Successful Authentication Research Articles

Optimizing point-of-sale services in MEC enabled near field wireless communications using multi-agent reinforcement learning

In the next-generation communication system, near-field communication (NFC) is a key enabler of contactless transactions, including mobile payments, ticketing, and access control. With the growing demand for contactless solutions, NFC technology will play a pivotal role in enabling secure and convenient payment experiences across various sectors. In contrast, Internet of Things (IoT) devices such as phones’ Point of Sale (PoS) constitute limited battery life and finite computational resources that act as a bottleneck to doing the authentication in a minimal amount of time. Because of this, it garnered considerable attention in both academic and industrial realms. To overcome this, in this work we consider the Multiple Mobile Edge Computing (MEC) as an effective solution that provides extensive computation to PoS connected to it. To address the above, this work considers the PoS-enabled multi-MEC network to guarantee NFC communication reliably and effectively. For this, we formulate the joint optimization problem to maximize the probability of successful authentication while minimizing the queueing delay by jointly optimizing the computation and communication resources by utilizing a multi-agent reinforcement learning optimization approach. Through extensive simulations based on real-world scenarios, the effectiveness of the proposed approach was demonstrated. The results demonstrate that adjusting the complexity and learning rates of the model, coupled with strategic allocation of edge resources, significantly increased authentication success rates. Furthermore, the optimal allocation strategy was found to be crucial in reducing latency and improving authentication success by approximately 9.75%, surpassing other approaches. This study highlights the importance of resource management in optimizing MEC systems, paving the way for advancements in establishing secure, efficient, and dependable systems within the Internet of Things framework.

Password based Smart Doorlock System using Arduino UNO for Enhanced Security

In recent years, the demand for secure access systems has increased significantly, especially in residential and commercial areas. Hence, this presents the design and implementation of a password-based door lock system using an Arduino microcontroller and a servo motor. The system provides a cost-effective and reliable solution for managing access to physical sites. The proposed system uses an Arduino microcontroller as the central device to control the authentication process and to control the servo motor that operates the door locking mechanism. A matrix keyboard is used to enter the password, which provides a user-friendly interface for communication. The servo motor is responsible for physically locking and unlocking the door mechanism based on the authentication result. The operational workflow of the system requires the user to enter a predetermined password using a keyboard. The Arduino microcontroller compares the entered password with the password stored in its memory. After successful authentication, a servo motor is operated to open the door, allowing access to the authorized person. Conversely, failed authentication will result in access being denied.

Improving the Security System for the Vehicle by Using the Driving License and Fingerprint Automation

In contemporary times, the widespread use of vehicles necessitates robust protection against theft, which is achieved through the integration of RFID tags and fingerprint authentication. This paper introduces a vehicle ignition system that leverages RFID tags and fingerprint recognition to safeguard vehicles from unauthorized access. Authorized RFID tags initiate the authentication process, complemented by fingerprint verification for driver identification. Upon successful authentication, a relay is activated, enabling the ignition system, while a red LED displays the status. In the event of authentication failure, an alarm buzzer prevents unauthorized entry. This system significantly enhances vehicle security and ensures a smooth user experience, with potential for customization and scalability across various vehicle models. Key components include In contemporary times, the widespread use of vehicles necessitates robust protection against theft, which is achieved through the integration of RFID tags and fingerprint authentication. This paper introduces a vehicle ignition system that leverages RFID tags and fingerprint recognition to safeguard vehicles from unauthorized access. Authorized RFID tags initiate the authentication process, complemented by fingerprint verification for driver identification. Upon successful authentication, a relay is activated, enabling the ignition system, while a red LED displays the status. In the event of authentication failure, an alarm buzzer prevents unauthorized entry. This system significantly enhances vehicle security and ensures a smooth user experience, with potential for customization and scalability across various vehicle models. Key components include Arduino, Fingerprint Sensor, RFID Reader, RFID Tag, GSM module, Relay, Motor, LED, and LCD. Key Words: Arduino, Fingerprint Sensor, RFID Reader, RFID Tag, GSM module, Relay, Motor, LED, and LCD.

