Search

Abstract People commonly use automated teller machines, also known as ATMs, in contemporary culture. The use of ATMs for currency withdrawal is becoming increasingly widespread in the modern world. Furthermore, attacks and break-ins have increased, highlighting the need for an ATM that is more secure and equipped with extra safety measures. The existing method of confirming these transactions through credit cards and ATMs carries a high level of risk. Card trapping, cash larceny, shoulder surfing, and ATM skimming are among the examples. The proposed system, which is based on biometrics and deep convolutional neural networks, can effectively resolve the problems associated with conventional ATM cards and PINs. The proposed method relies on face biometrics, which offers a novel technique to address the current challenge. This article presents a novel end-to-end multiscale attention-based light-weighted deep convolutional neural network (MA-LW-DCNN) framework for enhancing the accuracy of recognizing faces. The multiscale attention mechanism in face recognition enhances feature extraction by applying convolution filters at various scales, allowing the network to capture detailed and global facial features. It generates an attention map by normalizing characteristic maps and refining them using activation functions, improving recognition accuracy by focusing on essential face regions. The suggested system is assessed using a synthetic dataset against conventional machine and deep learning-based face recognition techniques. The experiment results for different individuals demonstrate an accuracy rate of around 99.84% in authenticating test samples. The proposed approach produced significantly improved evaluation measures precision, recall, and loss by 0.99, 0.99, and 0.16, respectively.

A patient-centered personal health records system has been actively promoted in recent years. Its purpose is to maintain long-term personal records and health improvement plans. It combines a cloud computing environment to build a personal health records system to quickly collect personal information and transfer it to the back end for storage for future access. However, in a cloud environment, the message transmission process is more open. Therefore, a lack of an authority security mechanism for the users of such an architecture will result in distrust and doubt by the users. This adversely affects the implementation and quality of long-term health plans. To protect the crucial privacy of the users from malicious attacks or theft, it is necessary to ensure that the users have different authority to access their personal health records under the cloud computing environment and manage the openness of their authority to other users. A secured identify authentication mechanism can ensure that only legitimate users can log in to the system and obtain system service resources through verification. For a personal health records system in the cloud computing environment, this study proposes a secure and reliable user authentication mechanism allowing relevant users access to the user's PHR in the cloud based on their authority. The proposed authentication method uses a password combined with a smart card, allowing the owner and authorized users to log in to the system and access the relevant personal records. In this study, an authentication method based on bilinear pairing was used to verify the identity of users and to effectively prevent malicious intrusion and theft. [ABSTRACT FROM AUTHOR]

Accurately understanding the travel demand of urban rail transit (URT) systems is crucial for effective operational management. Despite the recognition that the diversity in human activity patterns results in different travel demands, few studies have thoroughly investigated the heterogeneity among passengers and its impact on URT ridership. This study utilizes smart card data collected from the Beijing Subway to categorize passengers into four groups: tourist passengers, flexible commuters, regular commuters, and life-oriented passengers, based on their spatiotemporal travel patterns. Furthermore, a Multiscale Geographically Weighted Regression (MGWR) model is employed to examine the relationship between station-level ridership of URT and its determinants, including the built environment and station properties, for each passenger group. The results indicate that the influence of these determinants on station-level ridership varies across passenger groups and spatial scales. For instance, regular commuters exhibit lower sensitivity to accessibility on workdays, whereas those unfamiliar with the URT network are more concerned about the bus accessibility in pedestrian- or bicycle-unfriendly areas. Notably, for tourist and life-oriented passengers, the stations significantly affected by population density are concentrated in areas with a higher proportion of elderly individuals. Conversely, for flexible and regular commuters, these stations are predominantly situated in areas associated with internet technology and scientific research. These findings are valuable for policymakers in designing strategies tailored to different passenger groups to balance trip demand and capacity, thereby improving URT services and promoting a sustainable urban environment., Author(s): Qian Qian [1]; Yang Liu [2]; Min He [2]; Mingwei He [2]; Huimin Qian [3]; Zhuangbin Shi (corresponding author) [2] 1. Introduction Unbridled urban expansion and excessive reliance on [...]

Nowadays, smart card and password-based user authentication and key agreement schemes have become an integral mechanism to ensure only legitimate users get access to the data of wireless sensor networks (WSNs). In the recent past, lots of password-based multi-factor user authentication schemes have been developed by the researchers. However, most of them are not secure against various known attacks. Recently, two user authentication and key agreement schemes for WSNs are suggested by Chen and Chen (J Supercomput 77(12):13653–13675, 2021) and Qi and Chen (J Supercomput 77(12):13897–13910, 2021). They claim that their schemes are secure against all known attacks. We analyze the security of these schemes and demonstrate that these schemes are not secure against some common attacks (such as smart card lost attack) and do not provide common security features such as user untraceability and forward secrecy. By keeping all the merits of these schemes, we suggest a new provably secure user authentication and key agreement scheme using physically unclonable functions and elliptic curve cryptography. To verify the security and authentication properties of the suggested scheme, we use the well-known Proverif tool for formal security verification. We further prove its security informally. Finally, performance comparison with some recent schemes in terms of security features and computational cost is performed. Performance comparison results show the superiority of the suggested scheme over the existing schemes. [ABSTRACT FROM AUTHOR]

