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Android malware has emerged as a severe danger to national security because of the widespread usage of smartphones and the inherent risk it provides to its users. Due to code obfuscation, antivirus products and other typical detection algorithms struggle ...

(Mis-)information thrives on social media, so it has become increasingly important for users to tell real from misleading content because erroneously following misinformation can cause serious consequences. In this study, we investigated users’ ...

Image segmentation is an essential part of almost any image processing methodology and it play a critical role in protecting the region of interest on any substrate image before its actual analysis is prescribed. In fact, the accuracy of any processing ...

The author analyzes the problem of detecting the adaptive steganography by the J-UNIWARD method by steganoanalytical systems based on machine learning. As determined by the comparative analysis of the accuracy, the statistical models of ...

Intrusion detection remains one of the critical research issues in network security. Many machine learning algorithms have been proposed to develop intrusion detection systems, which can categorize network traffic into normal and anomalous classes. The ...

Image forensic is the important research area which deals to verify the authenticity of the digital image. Copy-move forgery is common type of forgery used to modify the image. This paper proposes passive blind forensic copy-move forgery detection ...

Internet of Things (IoT) involve large volumes of data generated from the interactions between devices and people, and security is a main alarm in IoT. Most of the anomaly detection techniques in IoT use supervised machine learning technique which involve ...

Distributed Denial of Services (DDoS) has become the most intrusive security threat on the Internet. Flash crowd attack is the most challenging problem among the attacks which targeting the web server during the Flash Events (FEs). It mimics the ...

Multistage detection has inspired a heated debate due to its capacity to take full advantage of each detector. Motivated by this, an investigation into multistage spectrum sensing is conducted and a two‐stage spectrum detector is proposed based on energy ...

Cognitive radio (CR) is a rapidly growing technology that can be employed to effectively utilise the radio spectrum. The detection accuracy of the CR user is compromised when a network is under degrading conditions like fading and shadowing effects. ...

Smart grid is an alternative solution of the conventional power grid which harnesses the power of the information technology to save the energy and meet todays' environment requirements. Due to the inherent vulnerabilities in the information technology, ...

Salient object detection can identify the most distinctive objects in a scene. In this study, a novel graph‐based approach is proposed to detect a salient object via reliable boundary seeds and saliency refinement. A natural image is firstly mapped to a ...

This study investigates users' coping responses in the process of phishing email detection. Three common responses are identified based on the coping literature: task-focused coping, emotion-focused coping i.e., worry and self-criticism, and avoidance ...

This study proposes a distributed outlier detection algorithm based on credibility feedback in wireless sensor networks. The algorithm consists of three stages, which are evaluating the initial credibility of sensor nodes, evaluating the final credibility ...

This tutorial will present an overview of program anomaly detection, which analyzes normal program behaviors and discovers aberrant executions caused by attacks, misconfigurations, program bugs, and unusual usage patterns. It was first introduced as an ...

As the detection methods of covert channels can provide a better way to detect the existence of advanced persistent threat, it has become a hot research topic in the field of network security. Although the existing methods can achieve feasible ...

In wireless local area network WLAN, accurately detecting the distributed denial of service DDoS attack is challenging. Hence in this paper, a fuzzy-based DDoS attacks mitigation technique is proposed to reduce the false positives. Initially the traffic ...

In this paper, the enhanced histogram features are proposed for detecting perturbed quantization (PQ) steganography applied to double-compression JPEG image. Firstly, the principle of PQ steganography is analyzed and the special positions for feature ...

Bayesian network (BN) classifiers with powerful reasoning capabilities have been increasingly utilized to detect intrusion with reasonable accuracy and efficiency. However, existing BN classifiers for intrusion detection suffer two problems. First, such ...

We investigate the problem of online detection of complex activities (such as cooking, lunch, work at desk), i.e., recognizing them while the activities are being performed using parts of the sensor data. In contrast to prior work, where complex ...