Self-enhancing GPS-Based Authentication Using Corresponding Address

Thảo, Trần Phương; Irvan, Mhd; Kobayashi, Ryosuke; Yamaguchi, Rie Shigetomi; Nakata, Toru

doi:10.1007/978-3-030-49669-2_19

Cited by 8 publications

(12 citation statements)

References 14 publications

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“…One special characteristic of SPCAuth is the way how deviations from regular usage behavior are detected. Related approaches [7]- [9] usually establish one machine learning model for each user, which is trained on the basis of previous interactions. The trained model is then used to decide whether the user behavior in the context of a given action originates from the known user.…”

Section: Objectives and Backgroundmentioning

confidence: 99%

“…MutliLock [8] and T.P. Thao's [9] approach address user authentication by means of biometric and behavioral features. MultiLock uses several data sources (e.g.…”

Section: Related Workmentioning

confidence: 99%

“…16KIS1142K incoming requests upon arrival at the application server and check whether transmitted information, such as IP addresses, are consistent with previous requests of the same user [4], [5]. Additionally, it can be helpful to observe user interactions with the application and detect discrepancies, for example by observing typing patterns, touchscreen usage and the physical location of the devices used [6]- [9]. As a result, continuous authentication settings [10] can be established, where the user's behavior is permanently evaluated and authentication decisions are revised.…”

Section: Introductionmentioning

confidence: 99%

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SPCAuth: Scalable and Privacy-Preserving Continuous Authentication for Web Applications

Monschein

Waldhorst

2021

2021 IEEE 46th Conference on Local Computer Networks (LCN)

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As password-based authentication fails to provide adequate security for online activities such as financial transactions, additional authentication factors are required. Such factors should provide both ease of use and an adequate level of privacy protection, while being easy to implement, operate and maintain, even for applications with thousands of users. As an approach meeting these requirements, we outline Scalable and Privacy-Preserving Continuous Authentication (SPCAuth). SPCAuth determines risk levels for actions that should be authenticated, without requiring explicit user interactions. It analyzes different aspects of user behavior by means of machine learning methods, while preserving the privacy of the affected individuals. SPCAuth trains only a single model per aspect of user behavior being considered, based on observations of all users, ensuring scalability and increasing accuracy for users with infrequent activities. In two experiments, we have confirmed that this key concept enables a scalable and accurate user authentication.

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Section: Objectives and Backgroundmentioning

confidence: 99%

“…MutliLock [8] and T.P. Thao's [9] approach address user authentication by means of biometric and behavioral features. MultiLock uses several data sources (e.g.…”

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

SPCAuth: Scalable and Privacy-Preserving Continuous Authentication for Web Applications

Monschein

Waldhorst

2021

2021 IEEE 46th Conference on Local Computer Networks (LCN)

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“…Given limited information from the GPS (longitude, latitude, and timestamp), if metadata that carries extra independent information can be obtained from the GPS itself, it can help to improve the accuracy. An example of GPS-based self-enhancement comes from [7] in which the address is extracted from the pair of longitude and latitude using a reverse geocoding.…”

Section: Attacks and Vulnerabilities In Current Smartphone Authentica...mentioning

confidence: 99%

Location-based Behavioral Authentication Using GPS Distance Coherence

Thao

2020

Preprint

Self Cite

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Most of the current user authentication systems are based on PIN code, password, or biometrics traits which can have some limitations in usage and security. Lifestyle authentication has become a new research approach. A promising idea for it is to use the location history since it is relatively unique. Even when people are living in the same area or have occasional travel, it does not vary from day to day. For Global Positioning System (GPS) data, the previous work used the longitude, the latitude, and the timestamp as the features for the classification. In this paper, we investigate a new approach utilizing the distance coherence which can be extracted from the GPS itself without the need to require other information. We applied three ensemble classification Ran-domForest, ExtraTrees, and Bagging algorithms; and the experimental result showed that the approach can achieve 99.42%, 99.12%, and 99.25% of accuracy, respectively.

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“…Understanding individual human mobility plays an important role especially when the geographic spread of the infectious virus that causes COVID-19 has taken the world into uncharted territory. Not only that, it is also a critical factor in policy planning [1], [2], travel demand forecasting [3], [4], location-based recommendation/service advertising [6], or location-based personal authentication [5]. M. Gonzalez et al [25] proved that human mobility follows a high degree of regularity.…”

Section: Introductionmentioning

confidence: 99%

Influences of Temporal Factors on GPS-based Human Mobility Lifestyle

Thao

2020

Preprint

Self Cite

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Analysis of human mobility from GPS trajectories becomes crucial in many aspects such as policy planning for urban citizens, location-based service recommendation/prediction, and especially mitigating the spread of biological and mobile viruses. In this paper, we propose a method to find temporal factors affecting the human mobility lifestyle. We collected GPS data from 100 smartphone users in Japan. We designed a model that consists of 13 temporal patterns. We then applied a multiple linear regression and found that people tend to keep their mobility habits on Thursday and the days in the second week of a month but tend to lose their habits on Friday. We also explained some reasons behind these findings.

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Self-enhancing GPS-Based Authentication Using Corresponding Address

Cited by 8 publications

References 14 publications

SPCAuth: Scalable and Privacy-Preserving Continuous Authentication for Web Applications

SPCAuth: Scalable and Privacy-Preserving Continuous Authentication for Web Applications

Location-based Behavioral Authentication Using GPS Distance Coherence

Influences of Temporal Factors on GPS-based Human Mobility Lifestyle

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