Security Features Research Articles

Enhancing User Experience in Private Bank Mobile Banking: Insights from Management Information System Analysis

This research explores the impact of Management Information Systems (MIS) on user experience in private bank mobile banking, focusing specifically on the effectiveness of m-BCA. Utilizing a descriptive quantitative approach, the study aims to understand how mobile banking features, including accessibility, user interface, security, and functionality, influence user satisfaction. Data were collected through direct experimentation with the m-BCA application, complemented by analysis from secondary data sources and a survey of 30 users. Results indicate that 93.3% of users find m-BCA effective for routine banking needs, attributing high ratings to its convenience and functionality. However, while 80% of respondents appreciate the current security measures, 20% cite the absence of advanced security features such as fingerprint and facial recognition as a drawback. The study also reveals mixed feedback on the user interface; while the straightforward design aids usability, 10% of users express a desire for a more visually appealing interface. Despite these areas for improvement, m-BCA’s comprehensive set of features is generally seen as effective, supporting users in performing essential transactions with ease and reliability. The findings suggest that enhancing interface aesthetics and integrating advanced security options could further boost user engagement and trust in mobile banking applications, underscoring MIS’s role in meeting evolving customer expectations in digital banking.

Balancing Security and Efficiency: A Power Consumption Analysis of a Lightweight Block Cipher

This research paper presents a detailed analysis of a lightweight block cipher’s (LWBC) power consumption and security features, specifically designed for IoT applications. To accurately measure energy consumption during the execution of the LWBC algorithm, we utilised the Qoitech Otii Arc, a specialised tool for optimising energy usage. Our experimental setup involved using the Otii Arc as a power source for an Arduino NodeMCU V3, running the LWBC security algorithm. Our methodology focused on energy consumption analysis using the shunt resistor technique. Our findings reveal that the LWBC is highly efficient and provides an effective solution for energy-limited IoT devices. We also conducted a comparative analysis of the proposed cipher against established LWBCs, which demonstrated its superior performance in terms of energy consumption per bit. The proposed LWBC was evaluated based on various key dimensions such as power efficiency, key and block size, rounds, cipher architecture, gate area, ROM, latency, and throughput. The results of our analysis indicate that the proposed LWBC is a promising cryptographic solution for energy-conscious and resource-limited IoT applications.

Controller Area Network (CAN) Bus Transceiver with Authentication Support and Enhanced Rail Converters

This paper presents an advanced Controller Area Network (CAN) bus transceiver designed to enhance security using frame-level authentication with the concept of a nonphysical virtual auxiliary data channel. We describe the newly conceived transceiver security features and provide results concerning the design, implementation, fabrication and test of the transceiver to validate its functionality and robust operation in the presence of systemic error sources including Process, Voltage, and Temperature (PVT) variations. The virtual auxiliary channel integrates CAN frame authentication signatures into the primary data payload via phase modulation while also providing compatibility with existing CAN protocols, interoperability with non-enhanced systems and requiring no network or software modifications. Enhanced rail converters are designed to facilitate single-rail to dual-rail data conversion and vice versa, preserving phase information and minimizing phase errors across various nonideal effects such as frequency drift, Process, Voltage, and Temperature (PVT) variations, and cable phase mismatch. This ensures reliable data transmission and robust authentication in the presence of adversarial cyberattacks such as packet injection. The receiver recovers both the CAN frame data and the security signature, comparing the latter with an authorized signature to provide a real-time “GO/NO_GO” signal for verifying packet authenticity and without exceeding the CAN clock jitter specifications.

Analysis of Customer Retention Determinant Factors on Generation Z Digital Wallet Services in Indonesia

This study aims to identify the factors influencing customer retention in Generation Z's use of digital wallet services in Indonesia. The research uses PLS-SEM through SmartPLS 4.1.0. A total of 334 respondents from various cities in Indonesia participated in the survey. The analysis employs outer model evaluation and inner model evaluation to examine the relationships between brand image, attention to safety, consumer satisfaction, and customer retention. The findings indicate that brand image does not have a direct effect on customer retention but exerts a significant indirect effect through consumer satisfaction. Consumer satisfaction fully mediates the relationship between brand image and retention, while it partially mediates the relationship between attention to safety and retention. The strength of the mediation effect was confirmed using the bootstrapping method. These results provide valuable insights for digital wallet service providers in developing strategies to retain Generation Z users by enhancing both brand image and security features, ultimately improving consumer satisfaction.