Driver Identification and Detection of Drowsiness while Driving

This paper introduces a cutting-edge approach that combines facial recognition and drowsiness detection technologies with Internet of Things capabilities, including 5G/6G connectivity, aimed at bolstering vehicle security and driver safety. The delineated two-phase project is tailored to strengthen security measures and address accidents stemming from driver distraction and fatigue. The initial phase is centered on facial recognition for driver authentication before vehicle initiation. Following successful authentication, the subsequent phase harnesses continuous eye monitoring features, leveraging edge computing for real-time processing to identify signs of drowsiness during the journey. Emphasis is placed on video-based identification and analysis to ensure robust drowsiness detection. Finally, the study highlights the potential of these innovations to revolutionize automotive security and accident prevention within the context of intelligent transport systems.

SafePass : Reinventing Digital Access with Visual Cryptography, Steganography, and Multi-Factor Authentication

Safe-Pass presents a user-friendly and secure solution for simplifying digital access. With a downloadable application that operates seamlessly across your devices, it eliminates the inconvenience of traditional passwords. The process begins with accessing the Master password app through a distinctive image-based authentication. Operating inconspicuously in the background, the app not only enhances the strength of your existing passwords but also manages and facilitates automatic logins. This system offers adaptable security options, enabling swift access through a single factor or heightened security through the combination of multiple factors. Addressing the persistent threat of phishing, wherein sensitive user information is compromised, we introduce an innovative approach leveraging Visual Cryptography and Steganography for enhanced online security. Our method involves the application of Visual Cryptography to confidential credentials, generating two shares. One share is stored on the server, while the other is concealed within a reCAPTCHA image or a user-defined image through Steganography. During login attempts, users provide their username along with the reCAPTCHA image or chosen image. Successful authentication grants access, while repeated failed attempts trigger email notifications. Master Login prioritizes user privacy, safeguarding passwords as individual and exclusive data. Data sharing or selling is never practiced, ensuring the confidentiality of user information.

TLS-handshake for Plug and Charge in vehicular communications

Electric vehicle technology has brought some important issues to order. Securing the communication between electric vehicle and charging station is an important one. The International Organization for Standardization released ISO 15118 standard to specify the communication between electric vehicles and electric vehicle supply equipment. The ISO 15118 standard requires Transport Layer Security function for secure charging communication between electric vehicle and charging station as mandatory. The Transport Layer Security requirements have been completely changed with the latest version of the standard (ISO 15118-20) and have not been clearly described and implemented yet. The implementation of the function causes an inevitable vulnerability due to non-functioning authentication resulting with the entire vehicle function and security system can suddenly stop working. For this reason, new Transport Layer Security protocol must urgently be analyzed, developed, integrated, and implemented.This study proposes solutions for the development, implementation, realization of Transport Layer Security handshake requirements and functions between electric vehicle and charging station with ISO 15118 protocol. The new and existing Transport Layer Security requirements, analyzed, evaluated and the new Transport Layer Security functions derived and fully described. Based on these requirements and functions, a Transport Layer Security communication sequence and processes are developed and implemented and validated on the test bench. The validation proved sufficient implementation of the Transport Layer Security functions (successful authentication, exchange of cipher suite parameters and generation of the TLS master key). The messages were prosperous encrypted and decrypted with the generated master key. Thus, Transport Layer Security handshake is developed, implemented, and validated with this study.

IoT-based Facelook and Fingerprint Safe Security System

This research aims to develop an advanced safe security system by combining Facelook and Fingerprint technologies based on the Internet of Things (IoT). These technologies are expected to provide a higher level of security and facilitate access for safe owners. Subsequently, testing is carried out on the safe's opening mechanism after successful authentication via both the fingerprint sensor and the face recognition system. These trials encompass the evaluation of success rates, the speed of the opening mechanism, and the overall response time. Data from the testing phase is collected and analyzed to comprehensively assess the system's performance. The average notification delivery delay for the face recognition system was measured at 2.67 seconds with a standard deviation of 0.37. The notification delivery data revealed an average delay of 2.04 seconds with a standard deviation of 0.38 These findings collectively affirm the effectiveness of the integrated face recognition and fingerprint system in the proposed safe security setup

Optical cryptosystem based on computational ghost imaging and nonlinear authentication.

