Mcafee, Inc.

Musarubra US LLC

Eric Donald Wuehler

Jonathan B King

German Lancioni

Tirumaleswar Reddy Konda

Harsha Ramamurthy Joshi

Arthur S Zeigler

Piyush Pramod Joshi

Shashank Mohan Jain

Celeste R Fralick

Sherin Mary Mathews

Amanda House

Antoine Bouchard

Methods, apparatus, systems, and articles of manufacture are disclosed to securely audit communications. An example apparatus includes a participant list generator to, responsive to a command to provision a secured group of devices in a network to prevent malicious activity, generate a participant device list including one or more endpoint devices and a control plane server; a privilege controller to, based on a policy indicated in the command, set read and write privileges for the one or more endpoint devices and the control plane server; a command controller to, based on the command, determine whether to generate a shared communication key using a shared system key; and a communication processor to encrypt communications between the one or more endpoint devices and the control plane server using the shared communication key.

Methods, apparatus, and articles of manufacture to securely audit communications

Example apparatus disclosed herein generate blocks of a blockchain, the blockchain to store a neural network that has input nodes, hidden nodes and output nodes, with respective ones of the blocks of the blockchain including respective code and respective data to represent corresponding ones of the output nodes of the neural network, a first one of the blocks including first code and first data to implement operations to be performed by a first one of the output nodes, the hidden nodes and the input nodes on input data applied to the neural network to determine an output of the first one of the output nodes. Disclosed example apparatus also train the neural network to determine at least portions of the respective data to include in the respective ones of the blocks of the blockchain, and forward the blockchain to a server that is to distribute the neural network to client(s).

Distribution of neural networks with blockchains

There is disclosed in one example a gateway apparatus to operate on an intranet, including: a hardware platform; and an access proxy engine to operate on the hardware platform and configured to: intercept an incoming packet; determine that the incoming packet is an access request directed to an access interface of a resource of the intranet; present an access checkpoint interface; receive an authentication input response; validate the authentication input response; and provide a redirection to the access interface of the device.

Gateway with access checkpoint

Mechanisms for split tunneling are provided. The mechanisms identify user devices and determine that communications for a first device of the user devices are to be tunneled. These mechanisms also receive a DNS request from a second device of the user devices, modify the DNS request to request meta information corresponding to a domain identified in the DNS request, and send the DNS request to a DNS server. The mechanisms further receive a response to the DNS request, wherein the response includes the meta information, determine that communications for the second device are not to be tunneled based at least in part on the meta information, and cause the communications for the first device to be tunneled and the communications for the second device to not be tunneled.

Systems, methods, and media for intelligent split-tunneling

An apparatus, related devices and methods, having memory; and a processor operable to execute instructions stored in the memory configured to cache a first data object and a second data object received from a source in a cache group based on metadata received from the source, where the metadata identifies the first and second data objects as related and the first data object as a trigger object; receive a request from a client for the first data object; identify, based on a determination that the first data object is invalid and is the trigger object, the first data object and the second data object as invalid; request a valid first data object and a valid second data object from the source; and cache the valid first and second data objects, received from the source, in the cache group.

Cache system for consistent retrieval of related objects

Particular embodiments described herein provide for a system that can be configured to facilitate the use of a blockchain for distributed denial of service attack mitigation, the system can include a network security provider and a validating node. The network security provider can recognize that a distributed denial of service (DDoS) attack is occurring, create a block that includes data related to the DDoS attack, and publish the block that includes the data related to the DDoS attack for addition to a blockchain. The validating node can validate the block that includes the data related to the DDoS attack and the block that includes the data related to the DDoS attack can be added to the blockchain. The block that includes the data related to the DDoS attack can be analyzed to determine how to mitigate a similar DDoS attack.

Using a blockchain for distributed denial of service attack mitigation

Example data leakage detection apparatus disclosed herein include a fingerprinter to generate a first data fingerprint of a first data item accessed from a data source. Disclosed example data leakage detection apparatus also include a blockchain scanner to scan a blockchain to detect whether a first blockchain record includes a second data fingerprint that matches the first data fingerprint of the first data item. Disclosed example data leakage detection apparatus further include a blockchain writer to write a second blockchain record to the blockchain when the second data fingerprint matches the first data fingerprint, the second blockchain record to indicate the first data item is associated with a data leak of a protected data item represented by the second data fingerprint. In some examples, the second blockchain record is to include the first data fingerprint and a first timestamp.

Data leakage mitigation with a blockchain

Sharing IoT device (IoTd) profile data is provided, comprising: generating at least one access control rule to protect an IoTd; publishing first IoTd profile data in a first new block (FNB) of a blockchain of a blockchain network (BN), wherein the first IoTd profile data comprises the at least one access control rule; and committing the FNB to the blockchain based on a consensus algorithm by: a manufacturer of the IoTd committing the FNB to the blockchain; a security vendor (SV) participating in the BN committing the FNB to the blockchain when the SV is a sole SV participating in the BN; or the SV committing the FNB to the blockchain based on consensus among at least the SV and a plurality of security vendors when the SV and the plurality of security vendors are participating in the BN.

Systems, methods, and media for sharing IoT device profile data

Methods, apparatus, systems, and articles of manufacture are disclosed for dynamic network classification using authenticated neighbor detection. An example includes a network comparator to determine whether a network to be connected by a computing device is a managed network based on network configuration information associated with the network, in response to determining the network is not a managed network, a neighbor comparator to determine a number of different computing devices on the network that are managed computing devices, and in response to determining that the number of the managed computing devices satisfies a threshold, a sensor controller to invoke a sensor of the computing device to obtain data from computing devices associated with the network, the computing devices including the managed computing devices.

Methods and apparatus for dynamic network classification using authenticated neighbor detection

A steganographic coding detector (and method) analyzes one or more pages of a file. For each page containing text strings, the detector counts a number of A0h and 20h characters for the text string. For each text string for which the number of A0h characters is greater than a first threshold, the detector sets a flag to a first state, The first threshold is computed based on the number of 20h characters in that text string. For each text string for which the number of 20h characters is less than the first threshold, the detector sets the flag to a second state. Responsive to the number of text strings that have a flag at the first state being greater than a second threshold, the detector marks the file as being steganographically encoded.

Growing community of inventors

Beaverton, OR, United States of America

Eric Donald Wuehler