HICSS Symposium on Cybersecurity Big Data Analytics
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While there has been a great deal of discussion around “Big Data” lately, including how it can revolutionize cybersecurity, actual research is limited. This Symposium seeks to let practitioners and academics present emerging cybersecurity big data research and challenges in domains such as data collection and processing, data analytics, data handling, machine learning, and visualization; as well as to present and discuss potential cybersecurity big data research topics and methodologies of interest to the cybersecurity community.Topics related to data include areas such as logs, network traffic data (PCAP), system process data, system memory data, and even complete virtualized system snapshots. Analytics topics include, but are not limited to, methodologies, techniques, and impacts of real-time processing for incident detection and/or prevention, data review for incident and anomaly detection, post incident response analytics, and IT audit related analytics. Data handling covers research and case studies into process and procedures. Visualization will look at all aspects of research related to visualizing the data, such as temporal, geographical, threat, actor, event based, and other data types. Automated machine covers all forms that leverage or require Big Data for support, including defensive measures and potential threat applications.