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Vehicular ad hoc networks (VANETs) are an emerging type of mobile ad hoc networks (MANETs) with robust applications in intelligent traffic management systems. VANET has drawn significant attention from the wireless communication research community and has become one of the most prominent research fields in intelligent transportation system (ITS) because of the potential to provide road safety and precautionary measures for the drivers and passengers. In this survey, we discussed the basic overview of the VANET from the architecture, communication methods, standards, characteristics, and VANET security services. Second, we presented the threats and attacks and the recent state-of-the-art methods of the VANET security services. Then, we comprehensively reviewed the authentication schemes that can protect vehicular networks from malicious nodes and fake messages. Third, we discussed the latest simulation tools and the performance of the authentication schemes in terms of simulation tools, which was followed by the VANET applications. Lastly, we identified the open research challenges and gave future research directions. In sum, this survey fills the gap of existing surveys and summarizes the latest research development. All the security attacks in VANETs and their related countermeasures are discussed with respect to ensuring secure communication. The authentication schemes and comprehensive applications were introduced and analyzed in detail. In addition, open research challenges and future research directions were issued.

There has been a tremendous growth in the number of smart devices and their applications (e.g., smart sensors, wearable devices, smart phones, smart cars, etc.) in use in our everyday lives. This is accompanied by a new form of interconnection between the physical and digital worlds, commonly known as the Internet of Things (IoT). This is a paradigm shift, where anything and everything can be interconnected via a communication medium. In such systems, security is a prime concern and protecting the resources (e.g., applications and services) from unauthorized access needs appropriately designed security and privacy solutions. Building secure systems for the IoT can only be achieved through a thorough understanding of the particular needs of such systems. The state of the art is lacking a systematic analysis of the security requirements for the IoT. Motivated by this, in this paper, we present a systematic approach to understand the security requirements for the IoT, which will help designing secure IoT systems for the future. In developing these requirements, we provide different scenarios and outline potential threats and attacks within the IoT. Based on the characteristics of the IoT, we group the possible threats and attacks into five areas, namely communications, device/services, users, mobility and integration of resources. We then examine the existing security requirements for IoT presented in the literature and detail our approach for security requirements for the IoT. We argue that by adhering to the proposed requirements, an IoT system can be designed securely by achieving much of the promised benefits of scalability, usability, connectivity, and flexibility in a practical and comprehensive manner.

Bring your own device (BYOD) paradigm that permits employees to come with their own mobile devices to join the organizational network is rapidly changing the organizational operation method by enhancing flexibility, productivity, and efficiency. Despite these benefits, security issues remain a concern in organizational settings. A considerable number of studies have been conducted and published in this domain without a detailed review of the security solution mechanisms. Moreover, some reviews conducted focused more on conventional approaches such as mobile content management, and application content management. Hence, the implementation of security in BYOD using the conventional method is ineffective. Thus, machine learning approaches seem to be the promising approach, which provides a solution to the security problem in the BYOD environment. This study presents a comprehensive systematic mapping review that focused on the application of the machine learning approach for the mitigation of security threats and attacks in the BYOD environment by highlighting the current trends in the existing studies. Five academic databases were searched and a total of 753 of the primary studies published between 2012 and 2021 were initially retrieved. These studies were screened based on their title, abstract and full text to check their eligibility and relevance for the study. However, forty primary studies were included and analyzed in the systematic mapping review (SMR). Based on the analysis and bubble plot mapping, significant research trends were identified on security threats and attacks, machine learning approaches, datasets usage, and evaluation metrics. The SMR result demonstrates the rise in the number of investigations regarding malware and unauthorized access to existing security threats and attacks. The SMR study indicates that supervised learning approaches such as SVM, DT, and RF are the most employed learning model by the previous research. Thus, there is an open research issue in the application of unsupervised learning approaches such as clustering and deep learning approaches. Therefore, the SMR has set the pace for creating new ground research in the machine learning implementation in the BYOD environment, which will offer invaluable insight into the study field, and researchers can employ it to find a research gap in the research domain.

Fog computing is an emerging computing paradigm that has come into consideration for the deployment of Internet of Things (IoT) applications amongst researchers and technology industries over the last few years. Fog is highly distributed and consists of a wide number of autonomous end devices, which contribute to the processing. However, the variety of devices offered across different users are not audited. Hence, the security of Fog devices is a major concern that should come into consideration. Therefore, to provide the necessary security for Fog devices, there is a need to understand what the security concerns are with regards to Fog. All aspects of Fog security, which have not been covered by other literature works, need to be identified and aggregated. On the other hand, privacy preservation for user’s data in Fog devices and application data processed in Fog devices is another concern. To provide the appropriate level of trust and privacy, there is a need to focus on authentication, threats and access control mechanisms as well as privacy protection techniques in Fog computing. In this paper, a survey along with a taxonomy is proposed, which presents an overview of existing security concerns in the context of the Fog computing paradigm. Moreover, the Blockchain-based solutions towards a secure Fog computing environment is presented and various research challenges and directions for future research are discussed.

