Hybrid Security Framework for Activity Based Authentication using RSA & Genetic Algorithm

In the current information age, security has achieved a tremendous importance in e-commerce applications involving financial transactions. Non-repudiation, data integrity, data confidentiality and authenticity, have become an integral part of information security. There is a tremendous risk involved in the communication of a plain text over Internet. Cryptography offers a solution for this type of risk which is referred to as a technique of encrypting and decrypting messages in such a way that they cannot be interpreted by anybody with the exception of a sender and an intended recipient. In majority of the e-commerce based applications where security is considered to be of prime importance, a single encryption algorithm is adopted for encrypting a password and the authentication information is stored on a single database server which becomes open to risks against different computer hacks. A novel solution for this problem is to generate an individual’s personal and dynamic activities which will be hard for the attackers to guess. Further, this can be combined with distributed technology where the authentication information is distributed over geographically separated multiple servers. In this paper authors have generated an activity based distributed 3D password incorporating various activities where the authentication information is distributed over geographically separated multiple authentication servers. The key pair is generated using RSA algorithm which is encrypted using single-point cross over and mutation of bits at the extreme position. This further adds another level of security and renders the key unbreakable by an unintended user. The configuration information pertaining to the distributed environment is stored in XML file which is parsed using Microsoft's XML Parser and the activity related information is stored in different servers which is encrypted using RSA algorithm. The technique employed combines RSA algorithm with Genetic Algorithm to offer a robust hybrid security framework in a distributed environment which is difficult to guess for an unintended user

Shallow Neural Network for Biometrics from the ECG-WATCH

Applications such as surveillance, banking and healthcare deal with sensitive data whose confidentiality and integrity depends on accurate human recognition. In this sense, the crucial mechanism for performing an effective access control is authentication, which unequivocally yields user identity. In 2018, just in North America, around 445K identity thefts have been denounced. The most adopted strategy for automatic identity recognition uses a secret for encrypting and decrypting the authentication information. This approach works very well until the secret is kept safe. Electrocardiograms (ECGs) can be exploited for biometric purposes because both the physiological and geometrical differences in each human heart correspond to uniqueness in the ECG morphology. Compared with classical biometric techniques, e.g. fingerprints, ECG-based methods can definitely be considered a more reliable and safer way for user authentication due to ECG inherent robustness to circumvention, obfuscation and replay attacks. In this paper, the ECG WATCH, a non-expensive wristwatch for recording ECGs anytime, anywhere, in just 10 s, is proposed for user authentication. The ECG WATCH acquisitions have been used to train a shallow neural network, which has reached a 99% classification accuracy and 100% intruder recognition rate

A Survey on Modality Characteristics, Performance Evaluation Metrics, and Security for Traditional and Wearable Biometric Systems

Biometric research is directed increasingly towards Wearable Biometric Systems (WBS) for user authentication and identification. However, prior to engaging in WBS research, how their operational dynamics and design considerations differ from those of Traditional Biometric Systems (TBS) must be understood. While the current literature is cognizant of those differences, there is no effective work that summarizes the factors where TBS and WBS differ, namely, their modality characteristics, performance, security and privacy. To bridge the gap, this paper accordingly reviews and compares the key characteristics of modalities, contrasts the metrics used to evaluate system performance, and highlights the divergence in critical vulnerabilities, attacks and defenses for TBS and WBS. It further discusses how these factors affect the design considerations for WBS, the open challenges and future directions of research in these areas. In doing so, the paper provides a big-picture overview of the important avenues of challenges and potential solutions that researchers entering the field should be aware of. Hence, this survey aims to be a starting point for researchers in comprehending the fundamental differences between TBS and WBS before understanding the core challenges associated with WBS and its design

