TRACKS - TOPICS

	GENERAL TRACK 1: INTELLIGENT DATA MINING FOR NETWORK SECURITY
	GENERAL TRACK 2: LEARNING METHODS FOR TEXT MINING IN INTELLIGENCE AND SECURITY
	GENERAL TRACK 3: SOFTCOMPUTING METHODS IN CRITICAL INFRASTRUCTURE PROTECTION
	FOCUS TRACK 1: INTELLIGENT SECURE METHODS IN RAILWAY OPERATION
	FOCUS TRACK 2: COMPUTATIONAL INTELLIGENCE IN BIOMETRICS FOR SECURITY
	TOPICS

Due to the vastity of the subject, CISIS arranges the scientific landscape according to basic tracks.

GENERAL TRACK 1:
INTELLIGENT DATA MINING FOR NETWORK SECURITY

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In massively networked systems, the huge amount of data provided by network-monitoring systems and the variable nature of cyber-attacks poses a major problem of Data Mining and Novelty Detection. Tools such as intelligent Intrusion Detection Systems, Defense Deployment, Log Correlators, Active Defense Methods etc. require the ability to represent, analyze, understand, and learn patterns from large data sets adaptively and in real time. Computational Intelligence can play a crucial role in providing modelling and learning methods for classification, novelty detection, and reaction planning.

GENERAL TRACK 2:
LEARNING METHODS FOR TEXT MINING IN INTELLIGENCE AND SECURITY

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Natural language processing is crucial in security tools that involve information extraction and knowledge acquistion from large corpora of documents, mainly for intelligence and law-enforcement purposes. Examining and correlating both open and private sources calls for a combined action of mining abilities and conceptual information handling, while machine-learning paradigms might enable text-mining systems to update representation, context, ontologies and reasoning tools at run-time.

GENERAL TRACK 3:
SOFTCOMPUTING METHODS IN CRITICAL INFRASTRUCTURE PROTECTION

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The pervasive nature of computer networked system is nowadays at the core of large service infrastructures covering basic, commercial and social services in critical areas such as energy, transportation, politics, law-enforcement, entertainment, etc. Security is a of paramount importance and adaptiveness to changing operational conditions is crucial to ensure prompt response and service continuity. Machine learning and Computational Intelligence methods can support the required flexibility by bringing in some abilities: 1) to learn continuously from experience, 2) to model the monitored environment dynamical, 3) to detect and infer threats or security breaches by using intelligent reasoning, 4) to plan and assit in deploying countermeasures to ensure the security of the controlled systems.

FOCUS TRACK 1:
INTELLIGENT SECURE METHODS IN RAILWAY OPERATION

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The wide-spread availability of high-performance, low-cost interconnection facilities recently pervaded a complex, critical domain such as railway operation and management. Novel and powerful architectures support traffic centralized and/or distributed control system, and critical issues are also represented by high-speed stretches. The basic requirement for interoparibility in global railway transportation calls for intelligent methods for interfacing with, adapting to, and properly interacting with complex railway systems. Security nowadays rivals safety as a crucial requirement for large network operation, and ICT infrastuctures with learning abilities will play a crucial role in the effective support of continuous operation and competitive commercial service.

FOCUS TRACK 2:
COMPUTATIONAL INTELLIGENCE IN BIOMETRICS FOR SECURITY

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National, personal, and information security receives increasing attention for the social and economical implications. Human verification, identification, recognition, and surveillance are complex, critical tasks for many applications in which security and privacy play an important role, e.g., monitoring and control of physical access to critical locations, information and software applications in information systems, e-commerce systems, and e-government systems. Similarly, human behavior analysis is important to detect dangerous patterns for environmental security or critical activities for data integrity and protection. Biometrics has been proved very effective to support these applications by analyzing and measuring human physical traits. Computational intelligence (including neural networks, fuzzy systems, evolutionary computation, multi-agent technologies, and machine learning) provides adaptable, evolvable and flexible technologies to implement advanced biometrics approaches.

TOPICS

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The Workshop topics can be identified by, but are not limited to, the following subjects:

• Machine Learning for Data Mining
• Data Mining Methods for Security
• Agent and Multi-Agent Systems
• Hybrid Systems
• Unsupervised Learning
• Classification Methods
• Novelty Detection

• Intrusion Detection Systems
• Log Correlation Methods
• Adaptive Defense of Network Infrastucture
• Adaptive Reasoning
• Information Forensics

• Document Classification and Processing
• Ontologies and Conceptual Information Processing
• Semantic Information Representation
• Natural Language Acquisition
• Web Semantics in Intelligence and Law-Enforcement

• Industrial and Commercial Applications of Intelligent Methods for Security
• Intelligent Control and Monitoring of Critical Systems
• Dynamic Adaptive Railway Operation
• Centralized Control Systems
• Adaptive Planning for Strategic Reasoning

• Intelligent Methods in Energy and Transportation
• Planning and Automated Reasoning in Large System Control

• Biometric Identification and Recognition
• Biometric Surveillance
• Biometric Access Control
• Extraction of Biometric Features (fingerprint, iris, face, voice, palm, gait)