The increasing deployment of Internet of Things (IoT) devices in mission-critical systems has made them more appealing to attackers. Cyberattacks on IoT devices have the potential to expose sensitive data, disrupt operations, and even endanger lives. As a result, IoT security has recently gained traction in both industry and academia. However, no research has examined existing IoT vulnerability assessment frameworks in a systematic and comprehensive manner. To address this gap, this paper systematically reviews and analyses the research challenges and state-of-the-art IoT vulnerability assessment frameworks while taking into account both breadth and depth. The study provides insight into current IoT vulnerability assessment approaches, which is useful for ongoing efforts to characterise cybersecurity risks and manage IoT vulnerabilities. It will be of interest to a spectrum of readers, including those in the IoT research community, researchers in cybersecurity, risk and vulnerability management professionals, and others. By offering the latest perspective on the present IoT vulnerability assessment techniques, this study will raise IoT security awareness and facilitate research into IoT vulnerability assessment methodologies. The knowledge provided by this study will also be beneficial to future academics who are interested in the issues and solutions surrounding IoT security. The report also assists in understanding the research direction in IoT vulnerability assessment approaches, making it beneficial for those looking to create new methods for determining IoT vulnerabilities.

Due to its uniquely suited to the knowledge era, the blockchain technology has currently become highly appealing to the next generation. In addition, such technology has been recently extended to the internet of things (IoT). In essence, the blockchain concept necessitates the use of a decentralized data operation system to store as well as to distribute data and the transactions across the net. Therefore, this study examines the specific concept of the blockchain as a decentralized data management system in the face of probable protection threats. Furthermore, it discusses the present solutions that can be used to counteract those attacks. The blockchain security enhancement solutions are included in this study by summarizing the key points of these solutions. Several blockchain systems and safety devices that register security defenselessness can be developed using such key points. At last, this paper discusses the pending matters and the outlook research paths of blockchain-IoT systems.

Critical Infrastructures (CIs), such as healthcare facilities, power grids, transportation systems, and financial institutions, are vital components of a functioning society, with the economy and safety being dependent on them. Nevertheless, they have become increasingly vulnerable to cyber threats and attacks in recent years. The main reason is their inability to quickly adapt to technological changes, employ updated cryptographic frameworks, and implement a thoroughly secure architecture based on their characteristics. In this study, the unique complexities of these systems are highlighted. Various verified cyberattacks that were executed against CIs in recent years are analyzed. Moreover, the general framework of CIs is demonstrated together with the employed technologies and cryptographic primitives. A thorough architecture of said technologies is developed to better understand the targeted components and easily identify potentially hidden threats. Afterwards, threat, adversary, and attack models that target critical systems and services are designed. The purpose is a better comprehension of the systems’ vulnerabilities, attack structures, motives, and targets for assisting CIs’ designers in creating secure frameworks and mechanisms, with the ability to mitigate such threats. Lastly, security controls and cryptography frameworks are demonstrated together with efficient mitigation architectures and implementations from the research community.

D2D is a promising paradigm of the 5G network offering a beneficial infrastructure and allowing different applications such as social applications, advertising services, or those supporting mutual connectivity of heterogenous objects, as well as those offering support in cases of natural disasters. Compared to conventional network communication, communication achieved by D2D technology shows a lower degree of security. It is necessary to modify existing security mechanisms and new solutions to be adapted to the application of D2D in the fifth generation network, which will raise the level of security in terms of authenticity verification, ensuring service availability and maintaining integrity.

As the number of software vulnerabilities increases, the research on software vulnerabilities becomes a focusing point in information security. A vulnerability could be exploited to attack the information asset with the weakness related to the vulnerability. However, multiple attacks may target one software product at the same time, and it is necessary to rank and prioritize those attacks in order to establish a better defense. This paper proposes a similarity measurement to compare and categorize vulnerabilities, and a set of security metrics to rank attacks based on vulnerability analysis. The vulnerability information is retrieved from a vulnerability management ontology integrating commonly used standards like CVE ( http://www.cve.mitre.org/ ), CWE ( http://www.cwe.mitre.org/ ), CVSS ( http://www.first.org/cvss/ ), and CAPEC ( http://www.capec.mitre.org/ ). This approach can be used in many areas of vulnerability management to secure information systems and e-business, such as vulnerability classification, mitigation and patching, threat detection and attack prevention.