Two-factor Authentication System Research Articles

ThumbUp: Secure Smartwatch Controller for Smart Homes Using Simple Hand Gestures

The development of creative applications and intelligent gadgets requires a secure and straightforward interface with human users. We propose, design, and implement ThumbUp, a smartwatch-based two-factor real-time identification and authentication system in which smartwatch users can identify and authenticate themselves using some simple hand and finger movements, such as thumb-up. ThumbUp leverages the signal from the Inertial Measurement Unit (IMU) in in Commercial-Off-The-Shelf (COTS) smart devices to discover the unique pattern generated by each user's simple gestures using a carefully constructed deep learning model. Smart homes provide a comfortable, safe, and efficient living environment, epecially help the sick and aged. We propose strategies for convenient and reliable control in smart homes with gesture command recognition. We build an Auto-Encoder-based filter that reconstructs the raw data to improve the representation of gesture features. Moreover, we adopt the random forest method to analyse the contextual command correlation. And we employ the authentication system based on smartwatch for personalized command feedback and ensure that illegals cannot use the device. We implement our system and undertake rigorous studies to determine its usefulness and efficiency over a three-month period with 65 users. It achieves a 97% accuracy for user classification and an EER of 0.014 for authentication task with a single simple gesture. And our method achieves 91% accuracy for command recognition and 96% command accuracy with contextual informations. Additionally, we conduct a study of user acceptability of our system and explain how gesture proficiency influences authentication accuracy.

Role Based Access Control Using Biometric the in Educational System

The purpose of a secure e-learning system based on cloud computing is to allow instructors and students to access their accounts at any time and from anywhere. These types of systems work to ensure that their users (instructors and students) are truly enrolled in the school or institute to prevent unauthorized users from accessing the resources and components of the system. Furthermore, the traditional authentication techniques used in the majority of educational systems suffer from several issues, such as cyber security attacks and weak management of resources. So, some students could be eager to take advantage of such a system's flaw in an effort to cheat. User authentication and end-user monitoring are more difficult in this situation. Multifactor adaptive authentication techniques are used to implement a system with simultaneous authentication. The proposed scheme system offers an effective, affordable, and human intervention-adaptive authentication and monitoring solution for e-learning environments. Additionally, our work can resist cyber security and contains some good metrics like mutual authentication, user anomalies, and others. In this paper, the proposed scheme system uses a two-factor authentication system based on Asymmetric Scalar Product Preserving Encryption (APSE) and fingerprint biometrics for managing and generating a user's account in a secure way. Our work also achieves a good balance between performance and security complexity compared to the state-of-the-art. So, we achieve good results for 1.69 ms for computation and 1280 bits for communication.

Card Defender - Credit Card Fraud Detection System

Abstract: As the world becomes increasingly digitized, online transactions have become an indispensable part of our daily lives. The increased use of credit cards for online purchases has resulted in a growing concern about credit card fraud, both for businesses and consumers. To combat this issue, we propose a two-factor authentication system that integrates credit card verification with webcam-based face recognition technology to prevent online transaction fraud. Our system provides a reliable and user-friendly solution for credit card fraud detection using face recognition. By implementing a two-factor authentication process, our system reduces the risk of fraud during online transactions and enhances the overall security of online payments

Towards Nonintrusive and Secure Mobile Two-Factor Authentication on Wearables

Mobile devices are promising to apply two-factor authentication to improve system security. Existing solutions have certain limits of requiring extra user effort, which might seriously affect user experience and delay authentication time. In this paper, we propose PPGPass, a novel mobile two-factor authentication system, which leverages Photoplethysmography (PPG) sensors available in most wrist-worn wearables. PPGPass simultaneously performs a password/pattern/signature authentication and a physiological-based authentication. To realize both nonintrusive and secure, we design a two-stage algorithm to separate clean heartbeat signals from PPG signals contaminated by motion artifacts so that users do not have to deliberately keep their bodies still. In addition, to deal with noncancelable issues when biometrics are compromised, we design a repeatable and non-invertible method to generate cancelable feature templates as alternative credentials. We leverage the great power of Random Forest and Support Vector Data Description to detect adversaries and verify a user's identity. To the best of our knowledge, PPGPass is the first nonintrusive and secure mobile two-factor authentication based on PPG sensors. Extensive experiments demonstrate that PPGPass can achieve the false acceptance rate of 3.11% and the false recognition rate of 3.71%, which confirms its high effectiveness, security, and usability.

