Humans vs. Robots vs. Robots vs. Humans: AI for Cybersecurity

According to some predictions, we are not far off from the beginning of the Third Wave of AI – a technological age that will see the rise of AI that are capable of generalization, contextual adaptation, and learning with minimal supervision or training data.

Sridhar Muppidi, CTO of IBM Security, agrees that “the possibilities are endless” when it comes to potential of AI, but thinks that some of the most important innovations will be seen in the applications of AI for cybersecurity. He highlights how AI tools are becoming increasingly necessary to analyze large amounts of data across multiple platforms and speed response times – including real time threat detection and prediction.

For their part, IBM leverages the capabilities of Watson – their AI, ML, and cognitive computing platform. As part of the Watson Platform Solutions, which is described as a “suite of integrated components,” Watson for Cybersecurity includes a number of applications and extensions (including QRadar for security analytics) to perform anomaly detection, threat hunting, and risk analysis in a variety of data contexts.

Amazon’s security tool offerings are similarly numerous, and are designed specifically for particular functions and environments. Their web content on this topic seems to agree with the premise of strengthening security through automation both in terms of threat detection (using ML and behavior models) as well as in response to threats.

That the big players in tech have entire suites of security offerings is in line with the tactics of DARPA’s Cyber Hunting At Scale (CHASE) program – which suggests that multiple automated AI and ML elements are essential to address the challenges of securing large scale distributed data networks, and that these elements working in concert in real time will be able to cast a wide net for threat detection and mitigation.

For access to DARPA’s CHASE site, copy/paste the below link into your browser:

Across the board, corporate and national leaders are increasing the level of importance they place on cybersecurity concerns heading into 2021 and beyond.

However, as quickly as AI is being developed for security purposes, hackers are seeking ways to creatively turn the technology against itself, and effectively fool or hijack the protective measures.

The race for advantage and innovation is perpetual.

Ben’s Take

Data Science is NOT the Hottest Field Today.

As everyone knows, data science is hot. And, strong, experienced data scientists are hard to find. But, believe it or not, what’s even hotter is the less sexy field of data engineering. It turns out that it’s even harder to find the folks who can design and build the pipelines that deliver big data (i.e. data engineers) to the folks who need that data (i.e. data scientists) than it is to find the data scientists themselves. So, if you know how to move data into Hadoop and Spark, and, more importantly, how to work with cloud data suites, especially AWS, you’re a hot commodity. The skills we look for in this area include Python and Scala, all of the AWS suite (Redshift, EC2, S3, and a bunch of other number-letter combinations), streaming technologies (e.g. Kafka, Kinesis, etc.), and SQL (yes, it’s still a thing!). Some background in data science is a great qualification but you needn’t be an expert data scientist to be a data engineer.

And, if you’re looking for data engineers, or data scientists, or any resource in the analytics and big data realm, talk to us! We’ve had good results filling a number of these roles lately, for both contract and permanent positions.

I’d love your input – Would you Work With an Offshore Contractor?

I think all of our clients would say that Dataspace’s competitive edge comes from our ability to screen technical candidates. You can see what this means when you consider the fact that only between 1 and 2% of the candidates we talk to make it through our screening process. But, this level of intense screening comes at a cost: we reject a large number of candidates that our competitors accept (you can find a whole series of blog posts on our web site about candidates we’ve rejected because of seemingly esoteric inconsistencies we’ve seen on their resumes – I suspect these folks pass through most other company’s screens).

So, given the limited number of truly talented contracting candidates in the US, we’ve been toying with a question: how would clients react to the option of talented, offshore contractors? Would clients be willing to work with such folks if they knew that they went through our current tech screening, a tougher communication screen, and some ongoing quality control processes? We’d be able to provide our customers with highly skilled folks quicker. We\’d also be able to support requests for part time resources, something that’s very tough to do today.

On the downside, of course, are potential timezone issues although I believe these can be managed in most cases.

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