Sistem parkir otomatis merupakan salah satu teknologi manajemen parkir yang saat ini banyak digunakan di berbagai instansi. Sistem parkir otomatis merupakan sistem parkir yang bekerja dengan menempatkan sebuah mesin portal parkir. Mesin portal parkir tersebut kemudian secara otomatis dapat membuka dan menutup portal serta merekam nomor kendaraan saat masuk dan keluar dengan menggunakan sebuah kunci akses berupa smart card. Salah satu kendala dalam penerapan sistem parkir otomatis adalah terjadinya kemacetan apabila kondisi lalu lintas sedang tinggi. Hal tersebut terjadi karena unit kontrol pada sistem parkir otomatis memerlukan waktu yang relatif lama saat melakukan proses pengambilan dan penyimpanan citra dari kamera. Dalam penelitian ini, dilakukan pengujian pada beberapa platform sistem tertanam yang nantinya digunakan sebagai unit kontrol pada sistem parkir otomatis, yaitu Raspberry Pi 3B, Raspberry Pi 4B, dan Orange Pi Zero Plus. Tujuan pengujian tersebut adalah untuk mencari platform unit kontrol terbaik dengan beberapa kriteria, yaitu memiliki waktu respons tercepat saat mengambil citra, memiliki waktu respons tercepat saat menyimpan citra, dan memiliki konsumsi daya yang rendah. Dari pengujian yang dilakukan, didapatkan hasil bahwa platform Raspberry Pi 4B memiliki waktu respons tercepat untuk mengambil dan menyimpan citra dengan waktu rata-rata sebesar 1.827,9 ms, sedangkan konsumsi daya terendah dicapai oleh platform Orange Pi Zero Plus dengan nilai sebesar 1,9 W. Dari hasil pengujian yang telah dilakukan, Raspberry Pi 4B direkomendasikan sebagai unit kontrol pada sistem parkir otomatis apabila sistem parkir otomatis memerlukan perangkat dengan kinerja tinggi. Sementara itu, jika sistem parkir otomatis memerlukan perangkat yang hemat daya, Orange Pi Zero Plus direkomendasikan sebagai unit kontrol pada sistem parkir otomatis.

Summary: Cloud computing is an emerging paradigm that enables on‐demand data storage without considering the local infrastructure limitations of end‐users. The extensive growth in number of servers, resources, and networks intensifies security and privacy concerns in clouds. This necessitates secure mutual authentication and key agreement mechanism to verify the legitimacy of participating entities. In accordance, several authentication protocols have been designed to authenticate end‐users over insecure channels. This article presents security analysis of recent protocols that claim to render security and privacy features. We demonstrate that Kaur et al.'s protocol is vulnerable to replay attack, Dharminder et al.'s protocol is prone to user traceability and known session‐specific temporary information (KSSTI) attacks, and Bouchaala et al.'s protocol is prone to replay and KSSTI attacks. To withstand the aforementioned attacks, we propose an enhanced protocol based on fuzzy verifier and elliptic curve cryptography for clouds. Our protocol safeguards against security attacks while providing privacy functionalities. The security analysis is illustrated under real‐or‐random model, and correctness is verified under the Scyther security verification tool. Finally, comparative analysis with existing protocols shows that our protocol delivers robust security with reasonable computational and communication overheads than state‐of‐the‐art protocols. [ABSTRACT FROM AUTHOR]

The widespread and growing interest in the Internet of Things (IoT) may be attributed to its usefulness in many different fields. Physical settings are probed for data,which is then transferred via linked networks. There are several hurdles to overcome when putting IoT into practice, frommanaging server infrastructure to coordinating the use of tiny sensors.When it comes to deploying IoT, everyone agrees that security is the biggest issue. This is due to the fact that a large number of IoT devices exist in the physicalworld and thatmany of themhave constrained resources such as electricity,memory, processing power, and square footage. This research intends to analyse resource-constrained IoT devices, including RFID tags, sensors, and smart cards, and the issues involved with protecting them in such restricted circumstances. Using lightweight cryptography, the information sent between these gadgets may be secured. In order to provide a holistic picture, this research evaluates and contrasts well-known algorithms based on their implementation cost, hardware/software efficiency, and attack resistance features.We also emphasised how essential lightweight encryption is for striking a good cost-to-performance-to-security ratio. [ABSTRACT FROM AUTHOR]

As Wireless Sensor Networks (WSN) uses the open channel for communication between the end users and the resource-constrained sensors; maintaining privacy and security is always a challenging task. In this context, Khalid et al. proposed a biometric-based user authentication and Key agreement (AKA) scheme in WSN based on intelligent sensors. However, during this research, it is found that the schemes have many computational flaws and are under the threat of different attacks, such as Impersonation attacks, Stolen Smart Card (SC) attacks, etc. So, to overcome the vulnerabilities found in Khalid et al.'s scheme, an improved robust mutual AKA scheme for WSNs having intelligent sensors is proposed in this article. Moreover, the correctness of the scheme is verified by Burrows–Abadi–Needham (BAN) logic, and the security is proved by Automated Validation of Internet Security Protocols and Applications (AVISPA) simulation tool. Through various security analysis, performance evaluation and comparison with the existing related schemes shows that the proposed scheme could not only highly resistance against various well-known attacks than others but also maintain the low cost at sensor nodes, as well. [ABSTRACT FROM AUTHOR]

