Protect healthcare system based on intelligent techniques

Al-Shaher, Mohamed Adel; Hameed, Rasha Talal; Țăpuș, Nicolae

doi:10.1109/codit.2017.8102628

Cited by 7 publications

(4 citation statements)

References 4 publications

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“…Finally, EHR electronic health records can be valuable human creations. It can be accessed using a particular domain or malicious codes [15]. reats can be noted and significantly impacted by their presence; threat management is most necessary for every business website and application.…”

Section: Literature Reviewmentioning

confidence: 99%

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Intelligence-based Network Security System to Predict the Possible Threats in Healthcare Data

Vijayakumar

Sukumaran²,

Murali³

et al. 2022

Security and Communication Networks

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The world is filled with exciting technologies and ideas; scientists build machines to avoid human intervention in completing work. It is highly challenging to complete the task without the artificial intelligence (AI) technology intervention. With technological development, specific processes or consultations are performed with doctors available worldwide. In this scenario, it could be noticed that health care is one of the world’s expected domains that require the most incredible attention in data security while performing data transfer. Nodes in the network are considered based on the weakest link to overcome the cyber attacker’s issues. Besides building the software for data storage, a better mechanism has to be incorporated to provide security to the stored data. This process is a delicate task for every network engineer. This paper will explain such concepts related to health prediction and health care by building the most robust network security systems. The proposed optimized neural network representation is differentiated with the available data conclusive process. From the outcomes, it is observed that the suggested representation achieves an accuracy of 98.89%, which is 4.76% higher than the existing model.

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Section: Literature Reviewmentioning

confidence: 99%

“…e accumulated scheme performance metric could be represented like a complex performance metric with in form of such a set of equations (15) and is represented below.…”

Section: Security and Communication Networkmentioning

confidence: 99%

Intelligence-based Network Security System to Predict the Possible Threats in Healthcare Data

Vijayakumar

Sukumaran²,

Murali³

et al. 2022

Security and Communication Networks

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“…In work performed by (Al-Shaher and al., 2017) in [80], they propose to protect the private healthcare system from known viruses, worms, spyware, and denial-of-service attacks by designing and implementing an Intelligent Healthcare Security System (IHSS). The IHSS integrates the firewall, network intrusion detection subsystem, and web filter.…”

Section: For Transmission Level Securitymentioning

confidence: 99%

Survey of Machine Learning Based Intrusion Detection Methods for Internet of Medical Things

Si-Ahmed¹,

Al-Garadi²,

Boustia³

2022

Preprint

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Internet of Medical Things (IoMT) represents an application of the Internet of Things, where health professionals perform remote analysis of physiological data collected using sensors that are associated with patients, allowing real-time and permanent monitoring of the patient's health condition and the detection of possible diseases at an early stage. However, the use of wireless communication for data transfer exposes this data to cyberattacks, and the sensitive and private nature of this data may represent a prime interest for attackers. The use of traditional security methods on equipment that is limited in terms of storage and computing capacity is ineffective. In this context, we have performed a comprehensive survey to investigate the use of the intrusion detection system based on machine learning (ML) for IoMT security. We presented the generic three-layer architecture of IoMT, the security requirement of IoMT security. We review the various threats that can affect IoMT security and identify the advantage, disadvantages, methods, and datasets used in each solution based on ML. Then we provide some challenges and limitations of applying ML on each layer of IoMT, which can serve as direction for future study.

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“…Penerapan firewall untuk pengamanan data [13] Enkripsi pada data RME, password dan backup sistem [14] Memberikan fitur hide (sembunyi) untuk mengatur mengenai data RME apa saja yang dapat ditampilkan atau disembunyikan dari pihak-pihak yang memiliki wewenang yang berbeda. [15] Enkripsi data, dan membuat data RME menjadi anonimus, jika data tersebut diambil untuk penelitian [16] Firewall, enkripsi dan dekripsi data RME, Audit Log, serta untuk menjaga keamanan data, data-data RME diawasi oleh seorang Chief Information Security Officer [17] Penerapan role-based dan autentifikasi personal dengan menggunakan enkripsi [12] [18] Password, kontrol akses dan firewall [8] Kontrol akses, Penyimpanan data dengan menggunakan Enkripsi, Audit untuk mengetahui siapa saja yang mengakses data dan apa saja perubahan yang dilakukan [19] Kontrol akses, Fungsi Log Audit untuk mengetahui kegiatan apa saja yang dilakukan pada data RME, Fungsi Agregasi data [20] Keamanan dengan menggunakan role-based [21] Role-Based Access Control (RBAC) [22] Skema autentifikasi dengan penggunaan ID [23] Kriptografi (tanda tangan digital, algoritma enkripsi, sertifikasi digital) [24] Mobile agents [25] Protokol kriptografi matriks RBAC [26] Tanda tangan digital [27] Cloud computing [28] Kontrol akses untuk mencegah orang yang tidak bertanggung jawab mengakses data RME.…”

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Literatur Review Permasalahan Privasi Pada Rekam Medis Elektronik

Ningtyas

Lubis

2018

pseudocode

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Rekam Medis Elektronik (RME) merupakan salah satu terobosan dari pemanfaatan teknologi informasi dalam bidang kesehatan bertujuan untuk mempermudah pelayanan kesehatan. Dengan semakin banyaknya penyedia layanan kesehatan yang memanfaatkan RME ini, yang harus diperhatikan bukan hanya masalah migrasi data dari konvensional menjadi digital, namun juga mengenai cara pengamanan data pada RME yang memiliki sifat sensitif dan rahasia yang selama ini permasalahan privasi belum diatur dan ditangani secara memadai pada proses pembuatan RME ini. Untuk menyelesaikan masalah tersebut, peneliti membuat sebuah literatur review mengenai teknik pengamanan data pada 20 artikel prosiding dan jurnal. Teknik pengamanan data yang seringkali digunakan sebagai usaha pengamanan data adalah kriptografi, firewall, dan kontrol akses. Kata Kunci: rekam medis elektronik, keamanan data, kriptografi, cyber-security Abstract: Electronic Medical Record (EMR) is one of the breakthroughs of the use of information technology in healthcare aims to facilitate health services. The number of healthcare providers utilizing EMR, which must be considered not only the problem of data migration from conventional to digital but also how to secure data on EMRs that privacy issues have not been adequately addressed and handled making the process of this EMR. To solve the problem, the researcher made a literature review of data security techniques in 20 articles proceedings and journals. Data security techniques that are often used as an effort to secure data is cryptography, firewall, and access control.

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Protect healthcare system based on intelligent techniques

Cited by 7 publications

References 4 publications

Intelligence-based Network Security System to Predict the Possible Threats in Healthcare Data

Intelligence-based Network Security System to Predict the Possible Threats in Healthcare Data

Survey of Machine Learning Based Intrusion Detection Methods for Internet of Medical Things

Literatur Review Permasalahan Privasi Pada Rekam Medis Elektronik

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