As the number and cleverness of cyber-attacks keep increasing rapidly, it's more important
than ever to have good ways to detect and prevent them. Recognizing cyber threats quickly …

Cybersecurity is crucial in today's interconnected world, as digital technologies are
increasingly used in various sectors. The risk of cyberattacks targeting financial, military, and …

To address the challenges of weak model generalization and limited model capacity
adaptation in traditional malware detection methods, this article presents a novel malware …

The proliferation of IoT services has spurred a surge in network attacks, heightening
cybersecurity concerns. Essential to network defense, intrusion detection and prevention …

Despite significant advancements in Android malware detection, current approaches face
notable challenges, particularly in handling obfuscation techniques, achieving high …

Highlights: What are the main findings? Development of a novel lightweight machine
learning classifier for anomaly detection in smart cars. Comparison with the baseline …

The escalating prevalence of malware necessitates a proactive and vigilant approach to its
detection and mitigation. The ramifications of a successful malware attack on cloud services …

Abstract Machine learning has been successfully applied in develo** malware detection
systems, with a primary focus on accuracy, and increasing attention to reducing …

The Passive Optical Network (PON) has been evolving continuously in terms of architecture
and capacity to keep up with the demand for high-speed Internet access in the access …

In the realm of cybersecurity, the detection and analysis of obfuscated malware remain a
critical challenge, especially in the context of memory dumps. This research paper presents …