# US 10,771,504 B2 · Systems and methods for identifying data breaches

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- Number: US 10,771,504 B2
- Document ID: US10771504B2
- Status: Granted
- Kind: B2
- Application number: 16/004,357
- Filed: 2018-06-09
- Published: 2019-12-12
- Granted: 2020-09-08
- Earliest claimed: 2018-06-09
- Assignees: NortonLifeLock Inc.
- Applicants: Symantec Corporation
- Inventors: SriHarsha Angara; Michael Lo; Srini Chillappa; Simon Tiku; Viral Mehta; John Meehan
- Web page: https://patentgrep.com/patent/US10771504B2

## CPC

- G06F 21/6245: {Protecting personal data, e.g. for financial or medical purposes}
- H04L 63/1491: {using deception as countermeasure, e.g. honeypots, honeynets, decoys or entrapment}
- G06F 21/6263: {during internet communication, e.g. revealing personal data from cookies}
- H04L 63/0421: {Anonymous communication, i.e. the party's identifiers are hidden from the other party or parties, e.g. using an anonymizer}
- G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N)
- H04L: TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION (arrangements common to telegraphic and telephonic communication H04M)

## Abstract

The disclosed computer-implemented method for detecting unauthorized data shares may include (1) providing a user of an anonymized inbox with an email alias to use for a particular online entity, (2) identifying one or more emails sent to the email alias from one or more different entities that are different from the particular online entity, (3) determining, based on the one or more emails having been sent by the different entities, that the particular online entity has shared the user's email alias with other entities, and (4) creating a privacy score for the particular online entity based at least in part on the determination that the particular online entity has shared the user's email alias with other entities. Various other methods, systems, and computer-readable media are also disclosed.

## Claims

### Claim 1

A computer-implemented method for detecting unauthorized data shares, at least a portion of the method being performed by a computing device comprising at least one processor, the method comprising:
creating a privacy score for a particular online entity based on data generated and aggregated by a security server of a security service, wherein:
the security service provides a plurality of digital security services to users, the digital security services comprising (1) an anonymized inbox service that manages anonymized email aliases for users and (2) a web content analysis service that analyzes web content; and
creating the privacy score comprises creating the privacy score based on (1) a determination, collected from the anonymized inbox service, that the particular online entity has shared a user's personal data with other entities and (2) a number of fingerprinting scripts, identified by a tracker crawler of the web content analysis service, being served from one or more domains owned by the particular online entity; and
providing the privacy score within a vendor reputation database maintained by the security service, wherein the database enables users to (1) query the database for privacy information about online entities and (2) contribute user-input that details privacy information about online entities.

### Claim 2 (depends on 1)

The computer-implemented method of claim 1, wherein:
creating the privacy score comprises creating the privacy score based additionally on a number of different entities, identified via the anonymized inbox service, with which the particular online entity has shared the user's personal data.

### Claim 3 (depends on 1)

The computer-implemented method of claim 1, wherein the determination that the particular online entity has shared the user's personal data comprises a determination that the particular online entity has shared at least one of:
an email address;
credit card information; and
a telephone number.

### Claim 4 (depends on 1)

The computer-implemented method of claim 1, further comprising:
creating the privacy score based additionally on at least one of a number of trackers and a number of advertisements identified, via the web content analysis service, on a website of the particular online entity.

### Claim 5 (depends on 1)

The computer-implemented method of claim 1, further comprising:
creating the privacy score based additionally on the web content analysis service having identified, on one or more additional websites, content in one or more advertisements and/or trackers that was present on a website of the particular online entity when the user visited the website.

### Claim 6 (depends on 1)

The computer-implemented method of claim 1, wherein:
the digital security services further comprise a data security monitoring service; and
creating the privacy score comprises creating the privacy score based additionally on determining, from the data security monitoring service, that the user's personal data has been leaked.

### Claim 7 (depends on 1)

The computer-implemented method of claim 1, wherein the privacy score comprises a numerical value within a numerical privacy scale.

### Claim 8 (depends on 1)

The computer-implemented method of claim 1, wherein the privacy score comprises a privacy categorization.