Photoluminescent Y2O3:Eu3+@PVA composite dispersions and films for anti-counterfeiting ink applications

The development of high-tech anti-counterfeiting inks to detect counterfeit products is a crucial task for almost every aspect of modern life around the world. Herein, we report the synthesis of photoluminescent xY2O3:Eu3+@PVA (x = 0, 1, 2.5, 5, 10, 15, and 20 wt%) composite dispersions and films and demonstrate their potential for anti-counterfeiting inks applications. Laser-synthesized m-Y2O3:Eu3+ nanoparticles (daver = 20.3 ± 6.9 nm) with strong red luminescence due to 5D0 → 7F0-4 transitions of Eu3+ were used as a pigment to create luminescent composites. Detailed photoluminescence properties of the obtained composite dispersions and films as a function of m-Y2O3:Eu3+ content were investigated in combination with SEM, EDX, UV–Vis and IR spectroscopy data. Tuning of the CIE coordinates of xY2O3:Eu3+@PVA is observed by changing the excitation wavelength. The results of SEM showed that the photoluminescent nanoparticles were uniformly distributed in the PVA film. Photoluminescent m-Y2O3:Eu3+-doped PVA composite inks can be applied via spray, brush, and screen-printing techniques to create security features on various surfaces, including glass, ceramics, paper, plastics, and currency notes. These inks remain stable for at least four months and offer a distinctive luminescent signature that is challenging to replicate, owing to the unique photoluminescence spectrum of Eu3+ in the monoclinic Y2O3 polymorph.

Ternary Eutectic Electrolyte for Flexible Wide-Temperature Zinc-Ion Batteries from -20 °C to 70 °C.

Aqueous Zn-ion batteries (ZIBs) have attracted attention for grid applications due to their cost-effectiveness and high security. However, their lifespan decreases at high temperatures due to declining interfacial stability and increased side reactions. To address these challenges, a ternary deep eutectic solvent-based flexible electrolyte, comprised of Zn(ClO4)2 ⋅ 6H2O, butanedinitrile (BD), and LiCl in an amphoteric polymer matrix, was developed to enable wide-temperature ZIBs working from -20 °C to 70 °C. The interactions among BD, Li+, and zinc hydrate alongside the amphoteric groups on the polyelectrolyte matrix could effectively suppress the interfacial side reactions and Zn dendrites formation. Consequently, the symmetric Zn cell demonstrates exceptional stability across a wide-temperature range, with the ability to survive up to 2780 hours (1 mA cm-2) at 50 °C. Furthermore, the flexible Zn||PANI battery can operate stably over 1000 cycles at 50 °C, boasting an initial specific capacity of 124.8 mAh g-1 and capacity retention rate of 87.9 % (3 A g-1). This work presents an effective strategy for designing high-stability energy storage devices with excellent security features that can function reliably across diverse temperature conditions.

A Study on Consumer Preference of UPI With Reference to Ahmedabad City

This study investigates the associations between age and preferences for various payment methods, particularly focusing on Unified Payments Interface (UPI). Utilizing a quantitative approach, we tested multiple alternative hypotheses to explore how age influences payment preferences and perceptions. Results indicate that younger consumers tend to favor UPI due to its convenience, while older adults exhibit a preference for traditional payment methods such as debit and credit cards. Concerns about security and usability are notably more pronounced among older users, suggesting the need for tailored educational initiatives and user-friendly designs. The findings contribute to existing consumer behavior theories by integrating age as a critical factor in technology adoption. Practical implications emphasize the importance of targeted marketing strategies, enhanced user experiences, and effective communication regarding security features to foster greater acceptance of digital payment systems across all demographics. Recommendations for future research include longitudinal studies, cross-cultural comparisons, and an exploration of emerging technologies in the payment landscape. Understanding these dynamics is crucial for stakeholders aiming to enhance digital payment adoption and ensure inclusivity in the financial ecosystem