We propose an optical encryption system that combines computational ghost imaging (CGI) with image authentication to enhance security. In this scheme, Hadamard patterns are projected onto the secret images, while their reflected light intensities are captured using a bucket detector (BD). To further strengthen the security of the collected secret data, we encrypt it as a series of binary matrices serving as ciphertext. During the authentication key generation, these encoded binary matrices serve as illumination patterns in the CGI system for a non-secret image, which is used as a reference image for authentication. The data captured by the BD is then binarized to generate the authentication key. Upon successful authentication, the receiver obtains the decryption keys. This method achieves both data compression for secret images and enhanced security during information transmission. We validate the feasibility of this method through computer simulations and optical experiments.

Secret Key Management in Wireless Sensor Network Based on Probabilistic Technique

Data confidentiality implies that data access is limited to authorized entities only, thus measured data and transmitted data by wireless sensors require optimum security and privacy. Various techniques have been employed to implement effective security mechanisms for a wireless sensor network. However, the arsenal of these potential solutions is useless, considering the constrained nature of the Wireless Sensor Network (WSN) resources in terms of memory, processing and computational capacity. While considering an effective solution for this situation, care must be taken not to trade the desired solution for other factors. This paper considers the implementation of a probabilistic approach for key management in WSN. In the implementation, all kinds of communication within the wireless sensor nodes are presented by forwarding encrypted keys for mutual authentication. A successful authentication opens a communication channel for the communicating nodes. The encrypted keys are computed by generating a polynomial which constitutes the hashed ID concatenated with the master key and Message Authentication Code (MAC) address of the node. The results presented from the simulation of this model are benchmarked with the Dynamically Generated Polynomial (DGP). The proposed model was simulated using MATLAB tools and the comparison of the results obtained shows that the proposed model outperforms the DGP model by 87%, based on the key metrics which are energy consumption, storage and communication overhead.

Wireless Vocal Command Driven Robotic Car Using Arduino

Wireless Voice Control is an idea. A robotic car is an electronic device utilized for security. RF modules are used by many of the independently controlled robots. However, for robotic control, this idea makes use of an Android smartphone. There are numerous more control instructions available than RF modules. For this, the Android user must install an application on his or her device. Users must then enable Bluetooth on their handheld gadgets. The user can issue commands such as proceed forward, get back, turn left, turn right, stop, break, show me your dance, and furthermore. In parallel, while the Robotic Car is in mobility, the user can view the live VIDEO broadcast from the camera installed on the Robotic Car. To properly link and receive live feeds, the user must configure their machine with the camera module by providing a User Name and Password. To ensure the SECURITY of the data remains confidential, successful authentication is required. After authentication and configuration, the user has several options for camera settings. The user can click LIVE snapshots at the same pace. Explore the live video on his or her own device. This process is carried out through an electronic device known for its ESP CAM32.

Security enhancement in a cloud environment using a hybrid chaotic algorithm with multifactor verification for user authentication

A hybrid chaotic-based DNA and multifactor authentication strategy are created to improve the protection of the cloud environment. Initially, multimodal data are collected from the data owner then the information is compressed by utilizing the deflate compression approach. The data is then encrypted using hybrid chaotic-based DNA cryptography to increase the security of data. In this hybrid algorithm DNA is used for the key generation and chaotic algorithm is utilized for the encryption process. On the other hand, a multifactor authentication method is created to access data from the cloud to block access by unauthorized users. In that technique, users are requested to enter the registered Password with the generated OTP from the mobile number. Then, the device serial number is another factor to verify the accessing device. Likewise, the user's fingerprint and iris recognition are also validated for accessing the data. The cloud-based data can be accessible following users' successful authentication. The simulation analysis shows that the encryption and decryption time reached for image, string and integer data is 24, 0.065, 37, 0.14, 28 and 0.14 s, respectively, for the cloud security algorithm. The proposed algorithm effectively mitigates space consumption and provides improved data security in a cloud environment.

