Dark Reading is part of the Informa Tech Division of Informa PLC

This site is operated by a business or businesses owned by Informa PLC and all copyright resides with them.Informa PLC's registered office is 5 Howick Place, London SW1P 1WG. Registered in England and Wales. Number 8860726.

Operations

12/12/2016
11:55 AM
Rutrell Yasin
Rutrell Yasin
Slideshows
Connect Directly
Twitter
RSS
E-Mail
50%
50%

5 Things Security Pros Need To Know About Machine Learning

Experts share best practices for data integrity, pattern recognition and computing power to help enterprises get the most out of machine learning-based technology for cybersecurity.
Previous
1 of 6
Next

The concept of machine learning has been around for decades. Machine Learning (ML) is a type of artificial intelligence (AI) that provides computers with the ability to learn without being explicitly programmed.

Industries and government agencies working with large amounts of data are using machine learning technology to glean insights from this data in real time. Financial institutions use the technology to identify investment opportunities and fraud. Utility companies use the technology to analyze sensor data to increase efficiency and save money. Healthcare practitioners are using the technology to identify trends that could improve diagnoses and patient treatment.

And, cybersecurity experts, inundated by reams of data generated by multiple information technology systems, security tools, networks, and other devices are deploying machine learning technology to detect and thwart internal and external cyber-attacks and threats.

“Machine learning helps humans be more efficient by [aggregating and analyzing] vast amounts of data. It’s not just the volume, but also the scope of data; more data at the same time and more facets of data at the same time,” says Sven Krasser, chief scientist at Crowdstrike, a developer of machine learning-based endpoint security tools.

“One of the big game changers is the emergence of cloud computing,” he says.  By using cloud-based infrastructures, security experts can aggregate more data from vast amounts of resources than ever before.” Traditional techniques where analysts sift through data in some manual fashion to generate rule sets doesn’t work well in today’s dynamically-changing threat environment, Krasser says.

System, sensors, and other networked-devices are generating so much data that it is increasingly difficult for human analysts to find those tidbits – the abnormalities and or patterns – that might give them the insights needed to identify an attack or potential threat, says Matt Wolff, chief data scientist with Cylance, a developer of endpoint security tools based on machine learning technology.

“So, machine learning is an excellent tool and the right approach to take when you have a data intensive problem that you want to solve,” Wolff says.

Industry executives and government agency officials are looking for ways to combat sophisticated attacks and relentless cyber adversaries while coping with a shortage of talented information security professionals. Machine learning-based security tools are yet another technology that they can add to their cyber arsenal.

DarkReading spoke with cybersecurity experts from CrowdStrike, Cylance, Darktrace, and IDC security researcher Peter Lindstrom to get a better sense of what organizations need to know about applying machine learning-based technology for cybersecurity in their organizations.

 

Rutrell Yasin has more than 30 years of experience writing about the application of information technology in business and government. View Full Bio

Previous
1 of 6
Next
Comment  | 
Print  | 
More Insights
Comments
Oldest First  |  Newest First  |  Threaded View
gopinathmohan861
50%
50%
gopinathmohan861,
User Rank: Apprentice
12/14/2016 | 10:11:16 AM
Machine Learning - Useful points
First of all, a big thanks for the article. The informations (5 security pros) mentioned in this article very useful. As AI and ML is going to rule future world, we need to consider these security pros.
JonKim
50%
50%
JonKim,
User Rank: Author
12/15/2016 | 3:02:27 PM
Insightful
Insightful, thank you for sharing.
US Turning Up the Heat on North Korea's Cyber Threat Operations
Jai Vijayan, Contributing Writer,  9/16/2019
MITRE Releases 2019 List of Top 25 Software Weaknesses
Kelly Sheridan, Staff Editor, Dark Reading,  9/17/2019
7 Ways VPNs Can Turn from Ally to Threat
Curtis Franklin Jr., Senior Editor at Dark Reading,  9/21/2019
Register for Dark Reading Newsletters
White Papers
Video
Cartoon Contest
Write a Caption, Win a Starbucks Card! Click Here
Latest Comment: This comment is waiting for review by our moderators.
Current Issue
7 Threats & Disruptive Forces Changing the Face of Cybersecurity
This Dark Reading Tech Digest gives an in-depth look at the biggest emerging threats and disruptive forces that are changing the face of cybersecurity today.
Flash Poll
The State of IT Operations and Cybersecurity Operations
The State of IT Operations and Cybersecurity Operations
Your enterprise's cyber risk may depend upon the relationship between the IT team and the security team. Heres some insight on what's working and what isn't in the data center.
Twitter Feed
Dark Reading - Bug Report
Bug Report
Enterprise Vulnerabilities
From DHS/US-CERT's National Vulnerability Database
CVE-2019-16695
PUBLISHED: 2019-09-22
phpIPAM 1.4 allows SQL injection via the app/admin/custom-fields/filter.php table parameter when action=add is used.
CVE-2019-16696
PUBLISHED: 2019-09-22
phpIPAM 1.4 allows SQL injection via the app/admin/custom-fields/edit.php table parameter when action=add is used.
CVE-2018-21018
PUBLISHED: 2019-09-22
Mastodon before 2.6.3 mishandles timeouts of incompletely established sessions.
CVE-2019-16692
PUBLISHED: 2019-09-22
phpIPAM 1.4 allows SQL injection via the app/admin/custom-fields/filter-result.php table parameter when action=add is used.
CVE-2019-16693
PUBLISHED: 2019-09-22
phpIPAM 1.4 allows SQL injection via the app/admin/custom-fields/order.php table parameter when action=add is used.