By Allen Graves
We already know that big data can be mined for any number of useful purposes. Industries, organizations and governments tap big data for everything from boosting sales to streamlining business processes – and for good reason.
Big data sets are so large that they defy traditional data-processing applications, thus offering the analysts who know how to compute them unprecedented insight into any number of trends or patterns.
In the cybersecurity industry, intelligence-driven security systems that mine big data are increasingly becoming the norm. Using big data to enhance public and private security makes sense. By analyzing information gathered from nontraditional sources like social network feeds, website activity and cloud-based documents, cybersecurity experts can assess vulnerabilities and target risks with more accuracy than ever.
Big data is singular in its potential to render millions of possible security events coherent. Mining it can bring together actionable information from disparate sources, offering real clarity in the oftentimes murky world of cyberspace.
Unfortunately, cybersecurity professionals aren’t the only ones to recognize big data’s potential to improve outcomes and optimize performance. Today’s hackers are also using big data to their advantage, sourcing large numbers of Trojan-infected computers for sensitive information like social security numbers and credit card numbers. Cybercriminals derive this information from machines infected with malicious plugins that query databases and then transfer the results to databases under the hackers’ direct control.
Perhaps even more disturbing, cybercriminals are also using big data to optimize their own performances. Just as businesses analyze big data to increase their efficiency, hackers exploit big data’s ability to streamline and improve their processes.
Likewise, big data helps cybercriminals monitor infected machines and compromised information systems to gauge the efficacy of each attack and refine their strategies. Cybercriminals know that big data’s biggest advantage is its utility as a learning tool.
Given the complexity and prevalence of data mining in general, cybersecurity professionals must adapt their approach to remain ahead of cybercriminals and insure the opportunities afforded by big data outweigh its perils. The following strategies may be a good place to start:
- Organizations and businesses are best served by tailored security solutions and processes that address their unique risk profile while collecting, analyzing, sharing and storing data. Traditional consumer security technologies simply lack the sophistication to preempt cybercriminals in the era of big data.
- Strong security infrastructures that integrate big data analytics when developing security solutions are essential. Likewise, IT professionals skilled in managing infrastructures that use big data, as well as data analytics experts and data scientists, are key contributors to a robust and adaptive cybersecurity team.
- New technology acquisition should prioritize flexibility, so that cybersecurity experts can continue to deploy data analytics to achieve solutions that respond to threats as they evolve over time.
Lastly, ongoing education and awareness of big data mining is critical. While many cybersecurity professionals are conversant with the term, they lack a complete understanding of what big data is and how it can both benefit and detract from cybersecurity.
Staying current on industry developments is the best defense against those who would use big data, one of the most powerful developments of the 21st century, for illicit purposes.
Allen Graves writes about technology and business process improvement on behalf of Villanova University’s 100% online degree and certificate programs.