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Trusted Unlock Zones Based on Environmental and Location Variables

IP.com Disclosure Number: IPCOM000247878D
Publication Date: 2016-Oct-09
Document File: 3 page(s) / 78K

Publishing Venue

The IP.com Prior Art Database

Abstract

Disclosed is a system composed of a smart device and an algorithm that determines a trusted device-unlock zone based on the following factors: environment, person awareness, trust level, conversation, sentimental analysis, and dynamic location. If the device is in a trusted zone, then the system automatically unlocks it.

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Trusted Unlock Zones Based on Environmental and Location Variables

With the latest growth and focus on mobility for business related devices , the increase of security restrictions for a user to access a device creates a burden the user needs to quickly access the device. Current methods to unlock a device include biometrics, complex passwords, pattern matching, among others. The main problem is that the smart device must be locked all the time ,

which means that the user must repeatedly enter a password throughout the day.

In some cases, the phone unlocking action can be extremely difficult to implement, if not dangerous (e.g., driving on a car, bicycling, walking the dog, pushing a wheelbarrow, etc.).

The novel solution is a system composed of a smart device and an algorithm that determines a trusted device -unlock zone based on the following factors: environment, person awareness, trust level, conversation, sentimental analysis, and dynamic location. If the device is in a trusted zone, then the system automatically unlocks it.

To determine the trusted zone, the system utilizes (but is not limited to) the following:


1. Location of the smart device (i.e., house, work, shopping mall, driving, etc.)


2. People in proximity to the user


3. Relationship the user has with the people in Step 2


4. Sentiment of the people in Step 2


5. Current relationship status with the people in Step 2

For the trust level computation, the factors are not limited to location, people in proximity, type of people (i.e., trusted or not trusted), and the sentiment analysis for people around. Definitions of computation components follow:


Location: a zone in which the smart device is in a specific moment. For instance, a user's home is considered a trusted area, but when a shopping mall is considered an untrusted area.


People in proximity: considered trusted when the user has a relationship with the person; otherwise, the person is not trusted. For instance, if any member of a user's family is in proximity to the user, then the system considers the zone trusted

Type of people: this refers to the category of people: family, friend, best friend, wife, etc.

Sentiment analysis: this factor can determine trust level of a zone. For example, a person who is a user's friend is, on a first instance, on a high trust level. However, in that moment, the system shows records that the user and the friend had a bad

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discussion on a messaging application; therefore, despite being a trusted person, this sentiment analysis can negatively impact the trust parameters. The system accordingly modifies the trust level in that particular situation.

All these factors can be combined in order to get a statistically significant value and put it into the security rules to establish a related action.

Figure: System diagram: Components and process

Referring to the system diagram:
100 Central...