The digitalization of society as a result of the Internet combines the physical and digital realms in its essence and relies on data and technology to facilitate value transfers, trust automation, and communication.
Governments, businesses, and military groups all across the world are collecting, analyzing, and storing data at ever-increasing rates.
Data protection and cybersecurity policies have therefore become extremely important.
Many examples of data compromise have also been reported as a result of firms' inadequate cybersecurity measures.
The effectiveness of today's cybersecurity technologies in avoiding data theft and leakage is undeniable, and they play a critical part in maintaining any organization's corporate reputation and data protection policy.
Cybercriminals, on the other hand, are creative and increasingly use automation to initiate cyberattacks. The saying "the question is not whether a corporation will be the victim of a cyberattack, but when" was coined for this reason.
Yet, traditional cybersecurity systems take longer to identify breaches and mitigate their operational impact. As a result, attackers and cybercriminals take advantage of this prolonged detection time to further compromise business networks and steal data that will subsequently be sold on the dark web.
In this situation, artificial intelligence can be crucial to a company's or organization's cybersecurity efforts since it makes it possible to swiftly identify and assess new exploits and vulnerabilities, minimizing harm and speeding up the IT team's response time of the affected company.
This article is focused on addressing this.
What benefits can artificial intelligence bring to cybersecurity?
The ability to complete tasks with the greatest efficiency and likelihood of success while also immediately spotting dangers is the first advantage of integrating artificial intelligence with current cybersecurity technologies.
In contrast to current cybersecurity solutions, which frequently struggle to keep up with the quick speed of development and mutation of new attack vectors, algorithms specialized to detect possible risks can be implemented in real-time to provide an instant response to the attack.
Another advantage is the capability of adaptive or machine learning algorithms used in intelligent security systems to identify and address risks as they arise (even if dynamic).
It's also important to note that such smart security systems have the innate capability to keep learning, scan the available information, and "predict" upcoming threats and appropriate reactions.
Artificial intelligence and cybersecurity policies
Currently, the usage of artificial intelligence is a key component in determining how assertive and proactive an organization's cybersecurity strategies will be. I would add that today, any business or industry's cybersecurity strategy must incorporate artificial intelligence along with current cybersecurity technologies.
With this in mind, artificial intelligence-enhanced machine-driven systems:
boost a system's capacity for resistance to ongoing attacks;
make it possible to tackle all incoming threats;
and make it possible to implement a more efficient cyber risk mitigation approach.
The real-time reaction to attacks is typically constrained by the speed and, occasionally, the "changing nature" of the attack in the configuration of a conventional cybersecurity policy, which does not take artificial intelligence into account.
Artificial intelligence, cybersecurity, and data protection
Critical technologies like cybersecurity and the Internet of Things cannot be solved without using AI, as data expansion is pushing traditional computing to the boundaries of its performance potential.
Up until recently, finding and fixing security flaws in enterprise infrastructure and datasets required human intervention.
IoT (Internet of Things) products and services are becoming more and more prevalent in our daily lives. It makes sense that by 2025, there will be 25.1 billion IoT devices, according to the GSM Association.
Now, in this setting, having a security strategy without the adoption of automated systems through artificial intelligence that collaborates with human agents is impossible and unavoidable.
The use of AI in improving compliance strategies and compliance with data protection laws
Artificial intelligence is already being used by several businesses in their compliance plans and for GDPR compliance.
NLP (Natural Language Processing), a form of artificial intelligence, has been used, for instance, to assist the organization in inferring the meaning of its legal contracts in a specific context (such as the setting of the LGPD), by examining the contractual terms and their links within the contract and to other corporate documents.
It would be feasible to create a "knowledge map" in this step from the analysis of contracts, emails, and documents integrated into corporate information systems (through NLP), which would serve as the cornerstone for the advancement of the organization's compliance efforts.
Possible evolutionary steps in sight! Stage and maturity of integrated solutions in the current market
The market is already leveraging AI capabilities to traditional security tools, blending human analysis with machine intelligence as well as how to develop solutions to accelerate the "automatic" discovery of bugs. This is in contrast to many organizations that are exploring "only" manual efforts to combine internal security findings and contextualize them with the external threat information.
One intriguing application of these "automatic" AI-based solutions is the deployment of bots to defend and patch security flaws on their own hosts while preying on weaknesses on other computers. In this instance, the bots show their speed by locating bugs more quickly than a hacker could.
Many managers and decision-makers are unaware of—or do not realize—that there are cyberattacks in the modern world that do not even require human involvement when it comes to the reach and maturity of integrated solutions. Hence, a shift in organizational culture is what is needed for this profile of integrated solutions to mature.
Regarding potential future evolutionary steps, cybersecurity will benefit greatly from a balanced blend of human intelligence (intuition, creativity), machine intelligence, and data science in the coming decade.
Although there are currently some issues with inaccurate results and useability with actual implementations of AI in cybersecurity, this type of approach will surely catch on in the large information security industry.
Take note, for instance, that today's "AV researcher" finds more than 50,000 viruses "every day," as opposed to not too long ago when he only saw 10,000 viruses in his whole career!
Furthermore, because of the shortage of human resources that the field experiences, the employment of artificial intelligence in cybersecurity will soon become necessary and required.
Did you know that a lack of qualified web security professionals affects more than 40% of businesses worldwide?
In a digital age, combining artificial intelligence with cybersecurity is not simply another business tool; it is a crucial component for companies looking to save the cost of avoiding breaches, spotting, and responding to inevitable cyberattacks.