Cognitive internet of things (IoT) gateways for data security and privacy protection in real-time context-based data applications

• US 10,733,311 B2
• Filed: 03/29/2017
• Issued: 08/04/2020
• Est. Priority Date: 03/29/2017
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Chen, Sue Ann, Jalali, Fatemeh, Salehi, Mahsa, Vishwanath, Arun
• Primary Examiner(s): Pwu, Jeffrey C
• Assistant Examiner(s): Corum, Jr., William A
• Application Number:
  US15/472,369
• Publication Number:
  US 20180285580A1
• Time in Patent Office: 1,224 Days
• CPC Class Codes: G06F 21/316 by observing the pattern of computer usage, e.g. typical user behaviour
• CPC Class Codes: G06F 21/6218 to a system of files or objects, e.g. local or distributed file system or database
• CPC Class Codes: G06F 21/6254 by anonymising data, e.g. decorrelating personal data from the owner's identification
• CPC Class Codes: G06Q 40/08 Insurance
• CPC Class Codes: H04W 12/02 Protecting privacy or anonymity, e.g. protecting personally identifiable information [PII]

Abstract

A cognitive IoT gateway may receive real-time data associated with a user from sensor devices that are detecting user data in real-time. The real-time data is analyzed to determine whether the real-time data indicates a deviation from a predicted user behavior data predicted based on historical data. The real-time data is transformed into collated data that removes protected and sensitive information from the real-time data, and the collated data is transmitted to a server computer, wherein the protected and sensitive information received from the sensor devices remain local to the cognitive IoT gateway. Updated information computed by the server computer based on the collated data is received and a real-time alert is sent to a user device notifying the user of the updated information.

Claims

1. A cognitive Internet of Things (IoT) gateway system, comprising:

a hardware processor communicatively coupled to a server computer and sensor devices;

the hardware processor receiving from the server computer a predicted user behavior data associated with a user, wherein the server computer has provided an offering to the user based on the predicted user behavior, the predicted user behavior data computed by executing a machine learning algorithm on historical data stored in a database;

the hardware processor receiving real-time data associated with the user from the sensor devices that are detecting user data in real-time,

the hardware processor determining whether the real-time data deviates from the predicted user behavior data, the predicted user behavior data being data based on which the offering was provided,

responsive to determining that the real-time data deviates from the predicted user behavior data, the hardware processor transforming the real-time data into collated data that removes protected and sensitive information from the real-time data, and transmitting the collated data to the server computer, wherein the protected and sensitive information received from the sensor devices remain local to the hardware processor,

the hardware processor receiving from the server computer an updated offering, the updated offering computed by the server computer based on the collated data, and

the hardware processor transmitting a real-time alert to a user device to notify the user of the updated offering from the server computer,

wherein the hardware processor transforming the real-time data into collated data that removes protected and sensitive information from the real-time data comprises at least the hardware processor transforming a geographical coordinate location data into an amount of time spent on a type of location the geographical coordinate location data can be categorized into, the hardware processor transmitting the collated data without the geographical coordinate location data,

wherein the offering is an insurance premium and the server computer is associated with an insurance industry providing insurance to the user, wherein the insurance premium that is offered to the user is dynamically adjusted based on user'"'"'s real-time behavior detected by the sensor devices,

wherein the offering is a home insurance premium and the user'"'"'s real-time behavior comprises occupancy of the user'"'"'s home, wherein the hardware processor determines whether the real-time data deviates from the predicted user behavior data by detecting that connection is not established between the hardware processor and the user device during a specified timeframe.

2. The system of claim 1, wherein the hardware processor is a component of a smartphone associated with the user.

3. The system of claim 1, wherein the sensors comprise one or more of a wearable device, a location tracking device, a camera, motion detector, and a utility usage sensor.

4. The system of claim 1, wherein the hardware processor is deployed with an app received from the server computer and the hardware processor performs the receiving steps, the determining steps, the transforming, and the transmitting steps by executing the app.

5. The system of claim 1, wherein the offering further includes a car insurance premium and the user'"'"'s real-time behavior comprises road conditions of a route in which the user is currently driving.

14. The system of claim 1, wherein the hardware processor transforming a geographical coordinate location data into an amount of time spent on a type of location the geographical coordinate location data can be categorized into, comprises at least, the hardware processor transforming the geographical coordinate location data into the amount of time spent on an unpaved road.

