Abstract: Apparatus and methods for using deepfakes defensively to detect fake, spoofed, and hoax accounts and posts on social media and elsewhere are provided. A program may gather verified images or writings of a target individual. The program may analyze the verified images and writings to create a baseline. The program may use deepfake algorithms to create exemplar deepfake images or writings. The program may store the data in a database. The program may search a network for social media accounts or posts that may meet the baseline and determine whether they are legitimate or illegitimate by comparing the contents of the accounts or posts with the exemplar deepfakes. When the program determines the accounts or posts are illegitimate, the program may initiate a takedown of those accounts or posts. The program may use machine learning algorithms to refine itself and become more accurate.

Abstract: In an embodiment, the present system can primarily determine the pilot bore profile of a horizontal directional drill (HDD) based on the number of rod sections added and the pitch reading from the underground transmitter at the front of the drill string (as communicated to the HDD drill rig via the walk-over locator), with such calculations being able to be made at the HDD drill rig and/or related remote display on the HDD drill rig. That is, since the length of a given rod section is known and the pitch readout is provided by the underground transmitter, the change in the overall depth of the drill string can be calculated, for example, on drill rod to drill rod basis based on rise over run geometry. The walk-over locator can then be used for a secondary confirmation of the actual depth, if conditions permit (e.g., in range of a direct walk-over).

Abstract: Methods for securing an electronic communication is provided. In a registration process, an anti-phish, personalized, security token may be created and/or selected for a predetermined account. The token may be stored in a database at an enterprise location. An electronic communication may be generated at a third-party location on behalf of the enterprise. The communication may be forwarded from the third-party location to a recipient associated with the account. The communication may be intercepted at an edge server. The edge server may be located at the third-party location or the enterprise location. The edge server may be in communication with the database. The edge server may select, from the database, the anti-phish token that is associated with the account. The selected token may be injected into the communication. The communication with the token may be transmitted to the recipient.

Abstract: An apparatus, method and computer program product are provided for predicting tire temperature levels. In one example, the apparatus receives input data indicating attributes of the target vehicle and attributes of target routes for the target vehicle. The apparatus causes a machine learning model to generate output data as a function of the input data, where the output data indicate a subset of the target routes of which the target vehicle can successfully traverse while using the at least one spare tire. The machine learning model is trained to generate the output data as a function of the input data based on training data, where the training data indicate events in which vehicles used spare tires to traverse routes. The training data indicate attributes of the vehicles and attributes of the routes.

Abstract: A portable locator device includes a display for providing instructions to an operator, an interface for receiving inputs from the operator, a positioning system receiver for receiving locating signals, and a controller operatively coupled with the display and communicatively coupled with the interface and the positioning system receiver. The controller is configured to determine a first position of the portable locator device, receive a first input from the interface indicative of an ending position proximate to the first position, determine a second position of the portable locator device, receive a second input from the interface indicative of a starting position proximate to the second position, determine a virtual drop-line between the starting position and the ending position, and provide instructions via the display for moving from the starting position to the ending position along the virtual drop-line.

Abstract: A system for network augmentation using virtual reality is provided. The system may include uploading data relating to a network, to a network augmentation system. The system may include retrieving data relating to network standards. The system may include retrieving data relating to historical network vulnerabilities. The system may include an artificial intelligence (“AI”) module. The AI module may be configured to analyze the network and determine possible network vulnerabilities. The AI module may be configured to output a three-dimensional map of the network to a display module. The three-dimensional map may be displayed on the display module. The three-dimensional map may include the identified possible network vulnerabilities. The system may be further configured to overlay solutions to the possible network vulnerabilities on the three-dimensional map.

Abstract: A location and product based task reminder is provided to p rompt a user's mobile handset a product based task reminder based upon proximity of the user's mobile handset relative to a task facilitation location. A task reminder system is provide in which reminders are based upon proximity of the user's mobile handset relative to a task facilitation location.

