Password Generation Research Articles

What should an ordinary person understand about the work of generative artificial intelligence? Proceedings of the competition "TRIZformashka-2024"

Three basic aspects of the operation of generative neural network models (generative artificial intelligence) are discussed in the article: the concept of a "token", the probabilistic nature of the generated response, and the concept of a "large model", the size of which ensures the pseudo-intelligent behavior of neural network chatbots. The issues of implementing generative models, areas and methods of their application are not discussed in principle.The materials of the "TRIZformashka-2024" competition, which was dedicated to neural network models, are provided. The fact of pseudo-intelligence of generative models is demonstrated. It turns out that a model trained on a single phrase "mama myla ramu" ("mama washed the frame") and using a context of a single letter for generation can sometimes behave as if it knows the rules of declension in the Russian language and is able to change a word by case!The concept of a "token" is considered in relation to the generation of texts, pictures and passwords. On the basis of "tokens" a practically useful method of generating passwords is built, difficult to guess, but easy to reproduce (difficult to forget).The concept of a "large model" is presented clearly and intelligibly due to its "visualization" by comparing it with physical quantities. (If one parameter of a neural network weighed one gram, then 200 freight trains would be needed to transport it. If one parameter had a length one millimeter, then the neural network would revolve around the Earth at the equator 25 times. If one second was required to learn one parameter, then it would be necessary to start training a modern neural network in the times of the Cro-Magnons.)The materials will be useful for studying generative artificial intelligence at any age.

EMhub: a web platform for data management and on-the-fly processing in scientific facilities.

Most scientific facilities produce large amounts of heterogeneous data at a rapid pace. Managing users, instruments, reports and invoices presents additional challenges. To address these challenges, EMhub, a web platform designed to support the daily operations and record-keeping of a scientific facility, has been introduced. EMhub enables the easy management of user information, instruments, bookings and projects. The application was initially developed to meet the needs of a cryoEM facility, but its functionality and adaptability have proven to be broad enough to be extended to other data-generating centers. The expansion ofEMHub is enabled by the modular nature of its core functionalities. The application allows external processes to be connected via a REST API, automating tasks such as folder creation, user and password generation, and theexecution of real-time data-processing pipelines. EMhub has been used for several years at the Swedish National CryoEM Facility and has been installed in the CryoEM center at the Structural Biology Department at St. Jude Children's Research Hospital. A fully automated single-particle pipeline has been implemented for on-the-fly data processing and analysis. At St. Jude, the X-Ray Crystallography Center and the Single-Molecule Imaging Center have already expanded the platform to support their operational and data-management workflows.

VISUAL CRYPTOGRAPHY WITH COLOR IMAGE ENCRYPTION VIA IMPROVED ELLIPTIC CURVE CRYPTOGRAPHY (ECC) AND OTP GENERATION: SELF-IMPROVED GOLD RUSH OPTIMIZATION ALGORITHM FOR OPTIMAL KEY GENERATION

Visual Cryptography is a cryptographic technique that involves encrypting images in such a way that decryption can be performed visually without the need for complex computations. This technique holds significant importance in secure image sharing, as it ensures that sensitive visual information remains confidential during transmission. Recognizing this significance, a novel approach named Self-Improved Gold Rush Optimization (SIGRO)-based Visual Cryptography has been proposed in this research. This approach encompasses two main phases: Embedding and Extraction. It involves encrypting three original images and two secret images using various encryption techniques such as Random grid-based secret image sharing, Extended Visual Cryptography Scheme (EVCS), and Kronecker product-based encryption, along with the integration of security measures like Modified HMAC-based One-Time Password generation technique (MHOTP) for Improved Elliptic Curve Cryptography (IECC)-based encryption and Baker's map-based encryption. In Kronecker product-based encryption stage, the SIGRO algorithm is utilized to generate optimal keys for encryption purposes. The SIGRO algorithm is proposed as a well-versed approach than the conventional Gold Rush Optimization (GRO) algorithm, incorporating three key enhancements. These enhancements significantly contribute to the efficacy and reliability of the SIGRO algorithm in generating optimal keys for Kronecker product-based encryption. Furthermore, the IECC-based encryption utilizes the MHOTP generation technique, where the OTPs generated by this technique serve as the keys for this encryption stage, enhancing the ECC algorithm into an IECC algorithm. The decryption process involves reversing the steps applied during various encryption stages. This proposed approach's significance lies in its ability to enhance security through a combination of encryption methods and security measures.

