Table of ContentsIntroductionIssues in Healthcare Cybersecurity SystemA Review of the Benefits of Implementing a Fog Computing System in IOTPrevent cyberattacks in the healthcare systemDiscussionIntroduction On May 12, 2017, a ransomware called “WannaCry” broke out on the Internet. This ransomware attacked Microsoft Windows systems embedded in hundreds of thousands of computers in over 100 different countries (Jesse, 2017). An extremely large number of important files and information were encrypted and users had to pay money in the form of Bitcoins to decrypt the data otherwise the hard drive would be formatted and the data would be lost. Hospitals in some countries, such as Britain, which were hardest hit, were attacked because computers containing huge amounts of important patient information were locked and doctors were threatened to pay to recover the data . Say no to plagiarism. Get a tailor-made essay on 'Why violent video games should not be banned'?Get the original essayWannaCry attacked more than 60 national hospital systems in Britain, and thousands of patients were affected by the cancellation of appointment or delay in treatments (Martin, Ghafur, Kinross, Hankin, Darzi, 2018). The attack also had a huge influence on other sectors such as finance, IT, education and manufacturing since computers were locked and access to data controlled. This document will mainly address the problems facing the health system; new technology would protect the health system against attacks; and suggestions for preventing cyberattacks in the healthcare system. Issues in Healthcare Cybersecurity System Information security issues are accompanied by the development of the Internet. In the Internet age, we must appreciate the benefits of information explosion and social convenience. On the other hand, we must bear the risk of information leakage. In the internal management of hospitals, information construction has become an irreversible development trend. Therefore, if hospitals want to use the Internet to improve management efficiency and optimize medical and health services, they must face security issues when building network systems. Strict and feasible management measures must be implemented to prevent network security risks. that medical information and management information can better serve patients and ensure the efficient operation of hospitals. Healthcare faces an even bigger cybersecurity challenge than any other industry. The outdated system and its weaknesses make it the easiest system for hackers to attack. According to Guy and his colleagues, the main reason healthcare is an “attractive target” is the large amount of valuable data. There are several common types of cyberattacks in the healthcare system: Data theft for financial gain (identity theft, theft of personal information for financial gain), data theft for impact (exposing medical treatment of celebrities to the public), ransomware (creating malware on the system and demanding money to decrypt it), data corruption (falsifying the medical record for financial gain), denial of security attacks service (sending unnecessary requests to block the network), professional email compromise (pretending to be doctors and initiatingfalse communications) and unintentional self-dealing (unintentional actions caused by staff using an outdated system) (Guy, Paul, Chris, Ara, James 2017). When the software company, like Microsoft, releases a security patch on its operational systems, there will be a software vulnerability that will be exposed to the public. Hackers will actively notice these vulnerabilities and start hacking the imperfect system to make money. Microsoft is releasing security patches for its latest Windows system for free. However, for users using an older Windows system, updating these patches can be very expensive (Tobias, 2017). Most originations would like to avoid network or system management fees like this, so they decided not to purchase and install the patch. Hackers will easily discover these imperfect systems and launch criminal activities. New technology that protects healthcare against cyberattacks. Healthcare is still one of the most important issues people face. It is very difficult to design an IoT-based system because the sensor that collects patient information, in the form of Big Data, must be very efficient. In addition, some sensors have relatively low calculation speed, memory, transmission speed and power. In some cases, actual data analysis must be performed. In this article, regardless of the transmission speed and power consumption of the devices, the issue of cybersecurity will be addressed. Cloud storage, such as iCloud, OneDrive, and Google Drive, has been widely accepted by people due to its storage, ease of access, and price. Most healthcare systems store their data in cloud storage. Almost everyone who has access to the Internet has cloud storage space ranging from GB to TB. People tend to save their private data in the cloud so that they can access it at any time. However, there are pros and cons. As cyber threats increase with the development of cloud technology, it may no longer be safe to save personal or confidential data in the cloud. According to Tian, ​​there are different types of cyber threats in cloud storage services, such as data loss, malicious modifications, cloud server outages, etc. There are serious cyber accidents. For example, the Apple iCloud data leak accident in 2016. The leak affected around 64 million accounts. (Tian, ​​2018). The cloud computing service can no longer meet user requirements for increased cybersecurity. Thus, fog computing, also called edge computing, appears to people as a more intelligent computing model. In cloud storage service, user uploads their file directly to the cloud. Then, the Cloud Server Provider (CSP) will assume the responsibility of users to control the data. Thus, users do not actually control the physical storage of their data, creating a barrier between data ownership and management. In this case, the risk of data leakage is increased. Currently, the number of devices such as Apple Watch, Garmin, Fitbit, etc., that collect data, as well as the amount of data processed, is increasing exponentially. Typically, public cloud computing provides computing space to process this data through a remote server. server. However, it takes time to upload the acquired data to a remote server for analysis and then the results are sent back to the original location. This slows down the process which requires an immediate response fromprofessionals, particularly in the field of health care. Moreover, when the Internet connection is unreliable, relying on the remote server becomes the core of the problem. And in other cases, data that does not require immediate response is mainly analyzed, processed and stored in the cloud to perform historical analysis and big data analysis. Therefore, the proposed use of fog computing differs from cloud computing. While there are also private clouds residing in enterprise data centers and not shared with others, these typically provide more compute-intensive services for multiple devices or even the entire IT infrastructure of the enterprise. 