Deconstructing Distributed Security: Centralized Management in a Distributed System

Cost and risk reductions in managing a distributed system provide the greatest benefits of centralized management. Securing these systems is made easier by a reduction in complexity as well as being highly focused and visible, as are support functions and overall storage aspects.

Distributed Data Security: Starting the Discussion

The benefits of distributed cloud computing are accompanied by new responsibilities for ensuring data is securely maintained wherever it resides—on-premises or in the cloud. One reality of cloud computing is the number of different cloud providers the typical enterprise employs to support its application and data needs. A growing percentage of enterprises have a multicloud strategy. Many even report running applications on an average of 3.4 public and private clouds and experimenting with 1.5 more for a total of 4.9 clouds. Multicloud enterprises are the norm.

The Balance Between Data Security and Digital Transformation

What was physical is rapidly becoming digital, as every industry undergoes a digital transformation. Digital wallets, with details about your identity and your credit card information encrypted somewhere in the cloud, are replacing credit and debit cards, which have largely replaced printed currency and checks. Newspapers, magazines, music and movies are consumed digitally. Robotics eliminate manual assembly processes and deliver consistent quality at lower cost. The notion of driving a car may soon become as outdated as dialing a phone.

RSA 2019: Distributing Security to the Edge

Imagine knowing everything about a customer before they come through the door – name, preferences and interests, buying history, who they are connected to, where they live, and more. That kind of intelligence makes it easy to strike up a conversation with the customer and make the right recommendations that can lead to sales. The more you know, the more chances you have to win.

Data Gravity and Cloud Security

Data gravity boosts the value of your data, especially when analytics are applied. Larger volumes of data provide greater insight into and understanding of the sources that generate the data: customers, devices, machinery, vehicles, et cetera. Size matters: A database of ten million customers holds greater business value and potential for insight than a database of ten thousand customers.

Data Privacy Day: 3 Trends to Watch

Today is Data Privacy Day, an international awareness day held annually on January 28 to promote the importance of respecting privacy, safeguarding data and enabling trust. It was initially celebrated in Europe in 2007 to commemorate the Jan 28, 1981 signing of Convention 108, the first legally binding international treaty dealing with privacy and data protection. Today, it is celebrated worldwide, with many events, resources and even a live stream sponsored by the National Cyber Security Alliance.

Maneuvering the Data Privacy Maze

Encryption has been the primary mechanism to protect data since public key encryption was invented in 1976. Encryption does not allow data to be “seen,” and generally applies to three data states: “in transit” data moving between different places, “at rest” data on disk and “in memory” data currently being processed on a system.

Can You Achieve HSM Security with Cloud Flexibility?

We’re immersed in the world of security this week at the RSA Conference 2018 in San Francisco. There’s no question that the recent flood of news regarding corporate data security breaches and the need for significantly better policies to protect personal information are just a couple of the reasons why this event could not be more timely and relevant.

Mobile Is Set to Increase the Big Data Landscape

At Mobile World Congress 2017 there is a lot of buzz around the massive amounts and types of data that mobile devices will be adding to the deluge of big data traffic that is already traveling over today’s enterprise networks.

Why Companies Are Jumping Into Data Lakes

A data lake is a storage mechanism designed to facilitate the colocation and use of many different types of data, including data that is date-defined using various schemata, structural frameworks, blobs and other files.