How Big Data is the Future of Business Security

Over time, instances of hacks seem to be breeding at a higher rate. Research in 2016 showed that over a million incidents of cyber crimes were reported in that year alone. Over time, malware attacks have become more challenging to fight and detect and are more sophisticated than before. One of the challenges that modern businesses are facing is to keep their network and systems protected from hackers and malware attacks. With these never-ending threats, even the most successful companies can’t sustain their growth and performance.

Big Data

Some business owners believe that big data is a threat to their enterprises while others view it as a savior. It enables entrepreneurs to store large volumes of data, observe, analyze, and detect any irregularity within a system or network. That’s what has made it a preferred choice in keeping cyber crimes at bay. The volumes of information available in big data reduce the time that an entrepreneur can take to detect and resolve a threat, allowing IT teams to predict and keep possibilities of invasion and intrusion at bay.

Recent research has shown approximately 84% of modern businesses leverage big data to block millions of these attacks. The introduction of big data in the operations of a company can result in a significant decline in security breaches. Enterprises can also detect any threat including malicious insider programs, weak and compromised devices, and ransomware or malware attacks using big data analytics tools. The following are ways big data analytics help modern businesses to revamp their cybersecurity measures.

Threat Visualization

Enterprises can use big data analytics programs to predict the intensity of a possible threat. Enterprises can also evaluate data patterns and sources to weigh the complexity of a probable hack. Big data analytics tools also allow users to compare their historical data with their current reports to understand the acceptable and prohibited trends.

Intelligent Risk Management

An enterprise might need to back up its tools with insights that data analysts can analyze to improve their security measures. The role of these automation tools is to ensure data analysts have access to this information more quickly than before. It also allows data experts to categorize, source, and address security threats as soon as possible.

Stay Secure

Penetration testing is helpful in generating insights for business processes and databases, which can help keep cybercriminals at bay. In short, penetration testing is a tool that protects a network or computer system against any malware attack, and enterprises can also use it to explore possible vulnerabilities. It is a drill exercise that business owners can use to check their weaknesses and capabilities of their existing analytics solutions and processes. Over time, penetration testing has become an essential practice in protecting business data and IT infrastructure in the modern world. Enterprises can use the findings of a penetration testing exercise to review their WAF security policies and enhance their processes fortification. Once an enterprise has strengthened its operations and configured its systems, it can undertake another penetration test to gauge how effective its preventive measures are and improve their advanced managed security services. Vulnerabilities in a network or IT infrastructure are in front of the business owner or the IT team and can still go unnoticed. The common places where vulnerabilities exist include risk end-user behavior, improper configuration, application flaws and services, and operating systems.

Models Prediction

Data experts can use big data analytics to build predictive models that can alert them as soon as an entry point of a threat pops up. Artificial intelligence and machine learning technologies play an integral role in the modeling of such a mechanism. As such, business owners can capitalize on analytics-based solutions to foresee and gear up possible threats within a network or processes. Big data, backed by AI and machine learning technologies, give hope that enterprises can protect their methods and databases against any form of hack or security breach.