Will Machine Learning Be Crucial for Ethical Crypto Hacking in 2020

Will machine learning be crucial for ethical crypto hacking in 2020?

Every day brings a new potential risk, every hour brings a threat and every minute sophisticated cybercriminals are continually on the lookout for the next big hacking strategy, every second they are finding new approaches to breach targets and infiltrate enterprises’ IT assets and sensitive data.

One of the best ways to deal with the rising wave of threats in this type of landscape is to encourage awareness and increase know-how about the latest risks and understand and find new ways how to guard against them.

You will be shocked to know that at the moment an emerging strategy that has gained popularity amongst hackers is the use of machine learning. But it is unfortunate to know, as many advanced, new and innovative technological processes, machine learning (ML) can also be leveraged for both useful enterprise purposes as well as malicious activity.

Blockchain till now was bulletproof, however, it is discovered that blockchain has lost its bulletproof jacket and now can be hacked like any other network. Machine learning can prove to be essential and helpful to ethical hackers to improve the security of this technology.

A growing number of security flaws were discovered.

Ethical hackers are still trying to adjust to the fact that blockchain networks are now vulnerable. They need to figure out how their black hat counterparts will manage to penetrate the defences of what was once believed to be the most secure titanium network in the world.

To develop better defenses they need to use sophisticated machine learning technology.

How machine learning can safeguard blockchain?

The real question is in the months to come how Ethical Hackers Can Employ Machine Learning to protect and shield Blockchain. What is unrealistically optimistic is people thinking that blockchain attacks will cease shortly. Because in the coming days, these blockchain attacks will get even worse.

Waiting for a piece of good news? Here it is- that there are different ways in which ethical hackers can use machine learning (ML) to support their more malevolent rivals.

Machine learning can identify patterns in smart botnets that try to assail blockchain

Botnets are the peer buddies of cyber criminals. They have been used in cyberattacks for years. Even though it is still vague, there is a high probability that hackers have used botnets to target blockchain.

To develop more sophisticated botnet attacks these days, black hat hackers have started using machine learning.

To support the cruel intentions cybercriminals are using machine learning that enables different nodes in botnets and even creates an entire separate botnet network to transmit with each other and make more vicious attacks.

It will be very challenging for security experts and traditional cybersecurity technology to identify the network activity produced using smart botnets. However, machine learning (ML) will make it simpler and easier to surveillance this type of pattern and deny access to the network and prevent attacks.

Machine Learning is Going to be “Essentialist” to Maintain Blockchain Security

Blockchain technology is known to be incredibly secure. However, it is not bulletproof, it’s not titanium. In years to come ethical hackers will need to use machine learning technology to strengthen the security of the blockchain.

Jafar Hasan
Jafar Hasan
About Author
Jafar Hasan is a seasoned cybersecurity professional and a respected educator at one of Indore’s premier ethical hacking institutes. With over a decade of experience in the field, he is dedicated to enhancing online security through ethical hacking practices. Jafar shares his knowledge through insightful articles focusing on cybersecurity and ethical hacking.
With a commitment to ethical practices, he shapes future cyber defenders and is a respected authority in cybersecurity. Trust his expertise to navigate online security complexities and stay updated on the latest developments in this ever-evolving landscape.

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