Why Machine Learning and AI Solutions Are a Must for Email Security

Email attacks against the enterprise have changed enormously over the past few years and have become increasingly sophisticated. Today, phishing attacks are the number one cause of data breaches within businesses and are consistent across all industries. Meanwhile, highly targeted Business Email Compromise (BEC) attacks have also become commonplace. The past few years have accelerated the volume of attacks as a result of the shift to remote operations in response to the global pandemic. Moreover, the pandemic has created disarray and uncertainty, which have allowed social-engineered tactics to be more successful than ever.

Today’s advanced types of email attacks are unique and highly dynamic, making them even more difficult to classify and identify. The problem from a security standpoint is that these attack techniques are able to evade traditional security measures such as secure email gateways (SEG), leaving organisations vulnerable to attack. Meanwhile, random code or visual differences can’t be easily perceived by the human eye. The result is that businesses are at a greater risk of compromise than ever before. 

To tackle these sophisticated, social-engineered attacks, businesses need more than robust technologies in place to stop large amounts of sophisticated spam and malware. They need a new generation of email security that can use advanced technology to deliver a fundamentally different approach to cybersecurity. Machine Learning and Artificial Intelligence (AI) are becoming vital tools in our fight against cybercrime and should form an important part of every company’s strategy and arsenal. 

What is Machine Learning and AI?

To understand how Machine Learning and AI are used in cybersecurity, we must first understand what these concepts mean.

At a very fundamental level, AI is a technology that enables a machine to simulate human behaviour. AI is based on statistics, psychology and cognitive science. What was originally designed to make computers more useful and capable of independent reasoning has evolved to deliver automation and formal reasoning.  

Machine Learning works to find hidden insights in data without being programmed to know where to look or what to conclude. The idea is that machines can learn and adapt through experience. AI, on the other hand, refers to a broader concept where machines execute tasks in an efficient but clever manner. AI uses machine learning and other advanced techniques to solve actual problems. Ultimately, AI aims to simulate human intelligence, but it can do so at an incredible scale, giving it superhuman potential. Additionally, the models and algorithms learn as they go, becoming smarter and more sophisticated with time. 

When we think of this in relation to cybersecurity, AI and Machine Learning can be used to detect malicious behaviour. Whereas in order for traditional solutions to categorise threats, they need to experience the presence of malware or malicious URLs to do so. Machine Learning and AI allow security technologies to recognise patterns, learn what the good or bad state looks like without these basic classifications. In fact, behavioural AI can analyse data, detect and recognise complex patterns, identify even the most subtle anomalies, and predict future outcomes. 

How is Machine Learning and AI Strengthening Email Security?

Abnormal is an email security solution that leverages advanced AI and Machine Learning techniques to understand, analyse, and protect organisations from email-borne threats. The solution starts by using cloud-native API architecture to integrate with both email and non-email data alongside existing solutions such as Microsoft Office 365. The system then creates a unified profile of every person within the business, mapping internal and cross-functional relationships and processes. It then uses all of this data to compare events against behavioural norms, thereby detecting risks that can’t be addressed by traditional methods SEG’s use. There are several benefits of implementing Abnormal’s solution:

  • Benchmarks normal end-user behaviour – through multi-channel analysis, the solution can detect anomalies outside the benchmark.
  • Accurately identifies compromised accounts – behavioural analysis can detect the slightest anomalies in end-user behaviour.
  • Continuously searches for compromised vendors – detects and stops suspicious emails from compromised vendors. 
  • Creates detailed case files of remediated emails – detailed incident reports allow informed decisions to be made in real-time.
  • Automatically remediates compromised accounts – in the event of a compromise, accounts are disabled in an instant and the security team is notified immediately.

With Abnormal Security, socially engineered attacks from compromised accounts can be stopped in their tracks and the complexities unravelled for security teams to address. Ultimately, by using behavioural AI, the solution modernises email security, reduces complexity, and increases the value of threat detection. 

How to Leverage Machine Learning and AI to Protect Your Business

Machine Learning and AI will undoubtedly form a crucial component in the future of email security. Ultimately, if your business wants a strong security solution, you need to bring these technologies together with a multi-layered and fully integrated approach. 

Contact InfoTrust today for a consultation on Abnormal Security’s cloud-native API-based solution and find out how you can leverage the power of Machine Learning and AI for comprehensive email protection, detection and response. 

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