As enterprises grow digitally, data becomes their biggest asset. Big Data is a gold mine. Its security is critical, so enterprises must manage it well.
Big Data is prone to complex security attacks and vulnerabilities like other digital business assets. Enterprise-level security is a major concern as enterprises go through digital transformation.
What is Big Data Security?
Big Data security secures data and analytics from threat actors, attacks, or malicious activities. Big Data’s security patches can be compromised on online and offline platforms.
Security is a big concern for Big Data. Any attack on the data will mean huge losses for the company. This loss will be both in terms of reputation as well as business.
As data production and consumption are rising, organizations must look into all vulnerabilities that may be present in their security strategies. There could be loopholes in security measures, tools, and strategies impacting businesses.
Companies must take robust steps to strategize and invest in the right security solutions. They need to have robust and well-documented security policies and response roadmaps.
Why Businesses Need Security of Big Data
As Big Data contains a large volume of data, it always remains under threat radar to database security. The cost of a Data breach is extremely high. Enterprises need to deploy more scalable security tools to keep them safe. So, Big Data security management aims to correctly deploy the right security tools and strategies.
Big Data breaches happen due to
- improper access controls,
- malicious data generation,
- Distributed Denial of Service (DDoS) attacks, and
- vulnerabilities in frameworks and applications.
Three key stages focus on securing Big Data:
Stage 1: Securing the data transfer locations and platforms online and offline
Stage 2: Protection of data in the data storage system
Stage 3: Ensuring data privacy while using for business purposes
It is necessary to build and maintain a firewall for unauthorized users, maintain strong user authentication, and continuously monitor potential threats.
However, many enterprises find it challenging to secure their data. Here are the common challenges in securing Big Data:
- Loopholes in security entrance and exit points
- Insecure network perimeter
- Security audits
Importance of Big Data Security Management
Big Data security management is a continuous process that ensures all business data remains secure.
It works with several strategies, tactics, and tools. Security leaders must analyze their data, the market, and the impact of a breach.
The CISO should focus on developing data information security policies, identifying risks, and evaluating and reporting security threats. These activities are essential to keep complex data sets safe, especially from new data sources that may contain threat risks.
Companies must create awareness about data security management policies among employees.
They need to be trained in basic security activities. These may be small things like the potential risks that may occur through email attachments, phishing emails, and ransomware or Trojan attacks.
Employees need to be aware that a small mistake can bring down their company. They need to be trained to identify cyber-attack threats, vulnerabilities, and risks.
The IT security team needs to deploy tools that detect and protect systems operating at all data types and stages.
Big Data Security Management Tools for Enterprises
The list below highlights tools for enterprises to resolve data security challenges and manage the overall security infrastructure.
- Data Loss Prevention (DLP) software is used to secure information, compliance, and maintain backup operations for data. The tool helps companies manage and store data information and create a ready-to-take-action plan for potential threats.
- Identity management software helps track and control permissions for users to access data information. The software also helps maintain strong passwords, update password management systems, and provision user information.
- Data masking software operates with the help of data masking technology, which maintains sensitive information under strict privacy walls. Cryptographic algorithms are used to set firewalls that protect data by using random symbols or characters.
- Mobile data security software adds an extra security management layer to mobile devices. It strengthens the authentication process that allows only defined users to access data. The software also includes mobile application management services to manage malicious activities while accessing emails or other downloading platforms.
- Centralized Audit and Administration software helps to maintain and report threat activities against data and manages security compliance through analytics. For example, Apache Ranger is a framework that manages comprehensive data security across the Hadoop platform.
Also Read: 13 Essentials for Big Data Security
The Ways to Do Big Data Security Management:
- Keep a focus on data storage management: Paying attention to the storage management of Big Data is a necessary step. Companies can use a secure, untrusted data repository (SUNDR) to check unauthenticated activities on servers. In addition, Digital Rights Management and policy-based encryption schemes also ensure a robust security stance.
- Strengthen endpoint security: Securing endpoint security will help prevent data leakage. Companies can do it through SSL Certificates, which safeguard data across all business assets.
- Controlling hardware and software configurations: Managing hardware and software configurations is important every time information is retrieved. Updating configurations regularly will help keep all data sets under multiple layers of firewalls and control all accesses.
- Include cryptographic processing: Big Data encryption is necessary to protect sensitive data, databases, and datasets. Cryptographic tools will help in authentication processes, biometrics, and coding to keep data stored and secured.
The Bottom Line
Enterprise-level security software and technology are advancing in their functions to deliver optimum protection solutions.
Similarly, for Big Data security, business leaders can plan, budget a good investment, and set strategies to manage security measures.
Preventing data breaches with scalable security tools should be a priority for organizations that use Big Data.
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