Software-defined networking (SDN) is a new networking paradigm that provides centralized control, programmability, and a global view of topology in the controller. SDN is becoming more popular due to its high audibility, which also raises security and privacy concerns. SDN must be outfitted with the best security scheme to counter the evolving security attacks. A Distributed Denial-of-Service (DDoS) attack is a network attack that floods network links with illegitimate data using high-rate packet transmission. Illegitimate data traffic can overload network links, causing legitimate data to be dropped and network services to be unavailable. Low-rate Distributed Denial-of-Service (LDDoS) is a recent evolution of DDoS attack that has been emerged as one of the most serious vulnerabilities for the Internet, cloud computing platforms, the Internet of Things (IoT), and large data centers. Moreover, LDDoS attacks are more challenging to detect because this attack sends a large amount of illegitimate data that are disguised as legitimate traffic. Thus, traditional security mechanisms such as symmetric/asymmetric detection schemes that have been proposed to protect SDN from DDoS attacks may not be suitable or inefficient for detecting LDDoS attacks. Therefore, more research studies are needed in this domain. There are several survey papers addressing the detection mechanisms of DDoS attacks in SDN, but these studies have focused mainly on high-rate DDoS attacks. Alternatively, in this paper, we present an extensive survey of different detection mechanisms proposed to protect the SDN from LDDoS attacks using machine learning approaches. Our survey describes vulnerability issues in all layers of the SDN architecture that LDDoS attacks can exploit. Current challenges and future directions are also discussed. The survey can be used by researchers to explore and develop innovative and efficient techniques to enhance SDN’s protection against LDDoS attacks.

Recently, Wireless Sensor Networks (WSNs) have been deployed into a variety of applications including homeland security, military systems, and health care. Sensor nodes deployed in such networks are subject to several attacks such as sinkhole and select forwarding, wormhole, Hello flood, and replication attacks. Therefore, developing secure and energy-efficient routing protocols to protect WSNs against these attacks while efficiently utilizing the energy of the deployed nodes has become imperative. Several routing protocols have been proposed in the literature for WSNs. Most of these protocols assume static nodes and sinks to collect data from network fields. However, they may be highly movable, and recent advances show that mobile sensors in WSNs have a promising performance. Therefore, this paper surveys the state of the art on routing protocols related to WSNs and presents the security issues or problems associated with the current protocols as well as discusses the future trends and open research issues on secure routing protocols of WSNs.

Recent development in the field of Wireless communications and electronics has enabled the deployment of Wireless sensor Networks (WSNs) in an expanding variety of applications. Significantly, wireless communications have demonstrated profound significance in a variety of applications ranging from military to health applications and from home to industry. In WSNs, a major goal is conserving the sensor nodes' energy and thus maximizing the network lifetime. Several energy efficient routing protocols have been proposed in the literature. However, in these protocols, a path is selected based on the local energy view of a sensor node. In this paper, we propose an energy-efficient routing protocol that selects a communication path based on the global energy view of the network. The path selection criterion is based on an energy-weight function to reflect how balanced is the energy distribution among all nodes along the path. The energy weight function estimates the energy weight of different paths and the communication path with the best energy weight is selected. Simulation results indicate clearly that compared to the routing protocol in, our proposed protocol distributes the energy consumption evenly among the network nodes and thus maximizes the network life time.