The evaluation of data breaches and cybersecurity risks has not yet been formally addressed in modern business systems. There has been a tremendous increase in the generation, usage and consumption of industrial and business data as a result of smart and computational intensive software systems. This has resulted in an increase in the attack surface of these cyber systems. Consequently, there has been a consequent increase in the associated cybersecurity risks. However, no significant studies have been conducted that examine, compare, and evaluate the approaches used by the risk calculators to investigate the data breaches. The development of an efficient cybersecurity solution allows us to mitigate the data breaches threatened by the cybersecurity risks such as cyber-attacks against database storage, processing and management. In this paper, we develop a comprehensive, formal model that estimates the two components of security risks: breach cost and the likelihood of a data breach within 12 months. The data used in this model are taken from the industrial business report, which provides the necessary information collected and the calculators developed by the major organizations in the field. This model integrated with the cybersecurity solution uses consolidated factors that have a significant impact on the data breach risk. We propose mathematical models of how the factors impact the cost and the likelihood. These models allow us to conclude that results obtained through the models mitigate the data breaches in the potential and future business system dynamically.

The possible applications of communication based on big data have steadily increased in several industries, such as the autonomous vehicle industry, with a corresponding increase in security challenges, including cybersecurity vulnerabilities (CVs). The cybersecurity-related symmetry of big data communication systems used in autonomous vehicles may raise more vulnerabilities in the data communication process between these vehicles and IoT devices. The data involved in the CVs may be encrypted using an asymmetric and symmetric algorithm. Autonomous vehicles with proactive cybersecurity solutions, power-based cyberattacks, and dynamic countermeasures are the modern issues/developments with emerging technology and evolving attacks. Research on big data has been primarily focused on mitigating CVs and minimizing big data breaches using appropriate countermeasures known as security solutions. In the future, CVs in data communication between autonomous vehicles (DCAV), the weaknesses of autonomous vehicular networks (AVN), and cyber threats to network functions form the primary security issues in big data communication, AVN, and DCAV. Therefore, efficient countermeasure models and security algorithms are required to minimize CVs and data breaches. As a technique, policies and rules of CVs with proxy and demilitarized zone (DMZ) servers were combined to enhance the efficiency of the countermeasure. In this study, we propose an information security approach that depends on the increasing energy levels of attacks and CVs by identifying the energy levels of each attack. To show the results of the performance of our proposed countermeasure, CV and energy consumption are compared with different attacks. Thus, the countermeasures can secure big data communication and DCAV using security algorithms related to cybersecurity and effectively prevent CVs and big data breaches during data communication.

Software-defined networking (SDN) has emerged as a flexible and programmable network architecture that takes advantage of the benefits of global visibility and centralized control over a network. One of the main properties of the SDN architecture is the ability to offer a northbound interface (NBI), which enables network applications to access the SDN controller resources. However, the NBI can be compromised by a malicious application due to the lack of standardization and security aspects in the most current NBI designs. Therefore, in this paper, we propose a novel comprehensive security solution for securing the application–controller interface, named BCNBI. We propose a controller-independent lightweight blockchain architecture and exploit the security features of blockchain while limiting the blockchain’s computational overhead. BCNBI automatically verifies application and SDN controller credentials through token-based authentication. The proposed solution enforces fine-grained access control for each application’s API request and classifies the permission set into strict and normal policies, in order to add an extra level of security. In addition, the trustworthiness of applications is evaluated in order to prevent malicious activities. We implemented our blockchain-based solution to analyze its security, based on the confidentiality–integrity–availability model criteria, and evaluated the introduced overhead in terms of processing time and packet overhead. The experimental results demonstrate that the BCNBI can effectively secure the NBI, based on the fundamental security goals, while introducing insignificant overhead.

Sixth-generation (6G)-based communications have many applications and are emerging as a new system to utilize existing vehicles and communication devices in autonomous vehicles (AVs). Electric vehicles and AVs not supporting the integration of intelligent cybersecurity will become vulnerable, and their internal functions, features, and devices providing services will be damaged. This paper presents an intelligent cybersecurity model integrating intelligent features according to the emerging 6G-based technology based on evolving cyberattacks. The model’s novel design was developed using the necessary algorithms to provide quick and proactive decisions with intelligent cybersecurity based on 6G (IC6G) policies when AVs face cyberattacks. In this model, network security algorithms incorporating intelligent techniques are developed using applied cryptography. Money transaction handling services implemented in an AV are considered an example to determine the security and intelligence level depending on the IC6G policies. Intelligence, complexity, and energy efficiency (EE) are assessed. Finally, we conclude that the model results are effective for intelligently detecting and preventing cyberattacks on AVs.

The implementation of AI-based healthcare communication systems presents a significant challenge for the development of cost-effective medical environments. Despite numerous approaches introduced internationally, the field continues to grapple with real-world issues, demands, and a rising number of unforeseen diseases stemming from vulnerabilities, such as zero-day attacks. Purpose: The healthcare system, including communication between medical devices, must evolve alongside new technologies, such as AI-based proactive devices. Future healthcare hubs (future proactive devices), which will be deployed in various remote locations, utilize their own cybersecurity solutions to ensure secure AI-based healthcare communication services. Addressing these challenges requires managing potential issues arising in current medical scenarios. For instance, sudden security issues like ransomware attacks disrupting medical activities in London hospitals in May 2024 highlight the urgency of developing effective solutions that can be applied globally. Method: The AI-based approach offers a potential solution to these problems, although its implementation in medical security management presents challenges for the healthcare profession. While cybersecurity solutions are necessary, they can be developed through various management strategies. Anticipated Results: Implementing management solutions will require updating medical systems with AI-based policies. Efficient AI algorithms, derived from advanced mathematical or scientific techniques, are essential. The effectiveness of these solutions will ultimately determine the outcomes. Conclusions: Healthcare applications should be designed to be affordable while accommodating the essential facilities for human life.

The transportation industries forecast that by 2050 more than 50% of vehicles on the road will be autonomous vehicles, and automotive services will dynamically support all vehicles. All of them will be serviced using the latest technology, which includes the Software Defined Network (SDN) and available new generations (5G+ or 6G) at the time. Although many transportation services and rapid facilities are achievable dynamically, transportation services with automation and intelligent actions are still not mature because the legacy of transport services cannot be corporate with the 5G+. These expected problems can be improved through the following possible and manageable approaches: flexible framework of 5G automotive services from the legacy systems, designing energy-efficient and intelligent infrastructures with SDN, and managing security solutions that evolve with the emerging technology. An efficient model (flexible framework) is proposed to secure smart transportation services with a secure and intelligent connected system and security solutions based on the 5G concept. Although 5G is considered in this framework, the method and steps of design and solution phases will be adaptable to the 5G+ framework. Furthermore, the basic properties of SDN allowed us to design a novel approach for measuring data traffic related to transport services and transport management, such as the priority of the transportation services. With the emergence of 5G+ capabilities, transportation services expect more challenges through future user requirements, including dynamic security solutions, minimum latency, maximum energy efficiency (EE), etc. Future automotive services depend on many sensors and their messages received through secure communication systems with 5G+ capabilities. As a result, this theoretical model will prove that 5G capabilities provide security facilities, better latency, and EE within the transportation system. Moreover, this model can be extendable to improve the 5G+ transportation services.