKE, CRYSTALS-Kyber, and HQC post-quantum algorithms on Raspberry Pi IoT platforms, evaluating computational overhead, memory usage, and energy consumption.

Analysis of a provably secure reversible hybrid tokenization algorithm based on block ciphers, with formal security proofs meeting PCI DSS requirements.

Analysis of SOPG, a novel method for generating passwords in descending probability order using autoregressive neural networks, significantly improving attack efficiency.

Analysis of SOPG, a novel method for generating passwords in descending probability order using autoregressive neural networks, significantly improving password guessing efficiency.

Analysis of SOPG, a novel method for generating passwords in descending probability order using autoregressive neural networks, significantly improving password guessing efficiency.

This paper proposes a secure password generator using HMAC, CMAC, and KMAC-based PRNGs, validated via NIST SP 800-90B entropy and IID tests.

A research paper proposing a secure password generator using HMAC, CMAC, or KMAC-based PRNGs, validated via NIST SP 800-90B entropy and IID tests.

Analysis of a novel deep learning framework that creates adaptive password models using auxiliary user data, enabling system-specific password strength estimation without plaintext access.