4 Ways of Securing Big Data Sources

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The rise of cloud computing has enabled companies and agencies to collect and store big data in an easy and effective manner. As companies now keep big data, it has become paramount to find ways of safeguarding big data sources. Here are some of the ways how big data course can be protected.

1. Ensuring distributed programming frameworks are secure

Although distributed programming frameworks are a critical part of distributing big data, they are also at risk if leaking that data. They also carry untrusted data from various sources that can corrupt the aggregate results. To secure this framework, organizations must first authenticate the conformity of the framework to the existing security policy. Next, separate the data from all personal information to ensure privacy is not compromised. After that, you can now authorize access to files and using mandatory access control, ensure that the untrusted code does not leak information through system resources.

2. Safeguard non-relational data

Non-relational big data course are common, but they are also vulnerable to attacks. The first step to securing these sources is using an encrypted password and ensuring you have an end to end encryption. Once the basic security is over, you can also add data tagging and object level security. Next use the pluggable authentication modules to authenticate users while ensuring that any transaction, which is done is logged in for accountability purposes. At the final stages, use the fuzzing methods to expose cross-site scripting and vulnerabilities that may be present at the data node and application levels of distribution.

3. Ensure data storage and transaction logs are secure

It is important to have secure data storage management whether it is small data or big data. One of the ways you can achieve this is to have a digital identifier for every file or document that is stored. You can then use the secure untrusted data repository technique to detect any malicious server agents or unauthorized document modifications. Other methods that can also be useful include key rotation, lazy revocation, broadcast, and policy-based encryption schemes, together with digital rights management. However, none of these techniques can be used as a substitute for building secure cloud storage on top of the current infrastructure.

4. Screening input data

For starters, your organization should use only trusted certificates and be vigilant when carrying out resource testing. The other technique is connecting only trusted devices to your network using a mobile device management solution. Don’t forget to use an antivirus and malware protection device to reinforce the safety of your system and the big data stored within. Afterward, you can incorporate the use of statistical similarity detection and outlier detection to sort out malicious inputs while guarding your system against ID spoofing and Sybil attacks.

Use any of the techniques discussed above to ensure your system and data are safe.

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