Security X: Accelerated protection against critical threats


End to end vulnerability management, detection & response


What is Homoglyph?


In a Homoglyph Attack, also known as domain spoofing, an attacker tries to fool humans and computer systems by using such characters and symbols which may appear visually similar to characters used in the real domain but are different. Users are lured into clicking on the fake domain and redirected to a suspicious domain via which the attacker releases malware and collects sensitive information.



How can SecurityX help?

  • Monitoring network packets in real-time: When it detects domains containing suspicious-looking character sets, it automatically prevents access to that domain.
  • Alerts to potential attacks & spoofed websites: SecurityX continuously monitors and alerts you to potential attacks and spoofed websites. Once such sources are identified, SecurityX immediately removes them.
  • Safeguards company’s branding: Our team of specialists follow a foolproof remediation protocol to effectively mitigate the risks to your domain while helping you retain the company’s reputation.


Process Implemented Using Neural Network



We at SecurityX use a cutting-edge solution known as “Siamese Convolutional Neural Network (CNN).” to detect homoglyphs without the need to provide paired data.

Instead of comparing strings to a standard list to detect the homoglyph, CNN uses a “learned” metric system. CNN algorithms are built to detect the visual similarity of the rendered strings. It does so by converting the domain names to feature vectors or images. These images are then indexed using randomized KD-Trees to perform a comparison. When a new domain name is observed, it is converted to an image and searched in the KD-Tree index to find any visually similar matches. If a match exists, then a homoglyph attack is detected. This technique shows a considerable 13% to 45% improvement over baseline techniques.


Result-driven Anomaly detection



Our end-to-end anomaly detection system is useful in the real world to safeguard users’ critical information by preventing them from any such attack.
It detects anomalies across the business quickly and efficiently while reducing incident-related costs significantly. Built with a robust defense system, the SecurityX anomaly detection system works to handle any plausible threats at a lightning speed.


Accelerating Network Security with Artificial Intelligence & Machine Learning


Using artificial intelligence (AI) along with machine learning (ML), we can help catch data abnormalities even before they impact your business.



Disruptive technology to protect your business



Using AI models with ML is that they can be trained to automatically analyze datasets, decide what’s normal or abnormal behavior, and identify breaches in patterns quickly without any human intervention. With continuous self-learning mechanisms and the goldmine of massive knowledge it collects, the AI/ML model perpetually is in a state of predicting future anomalies rather precisely.
We developed state-of-the-art Machine Learning to predict whether there is an attack or not — in real-time. Our system was found to be accurate 99% of the time. For evaluation purposes, we compared our performance with other baselines and were found to outperform them.


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