Recently, there has been enormous development due to advancements in technology. Industries and enterprises are moving towards a digital system, and the oil and gas industries are no exception. There are several threats and risks in digital systems, which are controlled through cyber-security. For the first time in the theory of fuzzy sets, this research analyzes the relationships between cyber-security and cyber-crimes in the oil and gas sectors. The novel concepts of complex intuitionistic fuzzy relations (CIFRs) are introduced. Moreover, the types of CIFRs are defined and their properties are discussed. In addition, an application is presented that uses the Hasse diagram to make a decision regarding the most suitable cyber-security techniques to implement in an industry. Furthermore, the omnipotence of the proposed methods is explained by a comparative study.

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Many industries are developing robust models, capable of analyzing huge and complex data by using machine learning (ML) while delivering faster and more accurate results on vast scales. ML is a subfield of artificial intelligence, which is broadly defined as the capability of a machine to imitate intelligent human behavior. ML tools enable organizations to swiftly identify profitable opportunities and potential risks. Besides these uses, ML also has a wide range of applications in our daily lives. So, the development in ML is most important in this age of digital system to solve more complex problems. In order to further develop ML and diminish the uncertainties to improve accuracy, an innovative concept of complex bipolar intuitionistic fuzzy sets (CBIFSs) is introduced in this article. Further, the Cartesian product of two CBIFSs is defined. Moreover, the complex bipolar intuitionistic fuzzy relations (CBIFRs) and their types with suitable examples are defined. In addition, some important results and properties are also presented. The proposed modeling techniques are used to study different ML factors and their interrelationship, so that the functionality of ML might be enhanced. Furthermore, the advantages and benefits of proposed methods are described by their side to side comparison with preexisting frameworks in the literature.

Applications based on video and image in wireless sensor network are highly attractive due to their wealth of information. In this context, application for object recognition and tracking using image and video information is one the attractive approaches that can be applied for event detection and localization, security processes, following of the rare animal species and control of road traffic, and so forth. However, the implementation of such approach with WMSN requires a specific image processing scheme and efficient transmission protocol. In fact, because of the limited energy of the batteries embedded in motes, the power consumption is the major constraint facing network life time and reliability in WMSN. The efficiency and the validity of these multimedia applications over wireless sensor networks are then dependent on the capabilities of the designer to provide low-power scheme for data processing and energy-aware transmission protocols. This paper presents a contribution to the design of low complexity scheme based on object identification for efficient sensing of multimedia information in wireless multimedia sensor networks. It proposes a new solution and explores the associated performances of this scheme. The presented results in this paper attest the high efficiency to achieve low-power objects identification when implemented in wireless motes.

Artificial intelligence (AI) has made the life more efficient and powered many programs and services. AI is progressing rapidly, and the future is arriving faster than the predictions. Soon, AI will be more proficient as compared to humans in all aspects. Many industries are using AI for the analysis of data to find the best methods for investments. In this article, we developed the impacts of AI on different industries through the new concepts of complex bipolar picture fuzzy set (CBPFS) proposed in the current study. The CBPFS has an extensive structure that includes membership, abstinence, and nonmembership degrees with the ability to deal with multivariable problems. These degrees are fuzzy numbers between 0 and 1 inclusive; 0 being the lowest and 1 being the highest value for each degree, which reflect different meaning for membership, nonmembership, and abstinence. Furthermore, the paper explains the Cartesian product between CBPFSs and complex bipolar picture fuzzy relation (CBPFR) and its types with suitable example. Furthermore, through a comparison test with preexisting fuzzy set frameworks, some benefits of CBPFS are presented in this article.

Nowadays, healthcare has become an important area for the Internet of Things (IoT) to automate healthcare facilities to share and use patient data anytime and anywhere with Internet services. At present, the host-based Internet paradigm is used for sharing and accessing healthcare-related data. However, due to the location-dependent nature, it suffers from latency, mobility, and security. For this purpose, Named Data Networking (NDN) has been recommended as the future Internet paradigm to cover the shortcomings of the traditional host-based Internet paradigm. Unfortunately, the novel breed lacks a secure framework for healthcare. This article constructs an NDN-Based Internet of Medical Things (NDN-IoMT) framework using a lightweight certificateless (CLC) signature. We adopt the Hyperelliptic Curve Cryptosystem (HCC) to reduce cost, which provides strong security using a smaller key size compared to Elliptic Curve Cryptosystem (ECC). Furthermore, we validate the safety of the proposed scheme through AVISPA. For cost-efficiency, we compare the designed scheme with relevant certificateless signature schemes. The final result shows that our proposed scheme uses minimal network resources. Lastly, we deploy the given framework on NDN-IoMT.

Abstract. Multimedia communication is highly attractive in Wireless MultimediaSensor Networks (WMSN) due to their wealth of information's. However, the transmission of multimedia information such as image and video requires a specific scheme and an efficient communication protocol. In fact, the performances of multimedia based applications on WMSN are highly dependent on the capabilities of the designer to provide low-power data processing and energy-aware communication protocols. This chapter presents a contribution to the design of low complexity scheme for object identification using Wireless Multimedia Sensor Networks. The main idea behind the design of this scheme is to avoid useless multimedia data streaming on the network. In depth, it ensures the detection of the specific event (target) before sending image to notify the end user. The chapter discusses the capabilities of the proposed scheme to identify a target and to achieve low-power processing at the source mote while unloading the network. The power consumption and the time processing of this scheme were estimated for MICA2 and MICAZ motes and showed that it outperforms other methods for communication in WMSN such as the methods based on image compression.

Over the past 20 years, the emergence of social media and its developments have rapidly changed communication and information technology. Social media plays a necessary part in accessing information and communication. In spite of its many advantages, users have also been facing many threats on social media platforms. This research aims to analyze and resolve these threats by using the new concepts of complex cubic T spherical fuzzy sets (CCuTSFS) that have a broad structure including degrees of membership, neutral-membership, and non-membership. It does a better job of modeling uncertainty than any other preexisting structure. Furthermore, we defined the concepts of the Cartesian product (CP) between CCuTSFSs, complex cubic T spherical fuzzy relation (CCuTSFR) and the types of CCuTSFRs with appropriate examples. This study looked at the relationship between different types of security and threats on social media for the first time in fuzzy set theory. The proposed methods demonstrate how to control the effects of threats by using valid security methods. Finally, the benefits of the presented strategies are explained in the comparative study.