A novel deep learning based intrusion detection system for the IoT-Cloud platform with blockchain and data encryption mechanisms

The Internet of Things (IoT) integrated Cloud (IoT-Cloud) has gotten much attention in the past decade. This technology’s rapid growth makes it even more critical. As a result, it has become critical to protect data from attackers to maintain its integrity, confidentiality, protection, privacy, and the procedures required to handle it. Existing methods for detecting network anomalies are typically based on traditional machine learning (ML) models such as linear regression (LR), support vector machine (SVM), and so on. Although these methods can produce some outstanding results, they have low accuracy and rely heavily on manual traffic feature design, which has become obsolete in the age of big data. To overcome such drawbacks in intrusion detection (ID), this paper proposes a new deep learning (DL) model namely Morlet Wavelet Kernel Function included Long Short-Term Memory (MWKF-LSTM), to recognize the intrusions in the IoT-Cloud environment. Initially, to maintain a user’s privacy in the network, the SHA-512 hashing mechanism incorporated a blockchain authentication (SHABA) model is developed that checks the authenticity of every device/user in the network for data uploading in the cloud. After successful authentication, the data is transmitted to the cloud through various gateways. Then the intrusion detection system (IDS) using MWKF-LSTM is implemented to identify the type of intrusions present in the received IoT data. The MWKF-LSTM classifier comes up with the Differential Evaluation based Dragonfly Algorithm (DEDFA) optimal feature selection (FS) model for increasing the performance of the classification. After ID, the non-attacked data is encrypted and stored in the cloud securely utilizing Enhanced Elliptical Curve Cryptography (E2CC) mechanism. Finally, in the data retrieval phase, the user’s authentication is again checked to ensure user privacy and prevent the encrypted data in the cloud from intruders. Simulations and statistical analysis are performed, and the outcomes prove the superior performance of the presented approach over existing models.

Wireless Voice Controlled Robotic Car

The Wireless Voice Control Robotic Car project is a system used for security purposes. Although many wireless-controlled robots use RF modules, this project utilizes an Android smartphone for robotic control, with more control commands available compared to RF modules. To use this project, the user must install an application on their mobile device and turn on Bluetooth. Various commands, such as "go ahead," "get back," "turn left," "turn right," "stop," "break," and "show me your dance" are available. While the Robotic Car is in action, the user can watch a live video feed from the camera installed on it. In order to successfully connect to the live feed, users must configure their system with a username and password. Successful authentication is necessary to ensure that the data remains confidential. Once authentication and configuration are complete, the user has several options for camera settings

Secure Long-Range Autonomous Valet Parking: A Reservation Scheme With Three-Factor Authentication and Key Agreement

Long-range autonomous valet parking (LAVP) is a current trend, partly due to traffic congestion and parking headache. For large-scale parking demands, reservation is introduced to effectively manage valet parking. However, existing schemes focus on parking request verification and parking check-in, which aren't applicable to LAVP because they ignore identity legitimacy and communication security in the phase of picking up as well as dropping off passengers. One viable solution is authentication and key agreement (AKA) protocol. Generally, due to low entropy of passwords and dictionary attacks, three-factor (i.e. passwords, biometrics, and smart card) AKA is more secure than single- and two-factor AKA. Unfortunately, known attacks and high overheads hinder the application of three-factor AKA in real-world environments. Hence, one of the most tough tasks is to balance security and availability, especially how to address the potential threats introduced by each factor while taking full advantage of three factors. Inspired by the above challenges, we propose a provably secure three-factor AKA protocol for reservation services in LAVP, namely SecLAVP. Specifically, the passenger and the autonomous vehicle ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$AV$</tex-math></inline-formula> ) complete mutual authentication with the assistance of drop-off/pick-up point ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$DP$</tex-math></inline-formula> ). After successful authentication, the session key is generated between the passenger, <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$DP$</tex-math></inline-formula> , and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$AV$</tex-math></inline-formula> for secure communication. In the Real-Or-Random (ROR) model, we formally prove SecLAVP satisfies session-key security. Then, we apply AVISPA to simulate our proposed protocol, to demonstrate that SecLAVP can resist man-in-the-middle attacks. Additionally, informal security analysis indicates that SecLAVP satisfies our defined 16 design goals concerning security. Finally, we evaluate performance of SecLAVP in terms of communication overheads, computational overheads, and scheduling, to manifest the feasibility.