Rhythmic RFID Authentication

Passive RFID technology is widely used in user authentication and access control. We propose RF-Rhythm, a secure and usable two-factor RFID authentication system with strong resilience to lost/stolen/cloned RFID cards. In RF-Rhythm, each legitimate user performs a sequence of taps on his/her RFID card according to a self-chosen secret melody. Such rhythmic taps can induce phase changes in the backscattered signals, which the RFID reader can detect to recover the user’s tapping rhythm. In addition to verifying the RFID card’s identification information as usual, the backend server compares the extracted tapping rhythm with what it acquires in the user enrollment phase. The user passes authentication checks if and only if both verifications succeed. We also propose a novel phase-hopping protocol in which the RFID reader emits Continuous Wave (CW) with random phases for extracting the user’s secret tapping rhythm. Our protocol can prevent a capable adversary from extracting and then replaying a legitimate tapping rhythm from sniffed RFID signals. Comprehensive user experiments confirm the high security and usability of RF-Rhythm with false-positive and false-negative rates close to zero.

System of two­factor authentication of the user of the corporate environment using a QR code

In today's world, technologies are developing at a rapid pace. It is very difficult to imagine a sphere of human life where digital data is not used, for example, banking operations, distance learning, utility payments, online messaging have become commonplace for us. However, on the other hand, the question arose of how to ensure the reliability and confidentiality of this data. One of the methods was authentication when entering the system, that is, entering a login and password to identify the user. To date, this method is not reliable and quite vulnerable, because most users have started using the same passwords for login, or simply ignore their reliability and use rather primitive ones. As a result of such actions, more and more confidential user data is at risk of being acquired by unauthorized criminals. The idea to develop a two-factor authentication system using a QR code arose as a result of the urgency of this problem and the imperfection of existing software products. The basis will be the generation of a unique code that will be available only for a short period of time, which will be enough for the user to enter the system. This technology will allow dynamically changing the set of numbers required for authentication. If an attacker takes possession of it, he will not be able to use it, because it will change in the system in a fairly quick period of time. The article discusses the implementation of the two-factor authentication algorithm using a QR code, which has a simple appearance, but can store a large amount of data. Also, regardless of how much information the QR code contains, the data is displayed immediately after reading it. This provides an increased level of protection when the user enters the system and prevents unauthorized access to confidential data by cybercriminals. An approach using TOTP (Time-based One-time password) is also proposed, which will generate a one-time code based on a secret key. The main feature is the use of time as one of the parameters to generate a dynamic 6-digit password required for logging into the system. Also, its generation will be carried out automatically every 30 seconds, thus creating conditions for making its theft and unauthorized use impossible.

Assessment of digital literacy of civil servants

In the modern social world, there are various trends associated with digitalization, aimed primarily at the development and implementation of digital technologies in various spheres of society. Civil servants as a socio-professional group are developing, adapting to new unknown digital technologies. Currently, there is a problem of insufficient development of digital literacy among civil servants. This is evidenced by ongoing research, regulatory documents. The purpose of the study is to assess the level of digital literacy of civil servants, the subject of the study is the features of digital literacy in public administration. The scientific article used the methods of empirical sociological research: analysis of documents, the purpose of which is to study currently possible studies, scientific publications on the topic of digital literacy of civil servants and testing, the purpose of which is to assess the level of digital literacy among civil servants of the Government and the Presidential Administration of the Russian Federation. The results of the study are as follows: the analysis of respondents' responses showed that the respondents' most pronounced competence is "The ability to collect, process and analyze information data" (71.03%). The reason for this was the forced work with a large volume of incoming information in government agencies. The competence "The ability to use digital tools to ensure the cybersecurity of state structures" was the least important (38.11%). This suggests that most government employees are not familiar enough with the tools of using antivirus programs, two-factor authentication systems, password protection and do not take the existing threats to government systems seriously enough. The following recommendations are proposed based on the results of the study: to include in the programs and plans for the professional development of civil servants of a practice-oriented nature aimed at the formation and development of digital literacy, to develop competency models for specific categories of civil servants, to develop a special motivation system for civil servants, including material incentives, as well as non-material motivation.

