Phishing is a sophisticated social engineering attack that is created to steal the sensitive information of the victim such as credit cards or social security numbers and other sensitive data. To make the email look like it comes from trusted sources, most phishing attacks take the form of emails disguised. The subject line of that mail generally carries an urgent message in which it is required to drive immediate action, for instance, notice that an account has been compromised or that a service is about to be suspended.
The main aim of the attacker is to alarm the recipient and prompt immediate action, mainly downloading an attachment or clicking on a link without thinking about what they’re doing. That one click can result in a malware infection, which can lead to your private information getting stolen.
This scam is really worrisome for organizations as well as a major threat in the cybersecurity world. However, to detect and prevent phishing, there are several tools and techniques. One of the best tools for detecting and preventing phishing is artificial intelligence (AI). It works on algorithm basis and focuses on understanding as well as recognizing patterns from vast piles of data to create a system that can predict unusual behavior and anomalies. It evolves with time while learning patterns of normal behavior. These features of AI make it helpful in identifying phishing emails, spam, and malware.
You must be thinking How Artificial Intelligence (AI) will detect and prevent phishing attacks? What are the several ways AI can take on phishing attacks? This blog has answers to all your questions.
How Does Artificial Intelligence (AI) Detects Phishing Attacks?
As we all know that artificial intelligence (AI) can make email analysis faster as well as more accurate, but the main question arises here is that How exactly does AI work to detect and prevent phishing?
1. Looking for Anomalies and Warning Signals
A successful system based on artificial intelligence and machine learning is one that looks for anomalies as well as warning signals for phishing throughout the email, from the metadata to the message content. This includes, for instance, alerts based both on email behavior (e.g. forged senders) and message intent (such as urgent topics).
One of the main signs of a phishing attack is the sense of urgency in the message. If you got an email that requires quick action as well as have words that show urgency, the warning signal is lit. Artificial Intelligence (AI) then works to detect as well as understand the context of the message, checking if it is a common spam, a phishing attack or a legitimate message.
Let’s take the word “publicity” as an instance. In itself, the word may already be considered suspicious. However, an AI system seeks to understand more precisely whether or not the email is really a threat and how serious that threat is. This allows for a better distinction between phrases such as “Urgent: 30% OFF publicity” (in this case, indicating a simple spam) and “Fill in your card number right now to participate in the publicity” (in this case, indicating a phishing scam).
The exact logic applies to warning signs in the email header. For instance, AI identifies cases of email spoofing (forged senders), misspelled domains as well as other types of spoofing. The system significantly extends threat detection capabilities coupled with traditional engines such as SPF, DKIM and DMARC.
2. Analyzing the Message Context
AI has an ability to examine a message based on context which is another important point that makes AI one of the biggest defenses against phishing. In this way, an email is analyzed as a whole instead of just compared to other existing phishing scams.
The system will take into consideration, for instance, the presence or absence of a previous conversation, any data that the sender may be requesting in the email, the connection between the topic written in the subject and the message itself, among others.
Apart from this, to make the analysis highly accurate, AI-based email protection constantly learns from the data and the users and administrators feedback.
3. Understanding How Users Communicate
Nowadays, it is not easy to detect the frauds with the use of traditional email detection tools and security solutions. Specially, the type of fraud that hurts businesses the most today is very hard to detect. The reason for this is that it doesn’t involve the typical elements of a malicious email.
By opening a dialogue channel one by one, the hacker can send credible emails until he or she gets the person or target to perform a desired action. For instance, providing confidentiality, sata or sensitive data, making a bill payment, making a bank transfer, downloading a malicious file or malware.
It is necessary to use Artificial intelligence (AI) algorithms in preventing and detecting these specialized scams that can understand how users communicate. For instance, knowing their typical behavior, their textual patterns, as well as whether the context of the messages makes sense.
If there is anyone who wants to imitate the CEO of the company, for instance, the system must be able to identify changes in the executive’s communication pattern and block the attack before it causes any damage.
4 Ways Artificial Intelligence (AI) Can Take on Phishing Attacks
When Machine Artificial Intelligence stops adapting is the only instance when it fails. As technical development is updated daily, it is useful to note the below information to narrow down the knowledge gap and counter the attacks.
- To identify real-time threats, one should introduce Artificial Intelligence (AI) algorithms on every mobile phone, even on offline devices.
- To deduct the unnecessary hassle of unsecured passwords, these algorithms can help strengthen the security of mobile phones and double as an employee identification card.
- The evaluation of the efficacy of a cyber security strategy will be based on an enterprise’s ability to predict, comply, and deter threats.
- One should increase cyber security protection in a predictive manner. It is necessary to study the data from endpoint devices and predict any possibility instead of analyzing things after they have been executed. This will help to prevent any sophisticated breaching attempts at the right time.
As mentioned above, Artificial Intelligence (AI) is an important tool in detecting and preventing phishing. Usually, it uses data analysis and machine learning to examine metadata, content, context, and typical user behavior. In this way, it quickly and accurately identifies potential threats and prevents them from stealing your sensitive data.
Hope this guide has helped you understand how Artificial Intelligence (AI) helps in preventing phishing. Still have any questions or want to ask anything? Sennovate experts are just a call away. We’ll do our best to understand your needs and explain exactly how AI technology can protect you and your business.