Upgrade & Secure Your Future with DevOps, SRE, DevSecOps, MLOps!

We spend hours on Instagram and YouTube and waste money on coffee and fast food, but won’t spend 30 minutes a day learning skills to boost our careers.
Master in DevOps, SRE, DevSecOps & MLOps!

Learn from Guru Rajesh Kumar and double your salary in just one year.

Get Started Now!

Are we evaluating AI and machine learning for cybersecurity objectively?

Source- healthcareitnews.com

Artificial intelligence and machine learning hold as much promise, and perhaps peril, in the infosec realm as anywhere else. That was among the takeaways from the Tuesday morning keynote sessions here at RSA 2019.

“AI is the new foundation for our entire industry, it will enable us to better defend ourselves, to better detect threats, to out-innovate our adversaries, to solve other key issues,” said Steve Grobman, CTO of McAfee. “But we have to ask, are we looking at AI objectively? We cannot only focus on the potential, we must also understand the limitations and how it will be used against us.”

Grobman continued with an example of work McAfee did in taking public safety data sets about crime and with 50 lines of python and machine learning to predict whether crime would be committed in a specific region of the city based on certain parameters.

“We can identify hotspots to train citizens to make the city safer,” Grobman said. “But with the low barrier to entry for machine learning, a criminal could use the same data and tools to avoid being arrested.”

In addition to safety, public data sets are currently available across a range of areas, such as energy, critical infrastructure, and increasingly healthcare.

“It’s a simple classification,” said Celeste Fralick, McAfee chief data scientist. “The model has no idea whether it’s learning to detect cancer or optimize a crime spree. It’s just math.”

Fralick also pointed to other top concerns, such as AI for social exploits, generating false content that is highly believable, and the technology’s ability to combine the effectiveness of spear-phishing with the scale of traditional phishing.

“Most people don’t realize how fragile AI and ML can be,” Fralick added.

Adversaries, for instance, could manipulate or poison that goes into the system to generate false positives or false negatives.

Grobman added that despite the reasons for fear and speculation, AI and ML will reshape the human experience as dramatically as tools of the last century did and innovation lights the way forward.

For that to happen, though, AI, ML and the raft of emerging technologies have to be secure, as does the data, according to RSA CTO Zulfikar Ramzan.

“Digital transformation and trust go hand in hand,” Ramzan said. “We can innovate all day long but unless people are willing to trust and embrace those technologies it’s all for naught.”

Related Posts

What is Machine Learning and what are the Types of Machine Learning Tools Available?

What is Machine Learning? Machine Learning is a subfield of Artificial Intelligence that incorporates statistical models and algorithms to help computer systems learn from data and improve Read More

Read More

What is an Autonomous System and what are Applications of Autonomous Systems?

Introduction to Autonomous Systems Autonomous systems, once the stuff of science fiction, have become a reality in our world today. From self-driving cars to drones, robots, and Read More

Read More

What is Predictive Analytics and what is the Types of Predictive Analytics Tools

Introduction to Predictive Analytics Tools As businesses continue to collect vast amounts of data, it becomes increasingly challenging to make informed decisions that drive growth and improve Read More

Read More

What is Neural Network Libraries and What are the popular neural network libraries available today?

1. Introduction to Neural Network Libraries Neural networks are being used more and more in today’s technology landscape, powering everything from image recognition algorithms to natural language Read More

Read More

What is Reinforcement Learning and What are Reinforcement Learning Libraries?

Introduction to Reinforcement Learning Reinforcement learning is a machine learning technique that involves training an agent to make decisions based on trial and error. It is an Read More

Read More

What are Graphical Models? Why use Graphical Models Libraries and Types of Graphical Models Libraries?

Graphical Models Libraries are powerful tools that allow developers and data scientists to build complex models with more accuracy and less complexity. These libraries help in capturing Read More

Read More
Subscribe
Notify of
guest
2 Comments
Oldest
Newest Most Voted
Inline Feedbacks
View all comments
2
0
Would love your thoughts, please comment.x
()
x