Advanced Persistent Threat attack detection method in cloud computing based on autoencoder and softmax regression algorithm

APT (Advanced Persistent Threat) is a complex type of attack that steals personal data by staying in the infected system for a long time. When APT attacks take place in a dynamic and complex infrastructure such as the cloud, their detection by traditional methods is very difficult. To overcome the limitations of existing methods the paper proposes autoencoder based deep learning approach for APT attack detection. The advantage of this model is that it achieves a high classification result by identifying complex relationships between features in a database. Additionally, the model simplifies the process of classifying large volumes of data by reducing the size of data in the encoder. Here, first of all, the autoencoder neural network was applied, and informative features were studied from the network traffic data in an unsupervised manner. After the informative feature study, softmax regression layer was added to the top layer of the constructed autoencoder network to classify APT attacks. In this study, a deep neural network model constructed by adding different layers was tested on a database open to scientific research and compared to existing methods; the proposed method gave superior results in detection of APT attacks. The average detection accuracy of the proposed APT detection framework was achieved of 98.32%. A model for the application of the proposed approach to the cloud environment has been developed, and a two-factor authentication system based on the OTP (One-Time Password) mechanism has been proposed to strengthen the security of the cloud information system against APT attacks.

TOTP Moving Target Defense for sensitive network services

Edge computing is crucial for many of the new 5G business vertical use-cases, such as Industry 4.0 robots, safety-critical communications, and highly-efficient smart grids. However, the tighter integration of such impactful businesses into previously core network operations raises significant security, trustworthiness, and reliability issues. A business vertical must not compromise the Edge platform to other business verticals. Likewise, the vertical Network Services (NSs) entrusted to the Edge should not be compromisable by adversary action. Inspired by the existing Internet Services Two-Factor Authentication (2FA) systems, we propose a Moving Target Defense (MTD) mechanism that protects sensitive NSs using a port mutation akin to a seamless Time-based One-Time Password (TOTP) authentication. Our architecture leverages Software-Defined Networking (SDN) to perform the mutations, having the option of working exclusively as a Virtual Network Function (VNF) that can be instantiated on-demand, or in conjunction with OpenFlow hardware-accelerated switches for smarter resource usage. The straightforward Proof-of-Concept implementation showed the approach was viable, with good forwarding plane performance (exceeding the current Network Interface Controllers capabilities), and effective at stopping the unauthorized interactions with the NS being protected. Because the TOTP approach depends on time and there is commonly occurring jitter (e.g., network), the Threat Detection must make a trade-off between minimizing false-positives (too many alarms) and having false-negatives (attempts that go unreported). We have struck a balance that reduces the probability of a rogue probe reaching the NS to nearly 0.0045%, while the probability of stopping an attack but not generating the alarm is approximately 2%. Future work, such as adaptive delay compensation or the use of AI/ML, may further improve the effectiveness of the solution.

