Privacy and biometrics for smart healthcare systems: attacks, and techniques

Wells, Alec; Usman, Aminu Bello

doi:10.1080/19393555.2023.2260818

Cited by 5 publications

(3 citation statements)

References 107 publications

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“…In SHS, patients' confidential healthcare and financial data are used, shared, and accessed by unauthorized people and parties such as the government, researchers, pharmaceutical companies, and laboratories, thus posing severe privacy issues [6]. When cybercriminals access sensitive healthcare data such as medical records, test results, and prescriptions, they can sell them on the dark web or black market [3]. The two most dangerous threats to patient data privacy are a lack of understanding of healthcare policies and regulations and hackers [48].…”

Section: Privacy Concernsmentioning

confidence: 99%

“…The global shortage of health professionals, coupled with the advancement of emerging technologies, has given help to the healthcare industry, thus giving rise to smart healthcare [1] [2]. Wells and Usman [3] and Bu et al [4] defined smart healthcare as a healthcare system that integrates and uses various emerging technologies to monitor patients and instantly access their medical information remotely, connect healthcare stakeholders, and automatically diagnose and detect diseases at an early stage. In SHSs, wearable or nonwearable sensors are implanted in patients to monitor and collect physiological data such as cardiac activity, pulse rate, blood pressure, electrocardiogram, temperature, heart rate, respiratory rate, oxygen volume in the body, activity level, and brain waves, which help in monitoring patients' health conditions or environmental data such as air quality, temperature, humidity, etc.…”

Section: Introductionmentioning

confidence: 99%

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Cybersecurity for Sustainable Smart Healthcare: State of the Art, Taxonomy, Mechanisms, and Essential Roles

Ali,

M. Mijwil

2024

Mesopotamian Journal of CyberSecurity

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Cutting-edge technologies have been widely employed in healthcare delivery, resulting in transformative advances and promising enhanced patient care, operational efficiency, and resource usage. However, the proliferation of networked devices and data-driven systems has created new cybersecurity threats that jeopardize the integrity, confidentiality, and availability of critical healthcare data. This review paper offers a comprehensive evaluation of the current state of cybersecurity in the context of smart healthcare, presenting a structured taxonomy of its existing cyber threats, mechanisms and essential roles. This study explored cybersecurity and smart healthcare systems (SHSs). It identified and discussed the most pressing cyber threats and attacks that SHSs face, including fake base stations, medjacking, and Sybil attacks. This study examined the security measures deployed to combat cyber threats and attacks in SHSs. These measures include cryptographic-based techniques, digital watermarking, digital steganography, and many others. Patient data protection, the prevention of data breaches, and the maintenance of SHS integrity and availability are some of the roles of cybersecurity in ensuring sustainable smart healthcare. The long-term viability of smart healthcare depends on the constant assessment of cyber risks that harm healthcare providers, patients, and professionals. This review aims to inform policymakers, healthcare practitioners, and technology stakeholders about the critical imperatives and best practices for fostering a secure and resilient smart healthcare ecosystem by synthesizing insights from multidisciplinary perspectives, such as cybersecurity, healthcare management, and sustainability research. Understanding the most recent cybersecurity measures is critical for controlling escalating cyber threats and attacks on SHSs and networks and encouraging intelligent healthcare delivery.

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Section: Privacy Concernsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Cybersecurity for Sustainable Smart Healthcare: State of the Art, Taxonomy, Mechanisms, and Essential Roles

Ali,

M. Mijwil

2024

Mesopotamian Journal of CyberSecurity

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“…Moreover, the EEG recording protocol (visual evoked potential) contributes in a fundamental and decisive way to system's resistance against this type of attacks, users cannot control these. According to [57], other recognition factors such as fingerprint, face, voice, and iris are vulnerable to enumerated profiles of imposters.…”

Section: Security Analysismentioning

confidence: 99%

Cryptographic Algorithm Designed by Extracting Brainwave Patterns

Dragu,

Nicolae,

Frunzete

2024

Mathematics

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A new authentication method based on EEG signal is proposed here. Biometric features such as fingerprint scanning, facial recognition, iris scanning, voice recognition, and even brainwave patterns can be used for authentication methods. Brainwave patterns, also known as brain biometrics, can be captured using technologies like electroencephalography (EEG) to authenticate a user based on their unique brain activity. This method is still in the research phase and is not yet commonly used for authentication purposes. Extracting EEG features for authentication typically involves signal processing techniques to analyze the brainwave patterns. Here, a method based on statistics for extracting EEG features is designed to extract meaningful information and patterns from the brainwave data for various applications, including authentication, brain–computer interface systems, and neurofeedback training.

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