Artificial Intelligence, or AI, is becoming more or less a buzz component everywhere. It has now reached a point where even the most minute task can be performed seamlessly with its help. There was a time when writing an article or getting a painting, or designing work done required days or even weeks. Brainstorming for ideas or researching a topic was considered a delicate task, demanding special skills. As 2023 rolled in, all these tasks were made so simple sceptics would go far as to call it obnoxious. But truly, given how technology has advanced, being able to use and implement AI in the workforce can mostly be interpreted as resourcefulness. The corporate realm is perhaps one of the biggest potential subscribers to this new buzz.
If anything, AI is essentially a gateway to the internet, bringing the entire world under one umbrella. Doing so also means that anyone partaking in the AI trend also opens themselves up to new threats, even maybe to malicious AI softwares. But if AI can be used for evil, it can also be used to counter that very evil. Cybersecurity has long been a concern for every business and brand out there. It is noteworthy that, in cybersecurity, artificial intelligence is becoming more and more significant, both for good and harm. The most recent AI-based techniques may help organisations better identify risks and safeguard their systems and data resources.
Just to put it into perspective, the market for AI-based security products is expanding thanks in part to the increase in cyberattacks. According to research published in July 2022 by Acumen Research and Consulting, the worldwide market had a value of $14.9 billion in 2021 and was expected to grow to $133.8 billion by 2030. According to the Acumen analysis, market growth is anticipated to be fueled by trends, including the growing usage of the Internet of Things (IoT) and the increase in linked devices. New applications of AI for cybersecurity may be made possible by the expanding usage of cloud-based security services.
AI is a potent technology that provides cutting-edge capabilities to thwart assaults by safeguarding networks and services, identifying and preventing threats, and combating them. AI uses autonomous systems and learns patterns to stop new assaults, in contrast to conventional cybersecurity solutions, which simply identify existing threats. AI outperforms conventional systems even when just partially implemented, significantly reducing dangers. Traditional solutions may not be able to adequately safeguard corporate networks and services as assaults become more complex. In order to broaden the area of threat detection and improve security, AI is used in this situation.
Let’s explore a few benefits which AI can provide for cybersecurity:
Anomaly Detection
The capacity of AI to identify systemic abnormalities is among its most important advantages in cybersecurity. With AI, security professionals may be warned of possible dangers when they see unexpected activity or departures from known trends. Machine learning algorithms can discover patterns and data from prior assaults, preventing them from happening again before they may do serious harm.
Automation of Tasks
Repetitive operations can be automated by AI, freeing up cybersecurity experts to concentrate on more difficult duties. Without human interaction, automated systems can monitor networks, spot problems, and take corrective action. Automation lowers the possibility of human error, which may be expensive and time-consuming to fix.
Quick Response
AI has the potential to respond quickly to an attack. This is due to the ability of AI algorithms to instantly evaluate huge volumes of data and determine the origin and scope of an attack. This rapid reaction time can shorten the time it takes to recover from an assault and limit the harm.
Predictive Analysis
Predictive analysis may be used by AI systems to spot possible risks before they materialise. To achieve this, trends and data are analysed to determine the possibility of an attack. This enables companies to take preventative action before an incident occurs.
User Behaviour
AI may examine user activity to find trends and spot irregularities. This can aid in detecting insider dangers and stop data breaches brought on by negligent or malicious employee behaviour. Organisations can see possible hazards and address them before they harm by studying user behaviour.
Forbes reports that corporations invest a lot of money in automation and artificial intelligence (AI) technology. The Industrial IoT (IIoT), which strongly integrates AI technologies, is expected to grow into a $500 billion industry by 2025. AI keeps assisting businesses in protecting their networks and systems as they incorporate new technologies.
But with all that being said, it is natural to wonder if there is a downside to all the colours that hang in front of our eyes. The answer is no. Everything that offers well also carries the potential to bring harm. AI, in this case, is no different. Artificial Intelligence is far from being the perfect manifestation of our thoughts. It inherits most human flaws and is capable of causing downhill spirals if handled without care.
Bias
If AI systems are taught skewed data, they may become prejudiced. As a result, discriminatory actions may be taken, such as focusing on or disregarding specific racial or ethnic groups of people. False positives caused by bias in AI can be time- and money-consuming to correct.
Complexity
AI algorithms can be intricate and challenging to comprehend. Security staff may find it difficult to pinpoint the origin of an attack and choose the appropriate line of action as a result. AI algorithms may be difficult to debug, which makes it tough to catch problems.
Vulnerability
Even AI algorithms themselves may be attacked. AI algorithms have flaws that hackers may use to get into systems or influence the algorithms to harm. This can be especially dangerous if AI is used to make decisions that impact an organisation’s security.
Lacking Transparency
AI systems may lack transparency, which makes it challenging to comprehend how decisions are made. This might be an issue if judgments made by AI are contested or if the reasoning behind a decision has to be understood.
Costing
The development and upkeep of AI systems may be costly. This can be a major obstacle for businesses, especially smaller ones, that do not have the funding to invest in AI.
Now AI is still an emerging concept which needs much exploring before anything about it can be said conclusively. Thus far, it possesses both the upside and the downside, just like any product in the market. However, the potential cannot be denied or dismissed. Something so close to the human manifestation of perfection demands their implementation, even if it is for the sake of efficiency. In fact, there is a growing market for AI cybersecurity which is a very promising prospect in recent times.
The market for AI in cybersecurity is expanding significantly, with machine learning expected to have the largest revenue share by 2022. The machine learning technology category is anticipated to increase at a faster CAGR from 2023 to 2030 as a result of the adoption of deep learning across a variety of end-use industries. According to a recent study done by SkyQuest, the worldwide machine learning sector is predicted to increase rapidly and reach a value of USD 164.05 billion by 2028. This prediction shows the machine learning sector’s promising future in the AI cybersecurity market. Machine learning has emerged as a crucial weapon in battling these threats by allowing computers to learn from data and recognise patterns that might assist in detecting and preventing cyberattacks.
AI has become an essential piece of technology for supporting the work of human information security teams in recent years. AI delivers much-needed analysis and threat detection that cybersecurity professionals can use to decrease breach risk and strengthen security posture because humans can no longer scale to guard the dynamic corporate attack surface sufficiently.
Author- Shiddhartho Zaman
