Amjad Mehmood

TL;DR: A novel 3-level hybrid malware detection model for Android operating systems is developed, that can provide high detection accuracy by combining the benefits of the three different levels: 1) Static and Dynamic Analysis; 2) Local and Remote Host; and 3) Machine Learning Intelligence.

TL;DR: This survey paper classifies fault diagnosis methods in recent five years into three categories based on decision centers and key attributes of employed algorithms: centralized approaches, distributed approaches, and hybrid approaches.

TL;DR: This work mainly focuses on protecting an IoT infrastructure from distributed denial-of-service attacks generated by the intruders, and presents a new approach of using Naïve Bayes classification algorithm applied in intrusion detection systems (IDSs).

TL;DR: This work proposes an artificial neural network based energy-efficient and robust routing scheme for WSNs called ELDC, which outperforms LEACH protocol by 42 percent, and other state-of-the-art protocols by more than 30 percent.

TL;DR: An energy‐efficient multi‐level and distance‐aware clustering (EEMDC) mechanism for WSNs, in which the area of the network is divided into three logical layers, which depends upon the hop‐count‐based distance from the base station.