Navigating the Intersection of AI and Cyber Security

The field of cybersecurity has always been at the forefront of technological innovation, as trained cybersecurity specialists utilize ever-more innovative methods to keep malicious actors away from their essential corporate assets. The field of artificial intelligence (AI), on the other hand, has been on a comparable high-flying trajectory for about a decade already. The field of cybersecurity and artificial intelligence are coming into direct contact more frequently than ever before, a meeting that is expected to have far-reaching repercussions worldwide.

A study that was conducted by Cap Gemini in the previous year found that 63% of organizations have plans to adopt AI this year, and 69% of those firms are positive that they cannot respond to threats without AI. Zion Market Research predicts that the artificial intelligence (AI) market in the field of cybersecurity will rise to $30.91 billion by 2025, representing a compound annual growth rate (CAGR) of nearly 23 percent between 2019 and 2025. This estimate is based on the findings of a survey that was conducted by Zion Market Research.

The following are a few innovations that have resulted from the confluence of these two areas, along with an explanation of how these advances may influence conventional companies and the cybersecurity teams employed by such organizations.

The Scarcity of Cybersecurity Talent Drives the Adoption of Artificial Intelligence

Despite the tremendous growth in the number of cybersecurity programs in India, there is still a shortage of qualified applicants to fill vacant positions. The business publication Forbes published an article not long ago predicting that by the year 2020, the sector of cybersecurity will have 3.5 million open posts. That's more than three times as much as was left empty only six short years ago.

The expanding skills gap will offer an ongoing challenge to organizations that are already fighting a losing battle to withstand an onslaught of more dangerous threats from hackers and other cybercriminals. Because there is such a shortage of trained employees in the field of cybersecurity, as well as an increase in both the number and intensity of attacks, an increasing number of businesses, are turning to cyber AI in order to automate the security measures that they have already put into place. The use of AI as a trusted workhorse in various operations related to cybersecurity, from threat detection to quick response, is becoming more common.

When Good and Evil Confront Each Other in Adversarial AI

It is easy to forget that the struggle over cybersecurity is a two-way street, with cyber criminals trying their best to target infrastructure and cybersecurity supporters doing their best to keep bad actors at bay. However, it is important to remember that this conflict is a two-way highway. The term "adversarial AI" refers to a situation in which one party utilizes artificial intelligence to perfect

its assaults while the other side uses AI to safeguard its infrastructure. More than seventy percent of companies already have AI cybersecurity use cases under pilot testing. These use cases include fraud and intrusion detection, risk assessment communication, and behavioral analysis. This work can be completed more rapidly with the help of artificial intelligence, which can also learn from its failures to improve its defenses against future attacks. Even Certified Ethical Hackers (CEH), those who are skilled in the techniques used by cybercriminals but who utilize their expertise for the public good, stand to gain a great deal from this technology.

In addition, artificial intelligence is increasingly being utilized to evaluate risks in a manner that is more complex and is referred to as "risk context," rather than only simply delivering alerts of impending attacks. This approach "combines data-classification, trust modelling, and security analytics to give a better contextual understanding of a threat and to minimise the quantity of false positives," as the authors explain it.

AI, on the other hand, is making it easier for cybercriminals to carry out their attacks. One example of this is the mass monitoring of email communication in order to compromise accounts and credentials (typically through phishing attacks), as well as the quick and efficient execution of such attacks. Artificial intelligence has the ability to imitate human behavior in order to evade tougher security measures and get access to commercial networks. The battle will swing back and forth between good and bad players for the foreseeable future.

Competition to the End

Hackers are well aware of edge and endpoint computing's security shortcomings, which are typically the consequence of human error. This is an unwelcome side effect of the world's rising use of edge and endpoint computing, which is a growing trend. Gartner anticipates that configuration and user error will account for more than 85 percent of effective attacks on user endpoints in organizations by the year 2025. There has been a recent uptick in the number of hacking attempts directed toward edge devices such as cell phones and IoT readers.

AI has shown to be beneficial as a tool to defend endpoints from automated attacks. AI and machine learning are able to perform a variety of defensive tasks, such as building risk scores based on user behavior, geo-location, and other significant variables; supporting malware protection workflow all the way to servers; and using algorithms to determine when applications are at risk or unsafe (then moving those functions to more isolated systems).

Acquiring New Abilities Is a Crucial Part of Winning

The ongoing conflict between those who commit cybercrime and those who work to protect the internet from them is growing more complicated as powerful AI capabilities are brought into play. Your company will be successful if it cultivates relevant expertise, such as artificial intelligence (AI) engineers who are familiar with the process of building applications with a variety of intelligent agents and machine learning (ML) specialists who are well-versed in supervised and unsupervised learning, mathematical and heuristic techniques, and practical modeling. These types of professionals are essential for the success of your company. You should move forward with caution, but if you take the required steps to enhance your abilities, you will be able to navigate this intersection without any problems in the future


The importance of AI system security is highlighted by their widespread use in areas such as transportation, healthcare, law enforcement, and even military technology. In order to ensure the safety of automated decision-making systems, governments will need to examine issues such as transparency guidelines, certification and auditing standards, and accountability measures beyond the immediate benefits to the economy and national security.