MECHANISM FOR DUAL LOOKUP IN SECURE TELEPHONY IDENTITY REVISITED (STIR)

Secure Telephony Identity Revisited (STIR) is a framework that enables the cryptographic assertion and verification of an identity of a caller. Through an out-of-band (OOB) mechanism, an entity that cryptographically asserts caller identity places a Personal Assertion Token (PASSporT) in a Call Placement Service (CPS). To verify the identity of the caller, a verification service running at a callee contacts the same CPS to obtain, decrypt, and verify the PASSporT identity assertion. In large scale deployments, such as a contact center, there is likely to be a single main line number for all incoming calls and that called number would be expected to service several hundred calls per minute resulting in a significant load on a verification service. Additionally, the verification service would be expected to sift through several hundred PASSporT entries on a CPS to obtain, decrypt and validate the correct PASSporT for a given call. Techniques are presented herein to address these challenges by providing to a verification service the explicit location of the PASSporT for a given call in the CPS

PATH INFORMATION-DRIVEN QUIC PATH_CHALLENGE TO OPTIMIZE PATH SELECTION IN 5G NETWORKS

Proposed herein are techniques that make use of an extended Quick UDP Internet Connection (QUIC) PATH_CHALLENGE frame to perform dynamic path selection operations within a 5G Wi-Fi/cellular network to optimize end-to-end performance. The techniques presented herein expands the capabilities of the current PATH_CHALLENGE function, as defined in the Internet Engineering Task Force (IETF) QUIC drafts. The additional information gathered as part of the PATH_CHALLENGE and the PATH_RESPONSE frame are used to understand path characteristics and dynamically optimize traffic flows accordingly

MANUFACTURER USADGE DESCRIPTION (MUD) LAYER 2 (L2) SUPPORT FOR ENHANCED SECURITY AND FUNCTIONALITY FOR MULTIPLE NETWORK INTERFACES

The growth of Internet of things (IoT) devices is increasing dramatically. IoT devices often have multiple interfaces and connectivity options, but these may not be communicated to a network in an automated fashion. Techniques are presented herein that extend the Manufacturer Usage Description (MUD) artifact so that it may be used to effectively communicate information about an IoT device’s multiple connectivity options to a network in an automated manner and to notify the network of possible interface vulnerabilities so that any number of different actions (e.g., alerts, configuration checks, etc.) may be performed

OBFUSCATION AND ANONYMIZATION TECHNIQUES FOR NETWORK DATA SETS FOR MACHINE LEARNING

Techniques are described herein for securing data used for a machine learning algorithm. The frequency or top-k values calculated over time of the respective network traffic feature data sets are used instead of the actual data or a set thereof (this can also be extended to any other data sets). Here, the frequency represents the actual data and thereby obfuscates potential sensitive information that should not be used within an oftentimes shared cloud machine learning application

LEVERAGING RICH CALL DATA TO ENHANCE CUSTOMER EXPERIENCE

Secure Telephony Identity Revisited (STIR) is an effort currently being utilized to provide cryptographic assurance of caller Identity in an effort to combat robocalls and impersonation attacks. The STIR framework can be used to transport additional claims during the course of a call. These additional claims, known as Rich Call Data (RCD), may be leveraged to embed useful, context-driven information. In particular, techniques presented herein provide an overarching framework through which companies that have a technical support division can advertise a set of RCD keys that would allow callers to avoid having to navigate interactive voice response (IVR) menus, specify support contract numbers, provide device serial numbers, and explain the specifics of assistance required. By advertising a set of required RCD keys, support organizations can expect to receive RCD calls from their customers. On parsing the key set present within an RCD STIR claim, systems can route calls to the appropriate tech support representatives or automatically open support cases

EFFICIENTLY ALLOCATING RADIO RESOURCES IN THE DOWNLINK DIRECTION TO MEET QUALITY OF SERVICE REQUIREMENTS OF 5G WIRELESS NETWORKS

Slice Differentiator (SD) machine learning techniques are provided herein to efficiently allocate resources to meet Quality of Service (QoS) requirements in 5G wireless networks. This enables adaptive training based optimization of QoS weights for different services

On the interpretability of fuzzy cognitive maps

This paper proposes a post-hoc explanation method for computing concept attribution in Fuzzy Cognitive Map (FCM) models used for scenario analysis, based on SHapley Additive exPlanations (SHAP) values. The proposal is inspired by the lack of approaches to exploit the often-claimed intrinsic interpretability of FCM models while considering their dynamic properties. Our method uses the initial activation values of concepts as input features, while the outputs are considered as the hidden states produced by the FCM model during the recurrent reasoning process. Hence, the relevance of neural concepts is computed taking into account the model’s dynamic properties and hidden states, which result from the interaction among the initial conditions, the weight matrix, the activation function, and the selected reasoning rule. The proposed post-hoc method can handle situations where the FCM model might not converge or converge to a unique fixed-point attractor where the final activation values of neural concepts are invariant. The effectiveness of the proposed approach is demonstrated through experiments conducted on real-world case studies

UNIQUE GESTURE TRIGGERED MESSAGE/SOS ALERTING USING REAL-TIME VIDEO ANALYTICS

The United States government, as well as other countries, are actively working on implementing Smart Cities. While there are various use cases that are being explored for Smart Cities, such as environment monitoring, transportation, etc. using advanced technologies to improve the overall safety of inhabitants, it is also important to improve the overall security of the inhabitants. There are various standardized signaling/alerting techniques, such as signaling SOS or the like using physical gestures etc. that are often used to signal emergency situations. Proposed herein are techniques to utilize advanced technologies, such as Deep Fusion Video analytics, along with facial behavioral and gesture analysis techniques, to configure unique, per-user-based Gesture to Signal Mappings for that can be used to trigger SOS/emergency and/or other types of alerts/actions upon detecting gestures of a given user

USING BLOCKCHAIN TO SIMPLIFY SESSION INITIATION PROTOCOL OVERLOAD CONTROL

Techniques are described herein by which the Session Initiation Protocol (SIP) server overload problem may be significantly simplified by using a distributed system where transactions can be authorized and stored. For example, a technology like blockchain may enable a centralized, shared, and secure transaction database to be used to communicate SIP server overload information. SIP server overload information may be shared between servers that are part of a trust domain. The trust domain may be confined within a network or span across network boundaries (e.g., between enterprise edges / SIP trunk providers / SIP calling cloud providers)

AUTOMATING NETWORK DEVICE CONFIGURATION TEMPLATE DISCOVERY

Establishing network device golden configuration templates typically relies on largely manual efforts and a dialogue between network consulting engineers and customers. Techniques are presented herein that streamline the process of discovering and baselining network standards by examining underlying themes and relationships between micro-templates in customer environments. Aspects of the presented techniques employ a Masked-Language Model (MLM), in a way that an MLM was not necessarily intended, to detect locally significant attributes in network device configurations for the express purpose of identifying structures that are common across a set of devices. Under further aspects of the presented techniques, the creation of association rules between configuration blocks and the devices on which they are found allows for the identification of underlying themes in configurations that form the basis of network standards and platform-based templates