5 Types of Big Data Security Issues

Companies need to be aware of big data security issues to avoid privacy risks and use the technology to its maximum potential.

In the digital era, data has become a major asset for businesses. Companies use modern technologies such as big data to collect and process data. With these capabilities, big data has transformed many industries such as healthcare, retail, and agriculture. The applications of big data help companies in improving business operations and predicting industry trends. However, this technology can be used with cruel intentions. Without proper data security, hackers can create a major threat to user privacy. Hence, companies must be aware of big data security issues and their negative impact.

Big Data Security Issues

1. Distributed Systems

Big data solutions distribute data and operations across many systems for quicker processing and analysis. Such distributed systems can balance the load and avoid the creation of a single point of failure. However, such systems can be quite vulnerable to security threats. Hackers need to attack only one system to infiltrate the entire network. Hence, cybercriminals can easily gain access to sensitive data and damage connected systems.

2. Data Access

Big data systems require access controls to restrict access to sensitive data. Failing to do so, any user can access confidential data and some may use it for malicious purposes. Also, cybercriminals can hack systems that are connected to big data systems to steal sensitive data. Hence, companies that use big data need to check and verify every user’s identity. In case a company uses inadequate identity verification methods, they may grant access to unauthorized users or hackers. Such illegal access can compromise sensitive data. This data can be leaked online or sold to third-parties.

3. Incorrect Data

Cybercriminals can affect the accuracy of big data systems by manipulating stored data. To do this, cybercriminals can create false data and feed such data to big data systems. For example, healthcare institutions can use big data systems to study their patients’ medical records. Hackers can modify this data to generate incorrect results. Such flawed results cannot be easily noticed and companies may continue to use inaccurate data. Cyber attacks like these seriously impact data integrity and the performance of big data systems.

4. Privacy Violations

Big data systems often contain confidential data, which is quite concerning to many people. Such big data privacy threats are already being discussed by experts across the globe. Besides, cybercriminals often attack big data systems to compromise sensitive data with data breaches. Such data breaches have made headlines and sensitive data of millions of people has been stolen. This confidential data can also be leaked online. For example, bank transactions, social security numbers, and other confidential data of 885 million people were leaked online recently. These security issues can threaten the privacy of people.

5. Inadequate Cloud Security

The data collected by big data systems is often stored on cloud systems. This can be a potential security threat. Cybercriminals have breached cloud data of many reputed companies. These issues can occur if the stored data is not encrypted and proper data security is not in place. Without these, hackers can easily access sensitive data. Companies need to address these big data security issues and focus on overcoming them before adoption. To fix such security issues, companies can encrypt all sensitive data and use intrusion prevention systems to detect network intruders. Along with these, companies can use multi-factor authentication to authenticate users with biometric data as well as passwords. Such authentication mechanisms can help in protecting sensitive data from hackers. Besides, companies can also conduct regular security audits to find vulnerabilities and loopholes in the existing security approach.