Ternary Eutectic Electrolyte for Flexible Wide‐Temperature Zinc‐Ion Batteries from −20 °C to 70 °C

AbstractAqueous Zn‐ion batteries (ZIBs) have attracted attention for grid applications due to their cost‐effectiveness and high security. However, their lifespan decreases at high temperatures due to declining interfacial stability and increased side reactions. To address these challenges, a ternary deep eutectic solvent‐based flexible electrolyte, comprised of Zn(ClO4)2 ⋅ 6H2O, butanedinitrile (BD), and LiCl in an amphoteric polymer matrix, was developed to enable wide‐temperature ZIBs working from −20 °C to 70 °C. The interactions among BD, Li+, and zinc hydrate alongside the amphoteric groups on the polyelectrolyte matrix could effectively suppress the interfacial side reactions and Zn dendrites formation. Consequently, the symmetric Zn cell demonstrates exceptional stability across a wide‐temperature range, with the ability to survive up to 2780 hours (1 mA cm−2) at 50 °C. Furthermore, the flexible Zn||PANI battery can operate stably over 1000 cycles at 50 °C, boasting an initial specific capacity of 124.8 mAh g−1 and capacity retention rate of 87.9 % (3 A g−1). This work presents an effective strategy for designing high‐stability energy storage devices with excellent security features that can function reliably across diverse temperature conditions.

Comparative analysis of remote user authentication schemes based on external memory

Because of recent availability of remote services and resources, remote user authentication becomes an essential component of all digital environment. Remote user login authentication is the process of validating the identity of a user. Users present their credentials, such as username and password, as evidence of their identity. The most practical and effectively implemented remote user authentication scheme is the smart card-based one, however, because it is expensive to acquire and operate smart card facilities, users may find it challenging to employ smart card authentication schemes in remote environments. Mobility and simplicity of acquisition—especially for remote access—are the benefits of using this external memory. Therefore, this research performs comparative analysis of these remote user authentication schemes based external memory. The schemes are first evaluated for security features and performance in terms of computation cost. The results of analysis shown that Buhari et al.’s scheme has the highest security feature and is the only scheme that uses light-weight tamper resistance client file, followed the reviewed Kumari et al.’s scheme which is the only scheme that handles user privacy. The most efficient scheme is Buhari et al.’s scheme followed by Rhee et al.’s scheme.

Edge Computing vs. Cloud Computing: A Comparative Analysis for Real-Time AI Applications

AbstractReal-time AI has been evidenced to be supported by two models, namely edge computing and cloud computing. This research seeks to compare the two methods: Latency, security features, and data processing capabilities will be among the most critical aspects of comparison. Real-time AI applications are envisioned to be robust through 2020, most of which will be used in applications such as autonomous automobile systems and IoT devices that demand low latency for data processing. As data processing is outsourced in clouds, it is elastic and centralized, but this deal faces latency problems when the distance between the source of data and the processing center is large. On the other hand, edge computing refers to conducting computation closer to the data source, which could reduce latency and enhance everyday real-time performance.This research assesses the above models based on the literature review, technical papers, and case studies from industries that depend more on real-time AI. According to the research, edge computing is typically more effective for latency-sensitive workloads, while cloud computing outperforms throughput-intensive applications. Security concerns, however, present themselves as having dual effects; while advancing the privacy of handling data through edge computing, it elevates new risks. As such, this study concludes that no clear winner depends on the necessary application, therefore recommending a symmetric mode for the requirements, where both latency time and computational needs are required. Further studies should be conducted to establish the coordinated implementation approach of these models.

Geofence‐Based Boundary Violation Detection Algorithms in Unmanned Aerial Vehicles

ABSTRACTGeofence is a virtual boundary that helps in location‐based services. Unmanned aerial vehicles (UAVs) fly without a pilot, and geofence helps in regulating these vehicles and constraints a UAV to enter the boundary of other UAV. However, these have to go through many safety and security features like avoiding collision, complying within the restricted area, and organizing airspaces with high traffic. The UAVs need to be within the boundaries to avoid various damages to property and loss of lives. Geofences help to detect boundary violation of UAVs to a great extent. This study uses various mathematical algorithms to create geofences and detect boundary violation of UAVs. The existing methods, Delaunay triangulation and triangle weight characterization with adjacency, are implemented. The existing methods have high execution time as well as high standard deviation and low accuracy. Further, a novel method for boundary violation detection is proposed using a convex hull to create geofences. The results show that the proposed method improves the execution time by 59.23% and accuracy by 1.35%.

