Bank of America Corporation

Harish Tammaji Kulkarni

Nhat Minh Nguyen

Kumudini Choyal

Ra Uf Ridzuan Bin Ma Arof

Simon Peter Lawrie

Ayush Anand

Chie Khiong Chin

Surendran Surendran

Nera Pershing Schwartz

Min Cao

Eric Ryan Camarata

Vaibhav Shankar Tambe

Mahesh Ramesh Bane

A system for inoculating a computer network against malware is described. Specifically, environmental indicators used by anti-analysis and target filtering mechanisms of a malware program may be determined based on analysis within a virtual or physical sandbox environment. The environmental indicators may be sent to computing devices associated with the computing network. The malware program, based on the environmental indicators, may be spoofed to assume that a computing device is associated with an anti-malware system, and/or is a device that is not to be infected. Based on this assumption, the malware program may not execute within the computing device.

Malware deterrence using computer environment indicators

Aspects of the disclosure relate to multi-factor user authentication for card-based payment transactions using blockchain tokens. An computing platform may receive, from a computing device, transaction details associated with a card-based payment transaction corresponding to a user, wherein the transaction details comprise a card number of a payment card. The computing platform may determine, based on the card number, a user device associated with the user. The computing platform may send, to the user device, a one-time passcode (OTP). After sending the OTP, the computing platform may receive a security key. The security key may be generated based on the sent OTP and a blockchain token hash. The computing platform may, based on the received security key, send, to the computing device, a message indicating whether the transaction is approved or declined.

Multi-factor user authentication using blockchain tokens

A system for multi-factor user authentication for payment card-based transactions are described. The multifactor authentication may be based on a one-time passcode/password (OTP) as sent by an authentication server. A user device may, based on receiving the OTP, send an authentication code. The authentication code may be generated/determined based on the OTP. The authentication code may be augmented biometric identifier (ID) of a user associated with the user device. The authentication server may validate a transaction based on the authentication code.

Multi-factor user authentication

Methods, systems, computer-readable media, and apparatuses for detecting and protecting against employee targeted phishing attacks. In some embodiments, a computing platform may monitor an endpoint device. The computing platform may receive a notification that a call has started on the endpoint device. The computing platform may receive data associated with the call. The computing platform may apply voice-to-text analysis of the received data. The computing platform may perform initial validations of the received data converted to text. The computing platform may match the text against threat actor scripts. The computing platform may update an information security threat score. The computing platform may send a message to the endpoint device indicating that a potential information security threat has been detected.

Detecting and protecting against employee targeted phishing attacks

Aspects of the disclosure relate to a dynamic event securitization and neural network analysis system. A dynamic event inspection and securitization computing platform comprising at least one processor, a communication interface, and memory storing computer-readable instructions may securitize event data prior to authorizing execution of the event. A neural network event analysis computing platform comprising at least one processor, a communication interface, and memory storing computer-readable instructions may utilize a plurality of event analysis modules, a neural network, and a decision engine to analyze the risk level values of data sharing events. The dynamic event inspection and securitization computing platform may interface with the neural network event analysis computing platform by generating data securitization flags that may be utilized by the neural network event analysis computing platform to modify event analysis results generated by the event analysis modules.

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Singapore, Singapore

Harish Tammaji Kulkarni