The growing role of AI in enterprise security 

Did you know that according to a study by Cybint, over 95% of cybersecurity breaches can be attributed to human mistakes? 

Today, enterprises are facing a huge onslaught of cybersecurity challenges due to the exponential growth of data, networks, devices, algorithms, and manual data processing systems. In response to these unprecedented security challenges, the value of AI (Artificial Intelligence) has increased like never before. Forward-thinking enterprises are turning to AI to enhance their cybersecurity efforts in the modern IT environment.  

So, what are the areas with the possible application of AI in cybersecurity? It’s amazing to contemplate that Ai could play a role in multiple areas like these: 

How is AI helping businesses? – Six use cases 

1. Human security analyst and SOC augmentation

This is one of the most common use cases to prove the role of artificial intelligence in cybersecurity. After all, AI will not replace human security professionals, but it will augment humans in specific areas where machines are more effective such as data analysis. The aim is to free up humans from time-consuming tasks. The incorporation of predictive analytics is a common activity in the security operations centre (SOC) workflows for querying large data sets.  

In this case, the cyber AI analysis program of Darktrace is highly useful in supporting human security professionals by surfacing high-priority events. It queries the massive pivots and data across networks to gather relevant context for investigations and sort out the low-priority cases. The cyber AI analysis utilizes a variety of deep learning, machine learning, and mathematical techniques to crunch multi-dimensional data, generate multiple queries at high speed and investigate various security threats simultaneously.  

 2. New attack recognition 

While conventional systems cannot keep a track of new malware every day, AI excel in this area. AI can spot potential malicious activities and cyber threats by using sophisticated algorithms that can zero in on unusual behaviour.  

AI systems can detect malware, ransomware attacks, run pattern recognition, and identify even the minute malicious behaviour before it impacts the system. The usage of predictive intelligence helps in analyzing the data curation by scraping through news, articles, and studies on cyber security threats. As the attack techniques are evolving like other advancements, the value of AI has also increased over time. AI helps in analyzing the huge amount of data sets, sources, outcomes, and types of events. The AI-based enterprise security system can provide intelligence on the latest cyberattacks, anomalies, and modern prevention strategies. It can help enterprises formulate prioritization decisions based on the latest knowledge of industry-specific and global security considerations and the likelihood of new threats. 

3. Behavioural analytics and risk scoring 

This analysis technique has been pioneered in modern industries like digital advertising, OTT platforms, and media, in addition to traditional sectors like financial services, insurance, and the like. These industries are utilizing behaviour analysis techniques to identify anti-fraud and authentication issues. For example, Mastercard leverages multi-factor data analysis to develop a dynamic user profile and assess risks at different events of the endpoint. The company utilizes deep learning and machine learning to analyze browser, traffic, surfing speed, typing speed of the user, keystroke and pressure, network, and location interactions, known versus new device connections, and more.  

Here, AI algorithms are used to analyze the behavioural patterns of users and devices, login parameters, geolocation, sensor data, and other key data sets to derive the likelihood of cyber security threats.  

4. User-based threat detections 

From the misuse of data to insider security threats, human action is also a major source of cyber security risks. Therefore, AI techniques have emerged to investigate user interactions with the IT environment and characterize user behaviour in the context of security attacks.  

The AI-based security system helps in identifying the user profiles and behavioural baselines to analyse security threats. Using machine learning models, AI analyses all the types of behaviour that could be performed across an attack lifecycle such as remote access, backdoor entry to software, hidden funnels, abuse of credentials, and the like. 

5. On-device detection across endpoints 

The rise of mobile device usage in enterprises has ushered in this kind of cybersecurity threat and changed the nature of security. Conventionally, the enterprises managed the typical endpoints like laptops but now, the employee’s mobile is the end-user. Whether a consumer, hacker, or employee, they are involved in communication channels, downloads, applications, and network interactions. When these mobile apps are in specific containers, it limits the conventional patch management practices. So, it is necessary to protect the mobile endpoint to secure the kill chain – from networks, phishing attempts, fake apps, or different types of malicious attacks.  

Here, there is a great value of AI as it can be leveraged across multiple attack vectors rather than deploying multiple detection systems for every vector. It will help in predicting the likelihood of security threats at any given point of interaction. 

6. Proactive security in disconnected environments 

As the devices and data are permeating the physical world, the ability to ensure security, and reduce the time to detect and respond to security concerns have come down to a question of computing power. The vast and complex technical infrastructures prevailing in enterprises today mean increased demand for security, efficiency, and safety of operations in mission-critical environments like energy, security, aviation, and defence.  

The intensive AI applications help in facilitating machine learning-based examination of files, documents, and scripts to determine the likelihood of malicious activities and analyses malware via on-premise support.  

What are the Best Tools for Artificial Intelligence in Cybersecurity? 

• Symantec's Targeted Attack Analytics 
  It is used to identify targeted private attacks. Machine learning and artificial intelligence are applied to the knowledge, processes, and capabilities of the security experts of Symantec.
• Sophos' Intercept X tool  
  It uses the deep learning neural network to function like a human brain. It gathers millions of features from files and decides where the file is harmful within some milliseconds.  
• IBM QRadar Advisor
  This tool counters cyber-attacks by utilizing the auto-examine signs of the security vulnerability. The solution also exploits synergies with other proven IBM products. For instance, IBM QRadar Advisor with Watson app complements the IBM QRadar Intelligence platform by bringing the power of cognitive AI to work on tasks like risk and incident analysis, triage, and response. 
• Vectra's Cognito 
  The identification of attackers and detection of security threats are automated in the Cognito tool. It collects cloud events, logs, behavioural algorithms, data on network usage to identify hidden attackers. 
• Darktrace Antigena 
  This is one of the most effective self-defence methods for the market today. Antigena provides the critical functionalities modern cybersecurity solutions need. But it takes a proactive approach and recognizes the role of digital antibodies to neutralize viruses and threats. It responds to malicious behaviour in real-time based on security threats. Explore more. 

Leverage AI to scale up your Cyber Security Strategy today  

With evolving global security threats, humans can’t respond to these automated attacks in real-time. To stay ahead of evolving cyber security threats, it is vital to adopt an integrated AI security solution and a team of security-certified professionals. The Darktrace Antigena tool protects from cyber-attacks including phishing, ransomware, cloud environment, and infrastructure threats. If you are looking to implement a one-stop security solution, Novigo can help you with the strategic execution and operations of your cybersecurity requirements.  Contact us now.