Over the past three decades, standardizing organizations (e.g., the National Institute of Standards and Technology and Internet Engineering Task Force) have investigated the efficiency of cryptographic algorithms and provided (technical) guidelines for practitioners. For example, the (Datagram) Transport Layer Security “(D)TLS” 1.2/1.3 was designed to help industries implement and integrate such methods through underpinning infrastructures of Internet of Everything (IoE) environments with efficiency and efficacy in mind. The main goal underpinning such protocols is to protect the Internet connections between IoE machines from malicious activities such as unauthorized eavesdropping, monitoring, and tampering with messages. In theory, these protocols are supposed to be secure. Still, most existing implementations partially follow the standard features of (D)TLS 1.2/3, leaving them vulnerable to risks such as side-channel and network attacks. In this paper, we critically review the standard protocols deployed for the security management of data and connected machines, and also examine the recently discovered vulnerabilities that lead to successful zero-day attacks in IoE environments. Then, we discuss various potential countermeasures in the form of organizational policy enforcement strategies and mitigation approaches that can be used by cybersecurity practitioners, decision- and policy-makers. Finally, we identify both proactive and reactive solutions for further consideration and study, as well as propose alternative mechanisms and e-governance policies for standardizing organizations and engineers in future solution designs.

It is increasingly challenging to deal with the volume,variety, velocity, and veracity of misinformation (e.g., dissemination of fake news contents, spurious posts, and fabricated images/videos) from different online platforms. In this article, we present an overview of existing machine learning and information hiding-based misinformation detection techniques and discuss the current threats and limitations of these approaches. Based on the discussion, we identify a number of potential countermeasures.

User authentication remains a challenging issue, despite the existence of a large number of proposed solutions, such as traditional text-based, graphical-based, biometrics-based, Web-based, and hardware-based schemes. For example, some of these schemes are not suitable for deployment in an Internet of Things (IoT) setting, partly due to the hardware and/or software constraints of IoT devices. The increasing popularity and pervasiveness of IoT equipment in a broad range of settings reinforces the importance of ensuring the security and privacy of IoT devices. Therefore, in this article, we conduct a comprehensive literature review and an empirical study to gain an in-depth understanding of the different authentication schemes as well as their vulnerabilities and deficits against various types of cyberattacks when applied in IoT-based systems. Based on the identified limitations, we recommend several mitigation strategies and discuss the practical implications of our findings.