A Deep Learning Approach to Subject Identification Based on Walking Patterns

For the time being, smartphone devices rely on direct interaction from the users for unlocking and authentication purposes through implicit authentication systems such as PINs, facial recognition or fingerprint scanning. While different passive two-factor authentication systems based on machine learning were explored in recent work, all require an implicit authentication system. In this study, the focus is to develop and introduce a passive authentication system based on walking patterns. In this scenario, the authentication system continuously authenticates the user in the background, without any further action. To the best of our knowledge, this is the first study in which the data sets are processed with the aim to generate better performing gait-based motion signals. Compared to previous studied work, we employ a processing stage in which we extract tiny frames of data from the motion signals. Our contribution of processing gait data, allows for more robust learning of the subject movement and lowers the number of samples required to classify a user thereafter. Hence, our approach is more robust compared to using raw gait signals. Further, we transform them into gray-scale images for deep neural network training and feature extraction. Conducting the experiments, the empirical results demonstrate that subjects can be identified with a very high accuracy through walking patterns employing the presented techniques. Empirical results outline that a system based on gait data can be utilized as a passive authentication system. Therefore, it is concluded that deep neural networks employing the technique described in this work for gait-based feature representation are well suited for continuous and unobtrusive authentication systems.

Two factor authentication framework based on ethereum blockchain with dApp as token generation system instead of third-party on web application

Authentication is a method for securing an account by verifying the user identity by inputting email with a password. Two factor authentications is an authentication system that combines the first-factor authentication with the second factor. General two factor authentication by entering an email or username with a password are similar. However, two factor authentication requires additional information that must be inputted by the user. Additional information can be in the form of tokens or one-time passwords (OTP). Two factor authentications generally still uses third-party services to generate token or OTP still have vulnerable because can attacked from tokens steal through MITM and found that the generated tokens with the same value. Therefore, we propose a two-factor authentication framework based on ethereum blockchain with dApp as token generation system. Firstly, outcome from the analysis of the system, next succeeded in creating a two-factor authentication system without using third-parties. Second, token system generate up to 3164 different tokens in one second and has been collisions tested. Third, security method to protect token from MITM attack. The attacker unable to get access caused all the checking are done by dApp user authentication.

Physical-Layer Authentication in Non-Orthogonal Multiple Access Systems

This paper concerns the problem of authenticating the transmitter device in non-orthogonal multiple access (NOMA) systems. This problem is important because of high vulnerabilities in wireless communications and an additional security vulnerability when some users collude with the adversary. In this paper, we consider two attacking scenarios. In the first scenario, there is no user that colludes with the adversary. In the second scenario, at least one user colludes with the adversary. In this paper, we propose an authentication approach in the down-link scheme of a NOMA system using physical-layer authentication mechanism because of its advantages: provide information theoretic security, reduce complexity, save power and allow us to construct a two-factor authentication system. Based on the aforementioned two attacking scenarios, we propose three physical-layer authentication schemes for a NOMA system: Physical-Layer Authentication with Shared Authentication Tag (PLA-SAT), Physical-Layer Authentication with Superimposed Independent authentication Tags (PLA-SIT), and Physical-Layer Authentication with TDM authentication tags (PLA-TDM). We analyze the theoretical performance of our schemes over fading channels and derive their closed-form expressions. Then, we optimize the parameters of our schemes to achieve both the reliability fairness and the authentication-accuracy fairness. We implemented our schemes and conducted extensive performance comparisons. Our experimental results show that for the first attacking scenario, the PLA-SAT scheme offers more than 97% authentication accuracy when the received SNR of the served user with poor channel condition is at least 10 dB. For the second attacking scenario, both the PLA-SIT scheme and the PLA-TDM scheme offer more than 97% authentication accuracy when the received SNR of the served user with poor channel condition is at least 12 dB.

Two-Factor Authentication System Using P300 Response to a Sequence of Human Photographs

This paper proposes a two-factor authentication system that utilizes the knowledge factor: the knowledge of client’s acquaintances as the key and inherence factor: P300 ERP responses to the visual stimuli as the medium. The system works by presenting a sequence of human photographs consisting of random people photographs mixed with a few of client’s acquaintances photographs that trigger P300 responses. The system then verifies the client by considering the correctness of P300 responses to the client’s acquaintances photographs. The proposed system achieves an error rate of nearly zero outperforming other brain-signal-based systems and has advantages over other conventional systems in the situations where the key is exposed to the imposer.