'enterprise, but at the same time, private clouds can still have higher latency. in relation to fog computing. Additionally, small or medium-sized businesses, in particular, might not have the capabilities to manage their own private clouds. Fog computing allows them to build up IT resources to automate and control their production without using their own cloud or transmitting large amounts of data to public clouds. (Chrétien, 2018). It was proposed in 2011 by Cisco that fog computing could become the next IoT technology. Fog Computing is not a server but consists of various computer functions or sensors. It is widely accepted in electrical appliances, manufacturers, vehicles or even street lights. Fog computing is as alive as cloud computing, which sits between personal computing and cloud computing. Computing resources are provided at the ends of the network. Compared to cloud computing, fog computing is more decentralized. Data is processed locally in large quantities. Analysis is performed on-site and fully portable. It is a decentralized computing infrastructure where data, compute, storage and applications are distributed in the most logical way between data sources and the cloud, which is the most efficient location. Fog computing has several distinct features: low latency, position awareness, wide geographic distribution, mobility-friendly applications, and support for more edge nodes. These features make mobile service deployment more convenient and cater to a wider range of node access. A review of the benefits of implementing a fog computing system in iot. Reduced Latency To reduce the physical distance between the data collection device and the processor, latency and potential response can be decreased compared to a device-to-cloud architecture. To mitigate computational tasks for a device-only architecture, latency can also be reduced. The motivation may also be to keep latency predictable. Privacy To reduce data propagation, data can be analyzed on a local gateway but not on a data center outside of users' control. Thus, user privacy protection can be improved compared to the device-to-cloud architecture. Energy Efficiency There are several ways to improve the energy efficiency of sensors on the fog platform. With increasing sensor sleep cycle lengths, the gateway can be responsible for any request or update and then the sensor is woken up to process the request. Additionally, intensive computations and some other services can be offloaded from battery-powered nodes. Bandwidth Compared to a device-to-cloud architecture, the amount of data to besending to the data center can be reduced using fog computing. First, the raw data must be filtered, analyzed, preprocessed or compressed so that not all data has to be sent to the center. Second, local nodes can also perform some analytics from the devices containing the cached data. ScalabilityFrom more centralized resources, local computing can reduce workload and can be spent as needed so that Fog Computing can improve the scalability of a system. ReliabilityFog computing can increase system reliability either to achieve redundancy by letting a few nodes in the network provide the same functionality or run calculations closer to the sensor nodes so that they are not too dependent on the network connection. However, security is another major reason why businesses seek fog computing. Application data, such as healthcare and point-of-sale transactions, are key sensitive targets for cybercrime analysis and targeting identity thieves. However, fog computing is capable of making this data strictly protected. According to the OpenFog Consortium, the Fog system is responsible for protecting the information communication between the IoT device and the cloud, thus ensuring the security of applications in real time. The Fog system can also be used to securely store devices internally, away from vulnerable public networks. . Secure storage of data backups can be achieved by deploying reliable backup services, such as the storage services provided by Mozy, allowing businesses to schedule automated backups with military-grade encryption protection. Various systems are implemented to detect and prevent malicious cyberattacks on the for platform. .Privacy preservation can minimize data communication with fog nodes to reduce risks to preserve personal and critical data during communication. Insider data mitigation combines behavioral profiling and decoy approaches to mitigate security threats. Secure policy-based resource management improves secure interaction, sharing, and interoperability between user-requested resources. Authentication in the Fog platform will enable the Fog platform and the end user to protect themselves from attacks with the help of public key infrastructure, Diffien-Hellman key exchange, techniques intrusion detection and monitoring of modified input values. Additionally, the use of Advanced Encryption Standard (AES) as the encryption algorithm is suitable for the fog platform. (Khan, S., 2017) Many other efforts have also been made to improve the issue of security and privacy in the environment. More secure and efficient protocols are implemented to reduce power consumption without sacrificing performance. With Fog Computing, a lightweight encryption algorithm can be introduced between the Fog and the devices to improve the efficiency of the communication process. Fog computing also offers various possibilities to detect unusual behavior and attacks with a signature or anomaly based system. In the application of IoT in healthcare, security is one of the most important aspects. Thus, a high level of security can be ensured using operating system level techniques at gateways such as IPtable, which is essentially a table of rules according to which permissions on certain.