A cost-effective counterfeiting prevention method using hashing, QR code, and website

In this paper, we proposed a cost-effective software method to prevent counterfeiting where we used a website, quick-response (QR) code, and hashing. At the early stage of the product, the system will create a unique ID and a password with a random password generator for all products. Then, the password hash would be stored along with the ID in the database. At the same time, the password would be converted into a QR code for each product. The manufacturer will collect the QR code and ID and attach them to the product. When consumers attempt to verify the product, they will enter the website provided by the manufacturer and scan the QR code. After applying the same hash used before, the code will be checked on the database. After a successful check, the product entity will be destroyed and the life of the product ends. This paper contains flowcharts, figures, cost estimation, and a detailed explanation of the system. As it only requires domain hosting, thus the fixed cost of the system is so lower to bear for small enterprises also. We built a similar system using PHP, HTML, JavaScript for websites, and MYSQL for databases.

BDPM: A secure batch dynamic password management scheme in industrial internet environments

The rapid development of Industrial Internet has promoted the deep integration of Information Technology (IT) and Industrial Control (IC), so that network attacks have gradually invaded IC zone. Password security is the first line of defense to ensure the security of IC devices. In this paper, we propose a secure Batch Dynamic Password Management (BDPM) scheme in Industrial Internet environments. Aiming to automatically configure strong passwords for IC devices, our scheme can achieve a batch password generation algorithm based on SM3 Cryptographic Hash Algorithm, which encrypts the input string and then intercepts and replaces the hash value to ensure the uniqueness and crack resistance of passwords. Moreover, we continuously monitor the status of vulnerable IT devices through a zero trust anomaly monitoring mechanism and introduce a password updating mechanism for relevant IC devices, which is triggered by sending an alarm to IC devices that have interaction rights with the compromised IT device. Subsequently, we construct a resilient blockchain called PS_chain and execute two different password storage schemes based on the threshold of password updates to ensure storage security and reduce the load on block storage. The security analysis shows that our scheme can defend against the threat model and can comprehensively improve the security of IC device passwords. The simulation results show that our scheme can enhance the strength of IC device passwords while securely storing IC device passwords in a low-load manner.

RoseCliff Algorithm: Making Passwords Dynamic

Authentication in the digital landscape faces persistent challenges due to evolving cyber threats. Traditional text-based passwords, which are vulnerable to various attacks, necessitate innovative solutions to fortify user systems. This paper introduces the RoseCliff Algorithm, which is a dual authentication mechanism designed to enhance resilience against sophisticated hacking attempts and to continuously evolve stored passwords. The study explores encryption techniques, including symmetric, asymmetric, and hybrid encryption, thereby addressing the emerging threats posed by quantum computers. The RoseCliff Algorithm introduces introduces dynamism into passwords that allows for more secured communication across multiple platforms. To assess the algorithm’s robustness, potential attacks such as brute force, dictionary attacks, man-in-the-middle attacks, and machine learning-based attacks are examined. The RoseCliff Algorithm, through its dynamic password generation and encryption methodology, proves effective against these threats. Usability evaluation encompasses the implementation and management phase, focusing on seamless integration, and the user experience, emphasizing clarity and satisfaction. Limitations are acknowledged, thus urging further research into encryption technique resilience, robustness against breaches, and the integration of emerging technologies. In conclusion, the RoseCliff Algorithm emerges as a promising solution, thereby effectively addressing the complexities of modern authentication challenges and providing a foundation for future research and enhancements in digital security.

Enhancing Residential Security: Implementation of an IoT-based Anti-Theft Flooring System

The Anti-Theft Flooring System (ATFS) is Internet of Things (IoT) solution developed for enhancing residential safety and security. The system employs pressure sensors that are integrated into the flooring or into the floor mat, this system easily identifies intruder presence upon stepping, initiating a secure One-Time Password (OTP) generation process. The OTP is dispatched to pre-registered mobile numbers, serving as a safe and secure verification mechanism. The OTP when entered correctly within time triggers the system to unlock the door automatically. In case, OTP is entered wrongly or remains unentered for a 60-second timeframe, a Global System for Mobile (GSM) communication module triggers an alarm to promptly inform the user of potential security threats. This is how the system seamlessly combines IoT technology for real-time communication, offering an effective and proactive approach to residential safety at lower costs.