0EISUA: Zero Effort Indoor Secure User Authentication

Two-factor authentication (2FA) systems implement by verifying at least two factors. A factor can be one or more of something a user knows (password, or phrase), something a user possesses (smart card, or smartphone), something a user is (fingerprint, or iris), something a user does (keystroke), or somewhere a user is (location). In a conventional 2FA system, a user is required to interacts (e.g., typing a passcode) in order to implement the second layer of authentication, which is not very user-friendly. Nowadays, smart devices (phones, laptops, tablets, etc.) can receive signals from different radio frequency technologies within range. As these devices move among networks (Wi-Fi access points, cell phone towers, etc.), they receive broadcast messages, some of which can be used to collect information. This information can be utilized in a variety of ways, such as establishing a connection, sharing information, locating devices, and, most appropriately, identifying users in range. The principal benefit of broadcast messages is that the devices can read and process the embedded information without being connected to the broadcaster. Moreover, the broadcast messages can be received only within a range of the wireless access point sending the broadcast, thus inherently limiting access to those devices in close physical proximity and facilitating many applications dependent on that proximity. In this paper, 0EISUA is proposed, a zero-effort two-factor authentication scheme based on something that is in the user’s environment (ambient access points). In our research, data from the broadcast messages are utilized to implement the second authentication factor by determining whether two devices are proximate or not to ensure that they belong to the same user, in a way that requires zero interaction from the user. The new proposed system introduced in this paper is experimentally tested.

Advanced security of two-factor authentication system using stego QR code

Advanced security of two-factor authentication system using stego QR code

This would work perfectly if it weren’t for all the humans: Two factor authentication in late modern societies

Late modern societies are now dependent on innumerable digitally networked technologies, yet there are intractable incongruencies between the technologies that we develop, and the corresponding technological literacies of users. This disjuncture has greatly increased the scope and scale of the risks to which globalized publics are exposed. With public cybersecurity literacies necessarily in decline as a result of the techno-social dynamism of “liquid modernity”, we now face an immense and exponentially growing matrix of cyberthreats and vulnerabilities, of which many carry potentially catastrophic consequences. Our interrogation of two-factor authentication systems, popularly implemented through short messaging services (SMSs), is demonstrative of vulnerabilities that continue to emerge as a result of widespread and entrenched disjunctures between the design of contemporary ICT systems, and the various flawed assumptions that undergird their implementation. We examined 400 authentication messages that were automatically posted to a public forum by Web sites commonly used to receive SMS authentication tokens on behalf of users. We found that 76.5 percent of those messages included the name of the application for which the message was intended: in so doing, over three quarters of our sample risked compromising their accounts. Occasionally, we even observed usernames and passwords posted together. The socio-technical implications of our findings for ICT system design in today’s globalized late modern societies are discussed.

A New Framework for Match on Card and Match on Host Quality Based Multimodal Biometric Authentication

Smart cards are widely used to deploy secure and cost effective identity management systems. Integration of biometrics into the smart card leads to a strong two-factor authentication system through the match on card (MOC) process. Since MOC uses fixed authentication strategies during the life cycle of smart card, this leads to a low performance and high failure to acquire error in uncontrolled noisy environments. To solve this problem, this paper proposes a sequential quality based framework for biometric authentication. In the proposed framework a set of classifiers have been used to manage the workflow of the framework based on the quality of samples. Accordingly, subjects can be dynamically authenticated using MOC and MOH. A multimodal chimera database is used to evaluate this framework. Our findings indicate that the proposed approach provides higher accuracy than the unimodal MOC and MOH by 11.29% and 5.12%, respectively. Furthermore, the proposed framework can authenticate 83.85% of users without auxiliary trait at the expense of only 1.21% lower accuracy compared to parallel fusion, which require acquisition of all traits for entire users. Analysis of the results demonstrates that the proposed approach provides a compromise between accuracy, user convenience, security and system complexity.

