While security and governance are challenges that all businesses must address, several distinctions are unique to big data that you should be aware of. If you're gathering data from unstructured data sources like social media sites, you need to make sure no viruses or fake links lurk in the text. If you include this information in your analytics system, you may be putting your firm at risk.
In this blog, we will discuss Data Protection options in detail. So, without any further delay, let's get started!
Data Protection
📘An unstructured data source may contain helpful information regarding the type of data.
📗Extraneous noise may be present in the consumer you're trying to understand. You must understand the nature of the data source. Has the information been double-checked? Is it safe and secure, and has it been inspected for intrusion? For example, more trustworthy social networking platforms will keep an eye out for trends of criminal conduct and deactivate accounts before they cause harm. This necessitates a level of complex big data analysis that not all websites can provide.
📘Your company may have found a fantastic website, but it has been hacked, and you have decided to use the data as part of your big data platform. The ramifications can be disastrous.
📗Not all security risks are intended to harm you. You don't want to use a big data source that contains sensitive, personally identifying information on your customers, as this could jeopardise your company's reputation.
Data Encryption
Some experts argue that different types of data require different types of protection and that data encryption may be overkill in some circumstances in a cloud context. Everything might be encrypted. You could encrypt your data. Data, for example, when you save it on your hard drive or email it to someone else. When we send it to a cloud provider and save it in its database, every layer can be encrypted.
Encrypting everything completely decreases your exposure, but it comes at a performance cost. Many experts, for example, recommend managing your keys rather than relying on a cloud provider to do it, which can be time-consuming. Keeping track of an excessive number of keys can be a hassle. Encrypting everything can also lead to additional problems. For example, if you want to encrypt data in a database, you'll need to check the data both when it's travelling (point-to-point encryption) and while it's being stored in the database. This treatment can be both costly and time-consuming. Also, even if you believe you've encrypted everything and are safe, you might not be.
Disadvantages of Encryption
📘One of the long-standing flaws with encryption schemes is that your information is vulnerable before and after encryption.
📗In a big data breach at Hannaford Supermarkets in 2008, hackers hid in the network for months and stole payment data when customers used their credit cards at the point of sale.
📘The data was not encrypted at the time of the incident.
📗Maintaining a large number of keys is inconvenient, and managing the keys' storage, archiving, and access is challenging. To solve this issue, produce and compute encryption keys as needed to simplify the process and improve security.
Data Anonymisation📚
When data is anonymised, all information that can be used to identify a specific person (such as a person's name, Social Security number, or credit card number) is removed. Although this strategy can safeguard some personal identification and thus privacy, you must be extremely cautious about how much data you remove. Even if that isn't enough, hackers can find out to whom the data belongs.
Tokenisation💰
This method secures sensitive data by replacing it with random tokens or alias values that are meaningless to anyone who obtains unauthorised access to it. This method reduces the likelihood that hackers will be able to do anything with the information.
Credit card details, passwords, personal information, and other sensitive data can all be protected via tokenisation. According to some experts, it is more secure than encryption.
Cloud Database Controls
In this technique, access controls are incorporated into the database to safeguard the entire database, eliminating the need to encrypt each individual piece of data.
Frequently Asked Questions
What is data anonymisation?
When data is anonymised, all information that can be used to identify a specific person (such as a person's name, Social Security number, or credit card number) is removed.
What is tokenisation?
Tokenisation secures sensitive data by replacing it with random tokens or alias values that are meaningless to anyone who obtains unauthorised access to it.
How is data safeguarded using the cloud database control technique?
In this technique, access controls are incorporated into the database to protect the entire database, eliminating the need to encrypt each individual piece of data.
Conclusion
In this article, we have extensively discussed various data protection options such as data encryption, data anonymisation, tokenisation and cloud database controls.
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