By Xuan Zhao
At a time when cyber attacks are of grave concern to nearly every organization and when new types and mutations of malware arrive daily, the intersection of the fields of artificial intelligence and computer security is yielding interesting and significant improvements in security technology. As a data scientist at Cylance, I straddle these two cutting-edge fields every day, working with our team to design the “brain” or the engine for malware detection and conviction.
Historically, applying machine learning to the area of cybersecurity has remained in the realm of academia. However, their problem settings are too idealized to be applied to the real world. Thus, we have to propose ideas and algorithms for solving the real world problems by ourselves, which nobody has ever explored before. I’m lucky and proud to have joined such a pioneering team as one of the first members. Our team members are all very smart and passionate, we can learn a lot from each other, and I feel inspired and energetic every day being in such a great environment.
My daily life here at Cylance is really like the time when I was working on my Ph.D. Work time and work location are both pretty flexible; I can start working anytime I want, I can also work anywhere I prefer, too. Sometimes I go to a coffee shop with my coworkers and work from there. I can also work from Hawaii or Alaska or anywhere in the world.
During a normal working day, I usually spend half an hour browsing the newly submitted research papers to keep myself updated with any new research coming in the area of machine learning or deep learning, and to see if there is any algorithm that is applicable to trends in the cybersecurity space or a project that I’m working on for the time being. I then spend most of the day working on the current project, e.g. performing literature research in related areas, proposing different approaches for the current problem, exploring and analyzing these approaches, before doing further research on how to improve the approaches based on the analysis results.
The team and I also will devote some time writing research papers, and giving presentations at various conferences. Recently, I presented at BlackHat USA 2016, and had a paper published at an IEEE conference. Our data science team also collaborates closely with expert security researchers to gain knowledge about trends and industry updates to determine how machine learning can help solve age-long issues. Being at the bleeding edge of security, there are no well-known or well-defined solutions, which provides us the freedom to try novel ideas out, which is something I find very exciting.
Nothing is more rewarding than seeing that a machine learning algorithm designed by my team can boost the accuracy of malware detection, predict a well-prepared, large-scale attack and find new types of malware, that will protect countless computers from being attacked.
Like other women working in the IT industry, I’m in a nearly all-male world. I learned from other women in the field that discrimination toward women in IT is really a thing: ideas proposed are more easily rejected, not too many key tasks are assigned to women, etc. However, this is not always the case. I am lucky enough to be part of a supportive, collaborative team where everyone is equal, and everyone’s idea is valued and carefully considered. If you have a good idea, it will never be forgotten. All my coworkers trust me, and never doubt my ability because I’m a woman, thus I don’t feel any degree of inequality, let alone discrimination. To my knowledge, more and more companies are treating female IT workers equally now.
There is another factor that prevents women from entering IT industry, and that’s often our own confidence. The environment we grew up in embeds us with the idea that we are not as good as men in terms of math and engineering.
I have seen a lot of smart, young women doubting their own abilities. Before joining Cylance, I got a Ph.D. in Electrical and Computer Engineering from Cornell University. There were 30 Ph.D. students entering this program the same year with me. Among them, only five were women. With the exception of me, all the women dropped out of the program after one to three years, mainly because of stress and lack of confidence.
I have volunteered and organized several events for women in engineering. In one event, I needed to teach high school girls to use Mathematica (a software that can solve all kinds of math problems). One of the girls refused to install it because she said that she didn’t think it was something she could use. It then became clear to me that these women are smart enough to accomplish what is assigned to them, but are oftentimes not confident enough to try.
This is all because of the environment we grew in, and what the society made us believe – men were supposed to be the ones handling engineering and math, not women. I grew up being told that “Inability constitutes the very virtue of a woman” and “To do well is inferior to marrying well.”
Being raised this way, young girls learn to believe that in the world of IT and math, they can’t compete with men. These girls might be geniuses in engineering and math, but growing up with this kind of belief often can deprive these smart girls of a science-based career path. This causes an ongoing negative cycle – fewer women enter IT classes, causing fewer jobs for them, which perpetuates the stereotype of men dominating the IT industry for years to come.
So what can we do to help this situation? A female who is already in the IT industry can be a good role model and influence young women to enter the field. Women need to be more confident in their abilities and believe in themselves. We are smart and talented and there is no reason why we should be considered less than boys in any aspect.
I’m very happy to find that the IT industry stereotype is changing. I served as the judge for a women’s hackathon last year, and found numerous smart girls there who designed websites and applications for elders to more conveniently find a nursing home. The IT industry is continuously being reshaped by women leaders too, like Mitchell Baker, Marissa Mayer, Carol Bartz, Sue Gardner, and Sheryl Sandberg, to name a few.
I hope this improvement will continue on so that we can welcome more and more girls and women into this exciting industry and contribute to these state-of-the-art technologies together. Personally, I would love to encourage more females to consider joining the cybersecurity industry where our contributions can be highly significant in protecting people and data around the world.
About Xuan Zhao
Xuan Zhao is a Data Scientist at Cylance, where she explores AI related research topics and their applications to the computer security space. Her specific research includes advanced machine learning topics, including work in the deep learning space.