1 | Page BDA-CS: Big Data Analytics in Critical Systems Special session at EMERGING 2016, October 9 - 13, 2016 - Venice, Italy http://www.iaria.org/conferences2016/EMERGING16.html Chair and Organizer Dr. William Hurst, Liverpool John Moores University, UK, W.Hurst@ljmu.ac.uk The technology being used in critical infrastructure systems has become more intelligent and adaptive to providing efficient services. A product, of this cumulative modern-day use of information technology, is the generation of significant volumes of data. As such, analysing behaviour within big data sets in order to detect security anomalies is becoming progressively problematic. Movements towards the use of technologies, which enable high computation power and storage, such as cloud computing, bring your own device (BYOD) and service automation has resulted in new challenges for security systems. There is a need to process data by using increasingly complex techniques to detect security breaches. Adaptive systems must be employed, and existing methods built upon, to provide well-structured defence in depth. The increase and sophistication of malware is now a concern for companies and governments. The task of developing effective protection methods remains a demanding one. There are significant weaknesses in the existing security currently in place. The use of wireless communication technologies within infrastructures facilitates interconnections and the exchange of information. However, in result, weaknesses are further aggravated. Additional access points are introduced into already complex critical infrastructure systems. In light of this, research has taken a trend towards the use of big data analytics in recent years. Techniques, such as machine learning and graph analysis, are now being investigated in order to support critical system security and process the big datasets being generated. The main challenge is that data sets are often unstructured and reside in imaging systems or ‘silos’. Real-time analysis can also result in network traffic being slowed by having to pass through a bottleneck. To-date, there have been many tools and techniques developed for open source intelligence gathering and big data analysis in forensic and security investigations. However, the analysis of massively increasing data sets, distributed within cross platforms, often goes beyond geopolitical borders. This remains a real challenge in forensic investigations. Yet, sophisticated methods, concerning big data analytics, are required to address the technical challenges facing the law enforcement community in particular. In light of the challenges discussed above, this special session invited authors to submit high-quality research papers on emerging big data analytics in critical systems (BDA-CS), covering topics which include (but are not limited to) the following:  Critical Infrastructure Data Analytics  Cyber Security  Forensics  Intelligent gathering  Big Data Analytics  Simulation  Machine Learning  Intrusion Detection  Control Systems  Cloud Computing  Data Fusion  Web Services