Hybrid dung beetle optimization based dimensionality reduction with deep learning based cybersecurity solution on IoT environment

The Internet of Things (IoT) interconnects various devices and objects through the Internet to interact with corresponding devices or machines. Now, consumers can purchase many internet-connected products, from automobiles to refrigerators. Extending network capacities to every aspect of life can save money and time, increase efficiency, and enable greater access to digital experiences. Cybersecurity analysts often refer to this as increasing the attack surface from which hackers can benefit. Implementing the proper security measures is crucial since IoT devices can be vulnerable to cyberattacks and are often built with limited security features. Securing IoT devices involves implementing security measures and best practices to secure them from potential vulnerabilities and threats. Deep learning (DL) models have recently analyzed the network pattern for detecting and responding to possible intrusions, improving cybersecurity with advanced threat detection abilities. Therefore, this study presents a new Hybrid Dung Beetle Optimization-based Dimensionality Reduction with a Deep Learning-based Cybersecurity Solution (HDBODR-DLCS) method on the IoT network. The primary goal of the HDBODR-DLCS technique is to perform dimensionality reduction with a hyperparameter tuning process for enhanced detection results. In the primary stage, the HDBODR-DLCS technique involves Z-score normalization to measure the input dataset. The HDBO model is used for dimensionality reduction, which mainly selects the relevant features and discards the irrelevant features. Besides, intrusions are detected using the attention bidirectional recurrent neural network (ABiRNN) model. Finally, an artificial rabbits optimization (ARO) based hyperparameter tuning process is performed, enhancing the overall classification performance. The empirical analysis of the HDBODR-DLCS method is tested under the benchmark IDS dataset. The simulation outcomes indicated the HDBODR-DLCS method's improved abilities over existing approaches.

Opto/Thermoresponsive Multimode Luminescence in Eu- and Er-Activated CaF2 Phosphor for High-Security Anticounterfeiting.

As the landscape of information storage and security continues to evolve, the deployment of sophisticated anticounterfeiting strategies with robust security features and multimodal luminescent capabilities becomes imperative. In this work, Eu3+ and Er3+ ions are codoped into CaF2 phosphors to achieve multimodel optical output. The self-reduction of Eu3+ within the CaF2 matrix gives rise to the coexistence of Eu3+ and Eu2+ ions, which manifests as a color transition from orange to blue as the excitation wavelength is varied from 300 to 335 nm. Moreover, the distinct temperature-dependent behaviors of Eu3+ and Eu2+ ions underscore the material's visible temperature-sensitive luminescence properties, characterized by remarkable thermal sensitivity (Sa = 0.0156 K-1, Sr = 0.83%K-1). Additionally, the strategic introduction of Er3+ ions adds an extra dimension, enabling the realization of color-tunable upconversion luminescence through the fine-tuning of Er3+ concentration. This synergistic integration culminates in the establishment of an efficient three-path authentication model within the CaF2 host matrix, facilitating a dynamic multicolor response to changes in the excitation wavelength and temperature. By harnessing these diverse luminescent modalities, the study delivers a versatile and potent anticounterfeiting solution, advancing the frontiers of information security.

Characteristics analysis and safety evaluation of vehicles turning over long distances

In order to explore the motion and safety characteristics of the U-turn vehicles at long-range U-turn intersections, based on the measured data of the U-turn vehicles at typical locations, we analyzed the characteristics of the U-turn vehicle's trajectories and traffic parameters with the help of probability theory and statistical knowledge, and established the U-turn trajectory model. We used Traffic Conflict Technology (TCT) and take Post Encroachment Time (PET) as the indicator to study the feature of vehicles security of - turn vehicles. Three conclusions are drawn from this study. First, there is a significant difference in the headway between long-range -turn vehicles and those at intersections without opening: the stability of the headway of long-range -turn vehicles is weak, and the release of vehicles is seriously disturbed by the turning flow; Secondly, when turning around at a long interval u-turn intersection, the starting position of vehicle turning is dispersed and the distribution of U-turn trajectories is quadratic distribution. Third, the setting of long interval turning lanes will increase the interference between traffic flows at intersections, thus increasing the number of conflicts with vehicles in the opposite direction. Cross-conflict accounts for the majority of conflicts in long interval U-turn intersections, and rear-end collision is the main conflict type in U-turn intersections without opening. The above research conclusions are helpful to improve the safety of long interval U-turn intersections.

