Biblio

This research provides security and safety extensions to a blockchain based solution whose target is e-health. The Advanced Blockchain platform is extended with intelligent monitoring for security and machine learning for detecting patient treatment medication safety issues. For the reasons of stringent HIPAA, HITECH, EU-GDPR and other regional regulations dictating security, safety and privacy requirements, the e-Health blockchains have to cover mandatory disclosure of violations or enforcements of policies during transaction flows involving healthcare. Our service solution further provides the benefits of resolving the abnormal flows of a medical treatment process, providing accountability of the service providers, enabling a trust health information environment for institutions to handle medication safely, giving patients a better safety guarantee, and enabling the authorities to supervise the security and safety of e-Health blockchains. The capabilities can be generalized to support a uniform smart solution across industry in a variety of blockchain applications.

With the recent advances in computing, artificial intelligence (AI) is quickly becoming a key component in the future of advanced applications. In one application in particular, AI has played a major role - that of revolutionizing traditional healthcare assistance. Using embodied interactive agents, or interactive robots, in healthcare scenarios has emerged as an innovative way to interact with patients. As an essential factor for interpersonal interaction, trust plays a crucial role in establishing and maintaining a patient-agent relationship. In this paper, we discuss a study related to healthcare in which we examine aspects of trust between humans and interactive robots during a therapy intervention in which the agent provides corrective feedback. A total of twenty participants were randomly assigned to receive corrective feedback from either a robotic agent or a human agent. Survey results indicate trust in a therapy intervention coupled with a robotic agent is comparable to that of trust in an intervention coupled with a human agent. Results also show a trend that the agent condition has a medium-sized effect on trust. In addition, we found that participants in the robot therapist condition are 3.5 times likely to have trust involved in their decision than the participants in the human therapist condition. These results indicate that the deployment of interactive robot agents in healthcare scenarios has the potential to maintain quality of health for future generations.

Smart personal insulin pumps have been widely adopted by type 1 diabetes. However, many wireless insulin pump systems lack security mechanisms to protect them from malicious attacks. In previous works, the read-write attacks over RF channels can be launched stealthily and could jeopardize patients' lives. Protecting patients from such attacks is urgent. To address this issue, we propose a novel visible light channel based access control scheme for wireless infusion insulin pumps. This scheme employs an infrared photodiode sensor as a receiver in an insulin pump, and an infrared LED as an emitter in a doctor's reader (USB) to transmit a PIN/shared key to authenticate the doctor's USB. The evaluation results demonstrate that our scheme can reliably pass the authentication process with a low false accept rate (0.05% at a distance of 5cm).

Mobile Healthcare Networks (MHN) continuouslycollect the patients' health data sensed by wearable devices, andanalyze the collected data pre-processed by servers combinedwith medical histories, such that disease diagnosis and treatmentare improved, and the heavy burden on the existing healthservices is released. However, the network is vulnerable to Sybilattacks, which would degrade network performance, disruptproceedings, manipulate data or cheat others maliciously. What'smore, the user is reluctant to leak identity privacy, so the identityprivacy preserving makes Sybil defenses more difficult. One ofthe best choices is mutually authenticating each other with noidentity information involved. Thus, we propose a fine-grainedauthentication scheme based on Attribute-Based Signature (ABS)using lattice assumption, where a signer is authorized by an at-tribute set instead of single identity string. This ABS scheme usesFiat-Shamir framework and supports flexible threshold signaturepredicates. Moreover, to anonymously guarantee integrity andavailability of health data in MHN, we design an anonymousanti-Sybil attack protocol based on our ABS scheme, so thatSybil attacks are prevented. As there is no linkability betweenidentities and services, the users' identity privacy is protected. Finally, we have analyzed the security and simulated the runningtime for our proposed ABS scheme.

The revolution of smart devices has a significant and positive impact on the lives of many people, especially in regard to elements of healthcare. In part, this revolution is attributed to technological advances that enable individuals to wear and use medical devices to monitor their health activities, but remotely. Also, these smart, wearable medical devices assist health care providers in monitoring their patients remotely, thereby enabling physicians to respond quickly in the event of emergencies. An ancillary advantage is that health care costs will be reduced, another benefit that, when paired with prompt medical treatment, indicates significant advances in the contemporary management of health care. However, the competition among manufacturers of these medical devices creates a complexity of small and smart wearable devices such as ECG and EMG. This complexity results in other issues such as patient security, privacy, confidentiality, and identity theft. In this paper, we discuss the design and implementation of a hybrid real-time cryptography algorithm to secure lightweight wearable medical devices. The proposed system is based on an emerging innovative technology between the genomic encryptions and the deterministic chaos method to provide a quick and secure cryptography algorithm for real-time health monitoring that permits for threats to patient confidentiality to be addressed. The proposed algorithm also considers the limitations of memory and size of the wearable health devices. The experimental results and the encryption analysis indicate that the proposed algorithm provides a high level of security for the remote health monitoring system.