Recovery of business intelligence systems: Towards guaranteed continuity of patient centric healthcare systems through a matrix-based recovery approach

Abstract

With the intensive use of the internet, patient centric healthcare systems shifted away from paper-based records towards a computerized format. Electronic patient centric healthcare databases contain information about patients that should be kept available for further reference. Healthcare databases contain potential data that makes them a goal for attackers. Hacking into these systems and publishing their contents online exposes them to a challenge that affects their continuity. Any denial of this service will not be tolerated since we cannot know when we need to retrieve a patient’s record. Denial of service affects the continuity of the healthcare system which in turn threatens patients’ lives, decreases the efficiency of the healthcare system and increases the operating costs of the attacked healthcare organization. Although there are many defensive security methods that have been devised, nonetheless malicious transactions may find a way to penetrate the secured safeguard and then modify critical data of healthcare databases. When a malicious transaction modifies a patient record in a database, the damage may spread to other records through valid transactions. Therefore, recovery techniques are required. The efficiency of the data recovery algorithm is substantial for e-healthcare systems. A patient cannot wait too long for his/her medical history to be recovered so that the correct medication be prescribed. Nevertheless, in order to have fast data recovery, an efficient damage assessment process should precede the recovery stage. The damage assessment must be performed as the intrusion detection system detects the malicious activity. The execution time of the recovery process is a crucial factor for measuring the performance because it is directly proportional to the denial of service time of any healthcare system. This paper presents a high performance damage assessment and recovery algorithm for e-healthcare systems. The algorithm provides fast damage assessment after an attack by a malicious transaction to keep the availability of the e-healthcare database. Reducing the execution time of recovery is the key target of our algorithm. The proposed algorithm outperforms the existing algorithm. It is about six times faster than the most recent proposed algorithm. In the worst case, the proposed algorithm takes 8.81 ms to discover the damaged part of the database; however, the fastest recent algorithm requires 50.91 ms. In the best case, the proposed algorithm requires 0.43 ms, which is 86 times faster than the fastest recent work. This is a significant reduction of execution time compared with other available approaches. Saving the damage assessment time means shorter denial of service periods, which in turn guarantees the continuity of the patient centric healthcare system.