scholarly journals Multifactor Authentication Methods: A Framework for Their Comparison and Selection

2020 ◽  
Author(s):  
Ignacio Velásquez ◽  
Angélica Caro ◽  
Alfonso Rodríguez
Keyword(s):  
Multifactor Authentication

scholarly journals Electromagnetic radiation-based IC device identification and verification using deep learning

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Hong-xin Zhang ◽  
Jia Liu ◽  
Jun Xu ◽  
Fan Zhang ◽  
Xiao-tong Cui ◽  
...  
Keyword(s):  
Radio Frequency ◽  
Electromagnetic Radiation ◽  
Integrated Circuit ◽  
Information Leakage ◽  
Physical Layer ◽  
Descent Method ◽  
Gradient Descent Method ◽  
Absolute Level ◽  
Device Identification ◽  
Multifactor Authentication

Abstract The electromagnetic radiation of electronic equipment carries information and can cause information leakage, which poses a serious threat to the security system; especially the information leakage caused by encryption or other important equipment will have more serious consequences. In the past decade or so, the attack technology and means for the physical layer have developed rapidly. And system designers have no effective method for this situation to eliminate or defend against threats with an absolute level of security. In recent years, device identification has been developed and improved as a physical-level technology to improve the security of integrated circuit (IC)-based multifactor authentication systems. Device identification tasks (including device identification and verification) are accomplished by monitoring and exploiting the characteristics of the IC’s unintentional electromagnetic radiation, without requiring any modification and process to hardware devices, thereby providing versatility and adapting existing hardware devices. Device identification based on deep residual networks and radio frequency is a technology applicable to the physical layer, which can improve the security of integrated circuit (IC)-based multifactor authentication systems. Device identification tasks (identification and verification) are accomplished by passively monitoring and utilizing the inherent properties of IC unintended RF transmissions without requiring any modifications to the analysis equipment. After the device performs a series of operations, the device is classified and identified using a deep residual neural network. The gradient descent method is used to adjust the network parameters, the batch training method is used to speed up the parameter tuning speed, the parameter regularization is used to improve the generalization, and finally, the Softmax classifier is used for classification. In the end, 28 chips of 4 models can be accurately identified into 4 categories, then the individual chips in each category can be identified, and finally 28 chips can be accurately identified, and the verification accuracy reached 100%. Therefore, the identification of radio frequency equipment based on deep residual network is very suitable as a countermeasure for implementing the device cloning technology and is expected to be related to various security issues.

scholarly journals Multifactor Authentication

2014 ◽  
Author(s):  
Ionuţ-Daniel BARBU ◽  
Gabriel PETRICĂ
Keyword(s):  
Information Security ◽  
Internet Of Things ◽  
Brute Force ◽  
Password Authentication ◽  
Multifactor Authentication ◽  
Processing Power ◽  
Defense In Depth

With the advent of Internet of Things, large number of devices became connected to the cloud via various services. From an Information Security perspective, this aspect adds additional tasks to the defense in depth layers. This article tackles the authentication level and its options. This topic has been chosen, as user/password authentication is obsolete and no longer secure. Despite the increased complexity of the passwords, the use of rainbow tables and the large processing power available, the systems are vulnerable to brute force attacks.

scholarly journals MyMaster : A Multifactor Authentication Scheme for Smart Home Device

2021 ◽  
Vol 9 (1) ◽  
pp. 89-96
Author(s):  
EMILLI LIJAU
Keyword(s):  
Smart Home ◽  
Mutual Authentication ◽  
Remote Access ◽  
The Internet ◽  
Home Gateway ◽  
Privacy Leakage ◽  
Intelligent Home ◽  
Multifactor Authentication ◽  
Intelligent Devices ◽  
Privacy And Confidentiality

Smart homes are one of the Internet of Things (IoT) applications most significant to enable people to operate intelligent devices on the Internet in their homes. However, when users can access an intelligent home system remotely, they have major privacy and confidentiality difficulties to overcome. Nothing has been done to improve the safety characteristics of an intelligent home with current research on authentication approaches. For example, to address these issues and to develop a reciprocal tracking authentication system with a critical aspect of a deal, we recommend an Internet based Smart Home System (IFTTT) model. As a controller and a safety guard, an IFTTT-Home Gateway provides a user with remote access to a Smart Home System within their company. The system is designed for mutual authentication with security features such as anonymity and full advance security by using Elliptical Curve Encryption, Nonces, XOR or cryptographic Hash functions. We also incorporate multi factor authentication (MFA) into the model to ensure more security and preventing privacy leakage.

Advances in Biometrics for Secure Human Authentication System

Biometrics ◽  
2017 ◽  
pp. 1834-1852
Author(s):  
Jagannath Mohan ◽  
Adalarasu Kanagasabai ◽  
Vetrivelan Pandu
Keyword(s):  
Recent Decade ◽  
Biometric Identification ◽  
Multimodal Biometrics ◽  
Biometric Analysis ◽  
Multifactor Authentication ◽  
Potential Alternative ◽  
Authentication System ◽  
Identification Techniques ◽  
Electrocardiogram Ecg ◽  
Pcg Signals

In the recent decade, one of our major concerns in the global technological society of information security is confirmation that a person accessing confidential information is authorized to perform so. Such mode of access is generally accomplished by a person's confirming their identity by the use of some method of authentication system. In present days, the requirement for safe security in storing individual information has been developing rapidly and among the potential alternative is implementing innovative biometric identification techniques. This chapter discusses how the advent of the 20th century has brought forth the security principles of identification and authentication in the field of biometric analysis. The chapter reviews vulnerabilities in biometric authentication and issues in system implementation. The chapter also proposes the multifactor authentication and the use of multimodal biometrics, i.e., the combination of Electrocardiogram (ECG) and Phonocardiogram (PCG) signals to enhance reliability in the authentication process.

Sign in / Sign up

Export Citation Format

Share Document