Guest Editorial by Margaret Cunningham, Principal Research Scientist, Forcepoint
Artificial intelligence, cognitive computing, and machine learning are among the most discussed technologies in the cybersecurity realm, but what do these solutions really mean to security professionals?
Are they just buzzwords, or can they truly help commercial and public sector organizations achieve stronger and more intelligent security postures?
Though these solutions hold great promise, the technology itself is only part of that answer.
The real key to good cybersecurity lies in applying cognitive science—including human beings’ ability to consider, reason, and learn—to cybersecurity practices.
Just like humans require multiple lines of input—languages, relationships, experiences, and more—to learn, effective cybersecurity cannot be done in isolation.
Done correctly, cybersecurity requires multiple sources and types of information to build an understanding of technology systems and vulnerabilities.
When challenged with a task of protecting and understanding a large and increasingly distributed system, a single indicator from a single discipline is inadequate.
But cybersecurity is just as much about people as it is about machines.
After all, people are often the softest targets, and can be highly susceptible to phishing and social engineering attacks and human error.
Furthermore, machines cannot be relied upon to make decisions on their own—at least not yet.
Raffael Marty, vice president of corporate strategy at Forcepoint, told attendees at Blackhat USA 2018 that people are becoming too reliant on machines to make decisions based on algorithms that no one understands.
Likewise, our 2019 cybersecurity predictions report maintains that there is no real AI in cybersecurity, and that humans are, will, and should remain a key part of the cybersecurity process for the foreseeable future.
(Hear directly from Raffael Marty, Vice President of Research and Intelligence at Forcepoint, discussing the Winter of AI in the 2019 Forcepoint Cybersecurity Predictions Report. Courtesy of Forcepoint and YouTube.)
To that extent, it’s helpful to look at ways in which six of the most basic tenets of cognitive science and human nature impact cybersecurity.
Cybersecurity’s emerging focus on behavioral analytics and biometrics depends on psychology, which is heavily rooted in measuring and making sense of human behavior.
Through psychology, we can better understand why someone might click on a suspicious link, open up a questionable email, or simply be tricked into divulging sensitive or personal information.
Knowing why someone does those things can help us prevent them from happening.
Understanding human psychology is also important for forensic investigations, constructing insider threat profiles, and establishing when to generate alerts to help with user education.
(Learn More from Nico Fischbach, Global Chief Technology Officer at Forcepoint, speaking to ‘A Counterfeit Reflection’ in the 2019 Forcepoint Cybersecurity Predictions Report. Courtesy of Forcepoint and YouTube.)
Philosophy is a critical exploration of reality and knowledge that can guide human belief systems about existence, learning, social systems, and ethics.
How we perceive the world—what we believe is real and meaningful—profoundly impacts our thought processes, ability to learn, and behaviors.
Understanding threats, use of data and surveillance, and even the existence and locations of adversaries are all philosophical problems that can be applied to cybersecurity.
Cognitive linguistics addresses topics associated with how language shapes thought and understanding.
This practice can be critical in discerning cybersecurity threats, as security often depends on understanding behavioral context through language.
For example, classification of documents and understanding where private data exists on a network can be supported through text mining and analytics. Also, user generated text can be used to identify risk factors or regulatory violations.
In cognitive science, anthropology helps us understand how humans build shared knowledge, engage in interpreting their environments, and how they relate to and act with the world.
As recent news events suggest, opinions, behaviors, and feelings can be easily shaped and swayed.
Security professionals who apply cultural and cognitive anthropology in practice can better understand the behaviors and potential impacts of trolls and bots.
Cognitive neuroscience examines the biology of thinking and cognition. It provides a deep understanding of neurons, neural circuits, and the parts of the brain that allow us to perform mental processes.
Neuroscience has profoundly impacted information processing, network design, computational modeling, and sensor development, all of which have direct ties to cybersecurity.
Neuroscience continues to inspire innovations in building tools to improve knowledge representation and reasoning in technology.
Finally, we return to AI, which is a computer simulation of human intelligence.
Its goal is to create increasingly autonomous learning and reasoning through a range of strategies, including speech recognition, natural language processing, and machine vision.
And while there’s great promise for AI in cybersecurity, cybersecurity professionals continue to grapple with how, when, and whether it’s safe to use AI.
As Marty wrote, there are limitations to AI, and there may be some cases where AI should never be applied at all.
At the end of the day, it’s no coincidence that scientists have applied key aspects of the human condition to trying to make machines smarter.
All of these things have contributed to human thought and learning for thousands of years.
It makes sense to apply them to our efforts to make a more intelligent machine that can be used to fortify organizations’ security postures.
While that effort may not take thousands of years, we’re not quite there yet.
Yes, technology has become significantly smarter, and can play an invaluable role in helping us make better cybersecurity decisions.
But people are still the ones that have to make those decisions.
Eventually, machines might catch up, but as researchers at Accenture recently found, the most effective combination remains machines and people working together.
For now, the human factor still very much matters.
About the Author
Dr. Margaret Cunningham is a principal research scientist for human behavior in Forcepoint’s Innovation Lab.
Her current passion is identifying critical interactions between humans and technology through a socio-technical systems lens, with a goal of establishing a better human-centric model for improving cybsersecurity.
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