Abstract: Methods and system are provided for tuning an artificial intelligence (“AI”) system. The methods and system may include training the AI system to identify distinct users their distinct interactions. The training may include receiving datatsets related to a plurality of distinct users and their plurality of distinct interactions. The AI system may parse the datasets to arrive at a plurality of sets of distinct interactions performed by respective distinct users, each distinct interaction may be associated with a level of security clearance. The AI system may receive a request from a user to access information. The methods and system may include the AI system initiating a communication with the user. The communication may be compared with the each set of distinct interactions until a user and level of security can be identified. The AI system may prompt the user to access information on the level of security clearance identified.

Abstract: A system may be used by an entity to determine and reduce risks that may result from employees communicating with clients or others using unauthorized communications channels. The system may monitor communications over authorized communication channels or obtain notifications from a monitoring system for explicit or implicit references to the use by employees of unauthorized communications channels. An AI/ML scoring engine may generate a communication-specific risk score that may be used to understand the degree of risk posed by the communication. The scoring engine may also generate an employee specific risk score that accounts for employee specific risk-related factors that may affect the risk associated with the communication. The risk scoring may be used to cause automated risk reduction operations to be performed, such as providing alerts to an employer or employee of risk issues or halting trading or communications by the employee.

Abstract: Apparatus and methods for an artificial intelligence implemented termination by an auditor artificial intelligence (“aAI”) of a malicious artificial intelligence (“mAI”) are provided. The aAI may detect a mAI on a network and determine which data the mAI can access on the network. The aAI may then degrade all or part of the data in various ways to prevent the mAI from producing valid content based on the data. The aAI may also create code and inject the code into the mAI to degrade the mAI's operations. As the mAI may rely on valid data to produce valid output, degrading the data may degrade the mAI.

Abstract: Apparatus and methods to verify human interaction through an encrypted channel are provided. A human verification program may create an encrypted channel between two or more devices when a communication between users of the devices is started. Data may be transferred over the encrypted channel when a user performs a verifiably human action. The data may be analyzed to determine whether the user is more likely than not a bot. The channel may be collapsed when a pre-determined condition is satisfied.

Abstract: Artificial intelligence (AI) systems may manipulate search results about an entity to inject a predetermined bias into the search results. A bias reduction artificial intelligence (AI) system and method may perform the same automated search about the entity on open source and closed source AI systems. The AI-generated search results for the open and closed source AI systems may be compared to determine differences in results. The differences may be analyzed to determine attempts by the AI systems to manipulate search results about the entity to inject predetermined bias. If an attempt at predetermined bias is identified, the bias reduction AI system may reduce the predetermined bias by sharing data about the entity between the open source AI system and the closed source AI system to cause the system to use machine learning to update the algorithms and the first and second data sets. Incentives may also be provided to the open and closed source AI systems to reduce biases.

Abstract: Apparatus and methods to verify human interaction through digital tokens are provided. A human verification program may create a principal digital token and assign it to the profiles of a plurality of users. When a first user of the plurality of users requests verification that a second user of the plurality of users is human and not a bot, the program may transmit the principal token to the second user. The second user may perform a verifiably human action and create a secondary token. The secondary token may be transmitted to the program. The program may analyze the secondary token and create a limited verification token when the second user is human and not a bot. The verification token may be transmitted to the first user.

Abstract: A personal artificial intelligence (AI) system may be used to conduct business with one or more entities. The personal AI system may automatically replicate security rules from another AI system to provide initial security rules and may adjust the initial security rules based on information about the user to generate revised security rules. The rules adjustments may also be based on the entities with which the user does business. An AI firewall may be generated to control access to the personal AI system by a second AI system, with which business may be conducted. To permit interactions with the second AI system, the AI firewall may require that the second AI system provide the personal AI system with data relating to previous transactions between the user and the operator of the second AI system. The data may include the monetary amount of each of multiple recent transactions.

