To begin with, it’s a big debate on how effective is AI’s role in the field of cybersecurity. We have seen, experienced and heard of AI accomplishments in industries like banking, healthcare, social and other enterprises, tacking challenges every second. That’s good. But how big is AI’s role in Cybersecurity?

 

Boy, cybersecurity is a tough game played online where you get to meet adversaries like hackers, doxers, black hats, malicious coders, letter bombers, phrackers, phreakers and….(phew!). The list of nemesis doesn’t stop there. As we take our breath, there are several new breeds of what-you-call-them cybercriminals brewing up in the womb of cybercrime out somewhere.

 

Is the AI technology up for it? It’s still a lingering question. However, recent phenomenal developments have showed that developers are leveraging Artificial Intelligence to the best of their abilities to counter the looming cyberthreats.

 

How efficient are they in achieving cyberhygiene and reducing attack surface at a scale?

Come, let’s explore.

 

We are smart. The hackers are smarter.

 

Hackers wait and watch and then they strike at the right time. Their MO is clear: to turn the very innovation that we created, against us.

Cloud computing offers various benefits, but not assured when it comes cyberthefts. Cloud consoles have become the main target for hackers. Once hackers take control of the console, they could intercept, manipulate, or even delete workloads leading the concerned party to bankruptcy. Or worse, they could threaten the cloud-first companies to pay huge ransoms, which is what is happening off lately.

 

Machine Learning or ML (a relative of AI) is great at reproducing things. It can learn while it spreads. Its intelligent. Hackers let lose trained ML programs to crawl through bank accounts, emails, a social media page, or any other sensitive platforms, where these smart programs can observe, imbibe and then reproduce fake copies to phish you off.

The simple truth is: For every digital and connected technology we create, the cyber criminals see them as a window of opportunity.

 

Hackers act fast, so should defenders

 

Hackers are fast and use ingeniously devised programs to automate their dirty trades to intercept, steal and hoodwink organizations.

 

Recent studies have shown that chasing cybercriminals is difficult and unique due to three factors:

1. The perpetrators are advanced and sophisticated

2. They don’t go by any rules

3. Scarcity of labelled data on cyber attacks

 

It sure makes sense that only with the same kind of agility as the perpetrators – or perhaps even better – can we be able to remain as a better match for these adversaries.

 

AI in the world of Cybersecurity

 

Traditionally, development and security teams’ roles were separate. In other words security was not always factored into the development of software products. As the speed and scale of hacking and other cyber crimes increased, so did the need for fusing development and security. The emergence of this practice roused the developers try out new and innovative technologies to fill the gaps. And AI is one such technology that is going the rounds.

 

Techniques such as machine learning, deep learning and neural networks are mushrooming everywhere. Frameworks such as Torch, TensorFlow, Caffe are boosting the hopes of cyberworld to bring AI into their fold.

27%

of executives say their organization plans to invest this year in cybersecurity safeguards that use AI and Machine Learning” – PwC 2018 Global State of Information Security Survey

 

Challenges and challenges.

 

Though businesses are eager to adopt AI into their stream to battle cyberthreats, sadly many of them lack substantial knowledge of the technology. Coming to practical implementation, AI and Machine Learning technology requires a solid amount of qualitative training data to train and develop artificial intelligence models.

 

As Ivan Novikov, CEO of Wallaram, an AI security firm puts it “more often than not, individual organizations lack the volume of activity, history, and diversity to build these models out on their own.” In these instances, he suggests, “the best solutions is to rely on a service or a vendor that can build AI models to share history across multiple organizations in the industry and learn from both the attackers and defenders to build the models that are both broad and deep”.

 

AI and Machine Learning technology requires a solid amount of qualitative training data to train and develop artificial intelligence models.”

 

Where does AI gain the upper hand?

 

To the hackers’ eyes the whole world is a land of opportunity. They spot blind spots which is hardly visible to our eyes. This means the cybersecurity professionals should unbelievably fast,  alert, and should be as witty as their enemies (cybercriminals). For example, in a traditional method, in order to discover vulnerability, security experts go by generating rules, instructions and signatures. They also manually generate virtual patches which could take longer than 20 man hours to do. But with AI in the fold, the entire process is automated and virtual patches can be generated in much, much lesser time.

 

Speed is the perpetrator’s strength. Today, the rate at which attacks spread is unreal. If needed they could spread havoc in matter of second at a global scale. This is where AI could prove its mettle. When AI programs are correctly trained and fed with relevant data, it could analyze tons of data at a fraction of a minute; inform and avert catastrophe, which can prove to be extremely difficult for humans to do.

 

AI algorithms are known to be very good at differentiating outliers from normal patterns. Instead of looking for matches based on specific signatures, AI blends with cyber by first making a baseline, and then from there it deep dives into abnormal events that causes the attack.

 

Another area where AI scores over human security teams is it lets you scale your operations for monitoring cyber systems, detecting breaches, incidents, and other issues.

 

AI Vs the human factor

 

In 2017, Facebook’s own AI-driven chatbot couple, (sweetly named Bob and Alice) put down a strange show. Apart from offering support to Facebook customers, these two chatbots had developed a secret language and were quietly conversing with each other. It seemed something right out of a science fiction farce. Strange, but true.

 

After guessing winners in 2016, an AI failed to predict the winning horse for the Kentucky Derby for 2017.

 

In October 2017, the discovery of some Google Home Minis secretly turning on themselves, recording voices of their owners, and sending tapes to Google had roused privacy nightmares among many users. Google announced a patch to fix the issue.

 

And the list is increasing. These may seem harmless, but imagine AI systems goofing up on massive scale or turning against it’s masters when its supposed to protect them.

 

To err is human. This means AI are not entirely infallible. There is always the other side to a coin.

 

Well, not really a conclusion…

 

While AI scores high in certain areas, the human touch remains unmatched to be replaced by anything artificial. As it happens, humans and AI should work together to achieve best possible outcomes. Though industries are abuzz with AI technology, we still have a long way to go before we hand over the entire mantle to Artificial Intelligence. Till that time human intelligence and artificial intelligence have to work side by side as we continue to combat cybercrimes…

 

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