Secure Marine Environment Communication: A Multiobject Authentication Protocol Based on Secret Sharing

In the field of marine communication, with the rapid development of the Internet of Things, big data, blockchain, and other new-generation information technology, marine information security is gradually being attached to more and more coastal countries, and marine information technology has ushered in epoch-making development opportunities. However, marine communication networks are open, and marine equipment is vulnerable to attacks on communication systems. On the one hand, a malicious adversary can intercept and analyze information, obtain relevant data with high probability, and even obtain the identity information of the equipment. On the other hand, attackers can also maliciously inject false information. At the same time, it is difficult for the existing marine information security technology to guarantee the confidentiality and authenticity of information simultaneously, which will bring substantial potential hidden dangers to the development of the ocean. We propose a multitarget authentication and key exchange protocol for secure communication. Our protocol assigns complex cryptographic operations to servers, thus balancing the system’s security and efficiency. The secret is divided into multiple subsecrets using the secret sharing feature, and the subsecret information is used to manage the identity credentials of resource-constrained devices. Then, after successful authentication, the server reassigns the subsecret information of the device to achieve the dynamic generation of identity credentials. Meanwhile, a multitarget authentication scheme is proposed based on recovering secrets. In addition, device extension measures are provided to replace or increase devices. Finally, well-established cryptographic assumptions are used to prove the protocol’s security. Simulation results verify the effectiveness of the protocol in multiobjective authentication.

BSKM-FC: Blockchain-based secured key management in a fog computing environment

With an increase in the number of devices in the edge layer connected to the fog server of the fog computing environment, it is found that vulnerable and unauthorized activities are also increasing relatively. Thus, there is a requirement for authorized access control in such an environment that is governed by secured and efficient key management between the communicating devices. Many researchers have presented conventional solutions for key management depending on a third party. The third party operated for a key generation or key distribution in a fog computing environment based on a centralized architecture which leads to the drawbacks like a single-point failure and inconsistency of key management. So, effective and secured key management between the edge devices which are willing to communicate is the major concern to be addressed in the current digital world to achieve access control. This paper proposes a BSKM-FC (Blockchain-based Secured Key Management in a Fog Computing Environment) which is a decentralized system in a fog computing environment without using a third party. The BSKM-FC makes use of a one-way hash chain for the generation of private and public key pairs and ECC (Elliptic Curve Cryptography) for secured sharing. Upon successful authentication, the session key generation at both edge devices is based on the key pair provided by the fog server and stored securely in the blockchain. The BSKM-FC system uses private blockchain technology in the fog layer to provide secured storage and management. The work is implemented in the Truffle Blockchain and found that BSKM-FC performs better in terms of overall block preparation time. The security analysis of the proposed scheme is carried out based on the ROR model and also verified using AVISPA for some known attacks. Informal security analysis of the proposed work is performed by considering some of the known attacks where we observe that the proposed scheme overcomes such attacks. Performance overhead analysis is demonstrated using MIRACL considering computation cost, communication cost, and storage cost. The results show that the proposed scheme meets security requirements and performs effectively. The computation overhead, communication overhead, storage overhead, and block preparation time of the proposed scheme were improved by 7% to 14%, 9% to 18%, 7% to 17%, and 14% to 28%, respectively, as compared to existing schemes.

An Efficient Authenticated Key Agreement Scheme Supporting Privacy-Preservation for Internet of Drones Communications.

In recent years, due to the rapid development of Internet of things (IoTs), various physical things (objects) in IoTs are smart enough to make their own decisions without the involvement of humans. The smart devices embedded in a drone can sense, collect, and transmit real-time data back to the controller from a designated environment via wireless communication technologies. The mobility, flexibility, reliability and energy efficiency of drones makes them more widely used in IoT environments such as commercial, military, entertainment applications, traffic surveillance and aerial photography. In a generalized IoD architecture, we have communications among the drones in a flying zone, among the drones and the control server, and also among the drones and authorized user. IoD still has many critical issues that need to be addressed, such as data access being carried out through a public channel and battery operated drones. To address these concerns in IoD communications, in this paper, an efficient authentication and secure communication scheme with privacy preservation is proposed and it only uses secure one-way hash function and bitwise XOR operations when control server, drone and user mutually authenticate each other. After the successful authentication, both IoD-based participants can agree on a common session key to secure the subsequent communication messages. The widely accepted ProVerif and BAN logic analysis have been used to assure that the proposed scheme is provably secure against existing well-known security attacks and ensures privacy. Finally, a comparative analysis is presented to demonstrate the proposed scheme preserves efficiency when compared to existing competitive schemes.

