Abstract:
Disclosed is a method and a system for detecting and managing phishing attack. The security product of the present invention enables a user to look at the activity of any other user and all of their owned devices before and after a phishing attack targeted at that user. The present invention also enables the user to look at the activity of the infrastructure and determine if an attack has occurred and what is the impact of that attack. The present invention also enables the user to view various attacks on their infrastructure.
Abstract:
Disclosed is a method and a system for AI-driven & AI-optimized decisions, actions, & workflows in process operations. The system has the ability to create, update, process, and link tickets automatically. The system can also automatically determine the transactions that should be converted into tickets. The system further processes any generated or created tickets through a set of AI models designed to produce classifications for tickets in real time and appends the AI driven classifications to the tickets. The system can analyze the content of the ticket and assign the ticket automatically to the appropriate ticket queue that is owned by a user or team.
Abstract:
The invention relates to novel betulinic acid derivatives of formula (I), wherein R is C(═CH2) CH3 or CH(CH3)2; R2 together with the adjacent carbonyl group forms a carboxylic acid, carboxylic acid ester or amide or substituted amide; R3 or R4 are hydrogen or aryl with the proviso that both are not independently hydrogen or alkyl or R3 and R4 are combined together to form an aryl ring optionally substituted with a group X, wherein X is selected from halogen, alkyl, cyano, nitro, alkoxy, amino or substituted amine; Y is N or O; and R1 is zero when Y is O, and R1 is hydrogen, alkyl or aryl alkyl when Y is N, useful for inhibition of tumor cancer cells.
Abstract:
Disclosed is a method and a system for using techniques to stitch cybersecurity, generate network risks and predictive mitigations. The method includes collecting data from several data sources and labeling events. The method includes creating a profile for each entity observed in the data with the behavior of the profile determined through the analytical analysis of the events in which the entity participates including the transference of labels from events to the entity. One or more profiles of an organization are identified that have changed and the change is processed using specific attack sequence detection to identify one or more risks associated with each profile. The method further includes notifying one or more users associated with the one or more profiles based on the one or more risks.
Abstract:
Disclosed is a method and a system a method and a system for auto learning, artificial intelligence (AI) applications development, and execution. Various applications or operations may be associated with training environment-agnostic AI models, automated AI app application performance monitoring, fault, quality and performance remediation through prediction of failures or suboptimal performance, privacy and secure AI training and inference mechanism for data and AI model sharing between untrusted parties, and building auto learning applications that can automatically learn and improve.
Abstract:
A dielectric resonator is disclosed. In one embodiment, the resonator includes i) a conductive case having a plurality of walls which together define an inner space, ii) a substrate placed at the bottom of the conductive case, and iii) a cylindrical dielectric resonator unit, mounted centrally on the substrate having a central longitudinal axis. The cylindrical dielectric resonator unit includes a dumbbell shaped hole located centrally in the resonator unit extending from a top to a bottom of the resonator unit. In one embodiment, the dumbbell shaped hole includes i) a top layer, ii) a bottom layer and iii) an intermediate layer sandwiched between the top and bottom layers. In one embodiment, the substrate and resonator unit are enclosed inside the conductive case.
Abstract:
Disclosed is a method and a system for using techniques to stitch cybersecurity, generate network risks and predictive mitigations. The method includes collecting data from several data sources and labeling events. The method includes creating a profile for each entity observed in the data with the behavior of the profile determined through the analytical analysis of the events in which the entity participates including the transference of labels from events to the entity. One or more profiles of an organization are identified that have changed and the change is processed using specific attack sequence detection to identify one or more risks associated with each profile. The method further includes notifying one or more users associated with the one or more profiles based on the one or more risks.
Abstract:
Embodiments of message organization and spam filtering based on user interaction are presented herein. In an implementation, user interaction with a plurality of messages in a user interface is monitored, which includes analyzing an amount of time spent by a user in interacting with each message. Subsequent messages may then be filtered based on the monitored user interaction. In another implementation, messages are processed that are received via a network using a spam filter that was generated based on monitored interaction of a user with previous messages. The processing results in a value describing a relative likelihood of importance of each of the processed message to the user. The processed messages are then arranged for display in an order, one to another, in a user interface based on respective values.