Artificial Intelligence and Machine Learning have opened many new growth platforms from an individual level to an organisational level. But, with these security breaches are also growing in full-fledge. Millions of amount are spent by the organisations to save their data. In fact, there is no surprise in having the 30 to 40 security products used for one platform. It is one of the most vulnerable concerns between the security officers.
ML and AI are offering a platform for professionals to implement practices related to cybersecurity by reducing the space for attack instead of continuous chase after a threat. There are a number of courses such as Online Machine Learning course are available over the internet about cybersecurity realm. The course helps in exposing the concepts of time series, supervision, reinforcement etc. Through these courses, the user will be able to resolve the real-life problems based on cybersecurity, healthcare, medicines, etc.
How AI based Cybersecurity is running
According to the ESG survey, 29% want to accelerate the incident detecting technologies such that the problem areas can be cured, detected in the first stage.
While 27% wants to accelerate the incident response, which implies setting the incidents according to the priority, operation improvement and also automating the tasks.
Around 24% wants to implement AI for communication, identification of risk in the business. In this process, AI will cover configuration errors, software vulnerabilities and threats such that immediate action can be taken.
And the remaining 22% wants to use AI for better understanding and for awareness. In short, wants to take a unified status of the network.
From the above points, at least we can assume that AI is not working on the vacuum. Rather, AI provides an incremental analytics on the technologies to bring out the best, efficient solution.
AI and ML are Shrinking the Surface for Cyber Attack
We have seen many phenomenal outcomes of AI in different sectors. Speech recognition, monitoring, natural language processing, self-driven cars, recommendation engines, healthcare and many more are the AI expertise.
But chasing the malicious activity is a different and hard thing in comparison to other activities. As we do not have any idea of the adversaries involved in the cybersecurity and also in a couple of seconds we have a huge heap of data. The three main factors are responsible for the trouble in chasing the bad.
- Sophisticated adversaries.
- It’s obvious that no rules are followed in cybercrimes.
- Data Scarcity.
The techniques introduced by AI/ML are ideal for shrinking the surface, which needs an automated understanding. There are two main reasons due to which AI and ML are ideal for cybersecurity.
The good software follows the rules which help the AI/ML technology to improve the security and update them.
There is a huge number of data available which is labeled as “data for goodware”
One of the common challenges is a constant change. AI/ML technology excels in solving the patterns which are changing continuously and difficult to understand.
AI and ML help in securing the IT environments from continuous changing and evolving threat by achieving the cyber hygiene.
Long-term and Short-Term Forecast
As technology has brought many good things in today’s era which results in a huge fan following but as we are getting more and more dependent on technology, it has also brought threats. The threats will exploit us before we have any other conscious machine. However, the goals of attackers might be attained till now if AI was not being used. AI was the reason that we don’t have to go through such a wave of attack.
These attacks are divided into four type of horizons; short-term hyper-personalization, medium-term disruptions, Long-term pervasive and Long-term situations.
Data Preservation
“Higher the number of vendors higher will be chances of attacks”. Because the increase in exposure gives the enormous options to the attackers to exploit the data servers in different ways. Many companies are facing the challenge of data integration with the world. To solve these type of problem innovation based on Blockchain is implemented.
There are various AI applications which are used for different tactics. AI Efforts can be seen through automation tool in security operations but they are just introductory. Although, it is very important to be careful, especially when the distributors are selling the tools in the name of AI. There are several vendors are available who think they have accomplished an AI version but hardly able to verify the malware signature. However, to reduce that some companies are giving emphasis on product outline which has rules-based detection engines.
Definitely, companies which are implementing AI properly are at best position. As companies who understand the malware attribution, threat intelligence sharing and data privacy will always stay ahead of all types of cybercrimes. Ultimately, the cybersecurity teams will be able to invest properly on AI and unlock the security benefits before threat occur.
Contributed by Varun dutta
