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.
Until next time,
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.
I’d love your input! Is this something you’d consider as a way to get quick access to hard to find skills? Send me your thoughts at Benjamin.Taub@Dataspace.com or, even better, let’s set up a quick call. Thank you!
Our data matching, deduplication, and linking solution, Golden Record has made huge strides since our last newsletter. In addition to security and user interface improvements, we’ve added a critical piece of functionality to our core engine: derived columns (DCs). We’re currently finishing up the user interface aspects of it.
DCs allow you to modify your data before you match it. For example, we’re testing a DC function to remove all special characters from strings. So, the social security number 000-00-0000 will match to 000000000 and the phone number (800) 555-1212 will match to 800.555.1212 and 8005551212. Another DC function creates soundex values to help work around spelling mistakes. So for example, the soundex values for Ben and BBen are equal as are the soundexes for Clark and Clarke. Cool!
DC functionality is built in a very flexible way so you should expect to see an expanding library of DC formulae. If there’s something you need, let me know. It probably won’t be too hard to add it!
And, if that’s not enough, GR’s website has gotten to be amazing! Check it out! (BTW, our marketing consultant has taken on all of our web and marketing tasks and has done a masterful job. Let me know if you need similar services, I’d be happy to hook you up!).
If you’d like a demo of Golden Record, or to play with it yourself, I’d love to get you an account. Just reach out to me and I’ll get right back to you.
Anyhow, I’m working on the next big GR enhancement, multipass matching, so I’ve got to go. Thanks so much for reading!
You can reach me at Benjamin.Taub@Dataspace.com
That’s all for now. Thanks for reading and stay safe!
JUST IN CASE YOU MISSED IT…
We’ve posted several new articles to our Dataspace Blog since our last newsletter. If you missed them the first time around, here’s your chance to check ’em out!
What do you think? How can we make this blog more useful to you? What topics would you like to see more of? Want to contribute an article? Just want to catch up and chat?
I’d love to hear from you! Email me at firstname.lastname@example.org.
Thanks for reading!