In this study, we suggest an interpretable fuzzy system for the classification of malicious domains. The proposed system is integration of Sugeno type fuzzy system and projection neural network, the main advantage of interpretable fuzzy system is to classify the patterns and self-explainable capability. Whereas the projection network is used to exact mapped fuzzy inference rules to the network's projection layer. On the other hands, the system is able to deal with large amount of real-time data. The proposed model is tested malicious URL datasets collected from Alexa. The experimental results show that the system is able to classify malicious domain with high accuracy and interpretability as compared to existing methods. The proposed model is usefull to classify malicious attacks and explain the couses behind the decision. The evaluation of model based on confusion matrices, ROC and the nauck index is used for the interpretability assessments.

A circularly polarized antenna based on a dual dipole topology is designed in this work. Circular polarization is achieved by placing two pair of parallel dipoles orthogonally and introducing a 90o phase difference between the four arms feeding the dipole using a phase shifter. The two arms of each dipole are located on the opposite sides of the single-layered substrate and fed using a probe feed. Disclosure to the environment can be negatively impact an antenna's radiation aspects and lead to greater. One way to protect these devices is to evaluate the proposed CP antenna with metamaterial radome design, which is closures that can shield antenna while improving the overall performance, by integrated with a metamaterial radome designed based on L-shaped unit cells. The application of this radome improved the impedance bandwidth from 3.9 % (without radome) to 6.3 % and the 3-dB axial ratio bandwidth from 3.2 % to 5.9 %. A prototype of the designed antenna structure is manufactured and measured. The designed and fabricated antenna has a simple structure and does not include disagreeable difficulty of the recently reported Complementary Cross-Dipole Antennas (CCDA). The antenna has a good radiation behavior in the improved desired gain of 4.31 dBi to at least 6.35 dBi due to the contribution of the radome. Design steps for achieving circular polarization and performance improvements are presented and validated experimentally using a fabricated prototype.

The expansion of the Internet and shared networks aids to the growth of records generated by nodes connected to the Internet. With the development of network attack technology, all Internet hosts have become targets of attack. When dealing with new attacks (such as smart ongoing threats) in a complex network environment, existing security strategies are powerless. Compared to existing security detection techniques, honeypot systems (IoT research) can analyze network packets or log files being attacked, and automatically monitor potential attack. Researchers can use this data to accurately capture the tactics, strategies, and techniques of threat actors to create defense strategies. However, for general security researchers, the immediate topic is how to improve the honeypot mechanism that attackers do not recognize and quietly capture their actions. Honeypot technology can be used not only as a passive information system, but also to combat zero-day and future attacks. In response to the rapid development of honeypot recognition with machine-learning technology, this paper proposes a new model of machine learning based on a linear regression algorithm with application and network layer characteristics. As a result of the experiment, we found that the proposed model was 97% more accurate than other machine learning algorithms.

In the past couple of years, the research on the Byzantine attack and its defense strategies has gained the worldwide increasing attention. In this paper, we present a secure protocol to escape from the Byzantine attack in the cognitive radio networks. This protocol is implemented using the Lamport-Shostak-Pease algorithm and blockchain technology. A reliable distributed computing system must be able to handle the faulty components to deliver the error less performance. These faulty components send the conflicting information to the other parts of the system. As a result, it creates a problem which is similar to the Byzantine Generals Problem (BGP). In order to design a reliable system, it is necessary to identify and overlook such faulty components.
In the cognitive radio networks, there are the two types of users i.e. primary and secondary users. The primary users hold the licensed spectrum whereas the secondary users hold the leased spectrum. In these CR networks, there can be a similar problem like BGP while allocating the spectrum to the secondary users. Also, it requires all the users to agree on a common value, even with some faulty users in the network. This is called as the Byzantine Agreement. Here we have addressed this Byzantine General problem to develop a reliable and secure spectrum allocation using the Lamport-Shostak-Pease algorithm. It can solve the BGP for n≥3m+1 users in the presence of ‘m’ faulters. In this implementation, the blockchain technology is used as the efficient decentralized database which records all the transactions of the users, like exchanging currency, mining, updating the blockchain and auctioning the spectrum for lease.

The world is now turning towards automation also the use of virtual reality is expanding day by day, the need for faster and reliable communication has been increased. This technology will play a key role towards the development of Smart Cities, where government is majorly focusing. The urge of quicker and more secure communication (wireless) is making us switch towards the 6G or sixth generation communication. To the benefit of its citizens and businesses, a smart city is a location where the traditional networks and services have been enhanced via the use of digital and telecommunication technology. Infrastructure, social capital, which also includes traditional skills and community institutions, and digital technologies are all combined in smart cities to promote sustainable economic growth and provide a desirable environment for all residents. By 2035, the publisher believes that as smart city infrastructure develops, 6G will be a crucial component of communications, applications, content, and commerce in smart cities. We go over the progress of beyond 5G and advanced 5G features in order to forecast important 6G requirements and showcase 6G potential. In comparison to 5G, we will also discuss 6G scenarios, requirements, and technology components. There are lots of challenges associated with 5G’s wireless communication network one of them is limited data speed. We will also be focusing on these challenges associated with technology and also the plans to use this technology towards the development of smart cities. The 5G wireless communication network is currently facing the challenge of limited data speed and billions of data-intensive applications are used. To resolve this problem many developers and researchers are working on advanced technologies so that they can consummate the wireless service demands. So that we can shift ourselves from 5G to 6G and fulfil our expectations towards smart city. In addition, there are varied use cases of the wireless 6G technology in education, media and entertainment, tourism.