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The rapid advancements in technology have paved the way for innovative solutions in the healthcare domain, aiming to improve scalability and security while enhancing patient care. This abstract introduces a cutting-edge approach, leveraging blockchain technology and hybrid deep learning techniques to revolutionize healthcare systems. Blockchain technology provides a decentralized and transparent framework, enabling secure data storage, sharing, and access control. By integrating blockchain into healthcare systems, data integrity, privacy, and interoperability can be ensured while eliminating the reliance on centralized authorities. In conjunction with blockchain, hybrid deep learning techniques offer powerful capabilities for data analysis and decision making in healthcare. Combining the strengths of deep learning algorithms with traditional machine learning approaches, hybrid deep learning enables accurate and efficient processing of complex healthcare data, including medical records, images, and sensor data. This research proposes a permissions-based blockchain framework for scalable and secure healthcare systems, integrating hybrid deep learning models. The framework ensures that only authorized entities can access and modify sensitive health information, preserving patient privacy while facilitating seamless data sharing and collaboration among healthcare providers. Additionally, the hybrid deep learning models enable real-time analysis of large-scale healthcare data, facilitating timely diagnosis, treatment recommendations, and disease prediction. The integration of blockchain and hybrid deep learning presents numerous benefits, including enhanced scalability, improved security, interoperability, and informed decision making in healthcare systems. However, challenges such as computational complexity, regulatory compliance, and ethical considerations need to be addressed for successful implementation. By harnessing the potential of blockchain and hybrid deep learning, healthcare systems can overcome traditional limitations, promoting efficient and secure data management, personalized patient care, and advancements in medical research. The proposed framework lays the foundation for a future healthcare ecosystem that prioritizes scalability, security, and improved patient outcomes.

The first Android-ready “G1” phone debuted in late October 2008. Since then, the growth of Android malware has been explosive, analogous to the rise in the popularity of Android. The major positive aspect of Android is its open-source nature, which empowers app developers to expand their work. However, authors with malicious intentions pose grave threats to users. In the presence of such threats, Android malware detection is the need of an hour. Consequently, researchers have proposed various techniques involving static, dynamic, and hybrid analysis to address such threats to numerous features in the last decade. However, the feature that most researchers have extensively used to perform malware analysis and detection in Android security is Android permission. Hence, to provide a clarified overview of the latest and past work done in Android malware analysis and detection, we perform a comprehensive literature review using permissions as a central feature or in combination with other components by collecting and analyzing 205 studies from 2009 to 2023. We extracted information such as the choice opted by researchers between analysis or detection, techniques used to select or rank the permissions feature set, features used along with permissions, detection models employed, malware datasets used by researchers, and limitations and challenges in the field of Android malware detection to propose some future research directions. In addition, on the basis of the information extracted, we answer the six research questions designed considering the above factors.

Mutual exclusion problem in the distributed system is a very basic and highly researched area in this domain. Various distributed mutual exclusion (DME) protocols exist till date to fulfill such cases on static as well as on dynamic distributed network topologies. Now a days, due to the high demand and applicability of flying ad hoc network (FANET) which is a subclass of ad hoc network, is in trend and has a huge potential for research to its various unexplored areas. In fact while comparing FANET with distributed system, FANET has been considered as a special variant of a distributed system with high dynamic network topology. Throughout our literature study, we found no permission-based (a subclass to DME solutions) DME algorithm proposed in FANET. Hence through this paper, we present a first permission-based DME algorithm in FANET as mutual exclusion algorithm for flying network-permission based (MEAFN-PB) with efficient results in terms of its performance measures and fault-tolerant capability to node failures. We then present a case study that explores various aspects of our proposed algorithm that helps to visualize its operations. We have also analyzed the atmospheric reaction and impact of gravitational force on UAVs during the fly.

In this article, the authors propose a new innovative method based on blockchain technology providing an analysis of Android applications in a decentralized, flexible, and reliable way. The proposed approach improves the typical operation of the blockchain technology that considers invalid (or “fraudulent”) any outcome different from other results found by the majority of network nodes. However, ignoring any result different from the majority without starting additional verification can cause losses in terms of data, time, computing power, or even system reliability and the integrity of its data. The purpose of the presented approach is to confirm or deny the legitimacy of any outcome different from the majority. This new concept will facilitate the detection of polymorphic programs by allowing nodes to adopt specific environments at any time to reduce the rejection of results deemed, wrongly, to be fraudulent. A proof of concept has been designed and implemented showing the feasibility of the proposed approach with a real case study.

Purpose - The aim of this study was to develop a theoretical model of email advertising effectiveness and to investigate differences between permission-based email and spamming. By examining different types of email (i.e. permission-based email and spamming), the present study empirically tested the theoretical linkage between email advertising values, perceived instrusiveness, and the attitudinal-behavioural dispositions towards email advertising.Design methodology approach - A survey was conducted using 221 respondents from Taiwan. Two scenarios were designed for the present study. The questionnaires were equally divided into two sets, with the first half containing a scenario depicting permission-based email, and the other half containing a scenario describing a spamming email. Each respondent only received one set of the survey.Findings - Results from a survey of 221 Internet users in Taiwan indicate that values and attitudes toward, and the perceived intrusiveness of, email advertising significantly affect consumers' behavioral dispositions toward email advertising. The results suggest that permission-based email is more effective as compared to spam email advertising. For solicited email, consumers perceived less intrusiveness if the email advertisement offered them financial incentives.Research limitations implications - The authors acknowledge four limitations in this study. These limitations however provide further direction for future studies in the discipline. The discussion of these limitations is provided.Practical implications - Importantly, this study yields significant theoretical and managerial implications. Concerned with the context of email advertising, the authors' work provides theoretical support for both constructs of advertising values and perceived intrusiveness as important. Concerned with the advertisers, this study renders important implications for better planning of marketing mix strategy using email.Originality value - This study provides new theoretical insights into factors influencing consumers' acceptance of email advertising by incorporating perceived intrusiveness as a mediator in the relationship between advertising values and attitudinal-behavioral dispositions. By empirically comparing the different types of email advertisements of permission-based email and spamming, the present study also offers better understanding and extending of the current literature on email advertising research.

PurposeThis study aims to assess consumers’ beliefs in three Middle Eastern Arab countries regarding attitudinal and behavioural responses towards permission-based direct email marketing (hereafter DEM) and the moderating role of gender in the hypothesised path model.Design/methodology/approachStructural equation modelling was used to test the hypothesised path model by using data collected from 829 respondents.FindingsThe findings show that attitude was found to fully mediate the relationship between beliefs and behavioural responses towards permission-based DEM. Gender moderates the relationship between beliefs and attitudes and responses to permission-based DEM. Notably, female respondents were found to react more actively when exposed to permission-based DEM.Research limitations/implicationsFurther qualitative research is needed to learn more about how and why individuals develop behavioural intentions in certain ways towards opt-in DEM. In addition, neuropsychology approaches such as eye-tracking are endorsed for future research to gain more insights and conquer biases associated with self-reporting procedures in countries where such technologies are deemed as legal and ethical to be used with human subjects.Practical implicationsAdvertisers promoting products and services in the Middle Eastern Arab context should take further steps to enhance the quality of information (including cultural sensitiveness) and the perceived entertainment value that could be delivered to consumers through permission-based DEM, especially for female internet users. Additionally, this study highly recommends the double opt-in approach to permission-based DEM.Originality/valueTo the best of the authors’ knowledge, this is the first attempt to address the gender role as a moderator of the path depicting the effectiveness of permission-based DEM approach in the Middle East (Arab counties) from beliefs to behavioural responses via attitudes.