Search results

Automatic dependent surveillance-broadcast (ADS-B) is the foundational technology of the next generation air transportation system defined by Federal Aviation Authority and is one of the most precise ways for tracking aircraft position. ADS-B is intended to provide greater situational awareness to the pilots by displaying the traffic information like aircraft ID, altitude, speed and other critical parameters on the Cockpit Display of Traffic Information displays in the cockpit. Unfortunately, due to the initial proposed nature of ADS-B protocol, it is neither encrypted nor has any other innate security mechanisms, which makes it an easy target for malicious attacks. The system is vulnerable to various active and passive attacks like message ingestion, message deletion, eavesdropping, jamming, etc., which has become an area of concern for the aviation industry. The purpose of this study is to propose a method based on modified advanced encryption standard (AES) algorithm to secure the ADS=B messages and increase the integrity of ADS-B data transmissions.

Though there are various cryptographic and non-cryptographic methods proposed to secure ADS-B data transmissions, it is evident that most of these systems have limitations in terms of cost, implementation or feasibility. The new proposed method implements AES encryption techniques on the ADS-B data on the sender side and correlated decryption mechanism at the receiver end. The system is designed based on the flight schedule data available from any flight planning systems and implementing the AES algorithm on the ADS-B data from each aircraft in the flight schedule.

The suitable hardware was developed using Raspberry pi, ESP32 and Ra-02. Several runs were done to verify the original message, transmitted data and received data. During transmission, encryption algorithm was being developed, which has got very high secured transmission, and during the reception, the data was secured. Field test was conducted to validate the transmission and quality. Several trials were done to validate the transmission process. The authors have successfully shown that the ADS-B data can be encrypted using AES algorithm. The authors are successful in transmitting and receiving the ADS-B data packet using the discussed hardware and software methodology. One major advantage of using the proposed solution is that the information received is encrypted, and the receiver ADS-B system can decrypt the messages on the receiving end. This clearly proves that when the data is received by an unknown receiver, the messages cannot be decrypted, as the receiver is not capable of decrypting the AES-authenticated messages transmitted by the authenticated source. Also, AES encryption is highly unlikely to be decrypted if the encryption key and the associated decryption key are not known.

Implementation of the developed solution in actual onboard avionics systems is not within the scope of this research. Hence, assessing in the real-time distances is not covered.

The authors propose to extend this as a software solution to the onboard avionics systems by considering the required architectural changes. This solution can also bring in positive results for unmanned air vehicles in addition to the commercial aircrafts. Enhancement of security to the key operational and navigation data elements is going to be invaluable for future air traffic management and saving lives of people.

The proposed solution has been practically implemented by developing the hardware and software as part of this research. This has been clearly brought out in the paper. The implementation has been tested using the actual ADS-B data/messages received from using the ADS-B receiver. The solution works perfectly, and this brings immense value to the aircraft-to-aircraft and aircraft-to-ground communications, specifically while using ADS-B data for communicating the position information. With the proposed architecture and minor software updates to the onboard avionics, this solution can enhance safety of flights.

The main aim of this study is to review different aspects of Industry 5.0 (I5.0) along with Kaizen measures to foster this novel aspect of industrial sustainability. The study makes a comprehensive study to explore the implementation status of I5.0 in industries, key technologies, adoption level in different nations and barriers to I5.0 adoption together with mitigation actions.

To do a systematic study of the literature, the authors have used preferred reporting items for systematic reviews and meta-analysis (PRISMA) methodology to extract articles related to the field of the study.

It has been found that academic literature on the I5.0 is continuously growing as the wheel of time is running. Most of the studies on I5.0 are conceptual-based, and manufacturing and medical industries are the flag bearer in the adoption of this novel aspect. Further, due to I5.0's infancy, many organizations face difficulty to adopt the same due to financial burden, resistive nature, a well-designed standard for cyber-physical systems (CPS) and an effective mechanism for human–robot collaboration. Further studies also provide avenues for future research in terms of the identification of collaborative mechanisms between machines and wells, the establishment of different standards for comparison and the development of I5.0-enabled models for different industrial domains.

The study is the first of its kind that reviews different facets of I5.0in conjunction with Kaizen's measures and application areas and provides avenues for future research to improve an organization's environmental and social sustainability.

This study aims to explore the potential application of blockchain technology in Lean Six Sigma (LSS) project through a proposed blockchain-LSS (BLSS) model. The proposed model can tackle real-time problems in information sharing, transparency and traceability in every stage of the LSS project.

The scoping review approach is used to develop the integrated model of the BLSS approach for operational excellence. The proposed model is validated through expert’s input, which is collected by a questionnaire survey method.

The prime function of the proposed BLSS model is the information sharing among the project team and real-time monitoring, transparency, traceability and immutability in the Define-Measure-Analyze-Improve-Control phase. The proposed model also consists the information about the role of blockchain features at each phase of the LSS project. The project team and industry employees can trace the success of the project at every moment, resulting in trust buildup and the elimination of fake data. Moreover, there would be no disputes among various sections/shops of the plant and employees to share the real information.