Combination of Alphanumeric Password and Graphic Authentication for Cyber Security

The main objective of this research is to create a more secure and user-friendly password-generation method that is less vulnerable to attacks such as shoulder surfing. Similarly, while textual or alphanumeric passwords are not entirely secure, they also come with certain limitations, including issues related to memory. The novelty of this research is the development of a new algorithm (Secure Password Algorithm/SPA) for password generation that uses graphics to generate textual input from users based on user perceptions. This method is more resilient against attacks like shoulder surfing and offers a more secure and user-friendly way of creating passwords. This research uses a combination of literature review and SPA proposals to create passwords with graphical and encryption techniques. The literature review examines the weaknesses of existing graphical and text password methods. The proposed algorithm focuses on user perception and confidential data to create more secure and easy-to-use passwords. The research results show that this research can provide a new, more secure, and user-friendly method of generating passwords such as shoulder surfing. Research supports software implementation of these algorithms and psychometric, psychological, and psychiatric studies to improve user input and protect systems from malicious attacks. Graphical passwords provide better recall compared to textual passwords, and the proposed algorithm for password generation using graphical and encryption techniques provides a more secure and user-friendly method of password generation that is less vulnerable to attacks such as shoulder surfing. The proposed new encryption algorithm has succeeded in overcoming various potential weaknesses and attacks on previous encryption methods. The test results demonstrate the efficiency and near invulnerability of the SPA algorithm against brute force attacks on specific security parameters. Tested alongside AES, shows comparable security levels, particularly in resource-constrained environments. To address doubts, the paper establishes evaluation standards for computational complexity, resistance to known attacks, and adaptability to evolving threats. The algorithm has the potential to be a stronger and more secure solution for generating passwords to safeguard confidential user information.

Secure One-time Password Generation using Shamir's Secret Sharing

- The process of authenticating users is critical for ensuring security. Static passwords are a popular and traditional authentication method due to their simplicity, but they are vulnerable to attacks such as password leakage, replay, guessing, eavesdropping, phishing, and spoofing, among others. One-time passwords (OTP) were introduced to address these limitations, but research has found that they are not immune to middle man attacks. To enhance the security of OTP, a new technique called Visual Cryptography Schema is proposed in this paper. In this method, we use Shamir’s Secret Sharing theory in which the main OTP is parted into three shares. Out of these shares, one is sent to the user and the other two shares are stored in different locations in the server. To retrieve

Mangling Rules Generation With Density-Based Clustering for Password Guessing

Rule-based password generation is one of the most effective and often employed techniques in the highly compute-intensive password recovery process. However, it is challenging to design and maintain a practical password mangling ruleset, which is a time-consuming task requiring specialized expertise. This paper therefore introduced MDBSCAN (Modified Density-Based Spatial Clustering of Applications with Noise), a novel density-based cluster approach in machine learning, to build an automatic password mangling rule generator. To evaluate the proposed method, cross-checks across 4 different real-world password datasets leaked from popular Internet services and applications are adopted. The results indicate that the proposed generator could produce high-quality mangling rules with a better hit rate and enhance current mangling rules by identifying hidden or omitted rules. The proposed approach also shows strong interpretability and computational efficiency. When examining the RockYou password dataset with the top 77 rules, the hit rate may rise by 11% to 104% proportionally to other well-known solutions. Furthermore, by combining the top 77 rules generated by MDBSCAN with those from other rulesets, 3–12.67% more real-world passwords can be retrieved.

Anticipate Password Security with Burp Suite Using the Brute Force Attack Method

Website is one of the information and communication media that requires internet to run. Password generation is still less aware of user security. This provokes cyber criminals to carry out attacks to retrieve user login passwords. One possible attack is a brute force attack by experimenting with all possible passwords. This research aims to discuss brute force attack techniques and how to prevent them so that users can be more careful in creating passwords and be more aware of the security of their passwords. This research shows that the brute force method can work perfectly if there is no Captcha on the web login, limiting logins that do not block accounts for a long time, and not using Two Factor Authentication.

