Nowadays, cyberattack surfaces in modern enterprise environments are enormous, and they are only growing in size and complexity. This means that analysing and improving a company’s cybersecurity posture requires more than just human intervention on the part of the organisation.
graphics based on artificial intelligence
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The use of artificial intelligence and machine learning is becoming increasingly important in information security because these technologies are capable of quickly analysing millions of data sets and tracking down a wide variety of cyber threats — from malware threats to shady behaviour that could result in a phishing attack.
These technologies are constantly learning and improving, drawing on data from both the past and the present to identify new types of attacks that could occur today or tomorrow.
In this post, we’ll look at the use of artificial intelligence in cybersecurity (both for good and for ill), as well as what experts and executives have to say about the subject.
The Benefits of Artificial Intelligence in Cybersecurity
Many advantages and applications of artificial intelligence can be found in a variety of fields, with cybersecurity being one of them. AI and machine learning can assist in keeping up with cybercriminals and automating threat detection and response more effectively than traditional software-driven or manual techniques, which are becoming increasingly common in today’s world of fast-evolving cyberattacks and rapid proliferation of devices.
Here are a few of the benefits and applications of artificial intelligence in cybersecurity:
Identifying and Defending Against New Threats
Artificial intelligence (AI) can be used to detect cyber threats and potentially malicious activities. Traditional software systems are simply unable to keep up with the sheer volume of new malware that is created every week, and this is an area where artificial intelligence can be of great assistance.
AI systems are being trained to detect malware, run pattern recognition, and detect even the smallest behaviours of malware or ransomware attacks before they enter the system. This is accomplished through the use of sophisticated algorithms.
Natural language processing, which is enabled by artificial intelligence, allows for superior predictive intelligence by scraping through articles, news, and studies on cyber threats and curating data on its own.
Information on new anomalies, cyberattacks, and prevention strategies can be gathered in this way. After all, cybercriminals are also influenced by fashion, and what is popular with them changes on a regular basis.
Cybersecurity systems that are based on artificial intelligence can provide the most up-to-date knowledge of global as well as industry-specific dangers, allowing for better formulation of critical prioritisation decisions based not only on what could be used to attack your systems, but also on what is most likely to be used to attack your systems.
Bots engaged in combat
Bots account for a significant portion of today’s internet traffic, and they can be dangerous. Bots can cause a great deal of damage, ranging from account takeovers using stolen credentials to bogus account creation and data fraud.
You cannot defeat automated threats solely through the use of manual responses. AI and machine learning aid in the development of a comprehensive understanding of website traffic and the differentiation between good bots (such as search engine crawlers) and bad bots (such as humans).
Artificial intelligence (AI) enables us to analyse massive amounts of data and allows cybersecurity teams to adapt their strategy to a constantly changing environment.
The answers to the questions ‘what does an average user journey look like’ and “what does a risky unusual user journey look like” can be found by looking at behavioural patterns, according to the researchers. According to Netacea’s Chief Technical Architect & Head of Data Science, Mark Greenwood, “From here, we can decipher the intent of their website traffic in order to gain an advantage over the bad bots and stay one step ahead of them.”
Predicting the likelihood of a data breach
Using artificial intelligence systems, you can create an IT asset inventory, which is a precise and detailed record of all the devices, users, and applications that have different levels of access to different systems.
Now, taking into account your asset inventory and threat exposure (as discussed above), AI-based systems can predict how and where you are most likely to be compromised, allowing you to plan and allocate resources to the most vulnerable areas.
Prescriptive insights derived from artificial intelligence-based analysis enable you to configure and improve controls and processes in order to strengthen your cyber resilience and security.
Endpoint Security that is more effective
The number of devices used for remote work is rapidly increasing, and artificial intelligence (AI) has a critical role to play in securing all of those endpoints.
Yes, antivirus solutions and virtual private networks (VPNs) can provide protection against remote malware and ransomware attacks, but they frequently rely on signatures to function. This means that in order to remain protected against the most recent threats, it is necessary to keep up with the most recent signature definition updates.
