Liu et al., 2018 - Google Patents
A mechanism for recognizing and suppressing the emergent behavior of UAV swarmLiu et al., 2018
View PDF- Document ID
- 13639761487201340378
- Author
- Liu Q
- He M
- Xu D
- Ding N
- Wang Y
- Publication year
- Publication venue
- Mathematical Problems in Engineering
External Links
Snippet
Similar to social animals in nature, UAV swarm is also a complex system that can produce emergent behavior. The emergent behavior of UAV swarm in specific airspace is undoubtedly the act that the defense side does not expect to see; therefore, recognition and …
- 230000001629 suppression 0 title abstract description 41
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computer systems based on biological models
- G06N3/02—Computer systems based on biological models using neural network models
- G06N3/04—Architectures, e.g. interconnection topology
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N99/00—Subject matter not provided for in other groups of this subclass
- G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/14—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
- H04L63/1408—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic by monitoring network traffic
- H04L63/1425—Traffic logging, e.g. anomaly detection
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/14—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
- H04L63/1408—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic by monitoring network traffic
- H04L63/1416—Event detection, e.g. attack signature detection
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N5/00—Computer systems utilising knowledge based models
- G06N5/04—Inference methods or devices
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N5/00—Computer systems utilising knowledge based models
- G06N5/02—Knowledge representation
- G06N5/022—Knowledge engineering, knowledge acquisition
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Liu et al. | A mechanism for recognizing and suppressing the emergent behavior of UAV swarm | |
Wang et al. | A bat algorithm with mutation for UCAV path planning | |
Théron et al. | When autonomous intelligent goodware will fight autonomous intelligent malware: A possible future of cyber defense | |
Kim et al. | Optimal task assignment for UAV swarm operations in hostile environments | |
Pasdar et al. | Cybersecurity solutions and techniques for internet of things integration in combat systems | |
Li et al. | Optimization of air defense system deployment against reconnaissance drone swarms | |
Qingwen et al. | Cooperative jamming resource allocation of UAV swarm based on multi-objective DPSO | |
Huang et al. | Exposing Spoofing Attack on Flocking‐Based Unmanned Aerial Vehicle Cluster: A Threat to Swarm Intelligence | |
Yan et al. | [Retracted] Optimization of UAV Cooperative Path Planning Mathematical Model Based on Personalized Multigroup Sparrow Search Algorithm in Complex Environment | |
Christensen et al. | Principles for small-unit sUAS tactical deployment from a combat-simulating agent-based model analysis | |
Jadav et al. | Blockchain-based secure and intelligent data dissemination framework for uavs in battlefield applications | |
Simonjan et al. | Reinforcement learning-based countermeasures against attacking uav swarms | |
Wang et al. | Tent Chaotic Map and Population Classification Evolution Strategy‐Based Dragonfly Algorithm for Global Optimization | |
Sapaty | Distributed technology for global dominance | |
Blouin | Is your world complex? An overview of complexity science and its potential for military applications | |
McLemore et al. | A model for geographically distributed combat interactions of swarming naval and air forces | |
Ye et al. | Cognitive cooperative-jamming decision method based on bee colony algorithm | |
Mallick | Artificial Intelligence in Armed Forces: An Analysis | |
Simonjan et al. | Inducing defenders to mislead an attacking uav swarm | |
Zhou et al. | Multi-UAVs path planning for data harvesting in adversarial scenarios | |
Gonzalez et al. | Adaptive cyberdefense with deception: A human–ai cognitive approach | |
Jiang et al. | Anti-drone policy learning based on self-attention multi-agent deterministic policy gradient | |
Altinoz | Evolving model for synchronous weapon target assignment problem | |
Behzadan et al. | Models and framework for adversarial attacks on complex adaptive systems | |
Jia et al. | An operational effectiveness evaluation method of the swarming UAVs air combat system |