The exponential proliferation of malware requires robust detection mechanisms for the security of global enterprises and national infrastructures. Conventional malware classification methods primarily depend on extensive datasets of ...

• We propose a novel deep learning model for classifying malicious software.
• It ...

Malware is a significant threat to the security of computer systems and networks worldwide, and its sophistication and diversity continue to increase over time. One of the key challenges in malware detection and classification is the ...

Efficient management of residential power consumption, particularly during peak demand, poses significant challenges. Deep learning models excel in predicting electricity demand but lack of interpretability due to the interdependent nature of ...

• We propose a new graph convolution network with subgraph embedding.
• It extracts ...

An aromatic hydrocarbon refers to an organic material having a carbon ring such as benzene and a functional group in the carbon ring. As the industry develops, natural pollution becomes harsh, new compounds emerge, and the exposure to ...

With the rapid increase in the amount of video data, efficient object recognition is mandatory for a system capable of automatically performing question and answering. In particular, real-world video environments with numerous types of objects and ...

With the advent of sophisticated deep learning models, various methods for classifying malware from structural features of source codes have been devised. Nevertheless, recent advanced detection-avoidance techniques actively imitate structural ...

Considering the fatality of malware attacks, the data-driven approach using massive malware observations has been verified. Deep learning-based approaches to learn the unified features by exploiting the local and sequential nature of control flow ...

Diagnosing autism spectrum disorder (ASD) is still challenging because of its complex disorder and insufficient evidence to diagnose. A recent research in psychiatry perspective demonstrates that there are no obvious reasons for ASD. However, ...

A phishing attack is defined as a type of cybersecurity attack that uses URLs that lead to phishing sites and steals credentials and personal information. Since there is a limitation on traditional deep learning to detect phishing URLs from only ...$$

In spite of various deep learning models devised, it is still a challenging task to classify in-vehicle noise because of the reverberation and the variance in the low-frequency band generated from the narrow interior space. Considering the ...

For defect inspection using computer vision, deep learning models have been introduced to improve the conventional rule-based pattern analysis. A lot of data is a prerequisite to the success of them, but the on-the-spot industrial field suffers ...

• This paper proposes a new hybrid method called CN-LCS of deep learning and learning classifier system.

Role-based access control (RBAC) in databases provides a valuable level of abstraction to promote security administration at the business enterprise level. With the capacity for adaptation and learning, machine learning algorithms are ...

In recent years, convolutional neural network has become a solution to many image processing problems due to high performance. It is particularly useful for applications in automated optical inspection systems related to industrial applications. ...

A database Intrusion Detection System (IDS) based on Role-based Access Control (RBAC) mechanism that has capability of learning and adaptation learns SQL transaction patterns represented by roles to detect insider attacks. In this paper, we ...

The explosive price volatility from the end of 2017 to January 2018 shows that bitcoin is a high risk asset. The deep reinforcement algorithm is straightforward idea for directly outputs the market management actions to achieve higher profit ...

• This paper proposes a transferred GAN based on a deep autoencoder for malware detection.

Detecting malicious software (malware) is important for computer security. Among the different types of malware, zero-day malware is problematic because it cannot be removed by antivirus systems. Existing malware detection mechanisms ...

The cyberbullying is becoming a significant social issue, in proportion to the proliferation of Social Network Service (SNS). The cyberbullying commentaries can be categorized into syntactic and semantic subsets. In this paper, we propose an ...

BSR (Buzz, squeak, and rattle) noises are essential criteria for the quality of a vehicle. It is necessary to classify them to handle them appropriately. Although many studies have been conducted to classify noise, they suffered some problems: the ...

Malicious software is generated with more and more modified features of which the methods to detect malicious software use characteristics. Automatic classification of malicious software is efficient because it does not need to store all ...