Can AI Improve Cybersecurity Measures in 2024

All fields are currently experiencing a heightened risk of cyber security threats due to the emergence of innovative hacking techniques. Artificial intelligence is a new frontier technology that has its potential in enhancing cybersecurity measures.

But are these engagements likely to make AI more effective at cybersecurity by 2024? In this article, the author will detail how Artificial Intelligence contributes to cybersecurity and make an assessment of the potential for the improvement of security within the next two years.

We present a selected list of capabilities of AI in cybersecurity as follows:

It is currently being deployed for threat identification, big data management, and for performing various security tasks. Some of the key ways AI can augment security include:Some of the key ways AI can augment security include:

– Identifying suspicious files, programs and codes by analyzing the code and the behavior of the system. Threat samples can be used to train an AI to find out typical attributes of malicious code.

– Identifying trends in activity that may be signs of a security breach or potential threats. In profiling, typical usage and network traffic patterns among the users can be identified, and anything outside these profiles is likely to raise an alarm.

– Various functions such as controlling firewall policies, securing data and regulating user rights. This relieves cybersecurity professionals from spending most of their time sifting through and analyzing the data and lets them advance to more strategic planning.

– MAS – Managing complexity in large-scale security data integration across systems and networks. AI can reveal patterns and correlations that are not easily noticed by human analysts, which may result in a higher level of threat detection.

Limitations Holding AI Back

While recent research clearly demonstrates that AI has become a viable cybersecurity tool, AI has its drawbacks that reduce effectiveness – and this is the case regardless of how ambitious or unrealistic the goal – be it to improve the current security situation within two years. Some of the obstacles include:Some of the obstacles include:

– Lack of generalization – AI algorithms are effective for specific problems and limited datasets, but cannot generalize well to other problems or datasets. The issue that most organizations face is the availability of sufficient data related to the business in question.

– Susceptibility to hackers – The main issue that arises with the increased use of machine learning is the ability of hackers to ‘poison’ datasets and algorithms and hide the attack from the AI cybersecurity system.

– The cybersecurity skills shortage – The problem of having a severe deficit of skilled cybersecurity workers is not a futuristic one – it is present today. The stacked bar chart in the following figure shows that adding AI/ML complexity to the first problem of talent scarcity only makes the situation worse.

– Lack of computing power – Due to the huge demand for computing power, several corporations may not be able to support effective AI. Many professionals and businesses benefit from cloud computing but they cannot afford to overlook risks.

– The most correct AI models function as “black boxes”. This refers to the explainability problems. Some of the questions that arise from this include; why do they decide on something, which is something that should not be acceptable in the cybersecurity arena?.

The question is whether AI can enhance the level of cybersecurity by 2024

As of now, AI is still in its infancy, and thus it cannot offer an immediate fix that will considerably enhance cybersecurity across the board by 2024.

The technology simply cannot be used effectively enough to make adoption worthwhile because there are just too many barriers.

However, as AI technologies are increasingly trained and invested in the relevant applications, AI security use cases will continue expanding. AI is not and should not be portrayed as the ultimate solution to all problems; it is all about solving measurable pain points.

Specific areas where experts predict AI will meaningfully improve cybersecurity in 2024 include:Specific areas where experts predict AI will meaningfully improve cybersecurity in 2024 include:

– Cloud security – The nimbleness and versatility of cloud-based tools enables organizations to centralize data processing as well as to share threat intelligence with partners in order to optimize AI efficiency.

– Phishing threat detection – Education plays a very important role but using carefully calibrated AI algorithms can reduce the chances of employees falling in the phishing trap a lot.

– This is due to the fact that insider threat identification – AI is able to detect system and activity anomalies and catch the employee stealing/deleting important information earlier.

AI will not turn organizational security on its head and lead to a new paradigm in a few years, but if algorithms are trained on the right problems, balanced by continued proportional growth of computing capabilities, and talent, it will deliver incremental but important improvements where it counts.

Conclusion

AI has proven useful in cyber defense but there are significant constraints concerning datasets, computational resources, skilled individuals, and explainability, which imply that the technology can only be utilized to incrementally enhance the overall security posture rather than offer a silver bullet that will help fix all problems within a short period.

Hence, with an incremental approach of deployment in the areas of concern such as cloud security and phishing, by 2024, specific security functions will be enhanced significantly through AI. Though, expanding protections to encompass whole corporations within under two years is something that cannot be achieved.

In this way, it is possible to maximize gains with minimal risks: using AI where it can be highly effective; investing in cloud where it offers the most value; investing in skills (in fact, this is likely the best use of the funds set aside for buying more AI power); and accepting some trade-offs around explainability to get the value of powerful threat detection. This is a tight schedule towards 2024 though threats such as data breaches and ransomware will ensure that there will be massive continued investment on AI security tools

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