An ensemble machine learning approach through effective feature extraction to classify fake news
There are numerous channels available such as social media, blogs, websites, etc., through
which people can easily access the news. It is due to the availability of these platforms that …
which people can easily access the news. It is due to the availability of these platforms that …
Deep learning approach for intelligent intrusion detection system
Machine learning techniques are being widely used to develop an intrusion detection
system (IDS) for detecting and classifying cyberattacks at the network-level and the host …
system (IDS) for detecting and classifying cyberattacks at the network-level and the host …
FED-IIoT: A robust federated malware detection architecture in industrial IoT
The sheer volume of industrial Internet of Things (IIoT) malware is one of the most serious
security threats in today's interconnected world, with new types of advanced persistent …
security threats in today's interconnected world, with new types of advanced persistent …
A review on cyber crimes on the internet of things
Abstract Internet of Things (IoT) devices are rapidly becoming universal. The success of IoT
can't be ignored in today's scenario; along with its attacks and threats on IoT devices and …
can't be ignored in today's scenario; along with its attacks and threats on IoT devices and …
A distributed ensemble design based intrusion detection system using fog computing to protect the internet of things networks
With the development of internet of things (IoT), capabilities of computing, networking
infrastructure, storage of data and management have come very close to the edge of …
infrastructure, storage of data and management have come very close to the edge of …
Deep graph neural network-based spammer detection under the perspective of heterogeneous cyberspace
Due to the severe threat to cyberspace security, detection of online spammers has been a
universal concern of academia. Nowadays, prevailing literature of this field almost leveraged …
universal concern of academia. Nowadays, prevailing literature of this field almost leveraged …
A hybrid deep learning image-based analysis for effective malware detection
The explosive growth of Internet and the recent increasing trends in automation using
intelligent applications have provided a veritable playground for malicious software …
intelligent applications have provided a veritable playground for malicious software …
Security by design for big data frameworks over cloud computing
Cloud deployment architectures have become a preferable computation model of Big Data
(BD) operations. Their scalability, flexibility, and cost-effectiveness motivated this trend. In a …
(BD) operations. Their scalability, flexibility, and cost-effectiveness motivated this trend. In a …
Intrusion detection in internet of things using supervised machine learning based on application and transport layer features using UNSW-NB15 data-set
Abstract Internet of Things (IoT) devices are well-connected; they generate and consume
data which involves transmission of data back and forth among various devices. Ensuring …
data which involves transmission of data back and forth among various devices. Ensuring …
Differentially private data fusion and deep learning framework for cyber–physical–social systems: State-of-the-art and perspectives
The modern technological advancement influences the growth of the cyber–physical system
and cyber–social system to a more advanced computing system cyber–physical–social …
and cyber–social system to a more advanced computing system cyber–physical–social …