This paper provides guidelines to practitioners and managers for integrating the LSS approach and blockchain. The blockchain helps managers and practitioners in better data traceability and transparency, monitoring of data as well as more sustainable LSS project management.

To the best of the authors’ knowledge, this is the first research attempt that developed an integrated model of blockchain and LSS approach to maintaining the immutable records of assets in projects and targeted Industry 4.0.

The potential of vehicle ad hoc networks (VANETs) to improve driver and passenger safety and security has made them a hot topic in the field of intelligent transportation systems (ITSs). VANETs have different characteristics and system architectures from mobile ad hoc networks (MANETs), with a primary focus on vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication. But protecting VANETs from malicious assaults is crucial because they can undermine network security and safety.

The black hole attack is a well-known danger to VANETs. It occurs when a hostile node introduces phony routing tables into the network, potentially damaging it and interfering with communication. A safe ad hoc on-demand distance vector (AODV) routing protocol has been created in response to this issue. By adding cryptographic features for source and target node verification to the route request (RREQ) and route reply (RREP) packets, this protocol improves upon the original AODV routing system.

Through the use of cryptographic-based encryption and decryption techniques, the suggested method fortifies the VANET connection. In addition, other network metrics are taken into account to assess the effectiveness of the secure AODV routing protocol under black hole attacks, including packet loss, end-to-end latency, packet delivery ratio (PDR) and routing request overhead. Results from simulations using an NS-2.33 simulator show how well the suggested fix works to enhance system performance and lessen the effects of black hole assaults on VANETs.

All things considered, the safe AODV routing protocol provides a strong method for improving security and dependability in VANET systems, protecting against malevolent attacks and guaranteeing smooth communication between cars and infrastructure.

This study addresses the ever-increasing cyber risks confronting the global banking sector, particularly in India, amid rapid technological advancements. The purpose of this study is to de velop an innovative cyber fraud (CF) response system that effectively controls cyber threats, prioritizes fraud, detects early warning signs (EWS) and suggests mitigation measures.

The methodology involves a detailed literature review on fraud identification, assessment methods, prevention techniques and a theoretical model for fraud prevention. Machine learning-based data analysis, using self-organizing maps, is used to assess the severity of CF dynamically and in real-time.

Findings reveal the multifaceted nature of CF, emphasizing the need for tailored control measures and a shift from reactive to proactive mitigation. The study introduces a paradigm shift by viewing each CF as a unique “fraud event,” incorporating EWS as a proactive intervention. This innovative approach distinguishes the study, allowing for the efficient prioritization of CFs.

The practical implications of such a study lie in its potential to enhance the banking sector’s resilience to cyber threats, safeguarding stability, reputation and overall risk management.

The originality stems from proposing a comprehensive framework that combines machine learning, EWS and a proactive mitigation model, addressing critical gaps in existing cyber security systems.

The study investigates the influence of perceived security (PS) on behavioral intention (BI) via the trust attitude process and explores the moderating effects of gender. PS in mobile wallets enhances user trust (TR), attitude (ATT) and intention (INT). Using a multiple and serial mediation model, both TR and ATT were found to mediate the relationship between PS and BI.

Drawing on the stimulus-organism-response (S-O-R) theory, the proposed conceptual model comprises PS, TR, ATT and BI. An online survey was conducted with a cross-sectional sample of 744 mobile wallet users in India. Partial least squares structural equation modeling (PLS-SEM) was used to analyze the hypothesized relationships and test the mediation effects.

Results show that the stimulus, PS, has a positive and significant influence on TR and ATT, which eventually has a positive influence on BI. The research model explains 64.4 percent of the variance in BI. Further, both TR and ATT independently and parallelly mediate the relationship PS and BI. Lastly, gender is found to moderate the relationship between TR and BI and ATT and BI.

The research showed the importance of PS, TR and ATT towards mobile wallet adoption INTs. Further, the findings support the idea that developing TR and ATT is essential for shaping INTs. This suggests that mobile wallet service providers should invest in methods that not just enhance user TR but also reinforce a positive ATT towards the platform. To demonstrate TR, mobile wallet providers must ensure the confidentiality and privacy of user data, keep customer interests in mind and fulfill commitments. Lastly, for strengthening customer TR, excellent customer support is extremely important.

While prior researchers have majorly used technology acceptance model (TAM) and unified theory of acceptance and use of technology (UTAUT) models to explain adoption INTs, this study examines the relationship between PS, TR, ATT and BI through the lens of the SOR framework.

The purpose of this study is to understand user perceptions and misconceptions regarding security tools. Security and privacy-preserving tools (for brevity, the authors term them as “security tools” in this paper, unless otherwise specified) are designed to protect the security and privacy of people in the digital environment. However, inappropriate use of these tools can lead to unexpected consequences that are preventable. Hence, it is significant to examine why users do not understand the security tools.

The authors conducted a qualitative study with 40 participants in the USA to investigate the prevalent misconceptions of people regarding security tools, their perceptions of data access and the corresponding impact on their usage behavior and data protection strategies.

