Ricardo is a DevOps engineer in Australia. Previously, he worked for Fluid Attacks as a security analyst and instructor. He also spent a couple of years developing and maintaining an educational platform focused on coding and security, where students learned by solving programming challenges. He also had his feet in academia for a while: he holds an MSc in Engineering and finished his dissertation in Germany. As with previous interviewees, we reached him out to discuss cybersecurity.
At first, he shared a bit of his experience in doing his MSc. To our surprise, he wasn’t that enthusiastic.
Why did you get frustrated about research?
The main issue was the friction and the amount of time you have to spend justifying ideas already validated by the industry. You end up allocating too much energy looking for the right paper or the proper journal to support the choice of your methods, which is probably already outdated compared to alternative sources of information. This is even more pronounced in cybersecurity.
Another aspect was that the academic settings weren’t fun enough for me. I enjoy learning about technology because I can apply my skills to solve problems of increasing complexity. However, I found myself researching and writing papers without having enough time to play with the methods I have designed. Some people like to work on improving state of the art in methods and tools by designing rigorous experiments. Other people enjoy applying the best-known techniques to solve new problems. I discovered that I am in the latter group
What can you say about academia and cybersecurity?
- There is a vast gap between what industry needs and what is taught in colleges. We need more training in security skills. It isn’t that difficult to learn; nonetheless, you still get to know plenty of developers with no notion of effective security practices. That’s the reason I was attracted to work on an education platform some time ago.
What you just mentioned is paradoxical. Why this paradox?
Some people get into college, waiting to be fed with everything needed to succeed in a future job. That job probably doesn’t exist yet; that’s the paradox. Therefore, no matter how much knowledge you accumulate. At some point, you will need to learn more every day. + +
For example, when I was an undergrad, all we know today as cloud computing wasn’t even mentioned, let alone how to protect those environments. In contrast, the industry was promoting these new ways of provisioning infrastructure, the tools were getting traction, and some companies were spreading knowledge and training people. But, this is the nature of our field. Computer science evolves so fast that academia is incapable of catching up. Self-teaching and self-learning are more widespread these days, and people are becoming more aware that they should keep learning.
How do you study? How do you learn what you need to do in your job?
What I’ve done is learning online through some of the many platforms available. I have earned some certifications that are being demanded by organizations, like AWS, GCP, or Kubernetes.
Sometimes I pick a topic I don’t know, set a goal, and start browsing web resources. I train myself around specific tasks that interest me. Moreover, I also learn every day at work, solving new problems.
Recently, I read somewhere that the most critical skill nowadays for students is to know how to search in Google. You seem to nail it…
It isn’t a joke! You find people these days getting stuck in their jobs just because they don’t look for resources online. They might say that they need to speak to an expert. Also, these experts many times just google things out. It’s more of a mindset, rather than an inability.
I work building secure IT infrastructure using tools like Terraform and GCP. I like applying software development practices to the process of provisioning cloud resources, also known as Infrastructure as Code (IaC). You could say I am working on the defensive side of security; I have heard you’re doing cool stuff on the offensive side as well, aren’t you?
Security, as part of the development process, is essential to Fluid Attacks. We are proud to be working with this approach for several years now. Our Continuous Hacking service relies on IaC to support our customers consistently and faster.
We turned into cybersecurity specifics, and like with the other people we have spoken with, we asked Ricardo about his opinion on machine learning (ML) and artificial intelligence (AI).
What is your opinion on the contributions from ML and AI to cybersecurity? Do you find hype here?
- We’re in the hype phase according to the famous Gartner curve. But, indeed, there are several ML useful applications. I did some research on the topic years ago, and I concluded the field was in its early development. Around that time, some people even believed ML/AI would replace developers in a few years, for example. Something went wrong because I still got my paycheck last month (laughing). ML is a marvelous tool, and its development should continue. There are astonishing achievements, for instance, in health diagnosis, computers beating humans playing games, etc., with clear implications for society. However, those results are very domain-specific, and most problems in real life aren’t that well defined.
Figure 1. Hype Cycle for Emerging Technologies, 2017.
Do you think ML and AI would soon help in addressing digital threats better?
To help yes, but not wholly address them. One of the most significant sources of vulnerabilities is what happens at the software design stage. Weaknesses created “by design”. For example, in eliciting requirements, some design decisions lead to developing functionalities in an insecure way. That is more frequent than thought. And this is crazy: these “by-design” weaknesses are so simple to avoid, that for a competent cybersecurity professional is almost unthinkable to find them. The problems with these weaknesses, if not identified in a development phase, is that they might not be easily fixed when the software is already deployed.
Perhaps, someday, a software solution could detect automatically that kind of problems involving human judgment in the elicitation of requirements. If so, we’re far from that.
Is this you just mentioned linked to the gap in teaching secure software development in academia? Do you think this can be solved?
- Of course, but it isn’t a particular challenge for universities; organizations, specifically development teams, should contribute too. Programmers must know this. But, other people involved in design processes, such as business analysts and software architects, should also get to know more about security. In the initial stages of development (requisites, domain analysis, design, etc.) it’s enormously helpful to include a cybersecurity guy that supervises and teaches people how to think about security and how to infuse it from the very beginning —thus avoiding potential setbacks in the future. Investing at that level is usually worth it.
The second part of this conversation will be published shortly. We hope you have enjoyed this post and we look forward to hearing from customers, partners, and friends. Do you want to share your thoughts? Do get in touch with us! Also, read about our DevSecOps solution, which helps teams implement security from the beginning of software development.
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