CyberAI: A Proactive and Robust Protection

“64% of companies worldwide have experienced at least one form of a cyber-attack.”
“There were 22 billion breached records in 2021.” “Every 39 seconds, there is a new attack somewhere on the web.”

Today, one of the biggest threats to organizations and businesses is cyber-attacks. Isn’t that concerning? Unfortunately, our go-to defense is firewalls. Security personnel oversee protecting an attack surface that is constantly expanding as modern business increasingly extends outside of its firewalls. Firewalls, however, cannot fully stop the ever-increasing cyber-attacks. Right now, only humans try to anticipate what other humans might do before they actually do it (Lazic, 2019).

This is where Artificial Intelligence (AI) steps in.

The global market for AI in cybersecurity is anticipated to grow at a CAGR (Compound Annual Growth Rate) of 23.6% from 2020 to 2027 and reach $46.3 billion, according to online statistics. Why? Because AI can learn in an adaptive way and recognize novel patterns; it also can speed up detection and response, reducing the workload on SOC analysts and enabling them to be more proactive.

Due to this, AI will become even more crucial in cybersecurity to fight against the top security threats in 2022.

Artificial Intelligence (AI)

Although the term artificial intelligence (AI) was first used in 1956, it is now more widely used because of increased data volumes, sophisticated algorithms, and advancements in technology. In the 1950s, early AI research investigated issues like symbolic methods and problem solving. The US Department of Defense became interested in this line of work in the 1960s and started training computers how to mimic human reasoning.

Since the intelligence of machines with machine learning capabilities has had significant effects on business, the scope of AI has greatly expanded (Oke, 2008). Before Siri, Alexa, or Cortana existed in 2003, the Defense Advanced Research Projects Agency (DARPA) developed intelligent personal assistants. This early work paved the way for the automation we see in computers today, including decision support systems and smart search systems that can be created to complement and enhance human abilities.

Why CyberAI?

Cybersecurity relies heavily on artificial intelligence (AI) in today’s era. Nowadays, there are a lot of bad actors using the internet to engage in illegal activities. Some of the cyberattacks issues that people always complain about are computer hacking and data loss (Dilek et al., 2015). To prevent hackers and con artists from accessing private data stored in cloud storage systems, AI has become increasingly important. By quickly identifying novel forms of malicious traffic or hacking attempts, it uses software with AI capabilities to expand human expertise (Bhagat, 2022).

What Can CyberAI Do for Organizations?

For businesses and organizations that use automation to boost output and process effectiveness, artificial intelligence (AI) is a crucial asset. Cybersecurity is one essential application that, according to IBM, makes the most use of AI today. Data breaches are becoming more frequent and sophisticated as a result of the rapid growth of digital transformation. AI has the potential to be a powerful weapon to fight against cyberattacks. Here are 4 CyberAI can do for organizations!

1. Anomaly Detection

Anomaly detection is defined as finding unusual occurrences, objects, or observations that are suspicious because they diverge significantly from expected patterns or behaviors. Effective anomaly detection procedures include the definition of “anomalous” for datasets, the setting of precise detection signals for analytical systems, and the input of feedback regarding accurate or inaccurate anomaly labeling for the system to learn. In this case, unsupervised machine learning can be used for anomaly detection on unlabeled data by analyzing the probability distribution of values using historical data to determine whether a new value is an anomaly.

2. Classification

Cybersecurity relies heavily on the detection and classification of cyberattacks. In order to understand how malicious attack samples differ from legitimate applications, it is crucial to analyze their behavior. AI algorithms learn from prior observations and apply that knowledge to new data. Classification process entails labeling artifacts with one of the categories (e.g., categorize a binary file into adware or ransomware categories).

3. Breach Risk Prediction

Businesses must be able to spot signs of compromise because breaches are unavoidable. By identifying “at risk” devices, exposing application vulnerabilities, and spotting malware and botnets, a good breach risk prediction is highly needed. Worry less, CyberAI can forecast how and where businesses are most likely to be attacked. Business can configure and improve controls and processes to more effectively increase its cyber resilience by using insights from AI analysis.

4. Threat Exposure and Incident Response

CyberAI can offer updated knowledge of threats to assist in prioritizing crucial actions based not only on what could be used to attack your business but also on what is likely to be used to attack your business. In addition, CyberAI can also offer better context for security alert prioritization and response, for quick incident response, and to surface root causes in order to mitigate vulnerabilities and prevent future problems.

All in all, CyberAI provides a proactive and robust protection which enables to respond faster than cyber-attackers, helping organizations predict an attacker’s next move and prepare an immediate response. Organizations that want to stay ahead in the digital transformation era should start investing in AI-based cybersecurity solutions now

For further information how AI can enhance your business, read more about how AI can improve your IT GRC and ways AI can lead to a successful digital transformation.