Iliash Implementation of the password complexity diagnostic system

Password diagnostic systems are becoming increasingly relevant in the modern world due to the growth of internet services and the need to protect personal data. Evaluating password complexity allows for assessing the strength of passwords against different types of attacks, including brute force, dictionary attacks, and other methods. In this work, a system for checking password complexity was developed, which takes into account new approaches to forming the uniqueness of the selected sequence of characters. As opposed to standard methods used in the most common password generating systems, such as length, the presence of special characters and numbers, and the use of upper and lower case letters, this work proposes to check for repetitions and matches with the most common passwords. For this purpose, a database of 10,000 passwords was connected to the developed system. To speed up the checking for matches, the Levenshtein distance algorithm was used. The Levenshtein algorithm works using dynamic programming. It considers two strings that need to be compared and creates a matrix that shows the minimum number of editing operations required to transform one string into the other. This implementation allowed for faster password generation compared to existing systems. The work details the algorithms for all the main stages of password complexity checking and proposes code implementation in Javascript. The Levenshtein algorithm can be useful for determining text similarity or searching for possible correct variants of misspelled words. It can also be used for implementing autocomplete in programs that use user input. The implemented system can be integrated into many different programs and web services for automatic password complexity determination, allowing for its use in various areas such as banking, medical services, and others. As a result of work on this project, it has been confirmed that using a password complexity diagnostic system can significantly reduce the risk of unauthorized access to systems containing important confidential information.

Designing a Random Password Generator Using Python Programming Language

Every individual who uses various online services, is concerned about security and privacy to safeguard personal information and data from hackers. The password-generating system is one of several generating systems available for the security of users' data. Because of the rise in sharing of information online, internet usage, electronic commerce transactions, and data transmission, both password security and authenticity have become grave issues. However, this shows that the password's strength (or length) is also necessary to be strong. As a result, cybersecurity experts generally advise using complex password combinations. However, due to difficult patterns, individuals frequently forget their passwords. Unlike previous random password generators, the authors are putting forth a novel approach in this paper that will produce a strong password. The Python programming language has been used to create the password-generating system. The authors have used pyperclip, tkinter, random and string libraries in the code design. According to various tests of the system carried out, the trustworthiness of the generated passwords is one hundred percent.

Enhancing video encryption: AES and blowfish algorithms with random password generation

Enhancing video encryption: AES and blowfish algorithms with random password generation

Balancing Password Security and User Convenience: Exploring the Potential of Prompt Models for Password Generation

With the increasing prevalence of cyber attacks and data breaches, the importance of strong passwords cannot be overstated. Password generating software has been widely used to generate complex passwords that are difficult to crack, but it has its limitations. One of the main problems with this kind of software is that it often generates passwords that are difficult to remember, leading to users write them down or reuse them across multiple accounts. In recent years, prompt models such as ChatGPT have emerged as a promising solution for generating strong and memorable passwords. By leveraging machine learning algorithms, these models can generate unique and complex passwords tailored to individual users’ preferences, making them easier to remember and more secure. However, the use of prompt models to generate passwords also raises concerns about exposing vulnerable passwords. Hackers can potentially use these models to predict passwords by analyzing a user’s online activity and personal data. Additionally, the constant need to change passwords to stay secure poses a challenge for both password generating software and prompt models. As technology continues to evolve, finding a balance between password security and user convenience remains a complex issue. While prompt models such as ChatGPT can offer a promising solution, it is essential to consider the potential risks and challenges associated with their use, including the constant need for password changes and the potential vulnerability of the generated passwords.

RUPA: A High Performance, Energy Efficient Accelerator for Rule-Based Password Generation in Heterogenous Password Recovery System

There has been a growing demand for energy efficient and high performance password recovery systems. As password generation and password validation are two integral components of any password recovery system, the former yet lags behind the latter in performance particularly for the case when the popular rule-based password generation method is applied to the heterogeneous CPU-FPGA system. In this paper, we thus present a high performance, energy efficient accelerator to speed up the rule functions in rule-based password generation. Dubbed RUPA, this proposed accelerator explores previously undiscovered computational features and memory access patterns for processing the rule functions. Specially, we show that the rule functions can be mapped to three distinct groups according to their character dependency graphs. Correspondingly, three kinds of datapath units, referred to as rule logic units, are created, and the rule functions from the same group will be processed in their shared rule logic unit. Compared with the state-of-the-art password recovery system built upon a CPU-GPU platform, the FPGA-based RUPA system achieves 5.3x speed improvement and is 33.1x more energy efficient. If RUPA is integrated into the popular password recovery tool John the Ripper (JtR), JtR's rule-based attack performance can soar by more than 48.7x.

