Veritas Technologies LLC

International Business Machines Corporation

Harshit Shah

Shailesh A Dargude

Pradeep Varma

Satish Grandhi

Rudrapatna Kallikote Shyamasundar

Anand Athavale

Ketan Shah

Neha Kamat

Jitendra Pore

The disclosed computer-implemented method for prioritizing and detecting file datasets based on metadata may include (i) receive a group of files from a data storage, (ii) train a machine-learning model utilizing a set of properties derived from metadata associated with the files, (iii) identify, utilizing the machine-learning model, a dataset including at least one candidate file that performs an action in a set of predetermined actions, and (iv) prioritize the action based on the dataset. Various other methods, systems, and computer-readable media are also disclosed.

Systems and methods for prioritizing and detecting file datasets based on metadata

The disclosed computer-implemented method for producing access control list caches including effective information access permissions across disparate storage devices may include (i) receiving, at a computing device, an instruction to prepare an access control list (ACL) cache and (ii) performing a security action. The security action may include (A) recursively parsing, at the computing device, at least one respective ACL for information stored on at least two disparate storage devices, (B) identifying, at each step of recursion, each direct user and each indirect user having information access permissions in at least one of the respective ACLs, (C) determining, for each unique user in the respective ACLs, per-control point effective permissions, and (D) storing the per-control point effective information access permissions in the ACL cache. Various other methods, systems, and computer-readable media are also disclosed.

Systems and methods for producing access control list caches including effective information access permissions across disparate storage devices

The disclosed computer-implemented method for protecting sensitive data against data loss may include (1) identifying a resource comprising sensitive data, (2) establishing, for the resource, an accessibility threshold that indicates a limit on permissions to access the resource, (3) monitoring how the permissions to access the resource drift over time by tracking changes in users' permissions to access the resource, (4) detecting, while tracking the changes in users' permissions to access the resource, that access to the resource has surpassed the accessibility threshold, and (5) in response to detecting that the access to the resource has surpassed the accessibility threshold, performing a security action to protect the sensitive data from potentially being exposed. Various other methods, systems, and computer-readable media are also disclosed.

Systems and methods for protecting sensitive data against data loss

The disclosed computer-implemented method for identifying potentially risky data users within organizations may include (1) monitoring computing activity of a member of an organization with respect to the member's access to data related to the organization, (2) generating, based at least in part on the member's computing activity, a baseline representation of the member's access to the data, (3) detecting at least one attempt by the member to access at least a portion of the data, (4) determining that the member's attempt to access the portion of data represents an anomaly that is suspiciously inconsistent with the baseline representation, and then in response to determining that the member's attempt to access the portion of data represents the anomaly, (5) classifying the member as a potential risk to the security of the data. Various other methods, systems, and computer-readable media are also disclosed.

Systems and methods for identifying potentially risky data users within organizations

Techniques for generating concurrent static single assignment (CSSA) are provided. The techniques include generating a clocked control flow graph of a program, for each thread of the program created through async instruction, determining each part of the program that can execute concurrently with each thread to create a pair comprising a thread and a parallel program part, for each pair that can execute concurrently, using one or more flow equations to perform node-by-node matching, and using the node-by-node matching to generate CSSA form for the program.

Concurrent static single assignment for general barrier synchronized parallel programs

Embodiments of the invention provide a table-free technique for detecting all temporal and spatial memory access errors in programs supporting general pointers. Embodiments of the invention provide such error checking using constant-time operations. Embodiments of the invention rely on fat pointers, whose size is contained within standard scalar sizes (up to two words) so that atomic hardware support for operations upon the pointers is obtained along with meaningful casts in-between pointers and other scalars. Optimized compilation of code becomes possible since the scalarized-for-free encoded pointers get register allocated and manipulated. Backward compatibility is enabled by the scalar pointer sizes, with automatic support provided for encoding and decoding of fat pointers in place for interaction with unprotected code.

Growing community of inventors

Mumbai, India

Harshit Shah