University of North Carolina at Chapel Hill

Emc Corporation

Emc IP Holding Company LLC

Indiana University

Michael Kendrick Reiter

Ari Juels

Alina Oprea

Yinqian Zhang

Ting-Fang Yen

John P Field

Apu Kapadia

Vijay Ganti

Viktor Heorhiadi

Alana Libonati

A processing device comprises a processor coupled to a memory and is configured to obtain data characterizing host devices of a computer network of an enterprise. The data is applied to a logistic regression model to generate malware infection risk scores for respective ones of the host devices. The malware infection risk scores indicate likelihoods that the respective host devices will become infected with malware. The logistic regression model incorporates features of the host devices including at least user demographic features, virtual private network (VPN) activity features and web activity features of the host devices, and the data characterizing the host devices comprises data for the incorporated features. Proactive measures are taken to prevent malware infection in a subset of the host devices based at least in part on the malware infection risk scores. The processing device may be implemented in the computer network or an associated network security system.

Determining risk of malware infection in enterprise hosts

The subject matter described herein includes methods, systems, and computer readable media for combating mobile device theft with user notarization. One method includes providing a supplicant video notarization system application executable on a supplicant device for initiating an interactive video call between a supplicant and a notary as a condition to the supplicant accessing a protected electronic resource. The method further includes providing a notary video notarization system application executable on a notary device through which the notary receives the interactive video call and interacts with the supplicant via the interactive video call to confirm the identity of the supplicant and that video of the supplicant provided in the call is live.

Methods, systems, and computer readable media for combating device theft with user notarization

At least one virtual machine implemented on a given physical machine in an information processing system is able to detect the presence of one or more other virtual machines that are also co-resident on that same physical machine. More particularly, at least one virtual machine is configured to avoid usage of a selected portion of a memory resource of the physical machine for a period of time, and to monitor the selected portion of the memory resource for activity during the period of time. Detection of a sufficient level of such activity indicates that the physical machine is also being shared by at least one other virtual machine. The memory resource of the physical machine may comprise, for example, a cache memory, and the selected portion of the memory resource may comprise one or more randomly selected sets of the cache memory.

Co-residency detection in a cloud-based system

Cloud infrastructure of a cloud service provider comprises a processing platform implementing a security policy enforcement framework. The security policy enforcement framework comprises a policy analyzer that is configured to identify at least one security policy associated with at least one tenant of the cloud service provider, to analyze the security policy against configuration information characterizing the cloud infrastructure of the cloud service provider, and to control execution of one or more applications of said at least one tenant within the cloud infrastructure in accordance with the security policy, based at least in part on one or more results of the analysis of the security policy. The security policy enforcement framework may be implemented in a platform-as-a-service (PaaS) layer of the cloud infrastructure, and may comprise a runtime controller, an operating system controller, a hypervisor controller and a PaaS controller.

Security policy enforcement framework for cloud-based information processing systems

Growing community of inventors

Chapel Hill, NC, United States of America

Michael Kendrick Reiter