Digital Password Research Articles

Cryptocurrency interest in geographical regions with high unemployment rates

Purpose- In regions with high unemployment rates, individuals often face economic uncertainty and may seek alternatives to traditional financial systems. In such circumstances, some individuals may turn to alternative investments and financial instruments, with cryptocurrencies such as Bitcoin being among them. The value of these cryptocurrencies is often volatile due to their speculative nature, which can lead investors to take on more significant risks. While this situation can result in substantial gains, it can also lead to significant financial losses. The primary use of cryptocurrencies is generally for investment purposes. Since cryptocurrencies are digital, they operate entirely in a virtual environment. The loss or theft of the digital password in the virtual space means the loss of the wallet. Security in cryptocurrencies is very weak. The lack of government guarantees and legal infrastructure globally poses certain threats to investors, making cryptocurrencies carry a higher risk compared to other investment instruments. This study will investigate the regional relationship between cryptocurrency interest and unemployment rates. The aim is to determine whether individuals living in geographical areas with high unemployment rates show more interest in cryptocurrencies compared to those in other geographical regions. Methodology- In line with the research objective, Google search engine data for the past 10 years has been analyzed using content analysis methodology. A query has been conducted to determine in which regions of Turkey cryptocurrency names are most frequently searched, and a comparison has been made on a provincial level across all 81 provinces. Additionally, considering the unemployment data provided by the Turkish Statistical Institute (TUIK), regions with high and low unemployment rates have been identified. Subsequently, an investigation has been carried out to determine whether there is any correlation between regional Google searches and unemployment rates in these areas. Findings- When examining the findings from the perspective of unemployment, it has been observed that the regions where cryptocurrency names are most frequently searched align with areas having the highest unemployment rates, while the least searched areas correspond to regions with lower unemployment rates. Among the 10 provinces with the highest unemployment rates, 8 of them are included in the list of 10 provinces with the highest Bitcoin search frequency. Similarly, 8 out of 10 provinces with the lowest employment rates are also listed among the 10 provinces with the highest Bitcoin search frequency. Furthermore, among the 10 provinces with the lowest per capita gross domestic product (GDP), 7 of them are included in the list of 10 provinces with the highest Bitcoin search frequency. Conclusion- As a result of the relationship analyses conducted in the research, it has been observed that in Turkey, regions with high unemployment rates, low employment rates, and low Gross Domestic Product (GDP) have a higher frequency of Bitcoin searches compared to other regions. Keywords: Cryptocurrency, unemployment, bitcoin JEL Codes: P44, E24, E44

Методика подвійної автентифікації для RFID систем управління доступом з підвищеним рівнем захисту

Currently, there are no uniform international standards for devices and systems that use radio frequency identification technology. Using tag alone as an identifier imposes certain restrictions on the level of protection of access control systems, since the unique tag identifier can be easily copied, so two-step authentication is required. The second level of protection can be a digital password entered via the keyboard. The work presents dual authentication technique for access control to the premises. Increasing the level of protection of radio frequency identification systems is achieved by the additional use of a digital password encrypted using a symmetric block encryption algorithm and recorded on the tag. This removes any restrictions on the number of registered users in the system, because passwords and IDs are stored on tags. The laboratory model of the device is based on the NodeMCU-32S Opensource platform with an RFID module that allows connection to most fog and cloud services of the Internet of things. The development is based on the ESP32 controller, which supports the necessary set of commands and hardware for implementing the methodology, in particular, wireless standards and communication protocols, hardware-accelerated encryption. The Cayenne service from MyDevices was chosen as the cloud platform, which made it possible to configure the device using the publish-subscribe messaging protocol and develop a graphical user interface. A log on the Cayenne platform is used to keep track of users, a character display is used to display the current status and settings of the device, and a serial interface is used to debug work algorithms. The software is implemented using the Arduino C programming language.

A Novel Method of User Identity Recognition Based on Finger Trajectory

User identity recognition is the key shield to protect users’ privacy data from disclosure and embezzlement. The user identity of mobile devices such as mobile phones mainly includes fingerprint recognition, nine-grid password, face recognition, digital password, etc. Due to the requirements of computing resources and convenience of mobile devices, these verification methods have their own shortcomings. In this paper, a user identity recognition technology based on finger trajectory is proposed. Based on the analysis of the users’ finger trajectory data, the feature of the user's finger movement trajectory is extracted to realize the identification of the user. Also, in this paper, we design and implement an android app, through which we collect the real finger trajectory data of 34 people and use K-means clustering combined with Bayesian classification to recognize and distinguish the user identity. The experimental results show that the finger trajectory has a good performance on identifying the users, which can be constructed as a new low-cost scheme for mobile device user identity recognition.