While security vulnerabilities are often rooted in people’s internet usage behavior, this study examined user’s mental models of the internet and unpacked how the misconceptions about security tools relate to those mental models.

Based on the findings, this study offers recommendations highlighting the design aspects of security tools that need careful attention from researchers and industry practitioners, to alleviate users’ misconceptions and provide them with accurate conceptual models toward the desired use of security tools.

The purpose of this study is to analyse cyberfraud in the South African banking industry using a multiple regression approach and develop a predictive model for the estimation and prediction of financial losses due to cyberfraud.

To mitigate the occurrence of cyberfraud, this study uses the multiple regression approach to correlate the relationship between financial loss and cyberfraud activities. The cyberfraud activities in South Africa are classified into three, namely, digital banking application, online and mobile banking fraud. Secondary data that captures the rate of cyberfraud occurrences within these three major categories with their resulting financial losses were used for the multiple regression analysis that was carried out in the Statistical Package for Social Science (SPSS, 2022 environment).

The results obtained indicate that the South African financial institutions still incur significant financial losses due to cyberfraud perpetration. The two main independent variables used to estimate the magnitude of financial loss in the South Africa’s banking industry are online (internet) banking fraud (X2) and mobile banking fraud (X3). Furthermore, a multiple regression model equation was developed for the prediction of financial loss as a function of the two independent variables (X2 and X3).

This study adds to the literature on cyberfraud mitigation. The findings may promote the combat against cyberfraud in the South Africa’s financial institutions. It may also assist South Africa’s financial institutions to predict the financial loss that financial institutions can incur over time. It is recommended that South Africa’s financial institutions pay attention to these two key variables and mitigate any associated risks as they are crucial in determining their profitability.

Existing literature indicated significant financial losses to cyberfraud perpetration without establishing any relationship between the magnitude of losses incurred and the prevalent forms of cyberfraud. Thus, the novelty of this study lies in the analysis of cyberfraud in the South African banking industry using a multiple regression approach to link financial losses to the perpetration of the prevalent forms of cyberfraud. It also develops a predictive model for the estimation and projection of financial losses.

The purpose of this paper is to elaborate the significance of safeguards in digital ecosystems and their role in generating trust among participants. This paper argues that the right mix and number of safeguards are crucial for an ecosystem’s growth and success. It offers ecosystem orchestrators concrete guidelines for how to implement and monitor safeguards.

This research is based on both consulting experience and publicly available information on several digital ecosystems.

This research conceptualizes safeguards as precautionary mechanisms that mandate or promote desirable behavior in an effort to engender trust among ecosystem participants. Safeguards can take various forms, including passwords, escrow, user privacy controls, ratings and reviews and policies and contracts. Striking the right balance of safeguards – neither too few nor too many – is crucial for ecosystem orchestrators. This paper identifies the factors that determine the optimal mix of safeguards, including the power asymmetry between sellers and buyers, the sophistication of participants, the nature of transactions, the cost of negative outcomes and the cost-benefit tradeoff.

To the best of the authors’ knowledge, this study is one of the first to illuminate the relationship between safeguards and trust in the context of digital ecosystem. It is also one of the few attempts to provide managerial guidance for ecosystem designers trying to structure their platform for trust.

This study aims to identify and rank the key success factors linked with digitalization in the Indian construction sector. Because the construction firms in India are in the early stages of implementing digitalization in their operations, it provides a framework from which they may focus on the effectiveness of digitalization.

This research study examines 12 success factors related to digitalization in construction, which are derived from various sectors. Furthermore, experts from the construction industry and academia have validated these factors with respect to the Indian construction sector. The multi-criteria decision-making techniques are further used to examine the interrelationship, ranking and weightage of digitalization success. Finally, the success factors are validated through a questionnaire-based empirical study followed by ranking using a t-test. The results from both approaches (company-specific and generalized) are compared and discussed.

This research identifies that selecting appropriate digital methods and techniques is a critical success factor as far as digitalization in the Indian construction scenario is concerned. Besides that, continuous monitoring and control in digital implementation significantly impact other factors.

While similar results are obtained from approaches adopted in the study, a few success factors appear to differ in terms of their ranking position. Further studies can explore the finer details that can explain the behavior pattern. This study can also be extended by assessing the structural relationship among the identified factors that can throw more light on the dynamics of the continuation of digitalization in construction which can further help in formulating policies or digitalization rollout.

The outcome of this study sheds light on construction business knowledge by stressing key success elements connected to digitalization in construction processes in the Indian construction sector. Moreover, this study shows that the success of digitalization in construction is similar to that of transformation in the information technology industry, where adopting suitable digital methods and techniques plays a vital role in the transformation process.

Despite the multiple benefits of construction digitalization, limited research focuses on digitalization success factors, making this study unique. Furthermore, this study demonstrates that integrating Fuzzy decision-making trial and evaluation laboratory and maximum mean de-entropy approaches may be used to successfully prioritize success factors in the nascent stage of construction digitalization.