Advances in wireless technology have resulted in the development of smart healthcare systems (SHS). In SHS, sensors, wearables, and devices monitor a patient’s vital parameters. These parameters are transmitted to designated emergency services or trusted healthcare professionals for evaluation. The security and privacy of vitals during collection and transmission is a major concern. Therefore, it is essential to discuss security techniques, concerns, and requirements in SHS. We review the methodologies, objectives, platforms, and techniques used in SHS. First, we present a novel classification scheme for SHS that ranks their methodologies within their applicable domains. Second, we create a classification scheme for literature concerning SHS. Third, we examine the most important security attacks in SHS and the countermeasures proposed in current literature. Finally, we identify the open research challenges in security and privacy of SHS and provide directions for future research.

Social gaming networks have become a new phenomenon, especially for young people, who may become addicted to some extent. However, this phenomenon also increases their susceptibility to hacking, cyber-attack, and other types of security breaches. Various studies have found that current technology is inadequate in terms of online security. Thus, researchers have started to pay attention to the human aspect of security, which is based on interactions with strangers who may trick other gamers into revealing personal or financial information, that is, social engineering. There is little in the social gaming network literature to help players, researchers, and organizations to address the human aspect of online security, and thus there is a need to investigate the factors affecting this aspect of security. The current study aims to identify the factors influencing social engineering victimization in social gaming networks. The model developed in this study is based on the health belief model and cooperation and competition theory. The results show that the perceived severity of the threat, perceived barriers, perceived benefits, self-efficacy, competition, and cooperation are significant factors in the prediction of social engineering victimization.

Past research suggests that the human ability to detect social engineering deception is very limited, and it is even more limited in the virtual environment of social networking sites (SNS) such as Facebook. At the organizational level, research suggests that social engineers could succeed even among those organizations that identify themselves as being aware of social engineering techniques. This may be partly due to the complexity of human behaviors in failing to recognize social engineering tricks in SNSs. Due to the vital role that persuasion and perception play on users’ decision to accept or reject social engineering tricks, this paper aims to investigate the impact of message characteristics on users’ susceptibility to social engineering victimization on Facebook. In doing so, we investigate the role of the central route of persuasion, peripheral route of persuasion, and perceived risk on susceptibility to social engineering on Facebook. In addition, we investigate the mediation effects between the explored factors, and whether there is any relationship between the effectiveness of them and users’ demographics.

Social networking sites (SNSs), with their large numbers of users and large information base, seem to be perfect breeding grounds for exploiting the vulnerabilities of people, the weakest link in security. Deceiving, persuading, or influencing people to provide information or to perform an action that will benefit the attacker is known as “social engineering.” While technology-based security has been addressed by research and may be well understood, social engineering is more challenging to understand and manage, especially in new environments such as SNSs, owing to some factors of SNSs that reduce the ability of users to detect the attack and increase the ability of attackers to launch it. This work will contribute to the knowledge of social engineering by presenting the first two conceptual models of social engineering attacks in SNSs. Phase-based and source-based models are presented, along with an intensive and comprehensive overview of different aspects of social engineering threats in SNSs

The study aimed to identify the role of readiness for artificial intelligence (AI) requirements (technical infrastructure, data sets, administrative and organizational readiness, laws and legislations, AI ethics, and societal challenges) in government innovation from the point of view of the employees in Jordanian government agencies. (342) valid questionnaires were collected from employees working at information technology departments of Jordanian government agencies. After analyzing the data, the study concluded that the level of availability of artificial intelligence in Jordanian government agencies is moderate, and the degree of availability of the sub-dimensions of artificial intelligence was moderate, except for two dimensions data sets and legislation, which came within high level. The availability of government innovation is high. The study also found there is a significant effect of artificial intelligence on government innovation in Jordanian government agencies and explained 62% of the variance in government innovation. The study recommended the need to pay attention to the development of artificial intelligence requirements because of continuous development in technology and environment, and to make this a continuous process. In addition, government agencies need to cooperate with public and private sector organizations, build partnerships with them for the benefit of both in developing artificial intelligence, and thus government innovation, and making artificial intelligence and government innovation on the ladder of their priorities and strategic plans.