Research on Security Verification Mechanism of Perception Layer Terminal of Power Internet of Things Based on Device Operation Fingerprint

Integrating the Internet of things technology into the power grid is a major development trend in the future, which can effectively improve the overall performance of the existing power grid. However, due to the traditional Internet of things mainly uses the form of digital password for security protection, due to the low security problems, there are great hidden dangers to the operation of the equipment. For this reason, this paper proposes a security verification mechanism for the perception layer terminal of the power Internet of things based on the device operation fingerprint. In this paper, the biometric fingerprint identification technology and Internet of things architecture are deeply studied, and the fingerprint identification algorithm process and steps are analyzed in detail, and the processing time of each step is compared. In order to improve the comprehensive performance of the security verification of the perception layer terminal of the Internet of things, according to the actual security requirements of the power Internet of things, combined with the biometric fingerprint identification technology, a new security verification system is established. In this paper, the security mechanism of RFID system is adopted, and the performance of fingerprint image filtering is improved by optimizing calculation method and simplifying algorithm. By improving the identity authentication mode and optimizing the data encryption transmission mechanism, the security protection performance of the perception layer of the power Internet of things is further improved. In the simulation test, the system identification accuracy rate of this paper reaches 99.75%, and the software implementation efficiency test results are good, which shows that the system in this paper has high security protection performance, and can meet the current security protection needs of the power Internet of things.

Authentication Database Leakage Detection

Authentication is the first step for any important applications. Password verification is widely employed in the Internet. Some advanced mechanisms including bio features, such as fingerprints or retina. However, digital password authentication credential is commonly used in the public. In other words, traditional password verification is still an important authentication credential mechanism for today's online services. Password database may be compromised. Once if the database is stolen, it is dangerous and critical for any services. Consequently, password database leakage becomes an important issue. Detection and countermeasure are essential for such a disaster. Our research proposing a scheme based on a authentication database storage mapping method to detect possible leakage of authentication database. By multiple mapping mechanism, if the authentication database is stolen, an attacker could not know any user's correct password. This method can reduce additional space of storing passwords with ability to detect security event for stolen authentication databases. Keywords:Application Security; System Security; Leakage Detection; Authentication database, Password DOI: 10.7176/NCS/12-01 Publication date: January 31 st 2021

Authentication Database Leakage Detection

Authentication is the first step for any important applications. Password verification is widely employed in the Internet. Some advanced mechanisms including bio features, such as fingerprints or retina. However, digital password authentication credential is commonly used in the public. In other words, traditional password verification is still an important authentication credential mechanism for today’s online services. Password database may be compromised. Once if the database is stolen, it is dangerous and critical for any services. Consequently, password database leakage becomes an important issue. Detection and countermeasure are essential for such a disaster. Our research proposing a scheme based on a authentication database storage mapping method to detect possible leakage of authentication database. By multiple mapping mechanism, if the authentication database is stolen, an attacker could not know any user’s correct password. This method can reduce additional space of storing passwords with ability to detect security event for stolen authentication databases.

Niffler: A Context‐Aware and User‐Independent Side‐Channel Attack System for Password Inference

Digital password lock has been commonly used on mobile devices as the primary authentication method. Researches have demonstrated that sensors embedded on mobile devices can be employed to infer the password. However, existing works focus on either each single keystroke inference or entire password sequence inference, which are user‐dependent and require huge efforts to collect the ground truth training data. In this paper, we design a novel side‐channel attack system, called Niffler, which leverages the user‐independent features of movements of tapping consecutive buttons to infer unlocking passwords on smartphones. We extract angle features to reflect the changing trends and build a multicategory classifier combining the dynamic time warping algorithm to infer the probability of each movement. We further use the Markov model to model the unlocking process and use the sequences with the highest probabilities as the attack candidates. Moreover, the sensor readings of successful attacks will be further fed back to continually improve the accuracy of the classifier. In our experiments, 100,000 samples collected from 25 participants are used to evaluate the performance of Niffler. The results show that Niffler achieves 70% and 85% accuracy with 10 attempts in user‐independent and user‐dependent environments with few training samples, respectively.