Abstract: Methods and systems for detecting a phishing attack on a computer device can involve scanning one or more email messages, and separating email parts from the one or more email messages, in response to scanning the at least one email message. In addition, the email parts of the at least one email message can be subject to a feature extraction operation. The email features extracted from the email parts can be then analyzed to determine whether or not any of the email features contain suspected phishing content, confirmed phishing content and benign email content.

Abstract: Methods and systems for detecting a phishing attack on a computer device can involve scanning one or more email messages, and separating email parts from the one or more email messages, in response to scanning the at least one email message. In addition, the email parts of the at least one email message can be subject to a feature extraction operation. The email features extracted from the email parts can be then analyzed to determine whether or not any of the email features contain suspected phishing content, confirmed phishing content and benign email content.

Abstract: Methods and systems for calibrating a medical imaging system based on visual feedback are described. A method includes projecting one or more points of a target area (real world) of the medical imaging system as an overlay on the feedback frame, wherein the feedback frame is an image of the target area captured by an imaging device of a visual feedback system. One or more points of the target area are then located on the feedback frame. Further, the method includes improving calibration accuracy of the medical imaging system by minimizing difference between one or more projected points and one or more point located on the feedback frame below a predefined threshold. The difference is minimized via an iterative error correction mechanism.