HoneyDetails: A prototype for ensuring patient’s information privacy and thwarting electronic health record threats based on decoys

Abstract

Advancements in electronic health record system allow patients to store and selectively share their medical records as needed with doctors. However, privacy concerns represent one of the major threats facing the electronic health record system. For instance, a cybercriminal may use a brute-force attack to authenticate into a patient’s account to steal the patient’s personal, medical or genetic details. This threat is amplified given that an individual’s genetic content is connected to their family, thus leading to security risks for their family members as well. Several cases of patient’s data theft have been reported where cybercriminals authenticated into the patient’s account, stole the patient’s medical data and assumed the identity of the patients. In some cases, the stolen data were used to access the patient’s accounts on other platforms and in other cases, to make fraudulent health insurance claims. Several measures have been suggested to address the security issues in electronic health record systems. Nevertheless, we emphasize that current measures proffer security in the short-term. This work studies the feasibility of using a decoy-based system named HoneyDetails in the security of the electronic health record system. HoneyDetails will serve fictitious medical data to the adversary during his hacking attempt to steal the patient’s data. However, the adversary will remain oblivious to the deceit due to the realistic structure of the data. Our findings indicate that the proposed system may serve as a potential measure for safeguarding against patient’s information theft.

Exploring the challenges of and solutions to sharing personal genomic data for use in healthcare

“…The ethics of this pathway, as well as regulations concerning possible misconduct 9,29 in terms of the use of this information, even anonymized, 30 has been investigated, 31 but clear pathways and studies with real world data do not exist in the field of privacy research. 4 With regard to biobank consent, De Vries et al 32 suggest that broad consent is preferred.…”

“…Such data are typically well hidden and kept in secret, and privacy concerns commonly arise when health-related data are in question. 7,8,9 However, the sharing of one’s health data is not only a threat but may also benefit individual patients as predictive medicine may enable physicians to start treatments at an early stage and before more severe symptoms develop. The use of this and all data generated in multiple clinical studies would benefit and not only benefit but is a necessity for the researchers to be able to make advancements on personalized care.…”

A deeper look into cybersecurity issues in the wake of Covid-19: A survey

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Clinical Information Systems Research in the Pandemic Year 2020

“…For those interested in the potentially seminal topic “blockchain in healthcare”, we have included a scoping review by Hasselgren et al in our candidate paper selection [ 20 ]. And for those interested in security, we have selected an inspiring article by Omolara et al They present a prototype called HoneyDetails, a deception-based defense system against cybercriminals seeking to steal patient data from EHR systems [ 21 ].…”