Splunk-Based Threat Intelligence of Cyber-Physical System: A Case Study with Smart Healthcare



Cyber-attack, Cyber-Physical System (CPS), Cyber Security, Denial-of-Service attacks, Eavesdropping attacks, Replay attacks, smart healthcare CPS, Zero-day attack


Cyber-Physical Systems (CPS) have been proven for many industrial applications like health monitoring, driverless cars, etc. CPS uses computer-based algorithms to monitor and control the IT infrastructure. CPS establishes a cyber-world connection with the physical world. This connection increases the risk of cyber-attacks. Risk assessment methods of traditional IT systems are not enough to assess the risk of CPS. Proper risk assessment and cyber Security of CPS are essential to overcome cyber threats at the very primary stage of their occurrence. This study has taken an effort to synthesize a secure and smart healthcare CPS system using Distributed Parallel Processing of Map Reduce (DPPMR) algorithm. This system monitors the health of remotely located patients as well as detects cyber-attacks on CPS in a short time to safeguard the sensor-based autonomous health monitoring system. This system sends cyber-attack notifications to CPS admin and emergency health condition notifications to the physician through a phone call, message, and email. This system has tested against specified cyber-attacks and monitors the health of 700+ patients for 50 days. This study has concluded that the detection time for cyber-attack and emergency health conditions is 60 seconds and the notification time is less than 90 seconds. Major cyber-attacks such as Zero-Day attack, Eavesdropping attack, Denial-of-Service attack, Brute Force attack, and Replay attack are considered in this study. Finally, a comparative analysis of developed security system with existing systems proved that security measures used by the developed system are more specific, accurate, and concentrated for CPS protection.


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Zero-Day Attack Detection




How to Cite

K. R. . Saraf and P. . Malathi, “Splunk-Based Threat Intelligence of Cyber-Physical System: A Case Study with Smart Healthcare”, Int J Intell Syst Appl Eng, vol. 11, no. 2, pp. 537–549, Feb. 2023.



Research Article