- Introduction to Big Data Analytics for Cyber Security
- NetFlow and Other Telemetry Sources for Big Data Analytics for Cyber Security
- Understanding Big Data Scalability: Big Data Analytics in the Internet of Everything
Understanding Big Data Scalability: Big Data Analytics in the Internet of Everything
Evidently, the challenges of big data analytics include the following:
- Data capture capabilities
- Data management (curation)
- Adequate and real-time search
- Sharing and transferring of information
- Deep-dive and automated analysis
- Adequate visualizations
Big data has become a hot topic due to the overabundance of data sources inundating today’s data stores as applications proliferate. These challenges will become even bigger as the world moves to the Internet of Everything (IoE), a term coined by Cisco. IoE is based on the foundation of the Internet of Things (IoT) by adding network intelligence that allows convergence, orchestration, and visibility across previously disparate systems. IoT is the networked connection of physical objects. IoT is one of many technology transitions that enable the IoE.
The goal is to make networked connections more relevant by turning information into actions that create new capabilities. The IoE consists of many technology transitions, including the IoT. The key concepts are as follows:
- Machine-to-machine connections: Including things such as IoT sensors, remote monitoring, industrial control systems, and so on
- People-to-people connections: Including collaboration technologies such as TelePresence, WebEx, and so on
- Machine-to-people connections: Including traditional and new applications
Big data analytics for cyber security in an IoE world will require substantial engineering to address the huge data sets. Scalability will be a huge challenge. In addition, the endless variety of IoT applications presents a security operational challenge. We are starting to experience these challenges nowadays. For instance, in a factory floor, embedded programmable logic controllers (PLCs) that operate manufacturing systems and robots can be a huge target for bad actors. Do we know all the potential true indicators of compromise so that we can perform deep-dive analysis and perform good incident response?
The need to combine threat intelligence and big data analytics will be paramount in this ever-changing world.