Big data analytics:Computational intelligence techniques and application areas

Big Data has significant impact in developing functional smart cities and supporting modern societies. In this paper, we investigate the importance of Big Data in modern life and economy, and discuss challenges arising from Big Data utilization. Different computational intelligence techniques have been considered as tools for Big Data analytics. We also explore the powerful combination of Big Data and Computational Intelligence (CI) and identify a number of areas, where novel applications in real world smart city problems can be developed by utilizing these powerful tools and techniques. We present a case study for intelligent transportation in the context of a smart city, and a novel data modelling methodology based on a biologically inspired universal generative modelling approach called Hierarchical Spatial-Temporal State Machine (HSTSM). We further discuss various implications of policy, protection, valuation and commercialization related to Big Data, its applications and deployment

Determining Training Needs for Cloud Infrastructure Investigations using I-STRIDE

As more businesses and users adopt cloud computing services, security vulnerabilities will be increasingly found and exploited. There are many technological and political challenges where investigation of potentially criminal incidents in the cloud are concerned. Security experts, however, must still be able to acquire and analyze data in a methodical, rigorous and forensically sound manner. This work applies the STRIDE asset-based risk assessment method to cloud computing infrastructure for the purpose of identifying and assessing an organization's ability to respond to and investigate breaches in cloud computing environments. An extension to the STRIDE risk assessment model is proposed to help organizations quickly respond to incidents while ensuring acquisition and integrity of the largest amount of digital evidence possible. Further, the proposed model allows organizations to assess the needs and capacity of their incident responders before an incident occurs.Comment: 13 pages, 3 figures, 3 tables, 5th International Conference on Digital Forensics and Cyber Crime; Digital Forensics and Cyber Crime, pp. 223-236, 201