Machine Vs Attacker: Using Machine Learning for Early Phishing Detection

Phishing Detection
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Seventy percent of the damage from a phishing attack occurs within the first hour of its launch. When it comes to phishing, speedy detection and takedown are crucial in helping organizations avoid hefty losses.

Traditional phishing detection methods lack the speed and accuracy to reliably catch all malicious links, leaving users open to attack, and organizations open to suffering the consequences. Email continues to be the primary delivery vehicle for most malware due to its effectiveness, especially in the targeted attacks within which phishing campaigns thrive.

When phishing is not detected in a timely manner, the consequences can be grave. Account takeover, or when a criminal gains illegitimate access to an account and subsequently uses it for profit, costs between $6.5-7 billion per year. Business Email Compromise, a highly targeted form of spear phishing, causes $5.3 billion in exposed losses. However, financial losses are not the only consequences of phishing attacks. If a user’s credentials are exposed in an attack against an organization whose services they use, they will lose trust both in the organization and its online transactional channels. The reputational losses combined with customer loss can add up to catastrophic damages to an organization.

So, what can organizations turn to in lieu of ineffective, outdated detection strategies? The answer lies in predictive URL classification models that employ the latest in machine learning technology. The models are trained to identify the key features of domain names, such as number sequences and amount of punctuation, using their training to rapidly analyze the risk potential of any given URL. After the machines sort through billions of data points, they then send the most at-risk URLs to human analysts to verify the legitimacy of the URLs. The detection process becomes more powerful than ever through the combination of machine learning and human intelligence.

Easy Solutions Detect Safe Browsing

Detect Safe Browsing (DSB) from Easy Solutions uses state-of-the-art predictive URL classification models to protect its customers from phishing attacks. The system, tested for accuracy against other machine learning models, is able to quickly and accurately determine if a URL is risky. From there, the information is sent to the Easy Solutions’ 24/7/365 Security Operations Center in order to determine if the URL redirects to a phishing site.

Phishing Detection
24×7 Monitoring for Complete Coverage

Additionally, Easy Solutions provides automated mitigation, including automatic site takedown requests, URL submissions to safe browsing providers, and real-time blacklisting of the URLs on customer endpoints. This means that, within minutes of the first user coming upon a phishing site, the entire customer base of an organization is automatically protected from the threat.

Click here to learn more about Detect Safe Browsing.

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