Securing User Authentication with Server-Side Voice Verification

User authentication is critical to the security of any information system. The traditional text-based passwords and even biometric systems based on face and fingerprint validation suffer from various drawbacks. Voice-based authentication systems have emerged as an effective alternative method. Within the user authentication systems, the server-side voice authentication systems added advantages. The purpose of this paper is to present an innovative approach to the use of voice verification for user authentication. This paper describes a new framework for the implementation of server-side voice authentication, ensuring that only the users who are authenticated and validated can access the system. In addition to providing enhanced security and a more pleasant user experience, this technology has potential applications in a wide range of fields.

A Short Review of the Literature on Assistive Technologies for Alzheimer’s Patients and Their Caregivers

Alzheimer’s is one of the most disabling neurocognitive diseases. A person diagnosed with Alzheimer’s slowly loses cognitive function and ultimately becomes entirely dependent upon the caregivers. Caregivers must help the patient in everyday activities ranging from walking to cooking, eating, and so on. In most caregiving facilities, a single caregiver often handles more than one patient, which results in caregiver burnout. Researchers are developing useful technologies to prevent caregiver burnouts and facilitate families in the best possible manner. The goal of this purposive short review of literature is to study the modern tools, devices, and gadgets available to Alzheimer’s patients and caregivers and understand the focus areas for future research. The review identified a range of products and technologies that help in monitoring to diagnosis, aid therapy, and reduce the burden on caregivers. These technologies play a vital role in improving the quality of life for both the patients and the caregivers. The study identified reducing cost of the devices, increasing robustness and dependability of the devices, and various aspects of the assistive technologies, including ethical and privacy issues, as the focus areas for future research.

Use of AI Voice Authentication Technology Instead of Traditional Keypads in Security Devices

Traditional keypads and text-based passwords are vulnerable to scams and hacks, leading to enormous levels of embezzlement and frauds apart from various other threats to data security. AI based voice authentication holds unparalleled value for data protection, security, and privacy, by providing an effective alternative to traditional password-based protection. This paper reports the findings of a limited literature review that forms the basis for further research towards enhancing the reliability and security of AI voice authentication. Based on the findings of the review of existing literature, this paper proposes that integration of the blockchain technology with the AI voice authentication can significantly enhance the data security, starting from mobile devices to the security of big agencies and banks. The key processes in implementing an AI voice authentication system are proposed as a conceptual model, to facilitate further research for implementation.

A Short Review of the Literature on Automatic Data Quality

Several organizations have migrated to the cloud for better quality in business engagements and security. Data quality is crucial in present-day activities. Information is generated and collected from data representing real-time facts and activities. Poor data quality affects the organizational decision-making policy and customer satisfaction, and influences the organization’s scheme of execution negatively. Data quality also has a massive influence on the accuracy, complexity and efficiency of the machine and deep learning tasks. There are several methods and tools to evaluate data quality to ensure smooth incorporation in model development. The bulk of data quality tools permit the assessment of sources of data only at a certain point in time, and the arrangement and automation are consequently an obligation of the user. In ensuring automatic data quality, several steps are involved in gathering data from different sources and monitoring data quality, and any problems with the data quality must be adequately addressed. There was a gap in the literature as no attempts have been made previously to collate all the advances in different dimensions of automatic data quality. This limited narrative review of existing literature sought to address this gap by correlating different steps and advancements related to the automatic data quality systems. The six crucial data quality dimensions in organizations were discussed, and big data were compared and classified. This review highlights existing data quality models and strategies that can contribute to the development of automatic data quality systems.