Intelligent Hybrid Technique to Secure Bluetooth Communications

Abbood, Alaa Ahmed; Shallal, Qahtan Makki; Jabbar, Haider Khalaf

doi:10.1007/978-981-33-6966-5_14

Cited by 3 publications

(2 citation statements)

References 12 publications

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“…This approach was combined with two methods which are a hybrid method and regression-based prediction algorithm [37] to process the same issue in this field. However, a fast Fourier transformation was used with a machine learning based ensemble model for generating appropriate medical recommendations to patients suffering from chronic diseases [38], [39].…”

Section: Effectiveness Comparison With Previous Methodsmentioning

confidence: 99%

Clustering similar time series data for the prediction the patients with heart disease

Lafta

AL‐Musaylh

Shallal

2022

IJEECS

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Developed intelligent technologies are become play a promising role in providing better decision-making and improving the medical services provided to the patients. A risk prediction task for short-term is big challenge task; however, it is a great importance for recommendation systems in health care field to provide patients with accurate and reliable recommendations. In this work, clustering method and least square support vector machine are used for prediction a short-term disease risk prediction. The clustering similar method is based on euclidean Distance which used to identify the similar sliding windows. The proposed model is trained by using the slide windows samples. Finally, the appropriate recommendations are generated for heart diseases patients who need to take a medical test or not for following day using least square support vector machine. A real dataset which collected from heart diseases patient is used for evaluation. The proposed method yields a good results related by the recommendations accuracy generated to chronicle heart patients and reduce the risk of incorrect recommendations.

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Section: Effectiveness Comparison With Previous Methodsmentioning

confidence: 99%

Clustering similar time series data for the prediction the patients with heart disease

Lafta

AL‐Musaylh

Shallal

2022

IJEECS

Self Cite

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“…A.Abbood et al, (Abbood, Shallal, & Jabbar, 2021) describes a "Intelligent Hybrid Technique," which denotes a complex technique that is likely to involve advanced algorithms or methodologies. This shows that Bluetooth communications could have a high level of security.…”

Section: Literature Reviewmentioning

confidence: 99%

Quantum Shield For IoT: Enhancing Bluetooth Security with a Novel Hybrid Encryption Algorithm

Shirazi,

Wahab,

Shah

et al. 2024

ABBDM

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Bluetooth communication enables effective data sharing for a wide range of applications, from audio streaming to IoT devices, boosting user ease and productivity. Bluetooth security difficulties stem from flaws in encryption mechanisms, which could allow unauthorized access or data interception. Current flaws include vulnerability to eavesdropping and device spoofing, emphasizing the need for improved security measures. The hybrid encryption technique suggested in this paper is a tribute to unprecedented innovation in Bluetooth security. It pioneers a multi-layered approach to data protection by seamlessly integrating AES, Blowfish, RSA, and SHA-256. This algorithm not only answers current security concerns, but it also teaches how to use cryptographic approaches strategically. Furthermore, its prudent use of RSA, which minimizes computing overhead, demonstrates a forward-thinking approach to combining security and efficiency. The algorithm's astounding great accuracy after multiple tests demonstrates its practical practicality, confirming its potential to transform Bluetooth security procedures. This effort establishes a new cryptographic standard, altering the landscape of wireless communication security.

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