Multi-Modal Biometric-Based Implicit Authentication of Wearable Device Users

Vhaduri, Sudip; Poellabauer, Christian

doi:10.1109/tifs.2019.2911170

Cited by 100 publications

(47 citation statements)

References 34 publications

(9 reference statements)

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“…Vhaduri and Poellabauer [22] proposed continuous user authentication scheme that uses 44 features extracted from various biometrics (calorie burn, metabolic equivalent of task (MET), heart rate and step count) using Fitbit Charge HR device and they achieved average accuracy of 87.37% with Quadratic SVM classifier in one-to-many approach and average accuracy of 93% with Quadratic SVM classifier in oneto-one approach. In their revised scheme [14], they adopted more features (65) with different feature selection approaches and 93% (sedentary) and 90% (non-sedentary) with equal error rates of 5% is obtained. However, the Fitbit framework only provides only one sample each minute and access to the raw data is not possible.…”

Section: Related Workmentioning

confidence: 99%

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Can a Smartband be Used for Continuous Implicit Authentication in Real Life

et al. 2020

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The use of cloud services that process privacy-sensitive information such as digital banking, pervasive healthcare, smart home applications requires an implicit continuous authentication solution, which will make these systems less vulnerable to the spoofing attacks. Physiological signals can be used for continuous authentication due to their uniqueness. Ubiquitous wrist-worn wearable devices are equipped with photoplethysmogram sensors, which enable us to extract heart rate variability (HRV) features. In this study, we show that these devices can be used for continuous physiological authentication for enhancing the security of the cloud, edge services, and IoT devices. A system that is suitable for the smartband framework comes with new challenges such as relatively low signal quality and artifacts due to placement, which were not encountered in full lead electrocardiogram systems. After the artifact removal, cleaned physiological signals are fed to the machine learning algorithms. In order to train our machine learning models, we collected physiological data using off-the-shelf smartbands and smartwatches in a real-life event. By applying a minimum quality threshold, we achieved a 3.96% Equal Error Rate. Performance evaluation shows that HRV is a strong candidate for continuous unobtrusive implicit physiological authentication.

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Section: Related Workmentioning

confidence: 99%

“…• One of the previous studies employed mean heart rate per minute which requires longer recordings and achieves approximately five minutes [14]. The proposed system uses more sophisticated HRV features derived from inter-beat intervals which are extracted from the raw PPG sensor data.…”

Section: Introductionmentioning

confidence: 99%

Can a Smartband be Used for Continuous Implicit Authentication in Real Life

et al. 2020

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“…The authentication for multiple servers is a difficult task for that BAN-logic is used for the effective security capability using multiple server architecture. The robust authentication scheme is used for Vehicle Sensor Networks (VSN) for continuous information of the vehicle and decentralized authentication for vehicle communication for fast efficient and security performance [12] [13]. The Proxy-based authentication scheme (PBAS) and Identity message-based authentication scheme (ID-MAP) is used for securing the message-related information which satisfies the Vehicular Ad-Hoc networks (VANETs) and edge computing scheme is also used for authentication of the further need of potential attacks.…”

Section: Dna Computing Based Encryption Algorithm For Wireless Multimmentioning

confidence: 99%

DNA Computing Based Encryption Algorithm for Wireless Multimedia Communication System

2020

IJITEE

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Transmission of digital images for wireless multimedia communication system requires reliable security in storage which is a challenging task. So many works are carried out to develop and implement the cryptographic techniques for a wireless multimedia communication system. A traditional symmetric key cryptographic algorithm such as Light weight Data Encryption Standard cipher, Advanced Encryption Standard cipher, Triple-DES, Twofish, Blowfish, RC5 etc played a major role to transmit and receive the multimedia (text, image and video) data. Proposed DNA computing based authentication algorithm provides secure transmission of multimedia data by using symmetric key cryptography techniques. DNA computing techniques provides a higher level of security and enables the user to store a large amount of data. Finally, it shows the implemented result analysis the performance of different symmetric key cryptographic techniques using the simulation parameters such as power consumption, key size, processing time, memory space, speed and latency. It also improves the security level by incorporating the advantage of DNA cryptography to achieve a high level of security against various attacks.

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“…Based on the review of the above literature, it appears that the continuous authentication method mixed with biometric features and physiological movement can address many security issues of mobile devices and applications [27]. However, each biometric of the characteristics such as fingerprints, iris, electroencephalography (EEG) data, voice, face, palm, ear, and gait, has its advantage or disadvantage.…”

Section: Related Workmentioning

confidence: 99%

A mobile app to make biometrics usage more secure

Singh¹,

Singh²

2020

Preprint

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With high paced growth in biometrics, its easy availability to capture various biometric features, it is <a>emerging as one of the most valuable technologies for multifactor authentication to verify a user’s identity, for data security. </a>Organizations encourage their members to use biometrics, but <a>they are hesitant to use due to perceived security risks. Because of its low usage rate, many medium and small segment organizations find it unfeasible to deploy robust biometric systems. </a>We propose a solution of an extra layer of security, via a low-cost mobile app framework, “Bio-Guard,” to use biometrics, more securely. We tested the app for its design, functions, usability, and it got a score of more than 71% on the usability scale and a reasonably low equal error rate (EER) of 6%. The survey to evaluate the usefulness of the app showed a favorable response of 80%. The results show a good potential of the app to make access to biometric data more secure. The app may enhance users’ confidence-level in encouraging higher participation of users in the usage of biometrics. Higher usage rates may make deployment of biometrics more cost-effective for many medium and small segment organizations to decrease their information security risk.

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Multi-Modal Biometric-Based Implicit Authentication of Wearable Device Users

Cited by 100 publications

References 34 publications

Can a Smartband be Used for Continuous Implicit Authentication in Real Life

Can a Smartband be Used for Continuous Implicit Authentication in Real Life

DNA Computing Based Encryption Algorithm for Wireless Multimedia Communication System

A mobile app to make biometrics usage more secure

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