Abhay V Kshirsagar

In the case of cybersecurity, fire must be fought with fire, or in this case, with automation. Companies must seek out and enforce preventative solutions that use automated methods of prevention. One such technology that preventatively protects companies and enterprises of all sizes is the Content Disarm and Reconstruction technology (CDR). CDR technology processes incoming files, analyzes and breaks down the content structure, then rebuilds a duplicate file with no loss of functionality – all in real-time. Through this process, end-users are able to receive any file, free of both known and unknown threats because CDR removes any content that is not approved by the organization. Machine learning is still in its early phases and phishing will only become more insidious as the technology matures and the process becomes even more automated.

To add to your post Yu Ming, these days big data techniques used to mine databases are being adopted by the military to glean more information from many different types of data it collects—from drones, automated cybersecurity systems, terrorist databases and many other sources which is helpful in performing military operations and hence is becoming a useful technology.

I like your article Yu Ming. In light of the fact that attacks are increasingly evolved and sophisticated, the reality is there is no longer a one size fits all approach to security. To defend against the modern cyber threat, organizations need a multiple-faced approach, and not to fall into the trap of implementing one measure. Those automated antivirus software or controls can easily be bypassed, which means that we need to think about defence-in-depth and monitoring-in-depth strategies to detect the undetectable.

Yu Ming, when it comes to fast data, it is important to capture the value in it properly. In fact, the best way to capture the value of incoming data is to react to it the instant it arrives. If businesses are processing incoming data in batches, they’ve already lost time and, thus, the value of that data. To process data arriving at tens of thousands to millions of events per second, they will need two technologies: First, a streaming system capable of delivering events as fast as they come in; and second, a data store capable of processing each item as fast as it arrives.