Phishing is a social engineering attack commonly used by cyber attackers that uses fraudulent manipulation tactics to trick corporate employees into clicking suspicious links, opening infected emails, or exposing their account information. According to a Cisco research report, 86% of enterprises have encountered phishing attacks, and as long as one internal employee falls victim to a phishing attack, the security of the entire organization's network system may be compromised.
Phishing is not strictly a "hack", but victims often suffer very serious losses. There are many popular anti-phishing tools that can protect enterprises, but to minimize the harm of phishing, enterprises should prioritize and deploy real-time detection technology. This article summarizes 5 real-time detection techniques that can help quickly identify and prevent phishing incidents from occurring.
01. User behavior analysis
"A wolf in sheep's clothing" cannot hide the true nature of a wolf! The behavior of legitimate users is very different from the behavior of malicious people. User Behavior Analysis (UEBA) is a powerful technology for detecting phishing attacks in real-time by continuously monitoring user behavior (such as browsing patterns, mouse movements, and keystrokes) to establish a security baseline for normal user activity. Any deviation from this baseline will be flagged as a potential phishing attempt. For example, when a user suddenly receives an email with a suspicious link, once he actually clicks on the email, the system will identify it as abnormal behavior and trigger an alert. With real-time user behavior analysis, organizations can become more adept at identifying phishing attacks that attempt to imitate legitimate user actions.
02. URL analysis and filtering
URL filtering is a technology that controls web page access based on users' URL requests. By allowing or prohibiting users from accessing certain web resources, the purpose of regulating online behavior and reducing security risks can be achieved. URL filtering can limit URL access based on URL classification, specific URL analysis, and other methods.
In real-time phishing attack detection, enterprises can leverage URL and domain reputation analysis tools to identify potentially malicious links and websites, and compare URLs to known phishing databases and blacklists to assess their reputation and trustworthiness. , once suspicious links are discovered, they should be flagged immediately to prevent users from accessing them. In addition, enterprises can use machine learning models to analyze the structure of URLs and look for clues of phishing attempts, such as small spelling mistakes or extra characters in the domain name. By verifying URLs in real time, enterprises can stop phishing attacks before harm occurs.
03. Email content analysis
Analyzing email content in real time is a key part of quickly detecting phishing attacks. Enterprises can use advanced scanning tools to scan inbound email content, such as email headers, attachments, and embedded links, in real time to identify potential phishing threats.
Some advanced content detection tools can also analyze email content for phishing indicators, including suspicious keywords, misspelled domain names, grammatical errors, or requests for sensitive information. By inspecting email content in real time, businesses can flag suspicious information in a timely manner and prevent users from falling victim to phishing attempts. In addition, analyzing attachments and embedded links can identify malicious files or redirect attempts, protecting users from potential malware infections.
04. Threat intelligence sharing
Timely sharing of threat intelligence can help enterprises detect phishing attacks in real time. By actively participating in threat intelligence networks and leveraging information from other security platforms, enterprises can access vast amounts of real-time threat data and discover attacks in progress.
Shared threat intelligence also enhances an organization's ability to detect emerging phishing attack patterns and stay abreast of the latest techniques used by cybercriminals. This collaborative intelligence sharing can help companies stay safe from ever-changing phishing attacks, further strengthening their digital security posture.
05. Use AI technology
Using AI technology to deal with phishing attacks will be a key part of real-time phishing attack detection. When AI technology represented by machine learning is combined with traditional attack detection capabilities, the detection efficiency of phishing attacks will be greatly improved. Machine learning algorithms can analyze large amounts of data, including email content, website characteristics and user interactions, to identify patterns and trends related to phishing attacks.
By training these AI algorithms on previous phishing data, they can learn to identify key indicators of common phishing attacks and adapt to emerging attack techniques. Through continuous learning, AI technology improves the accuracy of detecting real-time phishing attacks while reducing false positives, ensuring more effective protection against ever-changing phishing threats.
Reference link:
https://www.loginradius.com/blog/identity/real-time-techniques-detect-phishing-attacks/