Challenges and Advances in Analyzing TLS 1.3-Encrypted Traffic: A Comprehensive Survey

The widespread adoption of encrypted communication protocols has significantly enhanced network security and user privacy, simultaneously elevating the importance of encrypted traffic analysis across various domains, including network anomaly detection. The Transport Layer Security (TLS) 1.3 protocol, introduced in 2018, has gained rapid popularity due to its enhanced security features and improved performance. However, TLS 1.3’s security enhancements, such as encrypting more of the handshake process, present unprecedented challenges for encrypted traffic analysis, rendering traditional methods designed for TLS 1.2 and earlier versions ineffective and necessitating the development of novel analytical techniques. This comprehensive survey provides a thorough review of the latest advancements in TLS 1.3 traffic analysis. First, we examine the impact of TLS 1.3’s new features, including Encrypted ClientHello (ECH), 0-RTT session resumption, and Perfect Forward Secrecy (PFS), on existing traffic analysis techniques. We then present a systematic overview of state-of-the-art methods for analyzing TLS 1.3 traffic, encompassing middlebox-based interception, searchable encryption, and machine learning-based approaches. For each method, we provide a critical analysis of its advantages, limitations, and applicable scenarios. Furthermore, we compile and review key datasets utilized in machine learning-based TLS 1.3 traffic analysis research. Finally, we discuss the main challenges and potential future research directions for TLS 1.3 traffic analysis. Given that TLS 1.3 is still in the early stages of widespread deployment, research in this field remains nascent. This survey aims to provide researchers and practitioners with a comprehensive reference, facilitating the development of more effective TLS 1.3 traffic analysis techniques that balance network security requirements with user privacy protection.

Design of Provably Secure and Lightweight Authentication Protocol for Unmanned Aerial Vehicle systems

Drones also called Unmanned Aerial Vehicles (UAVs) have become more prominent in several applications such as package delivery, real-time object detection, tracking, traffic monitoring, security surveillance systems, and many others. As a key member of IoT, the group of Radio Frequency IDentification (RFID) technologies is referred to as Automatic Identification and Data Capturing (AIDC). In particular, RFID technology is becoming a contactless and wireless technique used to automatically identify and track the tagged objects via radio frequency signals. It also has drawn a lot of attention among researchers, scientists, industries, and practitioners due to its broad range of real-world applications in various fields. However, RFID systems face two key concerns related to security and privacy, where an adversary performs eavesdropping, tampering, modification, and even interception of the secret information of the RFID tags, which may cause forgery and privacy problems. In contrast to security and privacy, RFID tags have very limited computational power capability. To deal with these issues, this paper puts forward an RFID-based Lightweight and Provably Secure Authentication Protocol (LPSAP) for Unmanned Aerial Vehicle Systems. The proposed protocol uses secure Physically Unclonable Functions (PUFs), Elliptic-Curve Cryptography (ECC), secure one-way hash, bitwise XOR, and concatenation operations. We use Ouafi and Phan’s formal security model for analyzing security and privacy features such as traceability and mutual authentication. The rigorous informal analysis is carried out which ensures that our proposed protocol achieves various security and privacy features as well as resists various known security attacks. The performance analysis demonstrates that our proposed protocol outperforms other existing protocols. In addition, Scyther and Automated Validation of Internet Security Protocols and Applications (AVISPA) tool simulation results demonstrates that there is no security attack possible within bounds. Therefore, our proposed LPSAP protocol achieves an acceptable high level of security with the least computational, communication, and storage costs on passive RFID tags.

