Bank of America Corporation

Vasuki Anand

Shailendra Singh

Prashant Khare

Rajesh Agarwal

Sandeep Kumar Chauhan

Nandini Rathaur

Amardeep Singh Talwar

Pushpa Neelakantan

Kalyanasundaram Ramanathan

Tushar Agarwal

A processor performs a first scan of an environment associated with a software application and determines a first set of parameters indicative of characteristics of the environment. The processor performs a second scan of the component layers of the application and determines a second set of parameters indicative of characteristics of a software code associated with the application. The processor determines compatibility of a new technology with the environment based on the first set of parameters and with the application based on the second set of parameters. If the new technology is found compatible, the processor determines that the application can be upgraded based on the new technology.

System and method for upgrading a technology stack in a computing infrastructure

A system includes a memory and a processor configured to detect that a first alarm associated with a first software application has been triggered and determine one or more root causes associated with the first alarm. The processor accesses a plurality of data containers from the memory and, for each of the root causes, searches the data containers for a same or similar root cause that was previously resolved. Based on the search, the processor identifies a data container that stores data associated with resolution of a same or similar root cause, determines a self-healing method associated with the identified root cause, and implements the identified self-healing method to resolve the first root cause.

System and method for resolving a system alarm

A system includes a memory and a processor. The memory stores a baseline record associated with a device, which includes a set of parameters that were extracted from the device. The processor receives a request from the device to initiate a communication. In response to receiving the request to initiate the communication, the processor determines that an update to the device has modified the set of parameters of the device. In response to determining that that the update has modified the set of parameters, the processor extracts the modified set of parameters from the device, and stores a new record associated with the device in the memory, which includes the modified set of parameters extracted from the device. The processor additionally uses the new record to validate the request. In response to validating the request, the processor transmits the communication.

System and method for intelligent validation of communications initiated by internet of things devices

A system includes a memory and a processor configured to detect that a first alarm associated with a first software application has been triggered and perform a plurality of operations to resolve the first alarm. The processor accesses a plurality of rules from the memory and applies the plurality of rules to performing the plurality of operations to implement one or more of data security, data privacy and responsiveness associated with the resolution of the first alarm.

System and method for securing resolution of a system alarm

A system includes a memory and a processor. The memory stores a plurality of records associated with a device and a machine learning algorithm. The plurality of records includes a first record and a second record. The first record includes a first set of parameters extracted from the device at a first time. The second record includes a second set of parameters extracted from the device at a second time, with a difference between the first set of parameters and the second set of parameters resulting from of an update to the device. The machine learning algorithm is configured to determine a probability that the update was unauthorized. The processor executes the machine learning algorithm, and determines that the probability is greater than a threshold. In response to determining that the probability is greater than the threshold, the processor rejects a request transmitted by the device.

System and method for automatic identification of unauthorized updates to internet of things devices

A system includes a production computing environment including a plurality of components, a centralized data repository that receives and stores data feeds relating to one or more components as a data log and at least one processor configured to obtain the data log of each component, generate a current state vector for the component based on the data log, compare the current state vector to a normal state vector of the component, determine that the current state vector deviates from the normal state vector, and in response, predict an anomaly associated with the component using an iterative machine learning method. The at least one processor may be configured to correct the predicted anomaly by taking at least one pre-configured action corresponding to the predicted anomaly.

Automatic system anomaly detection

A system includes a production computing environment including a plurality of components, a centralized data repository that receives and stores data feeds relating to one or more components as a data log, a plurality of cloud infrastructures and at least one processor configured to receive the data feed relating to the components, predict an anomaly associated with a component based on the data feed relating to the component, identify a system configuration needed to run a current workload associated with the component, search each cloud infrastructure for a cloud instance that can support the identified system configuration, identify a cloud instance based on the search, initiate the identified cloud instance and switch the workload from an original system to the initiated cloud instance.

Restoring a system by load switching to an alternative cloud instance and self healing

A system includes a memory, and a processor. The processor receives a request to register a device. In response, the processor extracts a set of parameters from the device, and stores a baseline record associated with the device, which includes the set of parameters, in the memory. The processor determines that an update to the device modified the set of parameters. In response, the processor extracts the modified set of parameters from the device, and stores a new record associated with the device, which includes the modified set of parameters, in the memory. The baseline record was used to validate an identity of the device prior to the processor determining that the update modified the set of parameters. The new record is used to validate the identity of the device subsequent to the processor determining that the update modified the set of parameters.

Dynamic internet of things device records for use in validating communications from internet of things devices subject to data drift

Apparatus, systems and methods for providing a four-part, virtual reality (VR) customer service interaction between a customer service avatar operating on a VR platform and a customer using both a mobile device and a VR device are provided. Methods may include activating a VR session between the customer service avatar and the customer. Methods may include validating the VR session between the customer service avatar and the customer. Methods may include processing a co-browsing VR session request. Methods may include initiating the VR session between the customer service avatar and the customer.

Systems and methods for providing enhanced security features in a virtual reality (VR) onboarding session

Systems, methods, and apparatus for smart glasses based configuration of programming code are provided. A smart glasses device may capture a sequence of user eye positions using one or more sensors. A user interface may display one or more selectable programming functions. Each programming function may be pre-associated with a segment of programming code implementing the function. The user eye positions captured by the smart glasses may be filtered based on the degree of visual focus. A calibration engine may map each user eye position to one of the selectable programming functions displayed on the user interface. The selected programming functions may be ordered based on the sequence of user eye positions. A software application may be configured by assembling the segments of programming code associated with each programming function.

Smart glasses based configuration of programming code

A system and method are provided for dynamically updating a program. An anomaly related to a User Interface (UI) screen of a software application is detected, wherein the program is configured to extract information from a first spatial position on the UI screen. The information includes at least one of text, a computer icon or an image. It is determined, based on the software application, that the anomaly is caused by the information being moved from the first spatial position to a second spatial position on the UI screen. In response, the program is modified to cause the program to extract the information from the second spatial position. The modified program is deployed to extract the information from the second spatial position.

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Chennai, India

Vasuki Anand