In the event that virus definitions become out of date, whether as a result of the failure to update the antivirus solution or a lack of awareness on the part of the software vendor, this can be a source of concern. As a result, if a new type of malware attack is discovered, signature protection may not be able to provide adequate protection.
This approach differs from traditional endpoint protection in that it involves repeatedly training the endpoint in order to establish a baseline of behaviour for the endpoint. Any time something unusual occurs, artificial intelligence can detect it and take appropriate action, which could include notifying an appropriate technician or even rolling back an attack after it has been successfully completed. Tim Brown, VP of Security Architecture at SolarWinds, describes how this approach provides proactive protection against threats rather than waiting for signature updates to be released.
What Cybersecurity Executives Have to Say About Artificial Intelligence
The Capgemini Research Institute conducted an investigation into the role of artificial intelligence in cybersecurity, and their report, titled Reinventing Cybersecurity with Artificial Intelligence, strongly suggests that modern businesses should prioritise strengthening their cybersecurity defences with AI.
Because cyberpunks are already employing artificial intelligence technology to carry out cyberattacks, according to the survey’s respondents (850 executives from cybersecurity, information security, and IT operations across 10 countries), an AI-enabled response is necessary, they believe.
Some of the most important takeaways from the report are as follows:
- Three out of four executives who responded to the survey said that artificial intelligence allows their organisation to respond more quickly to security breaches.
- 69 percent of organisations believe artificial intelligence is required to respond to cyberattacks.
Three out of every five businesses believe that using artificial intelligence will improve the accuracy and efficiency of cyber analysts. - As networks grow in size and data becomes more complex, artificial intelligence (AI) becomes a more effective tool for meeting a company’s cybersecurity needs. Simply put, humans are incapable of dealing with the increasing complexity on their own, and the use of artificial intelligence (AI) will become inevitable sooner or later.
The Drawbacks of Artificial Intelligence in Cybersecurity
The benefits discussed above represent only a small portion of the potential of artificial intelligence in improving cybersecurity.
However, as with anything, there are some drawbacks to employing artificial intelligence in this field. Organizations would require significantly more resources and financial investments in order to develop and maintain an artificial intelligence system.
Furthermore, because AI systems are trained using data sets, you will need to collect a large number of different sets of malware codes, non-malicious codes, and anomalies to train your system. Acquisition of all of these data sets is time-consuming and necessitates investments that are beyond the financial means of most organisations.
AI systems can produce incorrect results and/or false positives if they do not have access to large amounts of data and events. Furthermore, obtaining inaccurate information from unreliable sources can have negative consequences.
The fact that cybercriminals can use artificial intelligence to analyse their malware and launch more sophisticated attacks is another significant disadvantage, which brings us to the next point…
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Adversaries make use of artificial intelligence (AI).
Instead of constantly on the lookout for malicious activity, cybersecurity professionals can use artificial intelligence to reinforce cybersecurity best practises and reduce the attack surface, reducing their workload.
On the other hand, cybercriminals can take advantage of the same artificial intelligence systems for their own malicious purposes. In the words of Accenture, adversarial artificial intelligence “causes machine learning models to misinterpret inputs into the system and behave in a way that is favourable to the attacker.”
For example, the “FaceID” access feature on an iPhone uses neural networks to recognise faces, making it vulnerable to adversarial artificial intelligence attacks. Cybercriminals could create adversarial images in order to circumvent the Face ID security features and easily continue their attack without drawing attention to themselves.
Conclusion
Artificial intelligence (AI) is quickly becoming a must-have technology for improving the performance of information security teams. Humans are no longer capable of adequately securing an enterprise-level attack surface, and artificial intelligence provides the much-needed analysis and threat identification that can be used by security professionals to reduce the risk of a breach and improve their organization’s security posture.
Furthermore, artificial intelligence can assist in the discovery and prioritisation of risks, the direction of incident response, and the identification of malware attacks before they occur.
As a result, even with the potential drawbacks, artificial intelligence will serve to advance cybersecurity and assist organisations in developing a more robust security posture.
