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How Can Big Data Help in Augmenting Cybersecurity?

With the ever-evolving cybercrimes, data handling, and security challenges, users must remain informed with ways to tackle them. The good news is that various enterprises are coming up with multiple solutions to combat the nuanced tools and mechanisms being used for data intrusions. The most prominent of them being Big Data Services. Big Data analytics in cybersecurity industry has various applications if enforced properly.

If we’re to believe the reports, the incidents of data breaches continue to rise every single year which is why we must make cybersecurity an absolute priority. The world faces more than 10,000 malicious files and 100,000 malicious websites on a daily basis. Phishing attacks account for over 80% of the reported security incidents.

Since the pandemic outbreak, remote workers have also been the target of alarming cyberattacks. Despite knowing about the risks related to cyberthreats, most of the companies were still not cautious and ended up being a victim to hackers and cybercriminals.

What is Cybersecurity?

Cybersecurity can basically be defined as a mechanism meant to protect your devices and the data contained in them. Its application also expands to networks and software. It’s not just a department that’s responsible for protecting your data, rather every step you take towards creating a safer environment for your system contributes to an overall secure user experience. 

A cyber threat comprises any malicious attempt at unauthorized access to a network for stealing private data or making changes to it. Phishing attacks, ransomware, malware, MITM, SQL Injection, Emotet, etc are just a few types of cyber threats. 

Why is Cybersecurity Important? 

Due to various vulnerabilities in the system, a company may end up becoming a victim of a cyberattack. There have been multiple instances of really dangerous cyberattacks in the past, for e.g the SamSam ransomware attack that took place in Atlanta, the Stuxnet worm that attacked the nuclear facilities in Iran in 2010, and one of the most recent and global data theft account- Pegasus, the spyware.

Overall cyberattacks cost the world economy more than $1 trillion according to McAfee- a leading cybersecurity firm. Apart from the financial point of view, there are many other benefits to cybersecurity like- managing and protecting big data thereby improving confidence in a company’s reputation and hence customer loyalty with a company.

There are various global laws like HIPAA, GDPR, DCC, etc that are enforced globally to protect citizen data and to regulate security standards.

Application of Cybersecurity

 Some steps that can be taken for securing your browser and system experience:

  1. Updating your software and OS every once in a while
  2. Using an anti-virus software
  3. Using strong passwords or opting for passwordless authentication (e.g. OTPs)
  4. Making sure that the website you’re visiting is safe. Look out for ‘HTTPS://’ at the beginning of the website’s domain name.
  5. Frequent risk assessments.
  6. Backing up data periodically to ensure minimum loss of data in case a data breach does happen.
  7. Using encryption to store and transfer data
  8. Keep yourself updated with information on the latest cyber-attacks.

Apart from these small steps, there are dedicated cybersecurity professionals and companies like Intruder, Cipher CIS, Symantec, Cisco, etc who are responsible for defending and even predicting data breaches on a much larger scale.

Their services include vulnerability assessment, external network security audit, cloud security, network security, endpoint security, etc. There are a few added benefits to cybersecurity like productivity enhancement, gaining client confidence in terms of data security, and improved system performance.

What is Big Data?

Big Data comprises a huge amount of data, structured or semi-structured. Data is generated in a high volume, at a great velocity, and in a huge variety. Did you know that Social Media is the highest contributor towards the generation of data?

Important tools like Apache Hadoop, HPCC, Statwing, Qubole, etc can be used to analyze and interpret a huge amount of data accurately and efficiently. The analysis and storage involve Artificial Intelligence and Machine learning as well. Big Data can in fact be converted into Actionable Intelligence to get an added advantage over one’s competitor. Data Analytics can also act as a catalyst to achieve an organization’s goals if applied properly.

Big Data is creating a revolution due to its multifold usage throughout the world. The retail industry benefits from an accurate representation of customer behaviors and patterns thereby contributing towards achieving higher sales. And the healthcare industry benefits by harnessing data pertaining to past records and thereby providing more personalized medications and even developing more effective treatments. Cybersecurity companies have been applying big data technologies for cybersecurity in recent times and the results have been promising.

Learn more about Big Data Analytics

Big Data’s role in mitigating cyber-threats

Considering the rate of both data production and cyberattacks, it’s not surprising that Big Data seems like the perfect solution to fight and prevent cybercrimes. Cyber professionals can comb through the huge amount of data in a time-efficient manner and thus detect and resolve the issues, enabling them to even prevent and predict any future possibilities of data invasion and data theft. Big Data analytics insights are crucial for the detection and prevention of cyber threats like ransomware, malware, phishing attacks, etc. 

 Using Big Data Analytics in cybersecurity comprises analytical tools, data management, and examination techniques that integrate data from various hosts, devices, and networks and then providing the information to sensors installed within, to detect and prevent any upcoming attacks. 

