Add to ORKGIt is not easy to extract essential features from a sequence of security data. It requires smart security experts to dig valuable information from enormous data. We propose a novel neural network structure, named filterNN, to extract essential features from text-based sequential data obtained from the dynamic analysis of malware. The filterNN contains a structure that can explicitly point out which part of the sequence (i.e., subsequence) is more important than the others for the latter classification task. Thus, security experts can quickly identify the characteristics of malware samples in a malware family and further identify the family behavior among them. The proposed filterNN is a framework that can adapt different NN classifiers (e.g...
Malware detection and classification are attracting more research nowadays due to the increasing num...
Smartphone apps are closely integrated with our daily lives, and mobile malware has brought about se...
With the ever-increasing threat of malware attacks, building an effective malware classifier to dete...
In the field of adversarial attacks, the generative adversarial network (GAN) has shown better perfo...
Anti-malware vendors receive daily thousands of potentially malicious binaries to analyse and catego...
The increase in number and variety of malware samples amplifies the need for improvement in automati...
A tremendous number of malicious programs have posed severe and evolving security threats to operati...
Malware is one of the most frequent cyberattacks, with its prevalence growing daily across the netwo...
Many different machine learning and deep learning techniques have been successfully employed for ma...
Currently, malware shows an explosive growth trend. Demand for classifying malware is also increasin...
Malware detection plays a crucial role in computer security. Recent researches mainly use machine le...
Performing large-scale malware classification is increasingly becoming a critical step in malware an...
Recently, people rely on mobile devices to conduct their daily fundamental activities. Simultaneousl...
Dynamic malware analysis executes the program in an isolated environment and monitors its run-time b...
Recently, people rely on mobile devices to conduct their daily fundamental activities. Simultaneousl...
Malware detection and classification are attracting more research nowadays due to the increasing num...
Smartphone apps are closely integrated with our daily lives, and mobile malware has brought about se...
With the ever-increasing threat of malware attacks, building an effective malware classifier to dete...
In the field of adversarial attacks, the generative adversarial network (GAN) has shown better perfo...
Anti-malware vendors receive daily thousands of potentially malicious binaries to analyse and catego...
The increase in number and variety of malware samples amplifies the need for improvement in automati...
A tremendous number of malicious programs have posed severe and evolving security threats to operati...
Malware is one of the most frequent cyberattacks, with its prevalence growing daily across the netwo...
Many different machine learning and deep learning techniques have been successfully employed for ma...
Currently, malware shows an explosive growth trend. Demand for classifying malware is also increasin...
Malware detection plays a crucial role in computer security. Recent researches mainly use machine le...
Performing large-scale malware classification is increasingly becoming a critical step in malware an...
Recently, people rely on mobile devices to conduct their daily fundamental activities. Simultaneousl...
Dynamic malware analysis executes the program in an isolated environment and monitors its run-time b...
Recently, people rely on mobile devices to conduct their daily fundamental activities. Simultaneousl...
Malware detection and classification are attracting more research nowadays due to the increasing num...
Smartphone apps are closely integrated with our daily lives, and mobile malware has brought about se...
With the ever-increasing threat of malware attacks, building an effective malware classifier to dete...