CISDA 2017 - 2017 IEEE Symposium on Computational Intelligence for Security and Defense Applications (IEEE CISDA'17)
Topics/Call fo Papers
Given the current global security environment, there has been increased interest within the security and defense communities in novel techniques for solving challenging problems. The genesis of this interest lies in the fact that repeated attempts of using traditional techniques have left many important problems unsolved, and in some cases, not addressed. New problems have emerged within the broad areas of security and defense that are difficult to tackle with conventional methods, thus requiring new techniques for detecting and adapting to emerging threats.
The purpose of the symposium is to present current and ongoing efforts in computational intelligence (e.g., neural networks, fuzzy systems, evolutionary computation, swarm intelligence, and other emerging learning or optimization techniques) as applied to security and defense problems.
Topics
ADVANCED ARCHITECTURES FOR DEFENSE OPERATIONS
Multi-Sensor Data Fusion
Hard-Soft Data Fusion
Context-Aware Data Fusion
Employment of Autonomous Vehicles
Intelligence Gathering and Exploitation
Mine Detection
Situational Assessment
Impact Assessment
Process and User Refinement
Automatic Target Recognition
Mission Weapon Pairing and Assignment
Sensor Cueing and Tasking
Self-Healing Systems
MODELING AND SIMULATION OF DEFENSE OPERATIONS
Logistics Support
Mission Planning and Execution
Resource Management
Red Teaming
Computational Red Teaming
Course of Action Generation and Recommendation
Models for War Games
Risk-Aware Decision Support
Multi-Agent Based Simulation
Critical Infrastructure Protection
Strategic Planning
Counterterrorism and Counterinsurgency
Behavioral or Cognitive Learning
Human Modeling: Behavior, Emotion, Motion
SECURITY APPLICATIONS
Surveillance
Suspect Behavior Profiling
Anomaly Detection
Automated Handling of Dangerous Situations or People
Stationary or Mobile Object Detection, Recognition and Classification
Intrusion Detection Systems
Cyber-Security
Air, Maritime and Land Security
Network Security
Biometrics Security
Forensics Security
Authentication Technologies
The purpose of the symposium is to present current and ongoing efforts in computational intelligence (e.g., neural networks, fuzzy systems, evolutionary computation, swarm intelligence, and other emerging learning or optimization techniques) as applied to security and defense problems.
Topics
ADVANCED ARCHITECTURES FOR DEFENSE OPERATIONS
Multi-Sensor Data Fusion
Hard-Soft Data Fusion
Context-Aware Data Fusion
Employment of Autonomous Vehicles
Intelligence Gathering and Exploitation
Mine Detection
Situational Assessment
Impact Assessment
Process and User Refinement
Automatic Target Recognition
Mission Weapon Pairing and Assignment
Sensor Cueing and Tasking
Self-Healing Systems
MODELING AND SIMULATION OF DEFENSE OPERATIONS
Logistics Support
Mission Planning and Execution
Resource Management
Red Teaming
Computational Red Teaming
Course of Action Generation and Recommendation
Models for War Games
Risk-Aware Decision Support
Multi-Agent Based Simulation
Critical Infrastructure Protection
Strategic Planning
Counterterrorism and Counterinsurgency
Behavioral or Cognitive Learning
Human Modeling: Behavior, Emotion, Motion
SECURITY APPLICATIONS
Surveillance
Suspect Behavior Profiling
Anomaly Detection
Automated Handling of Dangerous Situations or People
Stationary or Mobile Object Detection, Recognition and Classification
Intrusion Detection Systems
Cyber-Security
Air, Maritime and Land Security
Network Security
Biometrics Security
Forensics Security
Authentication Technologies
Other CFPs
- 2017 IEEE Symposium on Computational Intelligence in Scheduling and Network Design (IEEE CISND'17)
- 2017 IEEE Symposium on Computational Intelligence in Vehicles and Transportation Systems (IEEE CIVTS' 17)
- 2017 IEEE Symposium on Computational Intelligence for Wireless Systems (IEEE CIWS' 17)
- 2017 IEEE Symposium on Deep Learning (IEEE DL'17)
- 2017 IEEE Symposium on Evolving and Autonomous Learning Systems (EALS 2017)
Last modified: 2017-07-19 16:34:47