Saturday, January 23, 2021
  • Setup menu at Appearance » Menus and assign menu to Top Bar Navigation
Advertisement
  • AI Development
    • Artificial Intelligence
    • Machine Learning
    • Neural Networks
    • Learn to Code
  • Data
    • Blockchain
    • Big Data
    • Data Science
  • IT Security
    • Internet Privacy
    • Internet Security
  • Marketing
    • Digital Marketing
    • Marketing Technology
  • Technology Companies
  • Crypto News
No Result
View All Result
NikolaNews
  • AI Development
    • Artificial Intelligence
    • Machine Learning
    • Neural Networks
    • Learn to Code
  • Data
    • Blockchain
    • Big Data
    • Data Science
  • IT Security
    • Internet Privacy
    • Internet Security
  • Marketing
    • Digital Marketing
    • Marketing Technology
  • Technology Companies
  • Crypto News
No Result
View All Result
NikolaNews
No Result
View All Result
Home Machine Learning

AI security tech is making waves in incident response

March 18, 2019
in Machine Learning
AI security tech is making waves in incident response
586
SHARES
3.3k
VIEWS
Share on FacebookShare on Twitter

Credit: Google News

Cybersecurity strategies are increasingly tapping into artificial intelligence technology, including machine learning, to detect threats quickly and determine an accurate response.

You might also like

Fairness in Machine Learning Predictions – Web Hosting | Cloud Computing | Datacenter

Machine Learning & Big Data Analytics Education Market 2026| Querium • Knewton • Third Space Learning • Blackboard • Fishtree • Cognizant

Machine Learning Market Manufacturers Analysis 2020-2026 – The Courier

As the products mature, AI security technology is playing a big role in helping organizations fight off cyberattacks.

“We’re at an evolutionary inflection point with AI and machine learning, where there’s enough horsepower and compute and data to start finding security risks in new ways,” said Brian Johnson, a former CISO who is now co-founder and general partner of Silicon Valley-based information security firm Crucyble.

Organizations today use machine learning in SIEM software and related areas to detect anomalies and identify suspicious activities that indicate threats. By analyzing data and using logic to identify similarities to known malicious code, it can provide alerts to new and emerging attacks much sooner than human employees and previous technology iterations.

As a result, AI security technology both dramatically lowers the number of false positives and gives organizations more time to counteract real threats before damage is done.

“Every company has tons of logs to go through, and what machine learning does is do smart things like prioritize,” said John Pescatore, director of emerging security trends at the SANS Institute, a nonprofit that specializes in security and cybersecurity training. “So even with the same size security staff, the odds are much higher that they’re able to find the most dangerous events.”

AI security moves into the enterprise

Large organizations that can afford to hire the needed number of data scientists and employees with AI experience are building their own AI and machine learning capabilities, drawing on their own vast data sets to create algorithms customized to their unique needs, Pescatore said.

Most organizations, however, see such smart technologies coming into their enterprises in the security products they’re buying.

CISOs are seeking out such technologies: The PwC “2018 AI Predictions” report found that 27% of the responding 9,500 business and executive respondents were planning investments in security tools with AI or machine learning capabilities last year.

But even as executives turned to smart technologies to boost their cyberdefenses, experts said organizations should understand how to both maximize the value of AI in their cybersecurity practices and recognize its limits.

To do that, experts said CISOs should keep in mind the following things.

AI security tools won’t reduce the need for skilled security professionals. Experienced workers will remain crucial to robust security and compliance programs, as they’ll be the ones to analyze the potential threats identified by the AI tools. For example, only humans can understand context when analyzing issues and threats, security experts said.

Good CISOs still need to take a layered approach with diversity in their tools.
Steve Wilson analyst, Constellation Research

“AI is a decision-support tool — it should take some of the drudgery away from humans, but you always need a human being around to make the final call,” said Steve Wilson, vice president and principal analyst with Constellation Research.

While security pros shouldn’t worry about being completely replaced by AI, CISOs will be able to make better use of their employees by allowing them to focus on higher-value work instead of chasing false positives and handling mundane repetitive tasks, Pescatore said. As such, their security staff will need to be ready with the right skills to handle those increasingly complex tasks.

Actual investments are needed. Some security leaders and their executive colleagues are hesitant to make the investment in the artificial intelligence and machine learning capabilities because they feel their existing systems are adequate.

However, these new products provide more efficient and effective results that can quickly deliver a return on investment, said Crucyble co-founder Johnson, who is also part of the Center for Strategic and International Studies, a think tank in Washington, D.C. Moreover, these new capabilities will be essential to combat emerging cyberattacks that also use AI.

Data siloes must be broken down. Organizations need to train AI and machine learning systems with their data, yet they often have data residing in different places that needs to be brought together to give their systems the most accurate and complete picture of their operations, risks and security posture.

“If the security operations group doesn’t have data from the network operations group or the business system running in the cloud, then the AI tools can’t help,” Pescatore said.

Not all products will produce the same results. Vendors are increasingly touting their products’ AI security capabilities, but CISOs should ask their vendors to demonstrate how well their products actually work. “They need a vendor who has evidence in how these tools work in the wild, not in the lab,” Wilson said.

