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Machine Learning

New tech holds the key to stopping cybercrime, study finds

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Tuesday, February 12, 2019

You don’t have to look too hard to find a sobering example of cybercrime, as it's as pervasive as ever these days, even on the national level with recent reports that cyber criminals have access to critical infrastructure such as our national power grids and gas lines. The good news, though, is technology may be our best weapon against these invisible criminals.

In fact, the use of big data and blockchain technologies are key to fighting cybercrime, according to a new study from Frost & Sullivan that looks at how effective machine learning is in aiding early detection of cyber anomalies, and how good blockchain is at creating a trustworthy network between endpoints.

Frost and Sullivan noted that the rise of the Internet of Things has opened up numerous points of vulnerabilities, compelling cybersecurity companies, especially startups, to develop innovative solutions to protect enterprises from emerging threats. As cybercrime becomes more sophisticated and even a method of warfare, the research firm found, technologies such as machine learning, big data, and blockchain will become prominent.

"Deploying Big Data solutions is essential for companies to expand the scope of cybersecurity solutions beyond detection and mitigation of threats,” Hiten Shah, research analyst, TechVision, said in the announcement of the findings. "This technology can proactively predict breaches before they happen, as well as uncover patterns from past incidents to support policy decisions."

The study, Envisioning the Next-Generation Cybersecurity Practices, presents an overview of cybersecurity in enterprises and analyzes the drivers and challenges to the adoption of best practices in cybersecurity. It also covers the technologies impacting the future of cybersecurity and the main purchase factors.

"Startups need to make their products integrable with existing products and solutions as well as bundle their solutions with market-leading solutions from well-established companies," noted Shah. "Such collaborations will lead to mergers and acquisitions, ultimately enabling companies to provide more advanced solutions."

Technologies that are likely to find the most application opportunities include:

•    Big Data: It enables automated risk management and predictive analytics. Its  adoption will be mostly driven by the need to identify usage and behavioral patterns to help security operations spot anomalies.
•    Machine Learning: It allows security teams to prioritize corrective actions and automate real-time analysis of multiple variables. Using the vast pools of data collected by companies, machine-learning algorithms can zero in on the root cause of the attack and fix detected anomalies in the network.
•    Blockchain: The data stored on blockchain cannot be manipulated or erased by design. The tractability of activities performed on blockchain is integral to establishing a trustworthy network between endpoints. Furthermore, the decentralized nature of blockchain greatly increases the cost of breaching blockchain-based networks, which discourages hackers.

Envisioning the Next-Generation Cybersecurity Practices is part of Frost & Sullivan’s global Information & Communication Growth Partnership Service program.