Security Features Research Articles

Regulation mechanisms of smart tourism development in Kazakhstan

The process of digitalization within the realm of tourism is not merely a trend but rather a significant catalyst that is rapidly propelling the comprehensive transformation of the tourism industry into a new era of technological advancement. This intricate process fundamentally involves the seamless integration and application of cutting-edge digital technologies across various tourism-related activities and services. The advent of innovative solutions that harness the immense capabilities of artificial intelligence, the analytical power of big data, the security features of blockchain, and the interconnectedness provided by the Internet of Things primarily serves to enhance the overall quality of services offered, optimize pricing strategies to align with market demands, and improve risk management protocols within the industry. This paper methods uses 100 Scopus indexed papers about Smart Tourism Development in Kazakhstan. It is imperative to underscore the fact that the ongoing digitalization process, while offering numerous advantages, simultaneously imposes rigorous new requirements concerning the qualifications and competencies of staff members, as well as the paramount importance of data security measures and the protection of consumer rights in the digital environment. The effective management of this digital transformation necessitates a holistic and integrated approach that encompasses not only the development of robust infrastructure but also the enhancement of digital literacy among employees and the establishment of a dynamic and innovative ecosystem that encourages creativity and adaptability.

Full-process supported Simulation Platform Framework based on cloud computing and HPC integration

Simulation technology is widely used in many fields, it usually involves three processes, (i) pre-process, (ii) analysis solver, and (iii) post-process. Simulation calculations require a large amount of computing resources, and users usually need to use cloud and High-Performance Computing (HPC) systems to complete works. Simulation works are increasingly depending on the capacity of HPC or cloud, for cost reasons, people are more willing to use the services than self-built an HPC or Cloud computing cluster. However, that leads to the isolation of calculations and pre- and post-processing work, adding additional time for data transfer. Moreover, simulation engineers also want to use cloud servers in pre-processing and post-processing, since compared with local workstations, cloud servers have significant advantages in saving hardware investment, remote office collaboration, and data integration management. Therefore, we provide a platform framework based on cloud computing and HPC integration that supports the full process of simulation. Then, we implemented it in Tianhe-1A and Tianhe exascale supercomputers and THCloud environments. Through a city area-level explosion simulation experiment, it was verified that the framework can fully support the whole process of simulation, and effectively reduce the time of simulation work, improving the simulation engineer’s work efficiency. The study shows that the platform provides a feasible solution for full-process simulation. Compared with other platforms, it has the characteristics of full-process, high performance and high security.

The Integration of Artificial Intelligence in Secure Access Service Edge: Enhancing Network Security and Performance

Integrating Artificial Intelligence (AI) with Secure Access Service Edge (SASE) architecture represents a significant advancement in enterprise network security and management. This article examines the transformative impact of AI technologies on SASE implementations, focusing on enhanced threat detection capabilities, dynamic network optimization, and automated compliance management. The article comprehensively analyzes AI-driven security features, including real-time threat detection, zero-trust implementation, and privacy-preserving security measures. Through extensive evaluation of deployment scenarios and performance metrics, our research demonstrates significant improvements in security effectiveness and operational efficiency, including a 90% reduction in threat detection time, a 45% decrease in network latency, and a 65% reduction in manual configuration tasks. The article highlights the system's capability to maintain robust security while preserving data privacy through advanced encrypted traffic analysis techniques. The article addresses current integration challenges and provides insights into successful implementation strategies. This article contributes to the growing body of knowledge on AI-enhanced network security architectures and provides valuable insights for organizations seeking to modernize their security infrastructure while maintaining operational efficiency and compliance with evolving regulatory requirements.

