Welcome!

SDN Journal Authors: Liz McMillan, Yeshim Deniz, Elizabeth White, Pat Romanski, TJ Randall

Related Topics: @DXWorldExpo, Microservices Expo, Agile Computing, @CloudExpo, Cloud Security, SDN Journal

@DXWorldExpo: Article

Nine Biggest Data Encryption Myths, Busted

Battling common misperceptions about encryption and key management

Rarely a day goes by that you don't hear about a data breach. Hospital records stolen. Social media accounts hacked. Education transcripts revealed. Every industry is susceptible and every company is at risk. The result can be embarrassing and expensive at best and absolutely crippling at worst, with potential fines, time-consuming lawsuits, and subsequent loss of customer trust.

The steady pace of breaches reinforces the need for encryption as a last line of defense. Recently however, one of the oldest and most effective security tactics has been largely relegated to an afterthought in today's new cloud and big data environments.

This is the result of some common misperceptions about encryption and key management related to cost, performance and ease of use.

Today we set the record straight, breaking down the nine biggest encryptions myths.

Myth 1: Encryption is only for organizations that have compliance requirements. Certainly any company in a regulated industry that mandates data security and privacy should encrypt. That's a no brainer. But a better way to think about encryption is this: if you've got data about your products, customers, employees or market, that you believe is sensitive/competitive, then you should ALWAYS encrypt it, whether there's a legal obligation or not.

Myth 2: SSL encrypts data everywhere.
SSL only encrypts data in motion; it does not cover data at rest. As data is written to disk, whether it's stored for one minute or several years, it should be encrypted.

Myth 3: Encryption is too complicated and requires too many resources.
Data encryption can be as complicated or as easy as you want to make it. The key is to understand the type of data that needs to be encrypted, where it lives and who should have access to it. There are plenty of readily available, easy to use and affordable encryption tools on the market. If application performance is important, look for a transparent data encryption solution that sits beneath the application layer and does not require modifications to your operating system, application, data or storage.

Myth 4: Encryption will kill database performance.
There are a number of factors that impact database performance, and encryption is just one. Application-level encryption tends to pack the greatest performance hit, while the file-level encryption penalty is much lower. For maximum application performance, run block-level encryption on a system utilizing the Intel AES-NI co-processor.

Myth 5: Encryption doesn't make the cloud more secure.
On the contrary, in many cases storing encrypted data in the cloud is oftentimes more secure than keeping it on premises where insiders may have easier access. To ensure the safekeeping of encrypted data in the cloud, make sure you, not your cloud provider, maintain control of the encryption keys. If your provider requires you to hand over your keys, find another cloud service.

Myth 6: Encrypted data is secure data.
Too many organizations fail to effectively manage their encryption keys, either storing them on the same server as the encrypted data or allowing a cloud provider to manage them. Storing the key on the same server as your data or handing them over to your cloud provider is akin to locking your car and leaving the keys in the door. Good key management, with strong policy enforcement makes all the difference.

Myth 7: Key management requires expensive, cloud-adverse hardware.
While this was once true, today there are effective software-based solutions that enable organizations to deploy key management in the cloud or on premises. These solutions can typically be provisioned far faster than hardware security modules (HSMs), are very cloud friendly and meet most compliance statutes.

Myth 8: If your data is encrypted, it can't be stolen.
There is no security solution that will protect your data 100%. In fact, companies should operate with the mindset that their data can and likely will be compromised at some point in time. Data encryption can make the breach aftermath much more palatable though, since encrypted data cannot be decrypted without the key

Myth 9: Encryption is old school. I need a newer security technology to protect big data.
Data encryption is a proven security technique that works very well in modern NoSQL environments. As big data projects move from pilot to production, sensitive data such as protected health information (PHI), financial records, and other forms of personally identifiable information (PII) will likely be captured, processed, analyzed and stored.  Encryption is just as integral to securing data in NoSQL as it is in traditional relational database systems.

Firewalls and VPNs can provide some protection against data breaches and theft, but there is no substitute for strong encryption and effective key management, especially in big data and cloud environments. Now that the biggest myths have been busted, there's no longer an excuse not to encrypt.

More Stories By David Tishgart

David Tishgart is a Director of Product Marketing at Cloudera, focused on the company's cloud products, strategy, and partnerships. Prior to joining Cloudera, he ran business development and marketing at Gazzang, an enterprise security software company that was eventually acquired by Cloudera. He brings nearly two decades of experience in enterprise software, hardware, and services marketing to Cloudera. He holds a bachelor's degree in journalism from the University of Texas at Austin.

CloudEXPO Stories
With more than 30 Kubernetes solutions in the marketplace, it's tempting to think Kubernetes and the vendor ecosystem has solved the problem of operationalizing containers at scale or of automatically managing the elasticity of the underlying infrastructure that these solutions need to be truly scalable. Far from it. There are at least six major pain points that companies experience when they try to deploy and run Kubernetes in their complex environments. In this presentation, the speaker will detail these pain points and explain how cloud can address them.
The deluge of IoT sensor data collected from connected devices and the powerful AI required to make that data actionable are giving rise to a hybrid ecosystem in which cloud, on-prem and edge processes become interweaved. Attendees will learn how emerging composable infrastructure solutions deliver the adaptive architecture needed to manage this new data reality. Machine learning algorithms can better anticipate data storms and automate resources to support surges, including fully scalable GPU-centric compute for the most data-intensive applications. Hyperconverged systems already in place can be revitalized with vendor-agnostic, PCIe-deployed, disaggregated approach to composable, maximizing the value of previous investments.
When building large, cloud-based applications that operate at a high scale, it's important to maintain a high availability and resilience to failures. In order to do that, you must be tolerant of failures, even in light of failures in other areas of your application. "Fly two mistakes high" is an old adage in the radio control airplane hobby. It means, fly high enough so that if you make a mistake, you can continue flying with room to still make mistakes. In his session at 18th Cloud Expo, Lee Atchison, Principal Cloud Architect and Advocate at New Relic, discussed how this same philosophy can be applied to highly scaled applications, and can dramatically increase your resilience to failure.
Machine learning has taken residence at our cities' cores and now we can finally have "smart cities." Cities are a collection of buildings made to provide the structure and safety necessary for people to function, create and survive. Buildings are a pool of ever-changing performance data from large automated systems such as heating and cooling to the people that live and work within them. Through machine learning, buildings can optimize performance, reduce costs, and improve occupant comfort by sharing information within the building and with outside city infrastructure via real time shared cloud capabilities.
As Cybric's Chief Technology Officer, Mike D. Kail is responsible for the strategic vision and technical direction of the platform. Prior to founding Cybric, Mike was Yahoo's CIO and SVP of Infrastructure, where he led the IT and Data Center functions for the company. He has more than 24 years of IT Operations experience with a focus on highly-scalable architectures.