A Few Big Data Technologies for Cybersecurity

Predictive Nature: Big Data analytics make use of past records, algorithms, and statistics to look out for certain patterns which might’ve caused an issue in the past. Thereby, predicting future attacks while also providing information about previous attacks that might have occurred in a system.

Constant Monitoring: Data validates access to the systems while tracking logged-in activities thereby preventing a breach as well as managing passwords efficiently. 

Complete Automation: Professional Big Data analysts can actually automate the entire detection and prevention of threats process, saving time and human efforts.

Actionable Intelligence-Driven Risk-Management: With constant monitoring and processing of datasets, a foundation for actionable intelligence is formed which further plays a crucial role in detecting and predicting any cyberthreats 

Now, Big Data may apply any past or current insights pertaining to cybersecurity, collected from various sources to solve any issue. It, therefore, becomes rather convenient for the analysts to address and resolve any threats really fast.

Threat Forecast: With the help of AI algorithms, companies can even predict any upcoming threats based on past and present records and identification of any patterns after analyzing the dataset. Therefore, companies can take the necessary steps for the prevention of the threat actually taking place.

Real-Time Intrusion Detection: With the help of data analyzing tools like Apache Hadoop and HPCC that can basically automate the entire process, companies can be alerted about any intrusions taking place, as and when they might actually be happening, thereby enabling the businesses or companies to stop it from actually happening.

Big Data Analytics

There’s a huge amount of data that is collected through various mediums. Big Data demands cost-efficient, time-efficient, and innovative forms of information processing for enhanced insight and decision making. And it is necessary to maintain a well-balanced approach towards regulations and analytics when dealing with it. 

With the help of a few data analysis techniques such as data mining and machine learning algorithms processing of huge datasets becomes a lot more convenient. To do this, potential strategies like parallelization, divide-and-conquer, incremental learning, sampling, granular computing, feature or instance selection, can be used to reduce the computational time required to analyze the data and hence providing efficient results.

The size of large datasets can also be reduced in order to successfully identify any anomalies. The algorithm may offer an efficient data reduction method that effectively condenses the amount of data. It may also enable users to store the desired amount of data in a file and decrease the time in which the observations are retrieved for processing.

Big Data Security Analytics

An array of techniques like profiling, metadata collection, network analysis, data fusion, and predictive analytics prove just how powerful this technology can become if applied properly.  But at the same time it has provided for a treasure chest to cyber-criminals in the form of data, that is, a huge amount of sensitive and personal information, all stored in one place.

When cyber-criminals target a dataset of a company, the amount of information that they receive is worthwhile enough to take the effort of penetrating the many security layers. They obviously have a lot to gain going after a large dataset. This would also mean that companies have a lot to lose in case they face a cyber threat without having proper security measures in place.

To increase the security around Big Data:

  • Collaborating with other industry peers to create standards and share quality practices around data security.
  • Considering using attribute-based encryption 
  • Using trustworthy Big Data Management Services like Apache Hadoop.
  • Maintenance and monitoring of audit logs 

Big Data and Privacy

One of the main big data and cybersecurity dilemmas is privacy. Is Big Data a threat or an opportunity?

Big Data privacy is a matter of trust between the data owners and customers and Data owners simply must be sincere about protecting sensitive and personal user data. The more data that gets collected about users and customers, the easier it gets to understand their current behavior, draw inferences about their future behavior, and eventually develop deep and detailed profiles of their lives and preferences.

Hence it is of importance to be transparent with the privacy laws and regulations. Customers and users must know how their data is being used, how it’s being stored, and what steps are being taken by a company to comply with regulations that govern privacy and data protection.

Nevertheless, the fact of the matter here is that there are high chances that privacy can increase with the increase in dataset sizes. Basically, as the size of a dataset gets bigger, randomization increases thereby rendering it almost impossible to harm the privacy and integrity of users and proving that big data and cybersecurity can not only co-exist but also provide other crucial benefits.


Machine learning and artificial intelligence-powered big data analytics provide the utmost assurance that organizations can be kept secure from various cyber threats like hacking and data breaches. There are many Big Data analytics service providers who can make the best use of the power of big data, making businesses improve their cyber threat detection mechanisms as well as data management techniques.

Big Data also helps analysts to visualize future cyberattacks by taking the complexity from various data sources- past and current, and simplifying the patterns into visualizations to make maximum sense out of it. This technology would be most effective when organizations hire skilled personnel with appropriate knowledge and a thorough understanding of its benefits and limitations as well. Companies and businesses must also shoulder the responsibility and risk of protecting that data.

Talk to a Big Data Expert Today!

With the advent of a whole array of technologies like 5G, Cloud computing, IoT, etc it’s critical to invest in appropriate cybersecurity measures. This is when Big Data analytics companies play a crucial role. Not only would they provide a premium big data service pertaining to actually analyzing and making sense of the huge datasets but they would also be able to protect all the sensitive and personal user information, thereby resulting in increased customer trust and confidence in the company. Hence, merging and investing in the two leading technologies, Big Data and Cybersecurity would contribute towards encouraging results. 

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