Abstract:
PROBLEM TO BE SOLVED: To utilize a time when a user is concentrating on a challenge/response type test.SOLUTION: Advertisements are introduced to a challenge/response type test so that a chance of improving a brand power can be presented to a user. When the user tries to perform an access to content, a CAPTCHA test is presented to the user. The CAPTCHA test includes advertisements (for example, a logo, label or the like) and relevant questions to be answered by the user. The advertisements are selected on the basis of information relevant to the user. When the user succeeds in responding to the questions and/or making a response within a fixed time, a reward can be determined. On the basis of a cumulative response to the CAPTCHA test, cumulative total points can be kept for the user. The difficulty of the CAPTCHA test to be presented to the user can be increased according to the reward.
Abstract:
Systems and computer program products implement methods for detecting a man-in-the-middle (MITM) during HTTPS communications. The methods include establishing a TCP connection for the retrieval of a web page from a domain name using an alternate IP address that is different from the IP address of the target domain where receipt of the target web page in response to a HTTP GET message indicates that a MITM is present, using a domain name as the SNI in a TLS connection and an alternate domain name in a HTTP GET message where receipt of a target web page of the alternate domain name indicates that a MITM is present, and generating an alternate domain name using a domain generation algorithm and using the generated alternate domain name as the SNI in the TLS message where receipt of a certificate for the generated alternate domain name indicates that a MITM is present.
Abstract:
Methods, computer program products, and systems are presented. The methods include, for instance: identifying a training data set and defining a window for an initial beta value representing bias tolerated in formulating expectation conditional to each feature vector from the training data set. The conditional expectations are parallelly regularized by use of DNA computer. Amongst numerous combinations of candidate models, a best fit ensemble is produced as the machine learning model for predicting targeted outcomes based on inputs other than the training data set.
Abstract:
From a live streaming of a main content, an already streamed portion of the main content is analyzed to identify an occurrence of a climactic event in the main content. Based on the analysis, a set is constructed of feature values that are representative of the climactic event in the already streamed portion of the main content. A non-climactic period is forecasted during which a likelihood of an occurrence of any climactic event is below a threshold likelihood. A secondary content is inserted in the live streaming of the main content during the non-climactic period, such that a likelihood of the secondary content insertion interrupting the live streaming during a second climactic event is less than a second threshold of likelihood. The live streaming of the main content is continued after the secondary content is completely transmitted in the live streaming.
Abstract:
From a live streaming of a main content, an already streamed portion of the main content is analyzed to identify an occurrence of a climactic event in the main content. Based on the analysis, a set is constructed of feature values that are representative of the climactic event in the already streamed portion of the main content. A non-climactic period is forecasted during which a likelihood of an occurrence of any climactic event is below a threshold likelihood. A secondary content is inserted in the live streaming of the main content during the non-climactic period, such that a likelihood of the secondary content insertion interrupting the live streaming during a second climactic event is less than a second threshold of likelihood. The live streaming of the main content is continued after the secondary content is completely transmitted in the live streaming.
Abstract:
Systems and methods for automated resolution of over-specification and under-specification in a knowledge graph are disclosed. In embodiments, a method includes: determining, by a computing device, that a size of an object cluster of a knowledge graph meets a threshold value indicating under-specification of a knowledge base of the knowledge graph; determining, by the computing device, sub-classes for objects of the knowledge graph; re-initializing, by the computing device, the knowledge graph based on the sub-classes to generate a refined knowledge graph, wherein the size of the object cluster is reduced in the refined knowledge graph; and generating, by the computing device, an output based on information determined from the refined knowledge graph.
Abstract:
Various methods for detecting a man-in-the-middle (MITM) during HTTPS communications are disclosed including, in some aspects, establishing a TCP connection for the retrieval of a web page from a domain name using an alternate IP address that is different from the IP address of the target domain where receipt of the target web page in response to a HTTP GET message indicates that a MITM is present, using a domain name as the SNI in a TLS connection and an alternate domain name in a HTTP GET message where receipt of a target web page of the alternate domain name indicates that a MITM is present, and generating an alternate domain name using a domain generation algorithm and using the generated alternate domain name as the SNI in the TLS message where receipt of a certificate for the generated alternate domain name indicates that a MITM is present.