Abstract: Methods and system are provided for tuning an artificial intelligence (“AI”) system. The methods and system may include training the AI system to identify distinct users their distinct interactions. The training may include receiving datatsets related to a plurality of distinct users and their plurality of distinct interactions. The AI system may parse the datasets to arrive at a plurality of sets of distinct interactions performed by respective distinct users, each distinct interaction may be associated with a level of security clearance. The AI system may receive a request from a user to access information. The methods and system may include the AI system initiating a communication with the user. The communication may be compared with the each set of distinct interactions until a user and level of security can be identified. The AI system may prompt the user to access information on the level of security clearance identified.

Abstract: Systems and Method are provided for an Anti-Pattern Captcha. Methods may include AI software receiving a request from a user to access a system or website, the request comprising user credentials. Methods may include the AI software identifying a human user associated with the user credentials. Methods may include the AI software compiling data related to a plurality of unique behavior patterns associated with the human user when interacting online. Methods may include the AI software analyzing the compiled data to establish the unique behavior patterns. Methods may include the AI software presenting a challenge to the user. Methods may include the AI software verifying that the user is the human user upon a response to the challenge that deviates from at least one of the unique behavior patterns. Methods may include the AI software prompting the user to interact with the system or website upon verification.

Abstract: Artificial intelligence (AI) impersonation detection using an AI model is provided. Methods may train an AI model. The training may provide the AI model with a first dataset including a communication between two or more human users, a second and third dataset including an impersonation of the communication by a public AI model and a private AI model respectively. Methods may identify a first identifier set in the first dataset, a second identifier set in the second dataset and a third identifier set in the third dataset. Methods may create a parameter range for the first, second and third identifier set. The methods may include monitoring a production communication using the AI model. The AI model may compare the production communication with the parameter ranges. Methods may identify a smallest comparison value. Methods may, based on the identified smallest comparison value, identify the origin of the production communication.

Abstract: A method for securing communications received at an automated chatbot within an entity network is provided. The method may enable securing the communications by monitoring inputs received at the automated chatbot in order to identify whether there may be a probability that the input is generated by an artificial intelligence (“AI”) program. The method may include receiving a request to initiate a chat session at the automated chatbot. Each input received at the automated chatbot may be simultaneously retrieved by a processor associated with the chatbot for verifying. Each input may be analyzed by an AI auditor application in comparison to trained data stored in an AI model. The trained data may include characteristics that may be associated with input generated by the AI program. When any inputs correspond to the trained data, the AI auditor may pause the chat session at the automated chatbot and/or terminate the chat session.

Abstract: Systems and methods for an artificial intelligence-based auditor of artificial intelligence may be provided. The artificial-intelligence-based auditor may operate on one or more hardware processors. The artificial intelligence-based auditor may continually scan one or more operating artificial intelligence systems for productivity and operability. The scan may identify a data source powering the one or more operating artificial intelligence systems. The scan may measure a delta between an output from each of the one or more operating artificial intelligence systems. The scan may identify trends in quality of the one or more operating artificial intelligence systems. The scan may analyze instances where the one or more operating artificial intelligence systems outputted data outside of a parameter range. Based on the scan, the auditor may label each of the one or more operating artificial intelligence systems as positive, neutral or negative.

Abstract: Apparatus, methods and systems for continual biometric authentication of a user on a user device is provided. Methods may create, for the user, a biometric authentication reference model. Methods may store the biometric authentication reference model at a database associated with the user device. In response to an instantiation of a session by the user on the user device, methods may execute a continual biometric scan. The scanning may be executed until the session is terminated. Methods may identify a number of comparison points between the scanned and stored biometric identifiers. In response to determining that the number of identified comparison points is below a predetermined threshold number of comparison points, methods may initiate a passcode request. The passcode request may request a confirmation of a preset user-selected passcode. In response to determining that the passcode response does not match the preset user-selected passcode, methods may terminate the session.