In the United States alone, 9.7 billion emails reach their recipients’ inboxes every single day. But not all of them are as innocuous as they may seem. Some emails attempt to trick users into revealing their passwords, sharing sensitive data like banking details, or downloading ransomware-infested files.
Attackers don’t stick to the proven hits: they come up with new creative ways to trick users, leveraging new technologies like generative AI and techniques in the process. That’s why staying one step ahead of these new campaigns requires thinking outside the box of traditional cybersecurity approaches.
This is exactly where artificial intelligence and information security can come together. AI tools can be a game-changer in detecting phishing emails, malicious URLs, and infected attachments; automating incident response; and advancing threat intelligence. Here’s how.
Why AI and Machine Learning Cyber Security Matters More Than Ever in 2024
According to Verizon’s 2024 report, 68% of data breaches involve some form of human error. It can span from clicking a malicious link seemingly leading to unbiased websites to being tricked into authorizing a payment to fraudsters. I recommend only visiting verified sites with promotions, such as an essaypro coupon code.
Another survey, this time by ProofPoint, revealed that almost all users who took a risky action – 96% – knew they were exposing themselves to a cybersecurity risk.
Phishing remains a top concern for individuals and businesses alike, with 45% of phishing attacks falling under the spear phishing category. Business email compromise (BEC) and ransomware attacks are also among the most common attack vectors.
The year 2023 also marked the proliferation of a new attack type: callback phishing, or telephone-oriented attack delivery (TOAD). According to ProofPoint, an average of 10 million TOAD messages were sent monthly in 2023.
Why Email Security Matters
Failing to prevent a phishing attack can lead to disastrous consequences, with the most common ones being:
- Loss of data or intellectual property
- Ransomware infection
- Breach of customer data
- Compromised login credentials or accounts
- Widespread network outages or downtimes
As phishing becomes more prevalent, personal identity theft prevention is vital. Victims of phishing attempts frequently face identity theft, which occurs when attackers use personal information to even go as far as taking loans. Implementing personal identity theft protection or credit monitoring services can help detect unlawful use of sensitive information and deal with the aftermath in case of such breaches.
Generative AI Entered the Chat
Yes, phishing has been around for decades. However, the proliferation of ChatGPT and similar GenAI chatbots made it a lot easier to create highly personalized, sophisticated phishing content across a variety of languages.
GenAI also contributed to a substantial year-on-year rise in the number of BEC attacks in countries like Japan (35%), Korea (31%), and UAE (29%). The technology enabled attackers to create convincing content in a foreign language quickly and at scale.
Artificial Intelligence: What’s in the Name?
Artificial intelligence has become an umbrella term for anything from a predictive analytics engine to chatbots like ChatGPT and image generators like Stable Diffusion. So, before we jump into the intersection of AI and information security, let’s make sure we’re on the same page regarding what AI is.
Artificial intelligence, in its broadest meaning, enables applications to simulate human intelligence for purposes like:
- Reasoning and problem-solving
- Knowledge representation (answering questions)
- Planning and decision-making
- Natural language processing
Artificial intelligence comprises three major technology subsets:
- Machine learning (ML): AI applications that learn from historical data
- Deep learning: ML systems designed to imitate human brain functioning
- Generative AI (GenAI): Deep learning models capable of creating new content
Applications of AI span:
- Recommendation systems
- Personalized advice
- Virtual assistants
- Sentiment analysis
- Language translation
- Data analytics
- Natural language processing
- Spam filtering
- Classification and labeling
Can AI Do Cyber Security?
Yes, and cybersecurity specialists are already employing AI for this very purpose. Here’s how cybersecurity tools leverage various AI technologies to protect its users:
- Natural language processing (NLP) interprets content written in natural language
- Machine learning (ML) algorithms recognize patterns based on past incidents to identify threats
- Data mining collects, processes, and analyzes large datasets to reveal patterns in security incidents and gain insights into them
- Predictive analytics algorithms predict potential threats based on historical data
- Behavioral analytics algorithms detect anomalies in user behavior
- Automated decision-making enables prompt incident response once the threat is identified
How Is AI Used in Cybersecurity to Prevent Email Threats?
Artificial intelligence, in all of its various forms, can power phishing detection, threat intelligence collection, incident response, and more.
Content Analysis
Powered by NLP and ML, AI tools can analyze the contents of all incoming emails and detect malicious links or suspicious patterns in the text or email metadata. AI can also identify whether the email deviates from usual communication patterns.
For instance, if the email seemingly comes from a powerpoint presentation writing service but contains a link leading to a completely unrelated domain name, AI can automatically flag it as suspicious.
AI-powered content analysis can scan inbound emails for:
- Business email compromise attacks
- Vendor fraud
- Credential phishing
- Suspicious links
- Malware
Account Takeover Detection
The proliferation of cloud email has enabled attackers to exploit system misconfigurations and bypass authentication to gain access to legitimate email accounts. Through behavioral analysis, AI tools can detect suspicious activity in a given email account and secure it before it can be used to spread malware or steal data.
Threat Intelligence
Threat intelligence feeds were traditionally put together manually, meaning they couldn’t be updated instantly. AI tools can automatically add newly identified attacks to those feeds, enabling real-time threat intelligence. AI also allows email security tools to continuously learn from those feeds so that they can identify the latest attack vectors, patterns, and campaigns.
Incident Response
Once an email is flagged as a threat, AI tools can automatically quarantine it, ensuring it doesn’t reach its intended recipient – and preventing risky behavior that may lead to a security incident. Or, if a corporate email account activity shows signs of a takeover, AI tools can force a password reset or revoke access permissions for sensitive data.
Multi-Channel Defense
AI tools can go beyond analyzing the inbound and outbound email contents and account activity. In combination with data from other sources, such as internal messaging tools, AI tools can detect anomalous email activity and content with an even higher rate of accuracy.
In Conclusion
Implementing AI-powered cybersecurity tools allows for detecting threats more efficiently, leveraging real-time threat intelligence, and automating incident response to mitigate damage.
That said, AI isn’t a silver bullet when it comes to ensuring cybersecurity. As human error is a major factor in security incidents, educating yourself and your team on specific threats will go a long way.
