AI ML AND CLOUD COMPUTING WORKING TOGETHER



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AI ML AND COUD WORKING TOGETHER

ai al cybersecurity

No doubt that this world is moving towards the latest technologies every field of engineering and sciences researches are playing their vital role same goes for the software field in this world the latest and advanced working is being done on software field and if being specific software is not limited to anyone the particular field there are other as a computer network, big data field, web development, designing, mobile development information security, artificial intelligence, and cloud computing these fields are now at the high level and are truly responsible for such luxurious and advance a world that we are enjoying now.

In this research we will be focusing on the 3 major fields of software engineering that are 1) cybersecurity, Artificial intelligence, and cloud computing. We aim to discuss that how can Applying AI & Machine Learning techniques to improve security in the Cloud.

Here some questions arise like why are we choosing information security, cloud computing, and artificial intelligence?

As the rapid growth of cloud technology have been soo adapted that 96% of the companies are moving towards it but one of research found that almost the vulnerability in the system is too be still minimized for this about 49% of companies are interested to make their project security high with the implementation of Machine learning techniques. the mechanism applied by cybersecurity can prevent the security risk that could be found in the cloud companies the ml enables experts to come forward then to hackers to hack the system.

1. Big data processing;

In cybersecurity millions of tons of data are being processed on n regular basis, this massive amount of data must be analyzed, and here comes the event of ML algorithms to detect the cyber risk vulnerabilities and attacks by the system.it works on the principle of pattern matching the more data we have the more similar patterns are formed if somewhere we get the pattern that is dissimilar to the other the threat could found there.

2. Event prediction;

This can also be termed as the threat prediction or predictive analytic of threats, as simply the ML help us to detect the threat firstly the analyzing of data which is coming is done, after processing what is the data which is coming out on the other end. Both the detecting threats based on known behaviors and spotting out mechanism.

3. Detection of threats

For example, it is easy for machine learning to identify what’s is normal, like from when and where employees log into their systems, what they access regularly, and other traffic patterns and user activities. Any changes from these normal activities, for example, logging in the early timings of the morning, and get flagged.

1) AI TOOLS USED FOR CYBERSECURITY;

1. bioHAIFCS

This tool is a hybrid artificial intelligence framework to enhance the performance of cybersecurity. this combines the timely and machine learning method related to bio and also proved to be good for critical networking applications, military information systems, and networking as a whole.

2. Cyber Security Tool Kit (CyberSecTK)

This is a cybersecurity tool kit made from the python library for processing and featuring cybersecurity data information. this served as a bridge between cybersecurity and, machine learning techniques.

It is for the programming modules data sets and tutorials that support and enhance cybersecurity research.

Also, enable the experts to design a basic pipeline from scratch.

3. Cognito by Vectra

The special function of this tool is to detect and respond to the attacks inside the cloud storage, server, cloud IoT plate form, enterprises, and cloud data centers basic functionalities includes detecting the threats, empowering the threat hunters, accessing visibility to the development

4. StringSifter

StringSifter is a machine learning tool that automatically ranks the strings based on their malware analyzing technique. its first motive is to sit downstream from the string program, which means what it does it like the gets a list of input firstly and then after processing the strings delivers the output string and unknown pattern in string detect the threat in that string.

1) SOLUTIONS USED BY ENTERPRISES FOR SECURITY;

1. Analytics on Perspective

Examine the actions required for the analysis of data that comes from a cloud or normal databases.

2. Analytics on Diagnostic

Evaluation of root causes analysis especially for the incidents and attacks.

3. Analytics on Prediction

Determination of higher risk users and assets in the future and the probability of future possible threats occurrences.

4. Analytics on Detection

Identification of a large range of threats like hidden threats, unknown threats, bypassed threats, advanced malware, and lateral movement.

5. Analytics on Description

For getting the current status and performance measurement of recent analysis.

AI/ML

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