4 Ways of Machine Learning That Causes Disturbance in Cybersecurity Pros

Ugra Narayan Pandey | December 28th, 2018 | Cyber Security

“Several businesses worldwide are dependent upon machine learning products to achieve prevention against cloud security threats. These products might be not as much helpful as they should be either an aspect of storage or data transparency.”

On the basis of Narrative Science report, it is being found that 61% of enterprises had to implement artificial intelligence in their enterprises. This incorporation of business operations with AI technology will increase in upcoming years because in majority cases, people are dependent on machines for their work. A prediction is made by the company Deloitte that ‘the total number of medium and big companies working with machine learning are going to be double till the end of this year.

What’s The Problem With Machine Learning Technology?

A well-known and widely used form of Artificial Intelligence is Machine learning, which translates the bulk amount of data, apply different algorithms to the records, and makes a prediction on basis of its own observation. Some of the common examples that make use of machine learning concept in a broad manner are – Speech recognition, object recognition, facial recognition, and translation services. Typically, enterprises make use of this technology to address and process large amount data, which can never be sorted out by humans on timely basis. This form of AI is used in several organizations like Google, Microsoft, Amazon, and IBM, to enhance business functionality. Now just wait for a second!

Do you know that enterprises are also using machine learning concept for Cybersecurity purpose? Are you also one of them? If yes, first go through this post.

An assumption is made by people worldwide that machine learning makes lives of cloud data security executives easier because it tracks security problems in an effective manner. But, these kinds of users need to understand one thing – Alike other new technologies, machine learning also comprises some flaws within it. Later, these flaws might result in more headache while dealing with cloud security solutions.

In What Ways Do The Machine Learning Impact Cybersecurity?

Following are the ways in which machine learning procedure disturbs the settings of Cybersecurity:

  • If Goes Wrong, Result Will Be Disastrous – This form of AI is useful to defend attackers but, it could be destructive if it goes in wrong hands. In this specific scenario, the major risk is from the side of internal employees who work within the organization. The machine learning expert at Onica said that ‘An arms race is happening because each corner tries to compete for the another for making a better artificial intelligence machine.’ This form of AI works faster in comparison to humans – major reason due to which machine learning is used. But, this cause is not effective in the case of Cybersecurity. In cloud data security, machine learning works on the basis of its own observation. It does not take permission from the concerned authority to check the process and then, implement the action. Therefore, if a machine learning system goes in the wrong hand, it can prove itself a big threat to the company.
  • Absence of the Company’s Data Transparency – When a flaw is addressed in most of the online data protection systems, an administrator could go into deep to analyze that what incidence is caused and how. But, when machine learning is incorporated with Cybersecurity, it becomes almost impossible to pinpoint the cause of alerts. This scenario represents the absence of data transparency. Also, these message alerts end up with false notifications leading to wastage of time.
  • Entering of Correct Records – A machine learning application does not work when just and complete information are fed into it. Actually, these machines are little picky. The modern algorithms of this technology are based on the specific amount of data. If a quality output is expected by organizations, the input has to be of high quality. An expertise level of knowledge is required to get effective and true results from machine learning systems. Now suppose if in case people don’t update new sensitive data records of business in the machine learning system, it is again high chances of data breaches are there.
  • Human Involvement Is Still Necessary – Making use of machine learning systems in premises do not mean that there is no role of human beings. Especially in the case of Cybersecurity with machine learning, it is essentially required to hire an individual who regularly keeps an eye on this sort of system. This particular individual has to check whether all the programs are updated on business PCs or not. He or she is responsible to take care of business confidential records and determine employee’s behavior with their data.

That’s All For Today

As per the current scenario, we would recommend business users not to consolidate machine learning systems with Cybersecurity pros. Separate cloud data security machines are available in the marketplace, which is not thoroughly based on this algorithms. Also, when you adopt these kinds of automatic systems, make sure that a supervisor is there. The role of a supervisor will be to address cloud computing security risks in your firm.