In the wake of many high profile data breaches, from government institutions to retailers, there is an evolving environment in the data management world. An environment that requires more active security policy to be established in order to reduce the amount of time that sensitive data is unknowingly exposed to malicious sources. Having strictly preventive security policy although at times effective opens the door to a flood of destructive malware as relaxed policy in regards to monitoring of data movement can allow compromised systems to be unpatched for indeterminate periods of time, unnecessarily exposing data systems.
Active Monitoring Systems
Although preventative maintenance is an essential part of security, actively monitoring data systems can result in quicker detection of penetration by malicious software, these breaches may go unnoticed for long periods of time if only preventative security measures are taken in the data center. It’s a given that systems should should be monitored on a daily basis, but dealing with a large flood of data and knowing how to prioritize it is near impossible for a large data center. Especially in the face of remote access by authorized staff from various locations, of whom may unknowingly bring security risks into the operational environment. With such big data coming in so quickly from a variety of secure and insecure networks the only answer to monitoring such a large scale system of data transfer and accompanying network activity is software based analytics. Big data can be sorted and actively monitored in a meaningful manner through the analytics derived from computational algorithms, algorithms of which can sort malicious activity based on potential risk to reduce false positives or non factor threats that will be blocked by preventative security systems, giving security personnel a more focused view of malicious activity in the network. Any and all detection can be stored and logged for future reference to increase efficiency of automated detection systems. Software based analysis and monitoring of network activity can help identify issues as they stream in, with sorting of priority and potential risk security personnel are able to catch threats immedietly. This reduces liability as security breaches are detected on the fly, reducing exposure of sensitive data and the time of which malicious software has access to said data systems.