Highly Secure and Easy to Remember Password-Based Authentication Approach

Everyone connected and using the Internet is concerned regarding the security and also the privacy of their sensitive information available on the Internet. As authentication is the fundamental part of security, there are different authentication mechanisms through which the systems can be secured. The password-based authentication mechanism is a cheap and easy method for enforcing authentication in the systems for many years. The weakest aspect in password security is human, as they choose weak and easy to guess passwords or a highly secure and complex password which might be difficult to remember and recover the password. On the other hand, Dictionary and Brute force attacks are widely used to compromise the passwords of the users over the Internet. In this paper, a password generation system is proposed which generates a password based on the user’s input like, time and location data. The system generates a password that is highly secure, easy to remember, easy to recover, and can effectively defend against Brute force and dictionary attacks. The generated passwords have been checked in three online password checkers, which verifies that the system is generating highly secure and crack resistant passwords. The system is implemented using PHP scripting language with a user-friendly environment.

Enhancing the Concept of Generative Art

Abstract: Art that was entirely or partially produced by an autonomous system is referred to as generative art. An autonomous system is typically a non-human entity that is capable of making judgments on its own about aspects of a piece of art that would otherwise require direct input from the artist. We have created a GUI which lists the applications which are based on the concept of generative art. Our GUI contains applications like random password generation, abstract artworks, map generation, wallpaper generation. Password generator will provide randomly generated passwords which would be derived from the images created using image generation algorithms/scripts such as EPWT and python’s in-built random function which uses algorithms like mersenne twister, a pseudo-random number generator. This application aims to provide usefulness for old hashing algorithms which are getting obsolete day by day. Abstract artwork generator will generate random images for stimulating creativity of artists, designers, architectural and marketing firms for getting started on a new project. This generator uses general complex functions which contain scripts for different shapes and combinations. This approach is able to generate some innovative solutions and demonstrates the power of computational approach. A layout of the area with the requested coordinates and different constraints will be provided through map generating model. Wallpaper generation model will generate aesthetically pleasing wallpapers with adjustable features.

A Study of Password Management Behaviors of Young People

Password-based authentication is still the most widely used authentication method today. Unfortunately, passwords are the main culprit leading to cyberattacks. This study examines the behaviors of young people towards password generation and usage. The young people will ultimately become the future for society. An online survey with a sample of 265 respondents aged 10–24 was conducted between April and August 2021. The research utilized descriptive statistical analyses and compared the responses from young people with older people. The results suggest that although the survey participants seemed to have basic knowledge of creating complex passwords, they still possessed some aspects, which could lead to being a cyberattack target. This preliminary study provides information and increases awareness for policymakers and educators in such a way that it could be used to create an educational program on the importance of managing passwords securely. In addition, the study provides insights into the password management of young people between the ages of 10 and 24.

LWO vs. LWE Lattice Problems in Human-Computable Passwords Protocol

In this paper, we will compare the results of introducing the well-known Learning with Errors (LWE) and the newly discovered Learning with Options (LWO) lattice problems to a human-computable one-time passwords (OTP) protocol, designed for this purpose. This innovative post-quantum secure challenge-response protocol allows the user to calculate safely many thousands of such passwords, e.g. 6-digit OTP, in about 10 seconds. As a method of human-computer identification, safe also in untrusted systems and environments (Zero Trust), it allows the elimination of any supplementary gadgets/devices or theft-sensitive biometric data used by the Multi-Factor Authentication (MFA), and using only one secret as a universal private key for all obtainable online accounts. Moreover, all these accounts can use OTP calculated from this one secret known only by the user, not the verifier. The secret has the form of an outline similar to a handwritten autograph, designed in invisible ink on the mapping grid. The password generation process requires following such an invisible contour on the challenge matrix created randomly by the verifier and reading values from secret fields to calculate the OTP.