Abstract: A system, method, and computer program product are provided for dynamically configuring a virtual environment for identifying unwanted data. In use, a virtual environment located on a first device is dynamically configured based on at least one property of a second device. Further, unwanted data is identified, utilizing the virtual environment.

Abstract: There is disclosed in one example a network device, including: a hardware platform including at least a processor and a memory; a communication interface; and stored instructions on the memory to instruct the processor to provide a health monitoring engine (HME) configured to: communicatively couple to a network via the network interface; construct a reference template during a training period; observe watchdog behavior on the network during an observation period; identify an abnormality in the watchdog behavior including a substantial variance from the reference template; and trigger a resilience response to the substantial variance.

Abstract: Disclosed herein are distributed ledger systems and methods for efficiently creating and updating a query optimized distributed ledger. In particular, the present disclosure introduces methods and apparatuses for efficiently updating indexes when new blocks are added to the distributed ledger by using snapshots of data and appending new snapshot tables and indexes to previous snapshot tables and indexes.

Abstract: In an example, there is disclosed a computing apparatus having: a processor; a memory; a data interface; and one or more logic elements providing a verification engine to: receive via the data interface an input script including a request to access enterprise data; analyze the input script to determine that the input script complies with a data request criterion; apply an application programming interface (API) to the input script to collect the enterprise data; and send the enterprise data via the data interface.

Abstract: Disclosed herein are cloud-based machine learning systems and methods for monitoring networked devices to identify and classify characteristics, to infer typical or atypical behavior and assign reputation profiles across various networked devices, and to make remediation recommendations. In some embodiments, a cloud-based machine learning system may learn the typical operation and interfacing of a plurality of reputable devices that are known to be free from malicious software and other threats. In some embodiments, a cloud-based machine learning system may learn the typical operation and interfacing of a device, and may identify atypical operations or interfaces associated with that device by comparing the operations and interfaces to those of a plurality of networked devices or to those of a defined standard reference device.

Abstract: There is disclosed in one example an enterprise data server to provide regulated access of enterprise data to non-enterprise third parties, including: a hardware platform including a processor and a memory; a network interface; an enterprise data store, or an interface to access the enterprise data store; a reputation engine to receive a third-party script via the network interface and to assign a reputation to the third-party script; an ingress analyzer to scrutinize the third-party script according to the reputation and determine whether the third-party script may run; and a data collector to collect enterprise data from the enterprise data repository if the third-party script may run.

Abstract: Particular embodiments described herein provide for modular device assemblies and methods for enabling maintenance and servicing, particularly by an unmanned aerial vehicle. A device assembly comprises a plurality of modules, each module having control circuitry, a communications port and contact points to couple the modules. When the modules are coupled, the communications ports are connected to create a bus for communications between the modules. The modular device structure where modules are removable and replaceable allows for an unmanned aerial vehicle to perform maintenance on the device.

Abstract: In an example, there is disclosed a computing apparatus having: a processor; a memory; a data interface; and one or more logic elements providing a verification engine to: receive via the data interface an input script including a request to access enterprise data; analyze the input script to determine that the input script complies with a data request criterion; apply an application programming interface (API) to the input script to collect the enterprise data; and send the enterprise data via the data interface.

Abstract: A system, method, and computer program product are provided for dynamically configuring a virtual environment for identifying unwanted data. In use, a virtual environment located on a first device is dynamically configured based on at least one property of a second device. Further, unwanted data is identified, utilizing the virtual environment.

Abstract: Disclosed herein are distributed ledger systems and methods for efficiently creating and updating a query optimized distributed ledger. In particular, the present disclosure introduces methods and apparatuses for efficiently updating indexes when new blocks are added to the distributed ledger by using snapshots of data and appending new snapshot tables and indexes to previous snapshot tables and indexes.

Abstract: There is disclosed in one example a computing apparatus, including: an interface to a backup source in a current state; a backup storage having stored thereon a first backup version of a previous state of the source; and a backup engine to: compute a delta between the current state and the previous state; save via the backup storage a second backup version sufficient to reconstruct the current state; and assign the second backup version a reputation relative to one or more previous backup versions.

