Leverage big data analytics to improve enterprise security
Security concerns have never been more top of mind for business leaders, consumers and governments. The proliferation of the digital age impacts all aspects of life and is radically changing the way we think about security, in both the cyber and the physical world.
For example, in the largest bank robbery in history, hackers stole USD$45 million without entering a bank, writing a threatening note or using physical force. Instead, a complex web of networks and cyber know-how were the weapons of choice. It took law enforcement officials from 17 different countries to arrest seven individuals.
Law enforcement agencies must be able to respond to threats by leveraging timely information for a set of predefined behaviors, such as people, vehicles or objects crossing a tripwire or individuals accessing sensitive content inside a corporate network. Law enforcement must be able to identify and correlate incidents, social media analytics, video surveillance, geospatial records, sensor data — or any other source of data in motion — to proactively identify and monitor potential incidents.
This infographic helps visualize and understand the security challenges and how to best use big data analytics to tackle them. The infographic draws on the analogy of a city. Gone are the days when you could build a wall or set up a perimeter around the city. People, vehicles, planes, cellular communications, Internet traffic and more move in and out of the “city proper.” They all introduce risk, use different resources and have different security requirements. To properly protect a city (or your organization) a full analysis of happenings both inside and out is required. It is essential to not only react to security incidents but also to predict, prevent and take real-time action.
Fortunately, there is no shortage of data available for this type of big data analytics. More data, in more formats, is speeding across our enterprises. The challenge is to harness it before attackers make their move or identify vulnerabilities. As you attempt to counter physical and cyber attacks consider how to “establish a baseline”; essentially, model normal behavior of applications, users and assets so that anomalies can be early indicators of attack. Security intelligence with big data analytics helps organizations take advantage of the large volumes and wide variety of data speeding across the enterprise in order to anticipate and predict threats and act on predictive analytics. It allows organizations to analyze constantly changing data in motion and perform sophisticated analytics on captured data.
If you answer yes to any of the following questions, you need big data security analytics.
- Do you want to analyze and correlate broader data sets to prevent cyber attacks, physical threats, fraudulent claims or account takeovers?
- Do you need to enrich your security solution with email, social and other unstructured data to improve cyber threat detection and remediation?
- Do you need to better detect and monitor criminal and terrorist activity by correlating a broader variety of sources to uncover associations or patterns?
- Do you want to enhance your security and surveillance systems with real-time data from video, acoustic, thermal or other devices/sensors?