Comparison of Middlewares in Edge-to-Edge and Edge-to-Cloud Communication for Distributed ROS 2 Systems

AbstractThe increased data transmission and number of devices involved in communications among distributed systems make it challenging yet significantly necessary to have an efficient and reliable networking middleware. In robotics and autonomous systems, the wide application of ROS 2 brings the possibility of utilizing various networking middlewares together with DDS in ROS 2 for better communication among edge devices or between edge devices and the cloud. However, there is a lack of comprehensive communication performance comparison of integrating these networking middlewares with ROS 2. In this study, we provide a quantitative analysis for the communication performance of utilized networking middlewares including MQTT and Zenoh alongside DDS in ROS 2 among a multiple host system. For a complete and reliable comparison, we calculate the latency and throughput of these middlewares by sending distinct amounts and types of data through different network setups including Ethernet, Wi-Fi, and 4G. To further extend the evaluation to real-world application scenarios, we assess the drift error (the position changes) over time caused by these networking middlewares with the robot moving in an identical square-shaped path. Our results show that CycloneDDS performs better under Ethernet while Zenoh performs better under Wi-Fi and 4G. In the actual robot test, the robot moving trajectory drift error over time (96 s) via Zenoh is the smallest. It is worth noting we have a discussion of the CPU utilization of these networking middlewares and the perfosrmance impact caused by enabling the security feature in ROS 2 at the end of the paper.

Large-scale scattering-augmented optical encryption.

Data proliferation in the digital age necessitates robust encryption techniques to protect information privacy. Optical encryption leverages the multiple degrees of freedom inherent in light waves to encode information with parallel processing and enhanced security features. However, implementations of large-scale, high-security optical encryption have largely remained theoretical or limited to digital simulations due to hardware constraints, signal-to-noise ratio challenges, and precision fabrication of encoding elements. Here, we present an optical encryption platform utilizing scattering multiplexing ptychography, simultaneously enhancing security and throughput. Unlike optical encoders which rely on computer-generated randomness, our approach leverages the inherent complexity of light scattering as a natural unclonable function. This enables multi-dimensional encoding with superior randomness. Furthermore, the ptychographic configuration expands encryption throughput beyond hardware limitations through spatial multiplexing of different scatterer regions. We propose a hybrid decryption algorithm integrating model- and data-driven strategies, ensuring robust decryption against various sources of measurement noise and communication interference. We achieved optical encryption at a scale of ten-megapixel pixels with 1.23 µm resolution. Communication experiments validate the resilience of our decryption algorithm, yielding high-fidelity results even under extreme transmission conditions characterized by a 20% bit error rate. Our encryption platform offers a holistic solution for large-scale, high-security, and cost-effective cryptography.

Development of a Smart Lock System using QR Code Technology

A smart lock system refers to a modern security solution that enables users to remotely control access to their homes or businesses using a smart device such as smartphone, tablet, or computer. This paper presents the development of a smart lock system using Quick Response (QR) code technology to address the problem of insecurity, inconvenience, and inflexibility in access control. The proposed system eliminates the need for physical keys or complex authentication and verification methods. The system integrates an ESP8266 microcontroller, barcode scanner, 16x2 liquid-crystal display (LCD), solenoid lock, relay, and a 12V power supply. The system allows authorised users to generate unique QR codes representing their access credentials through a user-friendly interface. These QR codes are scanned by the system, which processes the codes, verifies access permissions via a central server and provides real-time feedback through the LCD. Upon successful verification, the system triggers a relay to control the solenoid lock, to grant or deny access. The implementation and testing of the smart lock system demonstrated successful operation. The performance indices include authentication speed, system reliability, accuracy and response time, which were evaluated and found to be satisfactory. The obtained results showed that the proposed system outperformed traditional methods such as keys, and fingerprint authentication, with an access speed of 2.00 seconds, which is significantly faster than the alternatives. Comparative analysis with existing access control techniques demonstrated the developed system's enhanced security features and user-friendly operation, making it applicable for residential, commercial, and industrial use. Additionally, the system's scalability and adaptability allow it to be customised for various environments, offering a versatile solution to diverse security challenges. This work contributes to the field of security technology by providing an efficient and scalable smart lock system with novel algorithms, which enhances the convenience, robustness of access control and seamless user experience.

