A method for HyperText Transfer Protocol (HTTP) based fingerprint and classification. The method includes training a HTTP-based machine-learning model, using machine-learning training techniques and a historical dataset of labelled Access Point HTTP service response features collected. The method is useful to detect benign or malicious classes, to assess the potential trustworthiness, to detect any type of bad behavior of an HTTP server, and any other threats that modify or implement an AP HTTP server or webpage. The method takes advantage of the captive portal detection packet exchange between a station and an Access Point (AP) to passively classify the AP.

Contextual session-based operational prediction greatly improves computer functioning. As a cloud service is provided, a current contextual session is generated using multiple events provided by the cloud service. The current contextual session is compared to a contextual session profile. The contextual session profile represents historical contextual sessions that have been historically logged in associated with the cloud service. If the current contextual session conforms to the contextual session profile, then the cloud service is normally operating as historically observed and may be predicted as normal operation. If, however, the current contextual session fails to conform to the contextual session profile, then the cloud service is not operating as historically observed and may be predicted as abnormal operation. Alerts and warning may be generated to notify of abnormal cloud service operation. The contextual session-based operational prediction produces a faster and more accurate detection of the abnormal operation.

Example embodiments of systems and methods for data transmission system between transmitting and receiving devices are provided. In an embodiment, each of the transmitting and receiving devices can contain a master key. The transmitting device can generate a diversified key using the master key, protect a counter value and encrypt data prior to transmitting to the receiving device, which can generate the diversified key based on the master key and can decrypt the data and validate the protected counter value using the diversified key.

Example embodiments of systems and methods for data transmission system between transmitting and receiving devices are provided. In an embodiment, each of the transmitting and receiving devices can contain a master key. The transmitting device can generate a diversified key using the master key, protect a counter value and encrypt data prior to transmitting to the receiving device, which can generate the diversified key based on the master key and can decrypt the data and validate the protected counter value using the diversified key.

Described embodiments provide systems and methods for context aware frictionless authentication. A server may determine authentication method information, contextual scores and contextual weights of a device, in connection with a user request to access a resource via the device. The authentication method information may include a weight and a completion duration for each of a plurality of authentication methods available via the device. The server may determine an authentication score for each of the plurality of authentication methods using the authentication method information, the contextual scores and the contextual weights of the device. The server may identify a first authentication method from the plurality of authentication methods, according to the determined authentication score. The server may authenticate the user request via the first authentication method using a first device that supports the first authentication method.

The disclosure provides an approach for authenticating a user of a computer system, wherein the computer system implements a virtual desktop infrastructure (VDI), the method comprising connecting to a computing device through a network, receiving from the computing device authentication credentials, and determining whether the authentication credentials match an authorized user of the computer system. The approach further comprises extracting from the computing device features of the computing device, retrieving a machine learning (ML) model associated with the authorized user, wherein the ML model is at least one of (a) a supervised ML model or (b) an unsupervised ML model, and executing the ML model to authenticate the features of the computing device.

Systems, methods, and computer-readable media are provided for managing mutual and transitive trust relationships between resources, such as Fog/Edge nodes, autonomous devices (e.g., IoT devices), and/or analog/biological resources to provide collaborative, trusted communication over a network for service delivery. Disclosed embodiments include a subject resource configured to assign an observed resource to a trust zone based on situational and contextual information. The situational information may indicate a vector of the observed resource with respect to the subject resource. The contextual information may be based in part on whether a relationship exists between the subject resource and the observed resource. The subject resource is configured to determine a trust level of the observed resource based on the determined trust zone. Other embodiments are disclosed and/or claimed.

The present disclosure discloses a management system, including an access point, a plurality of docking station devices, and a backend server. Each docking station device includes an interface, a sensor, a wireless sensor network transceiver circuit, a Wi-Fi transceiver circuit, and a control circuit. The interface is configured to couple electronic devices. The sensor is configured to measure a value. The wireless sensor network transceiver circuit is configured to receive and transmit data from and to the other docking station devices. The Wi-Fi transceiver circuit is configured to receive and transmit data from and to the access point. The backend serve is communicatively connected to the access point and one or several of the docking station devices. The docking station devices are communicatively connected to each other to form a mesh network.

Systems and methods for enabling context-aware zero-trust network access (ZTNA) using security posture insights received from an endpoint agent are provided. According to an embodiment, of a Zero Trust Network Access (ZTNA) service module receives from an endpoint device an access request to a protected object. An identity of a user of the endpoint device is verified via an identity management system. When the identify verification is affirmative: (i) receiving from an endpoint agent running on the endpoint device, security posture information associated with one or more of the endpoint device, the user, and the protected object; (ii) determining based on a set of ZTNA policies and the security posture information whether to allow the access request; and (iii) when the determination is affirmative, granting access to the protected object by the user via the endpoint device.

A method includes executing instructions associated with a public engagement computing platform on a server, publishing an agenda of a live event on the public engagement computing platform, and determining a set of trusted locations corresponding to a set of users of a number of client devices accessing the agenda. The method also includes analyzing communication pertinent to the agenda from at least a subset of the set of users, scoring at least the subset of the set of users based on the analyzed communication in accordance with the determined set of trusted locations and a relevance of the analyzed communication with respect to the agenda, and, in accordance with the scoring, determining a placement of the analyzed communication in an order of publicly viewable analyzed communication that is part of all analyzed communication pertinent to the agenda.