Abstract: A system, method, and computer program product are provided for dynamically configuring a virtual environment for identifying unwanted data. In use, a virtual environment located on a first device is dynamically configured based on at least one property of a second device. Further, unwanted data is identified, utilizing the virtual environment.

Abstract: Disclosed herein are distributed ledger systems and methods for efficiently creating and updating a query optimized distributed ledger. In particular, the present disclosure introduces methods and apparatuses for efficiently updating indexes when new blocks are added to the distributed ledger by using snapshots of data and appending new snapshot tables and indexes to previous snapshot tables and indexes.

Abstract: There is disclosed in one example a network device, including: a hardware platform including at least a processor and a memory; a communication interface; and stored instructions on the memory to instruct the processor to provide a health monitoring engine (HME) configured to: communicatively couple to a network via the network interface; construct a reference template during a training period; observe watchdog behavior on the network during an observation period; identify an abnormality in the watchdog behavior including a substantial variance from the reference template; and trigger a resilience response to the substantial variance.

Abstract: Technologies are provided in embodiments to monitor and analyze networks. The embodiments can cause a bit in a first bit sequence of a device filter to indicate a failure state based on not receiving a message from a node in a network during a reporting time interval, and upon the reporting time interval expiring, to combine the first bit sequence with a corresponding bit sequence of a shadow filter. The combination preserves, in the shadow filter, an indication of the failure state from the bit in the first bit sequence and any other indications of failure states from bits of the corresponding bit sequence of the shadow filter. More specific embodiments cause, upon the reporting interval expiring, a bit in a second bit sequence of the device filter to indicate a no failure state based on an indication of another no failure state in the first bit sequence.

Abstract: Technologies are provided in embodiments to analyze and control execution flow. At least some embodiments include decompiling object code of a software program on an endpoint to identify one or more branch instructions, receiving a list of one or more modifications associated with the object code, and modifying the object code based on the list and the identified one or more branch instructions to create new object code. The list of one or more modifications is based, at least in part, on telemetry data related to an execution of corresponding object code on at least one other endpoint. In more specific embodiments, a branch instruction of the one or more branch instructions is identified based, at least in part, on an absence of an instruction in the object code that validates the branch instruction.

Abstract: There is disclosed in one example a computing apparatus, including: an interface to a backup source in a current state; a backup storage having stored thereon a first backup version of a previous state of the source; and a backup engine to: compute a delta between the current state and the previous state; save via the backup storage a second backup version sufficient to reconstruct the current state; and assign the second backup version a reputation relative to one or more previous backup versions.

Abstract: Disclosed herein are cloud-based machine learning systems and methods for monitoring networked devices to identify and classify characteristics, to infer typical or atypical behavior and assign reputation profiles across various networked devices, and to make remediation recommendations. In some embodiments, a cloud-based machine learning system may learn the typical operation and interfacing of a plurality of reputable devices that are known to be free from malicious software and other threats. In some embodiments, a cloud-based machine learning system may learn the typical operation and interfacing of a device, and may identify atypical operations or interfaces associated with that device by comparing the operations and interfaces to those of a plurality of networked devices or to those of a defined standard reference device.

Abstract: In an example, there is disclosed a computing apparatus having: a processor; a memory; a data interface; and one or more logic elements providing a verification engine to: receive via the data interface an input script including a request to access enterprise data; analyze the input script to determine that the input script complies with a data request criterion; apply an application programming interface (API) to the input script to collect the enterprise data; and send the enterprise data via the data interface.

Abstract: Disclosed herein are distributed ledger systems and methods for efficiently creating and updating a query optimized distributed ledger. In particular, the present disclosure introduces methods and apparatuses for efficiently updating indexes when new blocks are added to the distributed ledger by using snapshots of data and appending new snapshot tables and indexes to previous snapshot tables and indexes.