The software-defined data center (SDDC) requires a new breed of security tools that not only handle the velocity of data being generated within a secure hybrid cloud but also handle the volume and variety of data. In fact, this new breed of security tools uses big data backends to manage the data being received, though it asks different questions of the data than normal for the products: security questions. The new breed of security tools either started as some form of performance management tool or employs performance management techniques to provide the data to to be queried.
Articles Tagged with Big Data
At the recent Misti Big Data Security conference many forms of securing big data were discussed from encrypting the entire big data pool to just encrypting the critical bits of data within the pool. On several of the talks there was general discussion on securing Hadoop as well as access to the pool of data. These security measures include RBAC, encryption of data in motion between hadoop nodes as well as tokenization or encryption on ingest of data. What was missing was greater control of who can access specific data once that data was in the pool. How could role based access controls by datum be put into effect? Is such protection too expensive given the time critical nature of analytics or are there other ways to implement datum security?
A big part of the secure hybrid cloud is the need for multi-tenant analytics to determine when security events and compliance issues happen. However, analytics cover many different aspects of security within the hybrid cloud, from being a control point for compliance to handling vulnerability scanning. What are the requirements for multi-tenant analytics?
On the May 30th Virtualization Security Podcast, Michael Webster (@vcdxnz001) joined us Live from HP Discover to discuss what we found at the show and other similar tools around the industry. The big data security news was a loosely coupled product named HAVEn which is derived from several products: Hadoop, Autonomy, Vertica, Enterprise Security, and any number of Apps. HAVEn’s main goal is to provide a platform on top of which HP and others can produce big data applications using Autonomy for unstructured data, Vertica for structured data, Enterprise Security for data governance and hadoop. HP has already built several security tools upon HAVEn, and I expect more. Even so, HAVEn is not the only tools to provide this functionality, but it may be the only one to include data governance in from the beginning.
At EMCworld 2013, one of the big stories was Pivotal and it’s importance to the EMC2 family and the future of computing. Pivotal is geared to provide the next generation of computing. According to EMC2 have gone past the Client-Server style to a scale-out, scale-up, big data, fast data Internet of Things form of computing. The real question however, is how can we move traditional business critical applications to this new model, or should we? Is there migration path one can take?
For years we have had an expectation of privacy while using our computers, tablets, phones, email, etc. However, with the advent of big data analysis and everything being on the internet, the internet of things, there is no longer the veil that makes up an Expectation of Privacy. Big Data has allowed us to be tracked in new ways and as we add more devices onto the internet, more of our habits will be tracked: Such as location of boats, planes, your mobile device. Purchasing habits, your location within a store, or theme park. Perhaps even your usage of your toaster, house doors, your refrigerator, etc.
Where do we draw the line? Is there such a thing as personal privacy anymore or do we assume we are being tracked everywhere? When does our social media life end and privacy begin? What is considered to invasive?