### Claim 9 (depends on 1)

The computer-implemented method of claim 1, further comprising:
creating the privacy score based additionally on identified news content describing a data breach by the particular online entity.

### Claim 10 (depends on 1)

The computer-implemented method of claim 1, wherein creating the privacy score comprises:
collecting data from the digital security services on a per user level for a plurality of users and then aggregating data from the plurality of users to generate the privacy score.

### Claim 11 (depends on 1)

The computer-implemented method of claim 1, further comprising:
determining that the privacy score falls below a privacy score threshold; and
protecting at least one of the user and an additional user against unauthorized data sharing by the particular online entity in response to the determination that the privacy score falls below the privacy score threshold.

### Claim 12 (depends on 11)

The computer-implemented method of claim 11, wherein protecting at least one of the user and the additional user comprises at least one of:
transmitting a warning prompt to at least one of the user and the additional user; and
blocking at least one of the user and the additional user from electronically sharing personal data with the particular online entity.

### Claim 13 (depends on 1)

The computer-implemented method of claim 1, wherein the particular online entity comprises at least one of:
an online vendor;
an online service; and
a website.

### Claim 14 (depends on 1)

The computer-implemented method of claim 1, wherein the anonymized inbox service determines that the particular online entity has shared the user's personal data by:
providing the user with an email alias to use for the particular online entity;
identifying one or more emails sent to the email alias from one or more different entities that are different from the particular online entity; and
determining, based on the one or more emails having been sent by the different entities, that the particular online entity has shared the user's email alias with other entities.

### Claim 15

A system for detecting unauthorized data shares, the system comprising:
a scoring module, stored in memory, that creates a privacy score for a particular online entity based on data generated and aggregated by a security server of a security service, wherein:
the security service provides a plurality of digital security services to users, the digital security services comprising (1) an anonymized inbox service that manages anonymized email aliases for users and (2) a web content analysis service that analyzes web content;
creating the privacy score comprises creating the privacy score based on (1) a determination, collected from the anonymized inbox service, that the particular online entity has shared a user's personal data with other entities and (2) a number of fingerprinting scripts, identified by a tracker crawler of the web content analysis service, being served from one or more domains owned by the particular online entity; and
the scoring module provides the privacy score within a vendor reputation database maintained by the security service, wherein the database enables users to (1) query the database for privacy information about online entities and (2) contribute user-input that details privacy information about online entities; and
at least one physical processor configured to execute the scoring module.

### Claim 16 (depends on 15)

The system of claim 15, wherein:
the scoring module creates the privacy score based additionally on a number of different entities, identified via the anonymized inbox service, with which the particular online entity has shared the user's personal data.

### Claim 17 (depends on 15)

The system of claim 15, wherein the determination that the particular online entity has shared the user's personal data comprises a determination that the particular online entity has shared at least one of:
an email address;
credit card information; and
a telephone number.

### Claim 18 (depends on 15)

The system of claim 15, wherein:
the scoring module creates the privacy score based additionally on at least one of a number of trackers and a number of advertisements identified, via the web content analysis service, on a website of the particular online entity.

### Claim 19 (depends on 15)

The system of claim 15, wherein the privacy score comprises a privacy categorization.

### Claim 20

A non-transitory computer-readable medium comprising one or more computer-readable instructions that, when executed by at least one processor of a computing device, cause the computing device to:
create a privacy score for a particular online entity based on data generated and aggregated by a security server of a security service, wherein:
the security service provides a plurality of digital security services to users, the digital security services comprising (1) an anonymized inbox service that manages anonymized email aliases for users and (2) a web content analysis service that analyzes web content; and
creating the privacy score comprises creating the privacy score based on (1) a determination, collected from the anonymized inbox service, that the particular online entity has shared a user's personal data with other entities and (2) a number of fingerprinting scripts, identified by a tracker crawler of the web content analysis service, being served from one or more domains owned by the particular online entity; and
provide the privacy score within a vendor reputation database maintained by the security service, wherein the database enables users to (1) query the database for privacy information about online entities and (2) contribute user-input that details privacy information about online entities.
