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Domain Name System (DNS) is a fundamental protocol and backbone of the internet that translates domain names to Internet Protocol (IP) addresses. Initially, it was only meant for mapping domain names, however, currently it is used to transfer data over the internet in the form of plain text. This attracts attackers to perform cyberattacks such as DNS spoofing, DNS amplification, and cache poisoning etc. Various solutions were proposed to protect DNS protocol from such attacks such as using DNS load balancers, OpenDNS by Cisco, DNSFilters etc. However, despite these security measures, the attac...

Distal radius fractures (DRFs) are one of the most common types of wrist fracture and can be subdivided into intra- and extra-articular fractures. Compared with extra-articular DRFs which spare the joint surface, intra-articular DRFs extend to the articular surface and can be more difficult to treat. Identification of articular involvement can provide valuable information about the characteristics of fracture patterns. In this study, a two-stage ensemble deep learning framework was proposed to differentiate intra- and extra-articular DRFs automatically on posteroanterior (PA) view wrist X-rays...

Over the past few years, the awful COVID-19 pandemic effect has become a lethal sickness. The processing of the gathered samples requires extra time due to the use of medical diagnostic equipment, methodologies, and clinical testing procedures for the early diagnosis of infected individuals. An innovative multimodal paradigm for the early diagnosis and precise categorization of COVID-19 is put up as a solution to this issue. To extract distinguishing features from the prepared chest X-ray picture and cough (audio) database, chest X-ray-based and cough-based model are used here. Other public ch...

Network traffic, which records users’ behaviors, is valuable data resources for diagnosing the health of the network. Mining anomaly in network is essential for network defense. Although traditional machine learning approaches have good performance, their dependence on huge training data set with expensive labels make them impractical. Furthermore, after complex hyperparameters tuning, the detection model may not work. Facing these challenges, in this paper, we propose Autoperman through supervised learning. In Autoperman, machine learning algorithms with fixed hyperparameters as feature ext...

An effective approach is proposed to predict the remaining fatigue life (RFL) of structures with stochastic parameters. The extended finite element method (XFEM) was firstly used to produce a large amount of datasets associated with structural responses and RFL. Then, a RFL prediction model was developed using the ensemble learning algorithm, which employed multiple machine-learning algorithms to learn useful degradation patterns of the structures from the XFEM datasets. Several numerical examples were investigated to evaluate the performance of proposed RFL prediction approach. The analysis r...