Abstract: A system for monitoring and optimizing fuel consumption by a genset at an oil rig is described. Gensets require large amounts of fuel to initiate and to maintain in a standby, idling position. The system accesses data in a drill plan to determine the present and future power requirements and initiates gensets if needed; otherwise gensets can be shut down. Excess power can be stored in a power storage unit such as a capacitor, battery, or a liquid air energy storage unit.

Abstract: Anti-impersonation techniques using device-context information and user behavior information from a session. The session can include a time period where a user of the client computer is performing an activity on the client computer (e.g., the session includes the user logging into an account online). The behavior information can include information on ways the user uses user input devices during the session. The device-context information can include HTTP session information. The techniques can include generating feature vector(s) for the received information, and comparing the feature vector(s) against model(s) of related historical information. The comparisons can provide level(s) of deviation of the feature vector(s) from the model(s). Also, the techniques can include determining whether the session is anomalous or normal according to the level(s) of deviation, and performing a security action in response to determining the session is anomalous.

Abstract: Technologies for classification of web security certificates using artificial neural networks. Some of the example technologies disclosed herein are directed specifically at classification of TLS certificates using artificial neural networks. The technologies include methods for identifying malicious use and generation of web security certificates, by using deep neural networks. In one example embodiment, content of TLS certificates can be used as input for deep neural networks to successfully identify certificates of malicious actors as well as malicious patterns used by attackers.

Abstract: Phishing enhancement and phishing detection enhancement technologies. The technologies can include determinations of an effectiveness rate of one or more phishing threat actors. The technologies can also include selection of effective URLs from at least one effective phishing threat actor. The technologies can also include generation or adjustment of a phishing system using a machine learning process to identify patterns in the selected effective URLs that enable the selected effective URLs to avoid detection by the phishing detection system. The technologies can also include generation of synthetic phishing URLs using the phishing system and the identified patterns. The technologies can also include adjustments or training of the phishing system or the phishing detection system according to the synthetic phishing URLs to enhance the systems.

Abstract: Anti-impersonation techniques using device-context information and user behavior information from a session. The session can include a time period where a user of the client computer is performing an activity on the client computer (e.g., the session includes the user logging into an account online). The behavior information can include information on ways the user uses user input devices during the session. The device-context information can include HTTP session information. The techniques can include generating feature vector(s) for the received information, and comparing the feature vector(s) against model(s) of related historical information. The comparisons can provide level(s) of deviation of the feature vector(s) from the model(s). Also, the techniques can include determining whether the session is anomalous or normal according to the level(s) of deviation, and performing a security action in response to determining the session is anomalous.

Abstract: Technologies for classification of web security certificates using artificial neural networks. Some of the example technologies disclosed herein are directed specifically at classification of TLS certificates using artificial neural networks. The technologies include methods for identifying malicious use and generation of web security certificates, by using deep neural networks. In one example embodiment, content of TLS certificates can be used as input for deep neural networks to successfully identify certificates of malicious actors as well as malicious patterns used by attackers.

Abstract: Phishing enhancement and phishing detection enhancement technologies. The technologies can include determinations of an effectiveness rate of one or more phishing threat actors. The technologies can also include selection of effective URLs from at least one effective phishing threat actor. The technologies can also include generation or adjustment of a phishing system using a machine learning process to identify patterns in the selected effective URLs that enable the selected effective URLs to avoid detection by the phishing detection system. The technologies can also include generation of synthetic phishing URLs using the phishing system and the identified patterns. The technologies can also include adjustments or training of the phishing system or the phishing detection system according to the synthetic phishing URLs to enhance the systems.

Abstract: An anchor balloon for conducting peripheral vascular disease procedures in an remote entry point such as an opposite extremity is provided, and includes a flexible catheter, which includes a wire lumen and a balloon lumen with a control port for connecting to balloon control and a balloon inflation port; and, a compliant anchor balloon connected near the flexible catheter distal end.