A5063541838- Anomaly Detection Techniques and Applications
- Network Security and Intrusion Detection
- Infrastructure Resilience and Vulnerability Analysis
- Evacuation and Crowd Dynamics
- Complex Network Analysis Techniques
- Advanced Malware Detection Techniques
- Cybercrime and Law Enforcement Studies
The rapid advancements in large language models (LLMs) have opened new avenues across various fields, including cybersecurity, which faces an ever-evolving threat landscape and need for innovative technologies. Despite initial explorations into the application of LLMs there is a lack comprehensive overview this research area. This paper bridge gap by providing systematic literature review, encompassing analysis over 180 works, spanning 25 more than 10 downstream scenarios. Our addresses...
The UAV (Unmanned Aerial Vehicle) has the advantages of mobility and flexibility, rapid concealment holistic vision. Coordinating with intelligent efficient precise dispatching “decision module” command centre, UAVs can meet public safety needs significant events. marathon is an open, long-distance, gathering sporting event, so on-site security hard to guarantee. To study application in risk early warning, we examine Hangzhou Marathon as example, analysing potential risks a scenarios by...
With the development of Internet technology, open networks and standardized protocols bring more potential security threats. How to propose effective identification prevention methods for some typical malicious program attacks is an important issue be considered active defense. However, most do not analyze risk in attack behavior, so this paper proposes a model based on dependency analysis. The takes character text as input, behavior string subjected word splitting embedding operations....
For attacks on systems during operation, the high false positive rate of traditional machine learning models is no longer able to detect cyber with accuracy. In this paper, we propose a behavior detection model based sequence and graph contrastive learning. The uses instruction strings from UNIX system records as input potential internal attacks. To better learn information, use two parallel algorithms Long Short-Term Memory Network (LSTM) Graph Attention (GAT), encode their complex...