The implementation of two-factor web authentication system based on facial recognition

AbstractThe security of the web is a very important issue, because every day we make a variety of operations in it, for different reasons, during the day. Apart from protecting the information, contacts, accounts and data on the web, such data should be inaccessible to third-party persons. This in turn depends on the success of the authentication process performed on the individual web. With authentication, it is possible for users to protect their information and make their transactions only for themselves. However, the authentication mechanism used at this point must have a high level of safety. With the purpose to damage a person's privacy and access account information and gain profit in this way, many malicious persons have developed various methods of attacks to bypass authentication mechanisms. These methods sometimes succeed on a variety of authentication mechanisms, and put users and relevant websites into a difficult situation, and may even damage them in a variety of aspects. In order to protect personal information on the web system and provide the security of transactions carried out at a high level, in this study, we propose a two-factor authentication mechanism based on facial recognition. Besides, we discuss some implementation details about the proposed method. The proposed method aims to bring a new approach to the authentication system to perform our online process with the highest security. In addition to the standard authentication systems, using face recognition as a secondary level of security will contribute to the emergence of a new authentication mechanism.

The implementation of two-factor web authentication system based on facial recognition

The security of the web is a very important issue, because every day we make a variety of operations in it, for different reasons, during the day. Apart from protecting the information, contacts, accounts and data on the web, such data should be inaccessible to third-party persons. This in turn depends on the success of the authentication process performed on the individual web. With authentication, it is possible for users to protect their information and make their transactions only for themselves. However, the authentication mechanism used at this point must have a high level of safety. With the purpose to damage a person's privacy and access account information and gain profit in this way, many malicious persons have developed various methods of attacks to bypass authentication mechanisms. These methods sometimes succeed on a variety of authentication mechanisms, and put users and relevant websites into a difficult situation, and may even damage them in a variety of aspects. In order to protect personal information on the web system and provide the security of transactions carried out at a high level, in this study, we propose a two-factor authentication mechanism based on facial recognition. Besides, we discuss some implementation details about the proposed method. The proposed method aims to bring a new approach to the authentication system to perform our online process with the highest security. In addition to the standard authentication systems, using face recognition as a secondary level of security will contribute to the emergence of a new authentication mechanism.
 
 Keywords: Web authentication, two-factor authentication, web security, facial recognition.
 
 The security of the web is a very important issue, because every day we make a variety of operations in it, for different reasons, during the day. Apart from protecting the information, contacts, accounts and data on the web, such data should be inaccessible to third-party persons. This in turn depends on the success of the authentication process performed on the individual web. With authentication, it is possible for users to protect their information and make their transactions only for themselves. However, the authentication mechanism used at this point must have a high level of safety. With the purpose to damage a person's privacy and access account information and gain profit in this way, many malicious persons have developed various methods of attacks to bypass authentication mechanisms. These methods sometimes succeed on a variety of authentication mechanisms, and put users and relevant websites into a difficult situation, and may even damage them in a variety of aspects. In order to protect personal information on the web system and provide the security of transactions carried out at a high level, in this study, we propose a two-factor authentication mechanism based on facial recognition. Besides, we discuss some implementation details about the proposed method. The proposed method aims to bring a new approach to the authentication system to perform our online process with the highest security. In addition to the standard authentication systems, using face recognition as a secondary level of security will contribute to the emergence of a new authentication mechanism.
 Keywords: Web authentication, two-factor authentication, web security, facial recognition.

Multi-Factor Authentication with OpenId in Virtualized Environments

Despite the number of users accessing and storing your personal information in cloud services has increased considerably, there still is a certain barrier regarding to cloud adoption. Data security and confidentiality can be considered one of main reasons that affect both sides, clients and cloud providers. Some techinques has been implemented to hamper the data violation and inapropriated access, such as two-factor authentication, that requires two or more factors to liberate the service access to an user. This work presents a performance analisys of two-factor authentication system considering three different virtual environments (KVM, Xen, and VMware Player hypervisors). For the two-factor authentication process, we use the traditional login and password mechanism, and the One Time Password (OTP), as second factor; and for the identity management, we use the OpenID protocol that allows a Single Sign One access. Results show KVM hypervisor has the best performance when compared to two others.