Why Artificial Intelligence Will Save Cybersecurity?

By : |September 4, 2019 0

Cybersecurity is in a dire state. Massive breaches are commonplace. A few years ago, 70 million Target customers were affected by a large-scale cyber attack. Target’s CIO was immediately let go in the wake of such an unthinkable disaster.

Breaches are affecting more and more citizens

Now 70 million seems like a tame number after revelations of devastating cybersecurity incidents like the Equifax breach, which affected 143 million Americans, and the Yahoo account debacle came to light. Each attack compromised millions upon millions, maybe even billions, of citizens. Worse still, the far-reaching effects of the fallout are still unknown.

In this day and age, cyber attacks affect all of us, whether we like it or not. Regardless of your position, your power, or your prestige, you could be a target. Increased risk of identity theft, doxxing, and credit card fraud is an unsavory consequence of the digital age.

Personal protection policies don’t cut it

Companies, large and small, hold your data. Government agencies lock away your details. Trusted institutions harbor personal identifying information. Whether or not they keep their data secure isn’t always up to us.

We can do all we can to update our passwords, encrypt our files, and even implement security checks on our personal devices, but it won’t stop hackers from breaking into large organizations. Personal protection is a great step for civilians, but it doesn’t address the larger problem. The main issue cybersecurity professionals are faced with is that security tools insufficient. We need better tools, predictive tools that can help implement the cybersecurity policies necessary to keep data safe.

Artificial intelligence is the key to analyzing malware

Artificial intelligence is a term that scares people. Cybersecurity should weigh more heavily on our minds than artificial intelligence, but, alas, fear isn’t a rational beast. Artificial intelligence shouldn’t be feared, but revered in the cybersecurity community. In fact, many tech luminaries and billionaires such as Elon Musk, Jeff Bezos, James Richman, Larry Page, and Satya Nadella, have been increasing their involvement and investments in the AI technology, according to Pure AI’s: “7 Innovators Investing Heavily in Artificial Intelligence”.

Artificial intelligence refers to many types of technologies that are loosely related. Many secure cloud platforms are powered by some sort of artificial intelligence. Machine learning is one of the related AI technologies and is a major area of interest for security experts.

How machine learning works

You can think of machine learning as a less sophisticated version of artificial intelligence. Basically, machine learning programs, as opposed to deep learning ones, can operate outside their original code (or parameters), but can’t do too much more than that.

Machine learning security programs are scanning the web for damaging software, finding patterns, and preventing phishing attacks.

Machine learning security programs are fighting evolving threats

At present, machine learning is being used to help tackle many of the cybersecurity nuisances. Most prominently, machine learning is being used to scan hacking programs. Most hackers don’t write code from scratch, they build upon existing malicious software, so identifying or “fingerprinting” malware can stymie hundreds of hacks.

More advanced machine learning security programs can find malware just by looking for similar characteristics, using vast training sets of existing malware programs to grow smarter. As malware evolves, we need machine learning programs to scan a vast amount of data, analyze subtle malware trends, and identify newly-minted malicious code.

Humans and machines must work together to address cyber attacks

Relying on artificial intelligence alone is naive. Machine learning security programs can be trained to scan for malicious code, but they can’t be trained to make sense of the data.

Professionals from all industries, from all walks of life, have to come together to utilize these technologies, thinking critically about the implications of their use.

Conclusion

Unfortunately, there’s precious little we can do to protect ourselves from coordinated cyber attacks. Sophisticated hacking organizations will continue to go for the jugular. While there are some strategies you can employ to reduce your exposure, ultimately, you can’t control the state of play.

As security policies continue to fail us, we have to create new strategies for addressing cybersecurity issues. Machine learning is proving to be an effective tool for combating cyber attacks by categorizing malicious code, sniffing out new trends, and stopping phishing attempts in their tracks.

Humans are fallible. This will be true no matter how smart our machines are. Every organization has weak points. Hackers will always try to exploit these weak points. Unfortunately, humans can only do so much to protect against cyber attacks. We have to enlist the help of machines to get the job done.

Guest Author: Greg Robinson, Tech Entrepreneur

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