API calls are programming interfaces used by applications. When it is difficult for an analyst to perform a direct reverse analysis of a program, the API provides an important basis for analyzing the behavior and functionality of the program. API add...
Malware detection is of great significance for maintaining the security of information systems. Malware obfuscation techniques and malware variants are increasingly emerging, but their samples and API (application programming interface) sequences are...
Malicious software (malware), in various forms and variants, continues to pose significant threats to user information security. Researchers have identified the effectiveness of utilizing API call sequences to identify malware. However, the evasion t...
In the malware detection process, obfuscated malicious codes cannot be efficiently and accurately detected solely in the dynamic or static feature space. Aiming at this problem, an integrative feature extraction algorithm based on simhash was propose...
This study presents a novel Similarity-Based Hybrid API Malware Detection Model (HAPI-MDM) aiming to enhance the accuracy of malware detection by leveraging the combined strengths of static and dynamic analysis of API calls. Faced with the pervasive...
Malware is one of the most significant threats in today’s computing world since the number of websites distributing malware is increasing at a rapid rate. Malware analysis and prevention methods are increasingly becoming necessary for computer system...
Recently, Android malicious code has increased dramatically and the technology of reinforcement is increasingly powerful. Due to the development of code obfuscation and polymorphic deformation technology, the current Android malicious code static det...
Data-driven public security networking and computer systems are always under threat from malicious codes known as malware; therefore, a large amount of research and development is taking place to find effective countermeasures. These countermeasures...
Signature-based malware detection is undermined by obfuscation and packing, motivating dynamic analysis of Application Programming Interface (API) call sequences. Existing image-based classifiers reach high accuracy but rarely explain why a sample be...
Behavioral malware analysis is a powerful technique used against zero-day and obfuscated malware. Additionally referred to as dynamic malware analysis, this approach employs various methods to achieve enhanced detection. One such method involves usin...
Despite recent remarkable advances in binary code analysis, malware developers still use complex anti-reversing techniques that make analysis difficult. Packers are used to protect malware, which are (commercial) tools that contain diverse anti-rever...
Android malware detection is increasingly important for mobile and edge security because malicious applications may compromise user privacy, device reliability, and sensitive service transactions. However, single-view static detection methods often p...
The escalating sophistication of ransomware requires defensive strategies that are both proactive against zero-day attacks and operationally efficient. Existing solutions often force a trade-off—sacrificing low false-positive rates for broad de...