Internet of Things (IoT) consists of smart devices that communicate with each other. It enables these devices to collect and exchange data. Besides, IoT has now a wide range of life applications such as industry, transportation, logistics, healthcare, smart environment, as well as personal, social gaming robot, and city information. Smart devices can have wired or wireless connection. As far as the wireless IoT is the main concern, many different wireless communication technologies and protocols can be used to connect the smart device such as Internet Protocol Version 6 (IPv6), over Low power Wireless Personal Area Networks (6LoWPAN), ZigBee, Bluetooth Low Energy (BLE), Z-Wave and Near Field Communication (NFC). They are short range standard network protocols, while SigFox and Cellular are Low Power Wide Area Network (LPWAN).standard protocols. This paper will be an attempt to review different communication protocols in IoT. In addition, it will compare between commonly IoT communication protocols, with an emphasis on the main features and behaviors of various metrics of power consumption security spreading data rate, and other features. This comparison aims at presenting guidelines for the researchers to be able to select the right protocol for different applications.

Botnet-based Distributed Denial of Service (DDoS) attacks are considered as the main concerns and problems of today's Internet. The damage of these attacks are very serious since the number of computers involved in these attacks is huge and distributed worldwide. However, many protocols such as Domain Name System (DNS) have several security vulnerabilities nowadays that are utilized by botnet attackers. The amplification attacks are the most popular attacks in the Internet which require robust hardware and software for security assurance. In this paper, we provide an overview of botnet-based DDoS attacks that use DNS as a basic infrastructure to launch attacks. We aim to make a better understanding of the most noted attacks to extend the knowledge about DDoS attacks and to analyze the importance of DNS services.

Several problems have been solved by nonlinear equation systems (NESs), including real-life issues in chemistry and neurophysiology. However, the accuracy of solutions is highly dependent on the efficiency of the algorithm used. In this paper, a Modified Sperm Swarm Optimization Algorithm called MSSO is introduced to solve NESs. MSSO combines Newton’s second-order iterative method with the Sperm Swarm Optimization Algorithm (SSO). Through this combination, MSSO’s search mechanism is improved, its convergence rate is accelerated, local optima are avoided, and more accurate solutions are provided. The method overcomes several drawbacks of Newton’s method, such as the initial points’ selection, falling into the trap of local optima, and divergence. In this study, MSSO was evaluated using eight NES benchmarks that are commonly used in the literature, three of which are from real-life applications. Furthermore, MSSO was compared with several well-known optimization algorithms, including the original SSO, Harris Hawk Optimization (HHO), Butterfly Optimization Algorithm (BOA), Ant Lion Optimizer (ALO), Particle Swarm Optimization (PSO), and Equilibrium Optimization (EO). According to the results, MSSO outperformed the compared algorithms across all selected benchmark systems in four aspects: stability, fitness values, best solutions, and convergence speed.

Internet Protocol version 6 (IPv6) over Low power Wireless Personal Area Networks (6LoWPAN) is extensively used in wireless sensor networks (WSNs) due to its ability to transmit IPv6 packet with low bandwidth and limited resources. 6LoWPAN has several operations in each layer. Most existing security challenges are focused on the network layer, which is represented by its routing protocol for low-power and lossy network (RPL). RPL components include WSN nodes that have constrained resources. Therefore, the exposure of RPL to various attacks may lead to network damage. A sinkhole attack is a routing attack that could affect the network topology. This paper aims to investigate the existing detection mechanisms used in detecting sinkhole attack on RPL-based networks. This work categorizes and presents each mechanism according to certain aspects. Then, their advantages and drawbacks with regard to resource consumption and false positive rate are discussed and compared.

A botnet is considered a serious issue that threatens cyber security. It is a mean used by cybercriminals for carrying out their illegal activities. Such activities may include click fraud and DDoS attacks. The present paper aims to propose a new filtering approach called “The Gunner System”. The mentioned approach involves rule-based Domain Name System (DNS) features for detecting botnets. Through this approach, the researchers expect that the accuracy of the DNS-based botnet detection will be enhanced.