Adoption and User Behaviour Towards Digital Payments by Millennial

The rapid adoption of digital payment systems has transformed the financial landscape, particularly among millennials, who are at the forefront of this technological shift. This study explores the adoption and user behaviour of digital payment methods among millennials in India. The research aims to identify the key factors influencing the decision to use digital payments, including convenience, security, trust, and government initiatives. Additionally, it examines how socio-cultural influences, mobile payment applications, and peer networks impact the payment choices of this demographic. Through a survey of 250 millennials, the study reveals that ease of use, trust in security features, and promotional incentives are the primary drivers of digital payment adoption. It also identifies challenges such as concerns over data privacy and digital literacy. The findings suggest that while millennials are increasingly adopting digital payment systems, their behaviour is shaped by a complex interplay of technological, economic, and social factors. The study provides insights into strategies for improving the digital payment ecosystem and encourages further research into the evolving behaviour of young consumers.

Online Voting System Using Blockchain: A Secure and Transparent Approach

Blockchain technology has emerged as a viable solution for secure and transparent digital voting systems. Traditional voting systems, particularly online voting mechanisms, are often vulnerable to security risks such as hacking, tampering, and vote manipulation. Furthermore, maintaining voter anonymity and ensuring data integrity are significant challenges. Blockchain, with its distributed and immutable ledger, offers potential solutions by providing a secure and decentralized approach to recording votes. This paper explores the architecture, implementation, and advantages of a blockchain-based online voting system that leverages the security features of blockchain technology to improve the voting process. By utilizing cryptographic principles and decentralized data storage, the system enhances transparency, reduces fraud risks, and ensures that votes remain immutable. The proposed system includes mechanisms for voter registration, vote casting, and result verification, all of which are secured by smart contracts. Experimental results demonstrate that blockchain can maintain voter anonymity, resist tampering, and provide an auditable voting trail. Additionally, the study discusses challenges in scalability, latency, and regulatory compliance, offering insights into potential improvements and future work. Overall, the research indicates that blockchain based voting has the potential to transform electoral processes, providing a trusted digital voting alternative that aligns with democratic principles. Key Words: Blockchain Technology, Digital Voting, Online Voting Systems, Data Integrity, Transparency, Security, Cryptography, Smart Contracts, Voter Anonymity, Tamper-Resistance, Immutable Ledger, Scalability, Decentralization.

ML-based Anomaly Detection for CAN Bus Network in Agriculture Machinery

The adoption of advanced automation and next-generation technologies like the Internet of Things (IoT) and modern communication networks has revolutionized the food and agriculture sector, boosting the efficiency and precision of farm machinery. However, this increased inter-connectivity has also exposed significant vulnerabilities, particularly in Controller Area Network (CAN) protocols, widely used in advanced agricultural machinery and equipment. Due to its lack of inherent security features, CAN is susceptible to various cyber-attacks, potentially leading to severe consequences if these attacks remain undetected and unmitigated. This paper introduces a supervised machine learning (ML)-based anomaly detection system (CAN-ADS) designed to detect various cyber-attacks on CAN-based agricultural machinery. The system leverages network traffic augmentation and data balancing techniques to train ML algorithms on CAN-specific datasets. Experimental results show that CAN-ADS achieves high accuracy (approx 98%) and true-positive rates with low false-negative rates (approx 1%).

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.

Enhancing Counterfeit Banknote Analysis: Case Studies Using TOF-SIMS

Counterfeiting banknotes poses a significant threat to economies worldwide, particularly in developing countries where cash transactions remain predominant. Despite advancements in security features, counterfeiters continue to adapt, necessitating more sophisticated analysis methods. Time of flight Secondary Ion Mass Spectrometry (TOF-SIMS) offers a powerful approach to surface chemical imaging and depth profiling of counterfeit currencies. Real cases of five different counterfeit Lebanese banknotes are studied, using TOF-SIMS to address specific questions regarding the composition and placement of replicated security features, gaining insights into counterfeit banknote production and the raw materials used. The findings provide essential information to decision-makers at the national bank, supporting the design of future currencies through the selection of security features best suited to the local market, thereby enhancing protection against financial fraud..

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.