The promise of large data security

Large data security is tantamount to relational data security. In fact, the difference is great. Not only is the real-time and the data quantity different, but also brings the unique difficulty the distributed architecture to have the difference. In addition, large data uses different storage modes and query patterns, and coordinates tasks across multiple network communication sessions. The techniques used by many security products to monitor, analyze log files, discover data, and assess vulnerabilities do not work effectively in large data environments. Most security products cannot be adjusted to meet large data-gathering areas or to fully understand the information they face. To address the security of large data, it is necessary to implement or fully design the architecture of most security tools. Large data is not yet in production: large data projects run outside of internal IT processes and use third party resources, so large data is considered "fudge" in some respects. But large data is actually a productive deployment that shares customer data, exchanges reports with different systems, and creates intellectual property that can determine business decisions. The existence of large data is a bit like the internet in the late 90: Many people used to think that Web sites and the Internet were "fad mania", but these technologies were already widely used in the industry when they started using the Internet heavily. Large data technology is also the "new generation", but its impact is real, and in our side. Existing security tools work on large data. You can connect existing products to the configuration of large data, but that does not mean that these products can be run. Sometimes, to "marry" large data to a security product, you need to adjust the way large data clusters are deployed, or adjust the way applications communicate with large data. Security products should not limit the core functionality of large data, otherwise they will not be referred to as large data. The problem is that most security products do impose some kind of constraint on large data. If your security vendor says that your product "can be run in a large data environment in a specific situation," then you may want to find a more professional solution. No sensitive data is stored in large data clusters: Large data clusters often unintentionally store sensitive data. Many large data initiators say they do not collect sensitive data. But when talking to architects and data administrators, they have different arguments. Typically, data sources, including sensitive information, are accepted into clusters of large data in order to get more data and provide better analysis. "Edit Recommendation" Large data security significance RSA emphasizes the importance of large data security collaboration Sophos: Big Data security worth digging "responsible editor: Blue Rain Tear TEL: (010) 68476606" Original: Big Data security promise return to network security home