6. A method of providing a cognitive IoT gateway, the method executed by at least one hardware processor communicatively coupled to at least a server computer and sensor devices, comprising:

receiving from the server computer a predicted user behavior data associated with a user, wherein the server computer has provided an offering to the user based on the predicted user behavior, the predicted user behavior data computed by executing a machine learning algorithm on historical data stored in a database;

receiving real-time data associated with the user from the sensor devices that are detecting user data in real-time;

determining whether the real-time data deviates from the predicted user behavior data, the predicted user behavior data being data based on which the offering was provided;

responsive to determining that the real-time data deviates from the predicted user behavior data, transforming the real-time data into collated data that removes protected and sensitive information from the real-time data, and transmitting the collated data to the server computer, wherein the protected and sensitive information received from the sensor devices remain local to the hardware processor;

receiving from the server computer an updated offering, the updated offering computed by the server computer based on the collated data; and

transmitting a real-time alert to a user device to notify the user of the updated offering from the server computer,

wherein the transforming the real-time data into collated data that removes protected and sensitive information from the real-time data comprises at least transforming a geographical coordinate location data into an amount of time spent on a type of location the geographical coordinate location data can be categorized into, wherein the collated data is transmitted to the server without the geographical coordinate location data,

wherein the offering is an insurance premium and the server computer is associated with an insurance industry providing insurance to the user, wherein the insurance premium that is offered to the user is dynamically adjusted based on user'"'"'s real-time behavior detected by the sensor devices,

wherein the offering is a home insurance premium and the user'"'"'s real-time behavior comprises occupancy of the user'"'"'s home, wherein the hardware processor determines whether the real-time data deviates from the predicted user behavior data by detecting that connection is not established between the hardware processor and the user device during a specified timeframe.

7. The method of claim 6, wherein the hardware processor is a component of a smartphone associated with the user.

8. The method of claim 6, wherein the sensors comprise one or more of a wearable device, a location tracking device, a camera, motion detector, and a utility usage sensor.

9. The method of claim 6, wherein the hardware processor is deployed with an app received from the server computer and the hardware processor performs the receiving steps, the determining steps, the transforming, and the transmitting steps by executing the app.

10. The method of claim 6, wherein the offering further includes a car insurance premium and the user'"'"'s real-time behavior comprises road conditions of a route in which the user is currently driving.

15. The method of claim 6, wherein the transforming a geographical coordinate location data into an amount of time spent on a type of location the geographical coordinate location data can be categorized into, comprises at least, transforming the geographical coordinate location data into the amount of time spent on an unpaved road.

11. A computer program product for providing a cognitive IoT gateway, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a device to cause the device to:

receive from a server computer a predicted user behavior data associated with a user, wherein the server computer has provided an offering to the user based on the predicted user behavior, the predicted user behavior data computed by executing a machine learning algorithm on historical data stored in a database;

receive real-time data associated with the user from sensor devices that are detecting user data in real-time;

determine whether the real-time data deviates from the predicted user behavior data, the predicted user behavior data being data based on which the offering was provided;

responsive to determining that the real-time data deviates from the predicted user behavior data, transform the real-time data into collated data that removes protected and sensitive information from the real-time data, and transmit the collated data to the server computer, wherein the protected and sensitive information received from the sensor devices remain local to the machine;

receive from the server computer an updated offering, the updated offering computed by the server computer based on the collated data; and

transmit a real-time alert to a user device to notify the user of the updated offering from the server computer,

wherein the offering is an insurance premium and the server computer is associated with an insurance industry providing insurance to the user, wherein the insurance premium that is offered to the user is dynamically adjusted based on user'"'"'s real-time behavior detected by the sensor devices,

wherein the offering is a home insurance premium and the user'"'"'s real-time behavior comprises occupancy of the user'"'"'s home, wherein the device is caused to determine whether the real-time data deviates from the predicted user behavior data by detecting that connection is not established between the device and the user device during a specified timeframe.

12. The computer program product of claim 11, wherein the machine is a component of a smartphone associated with the user.

13. The computer program product of claim 11, wherein the sensors comprise one or more of a wearable device, a location tracking device, a camera, motion detector, and a utility usage sensor.