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Home Future Tech AI

Is AI a Threat to Cybersecurity or a Solution to it?

by Guest
March 1, 2019 - Updated On September 11, 2020
in AI, Internet of Things
Reading Time: 6 mins read
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Is AI a Threat to Cybersecurity or a Solution to it?
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The sight of AI

To make smarter computers, smarter algorithms are required to provide smart thinking, cognitive approaches, and mind-boggling decision-making power. The AI has made it possible and enabled the machines to learn and think and have come with powerful systems known as expert systems

The AI systems so far created by the titans perform tweaking tasks like dialing phone calls, listen to your voice and act accordingly as in Siri, Google Assistant is a GOAT! (Greatest of All Time), and Bixby. Moreover, Huawei has taken a huge lump by creating neural processors. There are many who are working over data breach and cybersecurity to deal with the arising threats efficiently.

There are many more inventions to come in the future as organizations are working hard to make the best use of AI and its subsets. AI lovers who want to make a contribution to the digital world can take up a course on an Introduction to Artificial Intelligence which provides useful insights about its concepts and real-life implementations.

CyberCrime: The dark side of the World

The crime committed electronically is termed as to be cybercrime whether it’s getting access to social accounts without the owner’s consent, or phishing, spamming, bluejacking, hacking. The phishing, spamming, bluejacking, spoofing and some other honorable mentions are growing at an uncontrollable pace that in coming years they are going to be the sharks of the ocean CyberCrime.

Technically speaking, more the digital data and involvement of tycoons in your daily routine, more is the call to raise the bars of digital threats.

The digital footprints left by you are traced by the anonymous users to gain easy access to your personnel. These persons are often known by the clause ‘Hackers’. They outnumber the whole digital population over the globe.

Both the cybercrime and cyber-guard are at their pinnacle. Most of the companies are pitting AI to face AI. We are in the middle of the arms race of cyberworld. There are many threats that need to be dealt with and AI comes with a solution with most of them that can be eliminated. The comparison between Avg Vs Avast is also proved to be helpful to the users.

Major Threats of the CyberWorld

So enough of chit-chat let’s see the markings of this world.

1. Sophisticated Phishing

In layman language, the message sent to your device to install malware or expose sensitive data is an act of phishing. This is getting sophisticated day by day. The phishers are becoming more creative, for an instance, the employers of the companies have become a lot aware of the definitive techniques, so hackers make use of AI’s machine learning algorithms to compromise the organization’s network and systems.

2. Ransomware Strategies Evolved

Ransomware is created and deployed into victims machines to drive the victims under heavy loss of finances. I’m talking of billions and trillions of dollars. The hackers deploy numerous technologies to abduct victim’s databases and fetch them the real informatics to tear their fortunes.

3.The Weaponization of AI

The arsenal of AI is increasing at an unmeasurable pace. You can’t point fingers when a mischevious makes well use of machine learning algorithms for his behalf. One instance is spear phishing. ML models can well deceive the humans, in convincing fake messages, which can just churn their brains to the villain.

One can increase your knowledge from the learnings provided by University of San Diego about more cyber threats.

Solutions that AI provides for various Cybersecurity Threats

Both the cybercrime and cyber-guard are at their pinnacle. Most of the companies are pitting AI to face AI. We are in the middle of the arms race of cyberworld. There are many threats that need to be dealt with and AI comes with a solution with most of them that can be eliminated.

The inspiration has taken from the human body. The immune system of the body is designed in such a way that it can detect and fight the new threat, after that it remembers the very threat for the next time.

The so far cybersecurity solutions with the essence of machine learning at its baby steps can use algorithms to rectify digital threats the moment they occur, prior to the breach.

According to IBM, 90% of the cybercrime is a result of human error, the end users. The bad coding leaves loopholes which then comes into the limelight when the threat is imposed on the application. The vulnerabilities found in the network causes this whole trauma.  

1.Default Bias

The information technology department turns numb when the user or the client does not accept to alter default settings along with the two-factor authentication. This put them behind the bars of hackers and hence security is compromised.

Not opting for encryption when someone has worked a lot to ensure your safety.

Solution:

A Bayesian Algorithm used in machine learnng algorithms can be implemented to overcome this threat.

2.Conditioning

The oncoming of news regarding threats, denunciation of minor digital problems which are facile to eyes as phishing and on top of all this the abundance of security warnings implies, you are into the grey side and soon going to perish.

Solution:

Polynomial regression can be used to tackle conditioning.

3.Hype and Fear

The high profile’s leaked data or any compensation hits straight into the bullseye. This rings the bells of security experts to punch more keys efficiently and optimally. Whilst the attackers utilize this time’s wormhole to overcome other present vulnerabilities. It’s like using a bait, where the high delegate/celeb is just another scapegoat.

Solution:

Unsupervised Learnings classification algorithms can form a better solution

4.Habituation

The research has shown that constant beepings or security warnings make employees careless to respond to them. This opens and widens the road of the breach. The freeway is then responsible for data loss, finance exposure, exploiting industry relations too.

Solution:

Fine tuning the classification models’ hyper-parameters can upfront the habituation problem.

5.Peer Enforcement

The expansion of memory slots of one employee to the newbies is called peer enforcement. In this process training of employees perhaps moonlight their own knowledge but rarely alters the behavior.

Solution:

Data Security training is all about the practices and behavior of injecting ‘caution,’ to themselves and to machines.

The promise of AI

It’s really hopeless to pin your hope on unexpected expectations. The real root to the problem of cybersecurity is the very little span of the field. The countable persons are on the planet who really are studying this field, rest of the flock is being followed by the shepherd of IT application developments. So this upsurges the cyber world threats.

MIT snares with adaptive cybersecurity platform known as AI2. This is a virtual artificial intelligent analyst which restricts the false positives by the factor of 5. Follows the predictive algorithms of Supervised Learning. In the trial beginnings, the bad boy predicted 85% of cyber attacks. The AI2 traverses tonnes of millions of log lines for every 24 hours. On confirmation of results, the legitimate threats are tagged.

AI the Messiah!

The machine learning algorithms are awesome at netting the outliers amongst the patterns. A tactic is embraced where new violations have rendered useless. The approach of Unsupervised Learning is implicated where the procedure is, formulating a new baseline for normal events then scuba diving into the abnormal happenings to bring into the focal length of detecting attacks.

A Partner in Cutting Down Workloads for Security Operation Centres

AI leisures the security teams to perform scaling on their operations to watchdog systems for any breach or ascertaining the incidents and issues. Due to the enormous digital data, the semi-permeable membrane of human brain collapses.

The experts can’t find the attack elements agile enough. So the expert systems outweigh the beam balance of the two (AI systems and human experts).

 

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