Secure and Efficient k-anonymous Trajectory Privacy Protection Method based on Differential Privacy

The Location-based service scheme have already involved in every aspect of People's daily life and are increasingly used in various industries. Aiming at the problem of the security and efficiency of mobile terminal users’ trajectory privacy protection in location-based service, we propose a k-anonymous trajectory privacy protection scheme based on differential privacy. This scheme adopts differential privacy technology to add Laplace noise to the user's trajectory many times to generate 2k noise trajectory, and then according to the trajectory similarity to determine k-1 noise users whose trajectory are similar to the user trajectory, and sets them and the real user as an anonymous user group, and then uses the anonymous user group to request LBS services. Security analysis shows that the scheme satisfies the security features of anonymity, unforgeability, and anti-counterfeiting attack. The simulation results show that the scheme not only guarantees the similarity between the false trajectory and the real trajectory but also has higher execution efficiency.

Understanding critical service factors in neobanks: crafting strategies through text mining

Purpose This study aims to analyse and understand customer sentiments and perceptions from neobanking mobile applications by using advanced machine learning and text mining techniques. Design/methodology/approach This study explores a substantial large data set of 330,399 user reviews available in the form of unstructured textual data from neobanking mobile applications. This study is aimed to extract meaningful patterns, topics, sentiments and themes from the data. Findings The results show that the success of neobanking mobile applications depends on user experience, security features, personalised services and technological innovation. Research limitations/implications This study is limited to textual resources available in the public domain, and hence may not present the entire range of user experiences. Further studies should incorporate a wider range of data sources and investigate the impact of regional disparities on user preferences. Practical implications This study provides actionable ideas for neobanking service providers, enabling them to improve service quality and mobile application user experience by integrating customer input and the latest trends. These results can offer important inputs to the process of user interaction design, implementation of new features and customer support services. Originality/value This study uses text mining approaches to analyse neobanking mobile applications, which further contribute to the growing literature on digital banking and FinTech. This study offers a unique view of consumer behaviour and preferences in the realm of digital banking, which will add to the literature on the quality of service concerning mobile applications.

Regularity through randomness: Bioinspired quasi-amorphous photonic structures for multilevel information encryption

The biological world has produced a wealth of complex photonic materials offering abundant design inspirations. However, creating these intricate photonic structures intertwining order, disorder, and hierarchical arrangements remains challenging. Achieving this necessitates nano-fabrication technologies capable of integrating intended macroscopic properties while accommodating microscopic variability or randomness, akin to the operational principles observed in biological organisms. Here, we present quasi-amorphous photonic structure (QAPS) patterns with regulated sophisticated visual effects through hierarchically distributions of photonic elements with engineered randomness. Enabled by an infiltration-assisted (IFAST) inkjet printing method, the visual appearances of QAPS patterns are precisely controlled by collective harnessing of nanoscale resonant scattering of colloids, mesoscale interferences, and macroscale light transporting. The QAPS patterns exhibit isotropic diffuse colors, unprecedented iridescence and enable multichannel encrypted information that can be selectively identified using specific filters at particular specular illumination angles. Additionally, the intricate infiltration fields confer high adjustability in colloidal assembly, offering sophisticated packing geometries and color distributions at the microscale, which can serve as physical unclonable security features. The exceptional structural complexity and optical versatility of QAPSs enable the integration of multilevel security features within a single system, providing a promising roadmap to achieve larger information capacity, multichannel cryptography, and enhanced encryption levels.

A network security protection scheme for tax system based on elliptic curve cryptography

With the rapid development of modern information technology and network technology, the construction of tax informatization plays an important role in improving the level of tax management and work efficiency. However, in the centralized data processing mode, the establishment of large data center and the efficient, stable, and secure connection of server bandwidth have become key challenges. Moreover, the openness and interconnectivity of the tax system network pose various network security threats, seriously threatening the integrity and security of data. For the above issues, this article proposes a tax system network security protection scheme based on elliptic curve cryptography. This scheme combines hash function and elliptic curve cryptography to achieve user anonymity and secure generation of session keys, effectively ensuring the secure transmission of confidential information. The security and effectiveness of the scheme are verified through informal and formal security analysis based on security proof, BAN logic and AVISPA tool. And a comprehensive evaluation of the scheme is conducted, and the results show that the scheme significantly reduced the costs while providing security features.