In order to authenticate remote users for a distributed network-operated system, remote user authentication is crucial. A huge number of enterprise apps run on several servers and a remote user accessing services from several servers needs authentication for most of the cases. In this current research communication a smart card-based remote user authentication in a multi-server environment using user biometrics and a Chebyshev chaotic map is introduced. The server details are hidden from the user, and the user is only given the option of picking his or her service based on its requirements. The server is chosen by the registration center based on the service requested by the user, and a handshaking session is established between the user and the server. Both user and server have to authenticate to the registration center by message passing. Finally, a session key is obtained using this procedure, which is used to accomplish further communication. The proposed solution facilitates modifying passwords and enabling additional services easier. The proposed approach is authenticated using formal security analysis utilizing BAN logic. Security analysis and comparison with some state of the art schemes proves its suitability for multi-server environment. [ABSTRACT FROM AUTHOR]

AbstractSmart cards, integrated circuit cards, are frequently used to pay transportation fees in many countries such as the United States, the European Union, Korea and others. Smart card transaction histories in public transportation have been used in making diverse traffic policies. Unfortunately, data preprocessing is required to organize records to extract useful information since the raw data contain artifacts and incomplete information. The paired data, i.e. a boarding and its associated alighting, are one of the key pieces of information required to yield the city traffic demand. However, it is difficult to gather the paired data mainly because the card tagging policies and data collecting methods vary from city to city and from institution to institution. The broken trip links between the boarding and its associated alighting information are the most frequent incomplete data in the smart card histories. Although huge budgets are spent on annual traffic surveys in many countries, there are no accurate Smart card data analysis methods that cover all city cases due to high data complexity and limited base information. Among these two restrictions, limited information is more difficult to resolve because it has a large codomain, thousands of stops, for inference under tiny samples. It gives handicaps of applying well-known high-performance approaches such as deep learning and probability analysis. We propose a reconstruction method by a customized clustering algorithm based on coordinates of transactions-occurred stops, user trip histories and actual vehicle movement trajectories for incomplete trip pairs. The proposed method is derived from evaluating each passenger’s historical clusters and trip patterns. In a blind test 79.1% accuracy is achieved in predicting missing alighting stops while conventional methods reach only 42.3% accuracy.

The object of research is the effectiveness of the implementation of electronic fare collection systems on public transit. Applying the electronic fare collection systems is a general trend in improving public transport services for users. In the pre-war period, the systems began to be implemented in many cities of Ukraine. At the same time, this activity was not of a systemic nature and at the current stage it is mainly considered as a means of ensuring more convenient conditions for the use of scheduled passenger transport services for passengers. The article focuses on a broader understanding of the effectiveness of the fare collection systems implementation, their role in ensuring the internal integration of the multi-modal public transport system, increasing the operational efficiency, providing the safety of transportation and increasing the attractiveness of public transit services for the population as a real alternative for the private cars to use. The implementation efficiency of the electronic fare collection systems in public transit should be expressed through various aspects. There are 9 aspects to be considered: system integration; comfort ensuring; transportation safety assistance; operational efficiency and passengers’ travel time reduction; integration into the management and planning systems; implementation of the flexible fare system; conduction of the flexible fare policy; development of reasonable income distribution system; increase of the scheduled passenger transport services attractiveness. It is suggested to use systemic approach for integrated multimodal public transit system creation. It requires the development of an intelligent transport system that would integrate separate functions of the electronic fare collection system into controlling, managing and planning subsystems. The practical introduction of the solutions proposed regarding the prospects to develop electronic fare collection systems in the cities of Ukraine will make it possible to increase the efficiency of their use and contribute to the improvement of the quality of transport services for passengers. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic drastically changed the way of living for billions of people and severe restrictions were implemented by governments around the world, affecting the travel patterns of all citizens. This article investigates how travel patterns changed in the Greater Copenhagen area of Denmark during the full two-year period covering 2020 and 2021, thus allowing for an analysis of both the short-term and medium-term impacts as society gradually reopened and restrictions were lifted. The analysis covers large-scale travel survey data as well as a segmentation clustering analysis of public transport smart card data. The results showed that impacts were strongly linked to changes in trip purpose and were thus not uniformly distributed throughout the public transport system. User segmentation analysis revealed that most users changed to less intense travel use of public transport. The results highlight important policy implications in terms of how to adapt service provision within a public transport network more efficiently., Author(s): Vincent Henrion [1,2]; Jesper Bláfoss Ingvardson (corresponding author) [1]; Otto Anker Nielsen [1] 1. Introduction The worldwide spreading of the COVID-19 virus during the beginning of 2020 drastically changed [...]