Biblio
In healthcare 4.0 ecosystems, authentication of healthcare information allows health stakeholders to be assured that data is originated from correct source. Recently, biometric based authentication is a preferred choice, but as the templates are stored on central servers, there are high chances of copying and generating fake biometrics. An adversary can forge the biometric pattern, and gain access to critical health systems. Thus, to address the limitation, the paper proposes a scheme, PHBio, where an encryption-based biometric system is designed prior before storing the template to the server. Once a user provides his biometrics, the authentication process does not decrypt the data, rather uses a homomorphic-enabled Paillier cryptosystem. The scheme presents the encryption and the comparison part which is based on euclidean distance (EUD) strategy between the user input and the stored template on the server. We consider the minimum distance, and compare the same with a predefined threshold distance value to confirm a biometric match, and authenticate the user. The scheme is compared against parameters like accuracy, false rejection rates (FARs), and execution time. The proposed results indicate the validity of the scheme in real-time health setups.
Biometric security is the fastest growing area that receives considerable attention over the past few years. Digital hiding and encryption technologies provide an effective solution to secure biometric information from intentional or accidental attacks. Visual cryptography is the approach utilized for encrypting the information which is in the form of visual information for example images. Meanwhile, the biometric template stored in the databases are generally in the form of images, the visual cryptography could be employed effectively for encrypting the template from the attack. This study develops a share creation with improved encryption process for secure biometric verification (SCIEP-SBV) technique. The presented SCIEP-SBV technique majorly aims to attain security via encryption and share creation (SC) procedure. Firstly, the biometric images undergo SC process to produce several shares. For encryption process, homomorphic encryption (HE) technique is utilized in this work. To further improve the secrecy, an improved bald eagle search (IBES) approach was exploited in this work. The simulation values of the SCIEP-SBV system are tested on biometric images. The extensive comparison study demonstrated the improved outcomes of the SCIEP-SBV technique over compared methods.
With the advent of technology and owing to mankind’s reliance on technology, it is of utmost importance to safeguard people’s data and their identity. Biometrics have for long played an important role in providing that layer of security ranging from small scale uses such as house locks to enterprises using them for confidentiality purposes. In this paper we will provide an insight into behavioral biometrics that rely on identifying and measuring human characteristics or behavior. We review different types of behavioral parameters such as keystroke dynamics, gait, footstep pressure signals and more.
The current paper is proposing a three-factor authentication (3FA) scheme based on three components. In the first component a token and a password will be generated (this module represents the kernel of the three-factor authentication scheme - 3FA). In the second component a pass-code will be generated, using to the token resulted in the first phase. We will use RSA for encryption and decryption of the generated values (token and pass-code). For the token ID and passcode the user will use his smartphone. The third component uses a searchable encryption scheme, whose purpose is to retrieve the documents of the user from the cloud server, based on a keyword and his/her fingerprint. The documents are stored encrypted on a mistrust server (cloud environment) and searchable encryption will help us to search specific information and to access those documents in an encrypted content. We will introduce also a software simulation developed in C\# 8.0 for our scheme and a source code analysis for the main algorithms.
E- Health systems, specifically, Telecare Medical Information Systems (TMIS), are deployed in order to provide patients with specific diseases with healthcare services that are usually based on remote monitoring. Therefore, making an efficient, convenient and secure connection between users and medical servers over insecure channels within medical services is a rather major issue. In this context, because of the biometrics' characteristics, many biometrics-based three factor user authentication schemes have been proposed in the literature to secure user/server communication within medical services. In this paper, we make a brief study of the most interesting proposals. Then, we propose a new three-factor authentication and key agreement scheme for TMIS. Our scheme tends not only to fix the security drawbacks of some studied related work, but also, offers additional significant features while minimizing resource consumption. In addition, we perform a formal verification using the widely accepted formal security verification tool AVISPA to demonstrate that our proposed scheme is secure. Also, our comparative performance analysis reveals that our proposed scheme provides a lower resource consumption compared to other related work's proposals.
Keystroke dynamics study the way in which users input text via their keyboards, which is unique to each individual, and can form a component of a behavioral biometric system to improve existing account security. Keystroke dynamics systems on free-text data use n-graphs that measure the timing between consecutive keystrokes to distinguish between users. Many algorithms require 500, 1,000, or more keystrokes to achieve EERs of below 10%. In this paper, we propose an instance-based graph comparison algorithm to reduce the number of keystrokes required to authenticate users. Commonly used features such as monographs and digraphs are investigated. Feature importance is determined and used to construct a fused classifier. Detection error tradeoff (DET) curves are produced with different numbers of keystrokes. The fused classifier outperforms the state-of-the-art with EERs of 7.9%, 5.7%, 3.4%, and 2.7% for test samples of 50, 100, 200, and 500 keystrokes.
One of the basic behavioural biometric methods is keystroke element. Being less expensive and not requiring any extra bit of equipment is the main advantage of keystroke element. The primary concentration of this paper is to give an inevitable review of behavioural biometrics strategies, measurements and different methodologies and difficulties and future bearings specially of keystroke analysis and mouse dynamics. Keystrokes elements frameworks utilize insights, e.g. time between keystrokes, word decisions, word mixes, general speed of writing and so on. Mouse Dynamics is termed as the course of actions captured from the moving mouse by an individual when interacting with a GUI. These are representative factors which may be called mouse dynamics signature of an individual, and may be used for verification of identity of an individual. In this paper, we compare the authentication system based on keystroke dynamics and mouse dynamics.
Biometric authentication offers promise for mobile security, but its adoption can be controversial, both from a usability and security perspective. We describe a preliminary study, comparing recollections of biometric adoption by computer security experts and non-experts collected in semi-structured interviews. Initial decisions and thought processes around biometric adoption were recalled, as well as changes in those views over time. These findings should serve to better inform security education across differing levels of technical experience. Preliminary findings indicate that both user groups were influenced by similar sources of information; however, expert users differed in having more professional requirements affecting choices (e.g., BYOD). Furthermore, experts often added biometric authentication methods opportunistically during device updates, despite describing higher security concern and caution. Non-experts struggled with the setting up fingerprint biometrics, leading to poor adoption. Further interviews are still being conducted.
Biometric is used for identifying the person based on their traits. Fingerprint is one of the most important and most used biometric trait for person authentication. Fingerprint database must be stored in efficient way and in most secure way so that it is unable to hack by the hacker and it will be able to recognize the person fast in large database. In this paper, we proposed an efficient way of storing the fingerprint data for fast recognition. We are using LT codes for storing the x coordinates of minutiae points and fingerprint images is stored in encrypted form with the coordinates. We are using on-the-y gaussian algorithm for decoding the x coordinates and calculate the value for finding similarity in between two fingerprints.