Social media bots (automated accounts) attacks are organized crimes that pose potential
threats to public opinion, democracy, public health, stock market and other disciplines. While …

The widespread adoption of cloud-based and public legitimate services (CPLS) has
inadvertently opened up new avenues for cyber attackers to establish covert and resilient …

In recent years, malware has emerged as a critical security threat. In addition, malware
authors continue to embed numerous anti-detection features to evade the existing malware …

Analyzing malware based on API call sequence is an effective approach as the sequence
reflects the dynamic execution behavior of malware. Recent advancements in deep learning …

Analyzing malware based on API call sequences is an effective approach, as these
sequences reflect the dynamic execution behavior of malware. Recent advancements in …

Detecting strongly connected components (SCCs) in a directed graph is crucial for
understanding the structure of graphs. Most real-world graphs have one large SCC that …

The detection and anti-detection of social botnets constitute an arms race that enables social
botnets to evolve quickly. Existing host-side detection approaches cannot easily detect every …

Abstract Harmful Twitter Bots (HTBs) are widespread and adaptable to a wide range of
social network platforms. The use of social network bots on numerous social network …

Contemporary malware makes wide use of techniques to evade popular detection
approaches. Behavior-based detection is the most powerful approach to malware detection …

Distributed execution designs challenge behavioral analyses of anti-malware solutions by
spreading seemingly benign chunks of a malicious payload to multiple processes …