WALLET-BASED AUTHENTICATION ON COLLEGE INFORMATION SYSTEM

Since the widespread use of cryptocurrency, blockchain technology start to be adapted in various applications. Some businesses are already adopting blockchain technology because of its advantages such as data integrity and privacy. One of them is Web 3.0. Web 3.0 puts forward data decentralization so that users can choose what data will be sent to the server. User data is provided locally with the help of a crypto wallet and the server just receives wallet info. With this mechanism, user privacy can be maintained directly by the user himself. All data will be processed at the users' end first before being sent to the server. With the new mechanism of web 3.0 and the advantages of blockchain, we build an application to authenticate students' login activities and grant roles to them based on their wallets. In this paper, we use the prototyping model as the method to build the application. We managed to utilize students’ wallet addresses as credentials. And with the help of Web3 module, we managed to decentralize the authentication process. And as a result of the successful authentication process, students can access their data based on their roles.

Quality of Service aware secure data transmission model for Internet of Things assisted wireless sensor networks

AbstractWireless sensor networks (WSNs) are the most critical networks in developing various Internet of Things (IoT) based applications. However, such intelligent devices have drawbacks for energy, memory, processing, and computation resources. In addition, achieving Quality of Service (QoS) with secure data transmission (DT) is a significant challenge for WSNs. This article proposes efficient IoT authentication and energy‐aware safe DT models for achieving better QoS and security with lower energy consumption (EC) in WSNs. Initially, the network randomly deploys the sensor nodes (SNs) and performs the registration of the SNs with the base station (BS). Second, the Entropy‐based Jaccard similarity induced fuzzy C‐means clustering (EJS‐FCM) model clusters the SNs based on the intrinsic qualities of nodes. Then the boosted grasshopper optimization algorithm (BGOA) selects the cluster heads (CHs) optimally by considering major fitness parameters such as communication distance, energy, and distance centroid. Following that, an Adler‐32 hashing‐based authentication scheme performs authentication of every IoT node deployed in the network to provide safer DT. After successful authentication, secure hash elliptical curve cryptography (SHECC) encrypts the data collected from the CHs by incorporating a hashing function both in encryption and decryption, enhancing the IoT data's security level. Finally, in a cloud server (CS), the decentralized blockchain (BC) stores the encrypted data and the authentication credentials of the IoT devices from the BS, which provide additional security to the network. The results of the presented model show its performance efficiency over existing approaches for energy efficiency (EE), QoS, and security.

PrivFace: Fast Privacy-Preserving Face Authentication With Revocable and Reusable Biometric Credentials

Privacy concerns of using sensitive biometric data as credentials arise with the wide adoption of user-friendly face authentication. To protect the facial features of users, two important functions, i.e., <i>revocability</i> and <i>reusability</i> , are anticipated to be realized in a privacy-preserving face authentication design. Revocability requires an effective approach to deregister or replace user credentials when the authentication server is compromised; For reusability, the same credentials should appear independently to non-cooperating applications. Accomplishing these two properties is challenging as the uniqueness of facial features. In this article, we present <small>PrivFace</small> , a fast privacy-preserving face authentication, supporting revocable, and reusable biometric credentials. The core innovation is a novel secure inner product protocol that employs a lightweight random masking technique instead of time-consuming public-key cryptographic operations to efficiently measure facial data similarity. We rigorously analyze the security to show that the server cannot acquire the user's sensitive biological features during the authentication. Our experiment with real-world datasets shows that <small>PrivFace</small> is friendly to edge smart devices, which takes less than <inline-formula><tex-math notation="LaTeX">$100 ms$</tex-math></inline-formula> per successful authentication on a common smartphone and outperforms the prior art J. Lei, Q. Pei <i>et al.</i> [1]. by <inline-formula><tex-math notation="LaTeX">$20 \times$</tex-math></inline-formula> . We have made the relevant codes open-source to the community for further research.