Abstract: Various embodiments provide an approach to detect intrusion of connected IoT devices. In operation, features associated with behavioral attributes as well as volumetric attributes of network data patterns of different IoT devices is analyzed by means of statistical analysis to determine deviation from normal operation data traffic patterns to detect anomalous operations and possible intrusions. Data from multiple networks and devices is combined in the cloud to provide for improved base models for statistical analysis.

Abstract: Various embodiments provide an approach to controlled access to online content. Such control may be based on a multitude of factors including but not limited to website content, profile for the person consuming the data. In operation, machine-learning techniques are used to classify the websites based on community and social media inputs, crowd-sourced data, as well as access rules implemented by parents or system administrators. Feedback from users/admins of the system, including the instances of allowed or denied access to websites, in conjunction with other relevant parameters, is used for iterative machine-learning techniques. Embodiments may also allow for real, or near real-time, approval or denial of access to websites by registered admins.

Abstract: Embodiments of the present invention disclose systems and methods for controlled access to a website from a mobile device when the mobile device is connected with an external public or private network away from home. Certain embodiments provide for such protection and security through the use of smart and secure home router which is connected to the mobile device through a virtual private network, whether in a module form or as a standalone server.

Abstract: Various embodiments provide an approach to application of access rules for Internet access based on DHCP host names in absence of a unique MAC address. The access rules can be modified by giving due consideration to various parameters associated with the users of the system. The system can be configured and managed by using mobile apps and web interfaces.

Abstract: Various embodiments provide an approach to detect intrusion of connected IoT devices. In operation, features associated with behavioral attributes as well as volumetric attributes of network data patterns of different IoT devices is analyzed by means of statistical analysis to determine deviation from normal operation data traffic patterns to detect anomalous operations and possible intrusions. Data from multiple networks and devices is combined in the cloud to provide for improved base models for statistical analysis.

Abstract: Embodiments of the present invention disclose systems and methods for controlled access to a website from a mobile device when the mobile device is connected with an external public or private network away from home. Certain embodiments provide for such protection and security through the use of smart and secure home router which is connected to the mobile device through a virtual private network, whether in a module form or as a standalone server.

Abstract: Various embodiments provide an approach to controlled access to online content. Such control may be based on a multitude of factors including but not limited to website content, profile for the person consuming the data. In operation, machine-learning techniques are used to classify the websites based on community and social media inputs, crowd-sourced data, as well as access rules implemented by parents or system administrators. Feedback from users/admins of the system, including the instances of allowed or denied access to websites, in conjunction with other relevant parameters, is used for iterative machine-learning techniques. Embodiments may also allow for real, or near real-time, approval or denial of access to websites by registered admins.

Abstract: Embodiments of the present invention disclose systems and methods for controlled access to a website from a mobile device when the mobile device is connected with an external public or private network away from home. Certain embodiments provide for such protection and security through the use of smart and secure home router which is connected to the mobile device through a virtual private network, whether in a module form or as a standalone server.

Abstract: Various embodiments provide an approach to detect intrusion of connected IoT devices. In operation, features associated with behavioral attributes as well as volumetric attributes of network data patterns of different IoT devices is analyzed by means of statistical analysis to determine deviation from normal operation data traffic patterns to detect anomalous operations and possible intrusions. Data from multiple networks and devices is combined in the cloud to provide for improved base models for statistical analysis.

Abstract: Various embodiments provide an approach to controlled access of websites based on website content, and profile for the person consuming the data. In operation, machine learning techniques are used to classify the websites based on community and social media inputs, crowdsourced data, as well as access rules implemented by parents or system administrators. Feedback from users/admins of the system, including the instances of allowed or denied access to websites, in conjunction with other relevant parameters, is used for iterative machine learning techniques.

Abstract: Various embodiments provide an approach to controlled access of websites based on website content, and profile for the person consuming the data. In operation, machine learning techniques are used to classify the websites based on community and social media inputs, crowdsourced data, as well as access rules implemented by parents or system administrators. Feedback from users/admins of the system, including the instances of allowed or denied access to websites, in conjunction with other relevant parameters, is used for iterative machine learning techniques.

Abstract: Various embodiments provide an approach to controlled access to online content. Such control may be based on a multitude of factors including but not limited to website content, profile for the person consuming the data. In operation, machine-learning techniques are used to classify the websites based on community and social media inputs, crowd-sourced data, as well as access rules implemented by parents or system administrators. Feedback from users/admins of the system, including the instances of allowed or denied access to websites, in conjunction with other relevant parameters, is used for iterative machine-learning techniques. Embodiments may also allow for real, or near real-time, approval or denial of access to websites by registered admins.

Abstract: Various embodiments provide an approach to detect intrusion of connected IoT devices. In operation, features associated with behavioral attributes as well as volumetric attributes of network data patterns of different IoT devices is analyzed by means of statistical analysis to determine deviation from normal operation data traffic patterns to detect anomalous operations and possible intrusions. Data from multiple networks and devices is combined in the cloud to provide for improved base models for statistical analysis.

Abstract: Various embodiments provide an approach to controlled access to online content. Such control may be based on a multitude of factors including but not limited to website content, profile for the person consuming the data. In operation, machine-learning techniques are used to classify the websites based on community and social media inputs, crowd-sourced data, as well as access rules implemented by parents or system administrators. Feedback from users/admins of the system, including the instances of allowed or denied access to websites, in conjunction with other relevant parameters, is used for iterative machine-learning techniques. Embodiments may also allow for real, or near real-time, approval or denial of access to websites by registered admins.

Abstract: Various embodiments provide an approach to controlled access of websites based on website content, and profile for the person consuming the data. In operation, machine learning techniques are used to classify the websites based on community and social media inputs, crowdsourced data, as well as access rules implemented by parents or system administrators. Feedback from users/admins of the system, including the instances of allowed or denied access to websites, in conjunction with other relevant parameters, is used for iterative machine learning techniques.

Abstract: Various embodiments provide an approach to controlled access to online content. Such control may be based on a multitude of factors including but not limited to website content, profile for the person consuming the data. In operation, machine-learning techniques are used to classify the websites based on community and social media inputs, crowd-sourced data, as well as access rules implemented by parents or system administrators. Feedback from users/admins of the system, including the instances of allowed or denied access to websites, in conjunction with other relevant parameters, is used for iterative machine-learning techniques. Embodiments may also allow for real, or near real-time, approval or denial of access to websites by registered admins.