A Survey of Wearable Biometric Recognition Systems

The growing popularity of wearable devices is leading to new ways to interact with the environment, with other smart devices, and with other people. Wearables equipped with an array of sensors are able to capture the owner’s physiological and behavioural traits, thus are well suited for biometric authentication to control other devices or access digital services. However, wearable biometrics have substantial differences from traditional biometrics for computer systems, such as fingerprints, eye features, or voice. In this article, we discuss these differences and analyse how researchers are approaching the wearable biometrics field. We review and provide a categorization of wearable sensors useful for capturing biometric signals. We analyse the computational cost of the different signal processing techniques, an important practical factor in constrained devices such as wearables. Finally, we review and classify the most recent proposals in the field of wearable biometrics in terms of the structure of the biometric system proposed, their experimental setup, and their results. We also present a critique of experimental issues such as evaluation and feasibility aspects, and offer some final thoughts on research directions that need attention in future work

Activity-Aware Electrocardiogram-based Passive Ongoing Biometric Verification

Identity fraud due to lost, stolen or shared information or tokens that represent an individual\u27s identity is becoming a growing security concern. Biometric recognition - the identification or verification of claimed identity, shows great potential in bridging some of the existing security gaps. It has been shown that the human Electrocardiogram (ECG) exhibits sufficiently unique patterns for use in biometric recognition. But it also exhibits significant variability due to stress or activity, and signal artifacts due to movement. In this thesis, we develop a novel activity-aware ECG-based biometric recognition scheme that can verify/identify under different activity conditions. From a pattern recognition standpoint, we develop algorithms for preprocessing, feature extraction and probabilistic classification. We pay particular attention to the applicability of the proposed scheme in ongoing biometric verification of claimed identity. Finally we propose a wearable prototype architecture of our scheme

A survey of wearable biometric recognition systems

The growing popularity of wearable devices is leading to new ways to interact with the environment, with other smart devices, and with other people. Wearables equipped with an array of sensors are able to capture the owner's physiological and behavioural traits, thus are well suited for biometric authentication to control other devices or access digital services. However, wearable biometrics have substantial differences from traditional biometrics for computer systems, such as fingerprints, eye features, or voice. In this article, we discuss these differences and analyse how researchers are approaching the wearable biometrics field. We review and provide a categorization of wearable sensors useful for capturing biometric signals. We analyse the computational cost of the different signal processing techniques, an important practical factor in constrained devices such as wearables. Finally, we review and classify the most recent proposals in the field of wearable biometrics in terms of the structure of the biometric system proposed, their experimental setup, and their results. We also present a critique of experimental issues such as evaluation and feasibility aspects, and offer some final thoughts on research directions that need attention in future work.This work was partially supported by the MINECO grant TIN2013-46469-R (SPINY) and the CAM Grant S2013/ICE-3095 (CIBERDINE

Privacy-Protecting Techniques for Behavioral Data: A Survey

Our behavior (the way we talk, walk, or think) is unique and can be used as a biometric trait. It also correlates with sensitive attributes like emotions. Hence, techniques to protect individuals privacy against unwanted inferences are required. To consolidate knowledge in this area, we systematically reviewed applicable anonymization techniques. We taxonomize and compare existing solutions regarding privacy goals, conceptual operation, advantages, and limitations. Our analysis shows that some behavioral traits (e.g., voice) have received much attention, while others (e.g., eye-gaze, brainwaves) are mostly neglected. We also find that the evaluation methodology of behavioral anonymization techniques can be further improved

A Intelligent Fingerprint Based Biometric System for Personal Identification-A Survey

Today, because of the vulnerability of standard authentication system, law-breaking has accumulated within the past few years. Identity authentication that relies on biometric feature like face, iris, voice, hand pure mathematics, handwriting, retina, fingerprints will considerably decrease the fraud. so that they square measure being replaced by identity verification mechanisms. Among biometrics fingerprint systems are one amongst most generally researched and used. it\'s fashionable due to their easy accessibility. During this paper we tend to discuss the elaborated study of various gift implementation define strategies together with their comparative measures and result analysis thus as realize a brand new constructive technique for fingerprint recognition