Although the fifth generation (5G) wireless networks are yet to be fully investigated, the visionaries of the 6th generation (6G) echo systems have already come into the discussion. Therefore, in order to consolidate and solidify the security and privacy in 6G networks, we survey how security may impact the envisioned 6G wireless systems, possible challenges with different 6G technologies, and the potential solutions. We provide our vision on 6G security and security key performance indicators (KPIs) with the tentative threat landscape based on the foreseen 6G network architecture. Moreover, we discuss the security and privacy challenges that may encounter with the available 6G requirements and potential 6G applications. We also give the reader some insights into the standardization efforts and research-level projects relevant to 6G security. In particular, we discuss the security considerations with 6G enabling technologies such as distributed ledger technology (DLT), physical layer security, distributed AI/ML, visible light communication (VLC), THz, and quantum computing. All in all, this work intends to provide enlightening guidance for the subsequent research of 6G security and privacy at this initial phase of vision towards reality.

Software-Defined Networking (SDN) is a communication paradigm that brings cost efficiency and flexibility through software-defined functions resident on centralized controllers. Although SDN applications are introduced in a limited scope with related technologies still under development, operational SDN networks already face major security threats. Therefore, comprehensive and efficient solutions are crucial. Especially, large-scale security threats such as Distributed-Denial-of-Service (DDoS) attacks are jeopardizing safety and availability of data and services in these systems. A DDoS attack is aimed at making resources unavailable to legitimate users via overloading systems with excessive superfluous traffic from distributed sources. In this work, we describe and evaluate a joint entropy based security scheme, JESS, to enhance the SDN security with the aim of a reinforced SDN architecture against DDoS attacks. In particular, our proposed model devises a statistical solution to detect and mitigate these hazards. To the best of our knowledge, JESS is the first model that utilizes joint entropy for DDoS detection and mitigation in SDN environment. Since it relies on a statistical model, it does mitigate not only known attacks but also unfamiliar types in an efficient manner.

Email is of critical importance as a communication channel for both business and personal matters. Unfortunately, it is also often exploited for phishing attacks. To defend against such threats, many organizations have begun to provide anti-phishing training programs to their employees. A central question in the development of such programs is how they can be designed sustainably and effectively to minimize the vulnerability of employees to phishing attacks. In this paper, we survey and categorize works that consider different elements of such programs via a clearly laid-out methodology, and identify key findings in the technical literature. Overall, we find that researchers agree on the answers to many relevant questions regarding the utility and effectiveness of anti-phishing training. However, we identified influencing factors, such as the impact of age on the success of anti-phishing training programs, for which mixed findings are available. Finally, based on our comprehensive analysis, we describe how a well-founded anti-phishing training program should be designed and parameterized with a set of proposed research directions.

COVID-19 pandemic has affected the world in an unexpected manner. The human race is battling against the pandemic while schools, universities, industries, hospitals and governments are seeking new methods and technologies to seamlessly continue their usual operations. In response, this paper presents how 5G and IoT (Internet of Things) related technologies can be efficiently utilized and developed to fight against the COVID-19 pandemic. Several use-cases on how 5G and IoT can be enablers to provide innovative solutions in the areas of telehealth, contact tracing, education, retail and supply chains, e-government/ remote office/ information sharing, smart manufacturing and factory automation, e-tourism and entertainment are presented along with their technical requirements and challenges. It is envisaged that the proposed solutions will be instrumental to facilitate the usual lifestyle, work and other day-to-day activities of humans in the post-pandemic world.

Multi-access Edge Computing (MEC) is a novel edge computing paradigm that moves cloudbased processing and storage capabilities closer to mobile users by implementing server resources in the access nodes. MEC helps fulfill the stringent requirements of 5G and beyond networks to offer anytimeanywhere connectivity for many devices with ultra-low delay and huge bandwidths. Information-Centric Networking (ICN) is another prominent network technology that builds on a content-centric network architecture to overcome host-centric routing/operation shortcomings and to realize efficient pervasive and ubiquitous networking. It is envisaged to be employed in Future Internet including Beyond 5G (B5G) networks. The consolidation of ICN with MEC technology offers new opportunities to realize that vision and serve advanced use cases. However, various integration challenges are yet to be addressed to enable the wide-scale co-deployment of ICN with MEC in future networks. In this paper, we discuss and elaborate on ICN MEC integration to provide a comprehensive survey with a forward-looking perspective for B5G networks. In that regard, we deduce lessons learned from related works (for both 5G and B5G networks). We present ongoing standardization activities to highlight practical implications of such efforts. Moreover, we render key B5G use cases and highlight the role for ICN MEC integration for addressing their requirements. Finally, we layout research challenges and identify potential research directions. For this last contribution, we also provide a mapping of the latter to ICN integration challenges and use cases.