Tracking and Repairing Damaged Healthcare Databases Using the Matrix

Abstract

In a distributed mobile e-health care system, e-health service providers exchange data on the fly in response to user queries without any centralized control. Local databases in e-health service providers might be intercepted during the exchange of data and read by intruders; and malicious transactions may damage data that is highly confidential. In this case any centralized control for securing data cannot be assumed to protect confidential data. Therefore, securing health information from malicious attacks has become a major concern. Although prevention techniques are available, the history of system break-ins guarantees that there is no foolproof technique that totally eliminates security loopholes in a computer system. Hence, efficient damage assessment and recovery techniques are needed. Traditional methods require scanning the entire log from the point of attack to the end which is a slow procedure. In this paper, we present an efficient damage assessment and recovery algorithm to recover the database from malicious transactions. The algorithm is based on data dependency and uses a single matrix. The results of this work prove that our algorithm performs better than the other algorithms in both the damage assessment and the recovery stages.

Data Integrity Preservation Schemes in Smart Healthcare Systems That Use Fog Computing Distribution

“…The use of a single 2D matrix helps store dependencies between transactions by identifying the affected segment of the database. Kaddoura et al [2] recommended also the use of a single matrix for damage assessment and recovery of algorithms.…”

“…As a solution to cloud computing performance related issues, e.g., high response time and real time data processing [1], CISCO introduced fog computing in 2012 , as multiple clouds are deployed close to the ground. This promising technology (i.e., fog computing) enables end users to utilize computing and processing services at the edge of the network [2], which in turn reduces the response time and the computation overhead to the cloud data centers. Additionally, many studies predicted that the number of connected IoT devices would be increased to exceed billions of devices.…”

An Effective Hash Based Assessment and Recovery Algorithm for Healthcare Systems. (c2019)

“…The work done in (Haraty et al, , 2018Haraty and Sai, 2017;Haraty and Zbib, 2014;Haraty et al, 2016;Kaddoura et al, 2015) reduced the number of data structures utilized by the damage assessment algorithm. Transaction dependency approaches was utilized in both Haraty and Sai, 2017).…”

“…Transaction dependency approaches was utilized in both Haraty and Sai, 2017). On the other hand, other papers (Haraty et al, 2018;Haraty and Zbib, 2014;Haraty et al, 2016;Kaddoura et al, 2015) utilized the data dependency paradigm for assessing the damage.…”

“…Rather than using an extra two-dimensional array, Kaddoura et al (2015) utilized a single two-dimensional array. At the beginning, the used data structure contains no data; then, for each committed transaction a designated row is populated such that the matrix columns contain all the modified value of the data items.…”