The disclosure is directed towards controlling the persistency of information provided to a service worker. A method includes receiving a response that includes response data. The response is received at a security service and was transmitted by a second computing device in response to receiving an information request from a first computing device. The first computing device implements a service worker. Sensitive data included in the response data is identified. The response includes caching instructions that instruct the service worker to cache the sensitive data at the first computing device. In response to identifying the sensitive data, the caching instructions are updated such that any portion of the response data that the updated caching instructions instruct the service worker to cache at the first computing device excludes the sensitive data. The updated response is transmitted to the first computing device and includes the response data and the updated caching instructions.

A network security system for detecting MAC'less/transparent devices, the system comprising a data repository aka DB, operative to accumulate “fingerprint” data indicative of expected physical level characteristics for each of plural types of switch-device links (aka link types) interconnecting a switch and a hardware device, wherein at least one pair of links of different types differ from one another at least with respect to the chipset residing in the respective device connected to the respective switch by each respective link; apparatus for reading physical level characteristics of links in at least one network to be protected; and an output device configured to generate alerts of possible presence of a transparent device along at least one link if the physical level characteristics of the at least one link, as read by the apparatus, is anomalous relative to the “fingerprint” data stored in the data repository.

This disclosure relates to systems and methods for verifying the presentation of content to a target audience using generated metrics indicative of a likelihood that the content was presented to actual human individuals within the target audience. In some instances, such a metric may be associated with a probability model estimating that a user (e.g., a user of a device) is human and not a bot and/or other automated service. Metrics consistent with aspects of the disclosed embodiments may be generated based, at least in part, on user information received from a user and/or associated devices and/or associated services. Consistent with various disclosed embodiments, metrics indicative of whether a user is human, content distribution decisions and user agency decisions may use such metrics.

Described are a system, method, and computer program product for user network activity anomaly detection. The method includes receiving network resource data associated with network resource activity of a plurality of users and generating a plurality of layers of a multilayer graph from the network resource data. Each layer of the plurality of layers may include a plurality of nodes, which are associated with users, connected by a plurality of edges, which are representative of node interdependency. The method also includes generating a plurality of adjacency matrices from the plurality of layers and generating a merged single layer graph based on a weighted sum of the plurality of adjacency matrices. The method further includes generating anomaly scores for each node in the merged single layer graph and determining a set of anomalous users based on the anomaly scores.

Detecting a data leak by detecting user input in a first form, the user input satisfying a set of requirements, storing the user input in a memory, generating a synthetic input satisfying the set of requirements, transmitting a second form including the synthetic input, searching resources for the synthetic input, determining if the synthetic input is present among the resources according to the search, and acting upon the determination.

Methods and apparatus to establish secure low energy wireless communications in a process control system are disclosed. An example field device includes a Bluetooth Low Energy (BLE) interface to receive a first initialization message from a remote device over an unpaired BLE connection. The first initialization message includes a plaintext message containing authentication content. The authentication content is generated based on a private authentication token available to the remote device using middleware. The field device also includes a BLE message analyzer to validate the plaintext message based on the authentication content using the authentication token stored by the field device.

The subject matter described herein includes methods, systems, and computer readable media for threat simulation and threat mitigation recommendations. A method for threat simulation and threat mitigation recommendations includes performing a first threat simulation using at least one attack vector, wherein performing the first threat simulation includes generating simulated network traffic associated with the at least one attack vector and sending, via at least one intermediate node, the simulated network traffic to a test agent in a target network, wherein the test agent is configured to simulate at least one protected asset in the target network; determining, using simulated network traffic arrival metrics, at least one threat mitigation recommendation; and providing, via a user interface, the at least one threat mitigation recommendation to a user.

Domains and IPs are scored using domain resolution data to identify malicious domains and IPs. A domain and IP resolution graph for a set of domains and IPs in a system. A seed set of known malicious domains and known malicious IPs is selected from a malicious domain and malicious IP database. A graphical probabilistic propagation inference from the domain and IP resolution graph and the seed set of known malicious domains and known malicious IPs is generated. A malicious score is calculated for each domain in the set of domains and each IP in the set of IPs, and the malicious domain and malicious IP database is updated.

According to an example aspect of the present invention, there is provided a method including determining at least one possible downlink control information for the user equipment to schedule the data transmission, checking a scrambled version of the at least one possible downlink control information to determine whether the scrambled version of the at least one possible downlink control information defines valid downlink control information, transmitting the scrambled version of the at least one possible downlink control information and scheduling the data transmission based on the at least one possible downlink control information and if it is determined that the scrambled version of the at least one possible downlink control information defines valid downlink control information, scheduling the jamming transmission based on the scrambled version of the at least one possible downlink control information.

An information leakage detection method and a device using the same are disclosed. The method includes the following steps. Network connection data of an electronic device is obtained. Log data related to a (domain name system) DNS is extracted from the network connection data. A DNS request in the log data is analyzed to obtain multiple character distribution feature values according to an analysis result. The character distribution feature values reflect a character distribution status of a domain name in the DNS request under different classification rules. A machine learning model determines whether the DNS request is a malicious DNS request according to the character distribution feature values, and the malicious DNS request is used to carry leaked data to a remote host.