It’s also important to remember to manage your AI tools once they are in place. “Don’t ever set it and forget it,” Wilson said. “It’s never going to work like that.”

Security policies and processes should be reviewed and improved. AI and machine learning capabilities are usually paired with increased automation, so Pescatore said organizations need to ensure their processes are efficient and effective. Otherwise, the technology is built on broken systems.

It’s also important to note that these AI and machine learning capabilities should only be part of a diverse security program. In other words, don’t rely completely on emerging, AI security tech to protect data.

“Good CISOs still need to take a layered approach with diversity in their tools,” Wilson said, noting that organizations should always ensure they have a multipronged approach to security, risk and compliance. “No AI tool is ever going to be the silver bullet for all your problems, so always have some diversity.”

Credit: Google News

Previous Post

10 Powerful Examples Of AI Applications – Becoming Human: Artificial Intelligence Magazine

Next Post

Streamlio, an open-core streaming data fabric for the cloud era

Related Posts

Fairness in Machine Learning Predictions – Web Hosting | Cloud Computing | Datacenter
Machine Learning

Fairness in Machine Learning Predictions – Web Hosting | Cloud Computing | Datacenter

January 22, 2021
Machine Learning & Big Data Analytics Education Market 2026| Querium • Knewton • Third Space Learning • Blackboard • Fishtree • Cognizant
Machine Learning

Machine Learning & Big Data Analytics Education Market 2026| Querium • Knewton • Third Space Learning • Blackboard • Fishtree • Cognizant

January 22, 2021
Machine Learning Market Manufacturers Analysis 2020-2026 – The Courier
Machine Learning

Machine Learning Market Manufacturers Analysis 2020-2026 – The Courier

January 22, 2021
FDA Artificial Intelligence Machine Learning Action Plan – The National Law Review
Machine Learning

FDA Artificial Intelligence Machine Learning Action Plan – The National Law Review

January 22, 2021
Driving Intelligent Analysis through AI/Machine Learning
Machine Learning

Driving Intelligent Analysis through AI/Machine Learning

January 22, 2021
Next Post
Streamlio, an open-core streaming data fabric for the cloud era

Streamlio, an open-core streaming data fabric for the cloud era

Leave a Reply Cancel reply

Your email address will not be published. Required fields are marked *

Recommended

Plasticity in Deep Learning: Dynamic Adaptations for AI Self-Driving Cars

Plasticity in Deep Learning: Dynamic Adaptations for AI Self-Driving Cars

January 6, 2019
Microsoft, Google Use Artificial Intelligence to Fight Hackers

Microsoft, Google Use Artificial Intelligence to Fight Hackers

January 6, 2019

Categories

  • Artificial Intelligence
  • Big Data
  • Blockchain
  • Crypto News
  • Data Science
  • Digital Marketing
  • Internet Privacy
  • Internet Security
  • Learn to Code
  • Machine Learning
  • Marketing Technology
  • Neural Networks
  • Technology Companies

Don't miss it

As Bitcoin price surges, DDoS extortion gangs return in force
Internet Security

As Bitcoin price surges, DDoS extortion gangs return in force

January 23, 2021
Sharing eBook With Your Kindle Could Have Let Hackers Hijack Your Account
Internet Privacy

Sharing eBook With Your Kindle Could Have Let Hackers Hijack Your Account

January 23, 2021
Red Kill Switch for AI Autonomous Systems May Not be a Life Saver
Artificial Intelligence

Red Kill Switch for AI Autonomous Systems May Not be a Life Saver

January 22, 2021
Fairness in Machine Learning Predictions – Web Hosting | Cloud Computing | Datacenter
Machine Learning

Fairness in Machine Learning Predictions – Web Hosting | Cloud Computing | Datacenter

January 22, 2021
Ransomware victims aren’t reporting attacks to police. That’s causing a big problem
Internet Security

Hackers publish thousands of files after government agency refuses to pay ransom

January 22, 2021
Missing Link in a ‘Zero Trust’ Security Model—The Device You’re Connecting With!
Internet Privacy

Missing Link in a ‘Zero Trust’ Security Model—The Device You’re Connecting With!

January 22, 2021
NikolaNews

NikolaNews.com is an online News Portal which aims to share news about blockchain, AI, Big Data, and Data Privacy and more!

What’s New Here?

  • As Bitcoin price surges, DDoS extortion gangs return in force January 23, 2021
  • Sharing eBook With Your Kindle Could Have Let Hackers Hijack Your Account January 23, 2021
  • Red Kill Switch for AI Autonomous Systems May Not be a Life Saver January 22, 2021
  • Fairness in Machine Learning Predictions – Web Hosting | Cloud Computing | Datacenter January 22, 2021

Subscribe to get more!

© 2019 NikolaNews.com - Global Tech Updates

No Result
View All Result
  • AI Development
    • Artificial Intelligence
    • Machine Learning
    • Neural Networks
    • Learn to Code
  • Data
    • Blockchain
    • Big Data
    • Data Science
  • IT Security
    • Internet Privacy
    • Internet Security
  • Marketing
    • Digital Marketing
    • Marketing Technology
  • Technology Companies
  • Crypto News

© 2019 NikolaNews.com - Global Tech Updates