Emc Corporation

Emc IP Holding Company LLC

International Business Machines Corporation

Ayelet Avni

Yedidya Dotan

Boris Kronrod

Ayelet Levin

Bryan Knauss

Ayelet Eliezer

Lior Nudelman

Oren Menes

Fady Copty

Sharon Keidar-Barner

Ayman Jarrous

Ika Bar-Menachem

Maya Herskovic

Aviv Avital

Erez Yakoel

Theodor Mihalache

Shiri Lemel

Tamar Wisemon

In some examples, a system for authenticating users can include a processor to train a first predictive application based on a first set of user engagements with advertisements, wherein the first predictive application is associated with a first advertising identifier. The processor can also train a second predictive application based on a second set of user engagements with the advertisements, wherein the second predictive application is associated with a second advertising identifier. Additionally, the processor can compare the first predictive application and the second predictive application and authenticate a user in response to detecting a similarity of the first predictive application and the second predictive application is below a threshold value, wherein authenticating the user enables the user to access a resource or service.

User authentication based on predictive applications

A technique detects mobile device emulation. The technique involves identifying, by processing circuitry, a user apparatus for mobile device emulation detection. The technique further involves collecting, by the processing circuitry, motion sensor data from the identified user apparatus (e.g., samples of accelerometer attributes, gyroscopic attributes, gravity attributes, etc. over multiple time periods). The technique further involves performing, by the processing circuitry, a motion sensor data analysis operation based on the collected motion sensor data. A result of the motion sensor data analysis operation indicates whether the identified user apparatus is a physical mobile device or an emulated mobile device.

Detecting mobile device emulation

An improved technique involves generating KBA questions based on facts from fact sources pointed to by an activity log. A KBA system obtains an activity log from a computer of a user in an organization. For example, the computer records the user's web browsing history. The KBA system then considers each entry in the activity log as a source of facts for deriving KBA questions. In the case of a web browsing history, the KBA system generates facts from web pages that the user visited. The KBA system then derives new KBA questions from the facts so derived.

Question generation in knowledge-based authentication from activity logs

An improved technique generates questions to authenticate a user as part of a group. Along these lines, a KBA system, upon receiving a request to authenticate a particular user, collects facts having references to users of the group of users. The collected facts, however, may also include references to users not in the group of users. In building a set of questions for the particular user, the KBA system is capable of favoring facts having references to users of the group of users and few, if any, references to users not in the group of users; conversely, the KBA system is capable of discarding facts having too many references to users not in the group of users. The particular user's responses to the set of questions are indicative of whether the particular user belongs to the group.

Using link strength in knowledge-based authentication

An improved technique involves generating KBA questions from facts obtained from a personal information management (PIM) server under the control of an organization. Along these lines, such an organization acquires facts from documents such as emails, meeting notices, presentations, and spreadsheets that are stored on a PIM server such as a Microsoft&#xae; Exchange server or IBM Lotus&#xae; Domino server. A KBA server then generates KBA questions from the acquired facts and stores the KBA questions on a question server. In some arrangements, the KBA server filters out KBA questions based on the nature of the facts from which the KBA questions were derived. The remaining KBA questions are ranked based on historical question data; the KBA server provides the most highly ranked KBA questions to a user claiming to be a member of the organization.

Question generation in knowledge-based authentication for an enterprise

An improved technique employs knowledge-based authentication (KBA) based on data stored in a mobile apparatus. The mobile apparatus collects data from sources including email data, web browsing data, accessed YouTube video data, and GPS location data recently stored in the mobile apparatus. From such data, the mobile apparatus builds questions and stores the questions on a database on the phone. Upon receiving a request to access a resource stored in the mobile apparatus from a user, the mobile apparatus selects questions at random and ranks them according to a policy accessible to the mobile apparatus. The mobile apparatus presents the highest-ranked questions to the user. The mobile apparatus grants or rejects access to the resource based on an authentication result that the mobile apparatus generates from answers to the questions submitted by the user.

Knowledge-based authentication for restricting access to mobile devices

A method is used in managing knowledge-based authentication systems. Organization based information is analyzed for information that is suitable for creating a set of responses for a question. The question is used for authenticating a user. A set of responses is created for the question based on a set of parameters. The set of responses includes incorrect responses to the question along with a correct response. The incorrect responses helps in identifying an unauthorized user.

Managing knowledge-based authentication systems

An improved technique involves authenticating a user requesting access to a particular mobile device using knowledge-based authentication (KBA) questions generated from data taken from a group of mobile devices to which the particular mobile device belongs. Along these lines, consider a corporation that has a group of mobile devices distributed to its employees. The mobile devices provide data to an enterprise KBA (eKBA) server regarding events on each of the mobile devices. Because an owner of a mobile device belongs to a group of employees, the owner is able to answer questions regarding fellow employees. On the other hand, a malicious user that illegitimately gains access to the owner's mobile device will not be able to answer such questions, even if the malicious user knows details about the owner.

An improved technique involves converting facts from multiple fact sources to a common data format. Along these lines, for each fact source having a source-specific format, a KBA system provides an adaptor that converts incoming facts in the source-specific format to the common data format prior to generating questions. The KBA system stores the facts in the common format in a database for subsequent access. In response to an authorization request, the KBA system then builds questions based on the facts from multiple sources in the common data format stored in the database.

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Binyamina, Israel

Ayelet Avni