Cybercrime instances seem to be breeding like rabbits. According to security software maker Malwarebytes, its users reported 1 billion malware-based incidents from June to November 2016.
That was two years ago. Just picture this figure in 2018. Malware attacks have become more sophisticated and more difficult to detect and fight. Keeping precious business data protected against malware and hacking is one of the biggest challenges facing modern businesses. These never-ending cybersecurity threats make it extremely difficult to sustain business performance and growth.
Big Data: a savior?
Some say Big Data is a threat; others declare it a savior. Big Data can store large amounts of data and help analysts examine, observe, and detect irregularities within a network. That makes Big Data analytics an appealing idea to help escape cybercrimes.
The security-related information available from Big Data reduces the time required to detect and resolve an issue, allowing cyber analysts to predict and avoid the possibilities of intrusion and invasion.
According to a CSO Online report, 84% of business use Big Data to help block these attacks. They also reported a decent decline in security breaches after introducing Big Data analytics into their operations.
Insights from Big Data analytics tools can be used to detect cybersecurity threats, including malware/ransomware attacks, compromised and weak devices, and malicious insider programs. This is where Big Data analytics looks most promising in improving cybersecurity.
However, is it really possible to stay protected on an everyday basis?
The respondents in the CSO Online survey accept that they can’t use the power of Big Data analytics to its full potential for several reasons, such as the overwhelming volume of data; lack of the right tools, systems, and experts; and obsolete data. Big Data doesn’t provide rock-solid security due to poor mining and the absence of experts who know how to use analytics trends to fix gaps.
Intelligent risk management
To improve your cybersecurity efforts, your tools must be backed by intelligent risk-management insights that Big Data experts can easily interpret. The key purpose of using these automation tools should be to make the data available to analysts more easily and quickly. This approach will allow your experts to source, categorize, and handle security threats without delay.
Big Data analytics programs can help you foresee the class and intensity of cybersecurity threats. You can weigh the complexity of a possible attack by evaluating data sources and patterns. These tools also allow you to use current and historical data to get statistical understandings of which trends are acceptable and which are not.
Intelligent Big Data analytics enables experts to build a predictive model that can issue an alert as soon as it sees an entry point for a cybersecurity attack. Machine learning and artificial intelligence can play a major role in developing such a mechanism. Analytics-based solutions enable you to predict and gear up for possible events in your process.
Stay secure and ahead of hackers with penetration testing
Infrastructure penetration testing will give you insight for your business database and process and help keep hackers at bay. Penetration testing is a simulated malware attack against your computer systems and network to check for exploitable vulnerabilities. It is like a mock-drill exercise to check the capabilities of your process and existing analytics solutions. Penetration testing has become an essential step to protect IT infrastructure and business data.
Penetration testing involves five stages:
- Planning and reconnaissance
- Gaining access
- Maintaining access
- Analysis and Web application firewall (WAF) configuration
The results shown by a penetration test exercise can be used to enhance the fortification of a process by improving WAF security policies.
Once you have configured your policies and strengthened your process, you can do a new penetration test to gauge the effectiveness of your preventive measures.
Sometimes vulnerabilities in an infrastructure are right in front of the analysts and property owners and still manage to go unnoticed. Operating systems, services and application flaws, improper configurations, and risky end-user behavior are some of the most common places where cybersecurity vulnerabilities exist.
Big Data analytics solutions, backed by machine learning and artificial intelligence, give hope that businesses and processes can be kept secure in the face of a cybersecurity breach and hacking. Employing the power of Big Data, you can improve your data-management techniques and cyberthreat-detection mechanisms.
Monitoring and improving your approach can bulletproof your business. Periodic penetration tests can help ensure that your analytics program is working perfectly and efficiently.
Your users are one of your biggest cybersecurity threats. That’s why Investing In Endpoint Security is so important.