International Business Machines Corporation

Microsoft Technology Licensing, LLC

Eko India Financial Services Pvt. Ltd.

Prasad G Naldurg

Sriram Kottarakurichi Rajamani

John J Lambert

Stefan Schwoon

Sameep Mehta

Venkatraman Ramakrishna

Palanivel Andiappan Kodeswaran

Akshar Kaul

Manish Kesarwani

Gagandeep Singh

Arvind Seshadri

Sougata Mukherjea

Michael Steiner

Ranjita Bhagwan

Saurabh Panjwani

Tathagata Das

Raghav Bhaskar

Abhinav Sinha

Abhishek Sinha

Anupam Varghese

One embodiment provides a method, including: receiving, from a data owner, an input string of plaintext data comprising a plurality of characters for storage in a database of a third-party storage provider; arranging the plurality of characters of the input string as a half pyramid, wherein the half pyramid comprises a plurality of rows, each row comprising at least one more character than a preceding row; encrypting, using a secure encryption scheme and based upon a key, each row of the half pyramid independently from each other row of the half pyramid; and storing, in the database of the third-party storage provider, the encrypted rows of the half pyramid. Other aspects are claimed and described.

Half-pyramid data encryption

Methods, systems, and computer program products for secure distance computations are provided herein. A computer-implemented method includes transforming a set of multiple data points, thereby creating a multiple-dimension representation of the set of data points; storing multiple distinct portions of the multiple-dimension representation of the set of data points across multiple distinct cloud infrastructures; transforming a query point, thereby creating a multiple-dimension representation of the query point; sending multiple distinct portions of the multiple-dimension representation of the query point to the multiple distinct cloud infrastructures; calculating a distance between each of the stored distinct portions of the multiple-dimension representation of the set of data points and each of the sent distinct portions of the multiple-dimension representation of the query point; determining a total distance value by summing the calculated distances; and outputting the total distance value to at least one user.

Secure distance computations

Methods and arrangements for protecting enterprise data with respect to a hybrid application in a mobile device that accesses a global computer information network using enterprise infrastructure. A hybrid application is recognized in a mobile device, the hybrid application being configured to communicate with an enterprise network and a non-enterprise network. There are provided, in communication with the hybrid application, controls for segregating data flows from the enterprise network and non-enterprise network. A policy service is provided, which applies a policy for the segregating and governed routing of data flows from the enterprise network and the non-enterprise network. Other variants and embodiments are broadly contemplated herein.

Governed routing of enterprise data in hybrid mobile applications

Methods and arrangements for according access of a mobile device to an enterprise network. the presence of a mobile device relative to an enterprise network is detected, the enterprise network including a plurality of defined zones, wherein each zone is associated with a security level and with one or more resources. An agent of the mobile device is negotiated with to accord access to at least one of the defined zones. The negotiating includes: assessing at least one security constraint relative to the mobile device; and thereupon designating at least one zone to be accessible to the mobile device. Other variants and embodiments are broadly contemplated herein.

Dynamic enterprise boundary determination for external mobile devices

The present invention describes a method for authenticating a user of a mobile device by a verification authority, by making use of at least a personal identification number (PIN) and at least one cryptographic key, such that the PIN and the cryptographic key is known only to the user and the verification authority. The cryptographic key has at least one session key. Firstly, the user encodes the PIN by using at least one session key and then transfers the encoded PIN to a predefined address of the verification authority via the mobile device. Next, the verification authority decodes the PIN by using the cryptographic key authenticates the user if the decoded PIN matches a PIN stored corresponding to the user.

Authentication method and device

A facility is described for analyzing access control configurations. In various embodiments, the facility comprises an operating system having resources and identifications of principals, the principals having access control privileges relating to the resources, the access control privileges described by access control metadata; an access control scanner component that receives the access control metadata, determines relationships between principals and resources, and emits access control relations information; and an access control inference engine that receives the emitted access control relations information and an access control policy model, analyzes the received information and model, and emits a vulnerability report. In various embodiments, the facility generates an information flow based on access control relations, an access control mechanism model, and an access control policy model; determines, based on the generated information flow, whether privilege escalation is possible; and when privilege escalation is possible, indicates in a vulnerability report that privilege escalation is possible.

Analyzing access control configurations

An access control anomaly detection system and method to detect potential anomalies in access control permissions and report those potential anomalies in real time to an administrator for possible action. Embodiments of the system and method input access control lists and semantic groups (or any dataset having binary matrices) to perform automated anomaly detection. This input is processed in three broad phases. First, policy statements are extracted from the access control lists. Next, object-level anomaly detection is performed using thresholds by categorizing outliers in the policies discovered in the first phase as potential anomalies. This object-level anomaly detection can yield object-level security anomalies and object-level accessibility anomalies. Group-level anomaly detection is performed in the third phase by using semantic groups and user sets extracted in first phase to find maximal overlaps using group mapping. This group-level anomaly detection can yield group-level security anomalies and group-level accessibility anomalies.

Detecting anomalies in access control lists

A facility is described for analyzing access control configurations. In various embodiments, the facility comprises an operating system having resources and identifications of principals, the principals having access control privileges relating to the resources, the access control privileges described by access control metadata; an access control scanner component that receives the access control metadata, determines relationships between the principals and the resources, and emits access control relations information; and an access control inference engine that receives the emitted access control relations information and an access control policy model, analyzes the received information and model, and emits a vulnerability report. In various embodiments, the facility generates an information flow based on access control relations, an access control mechanism model, and an access control policy model; determines, based on the generated information flow, whether privilege escalation is possible; and when privilege escalation is possible, indicates in a vulnerability report that the privilege escalation is possible.

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Bengaluru, India

Prasad G Naldurg