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A lightweight AES Algorithm Implementation for Secure IoT Environment
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In recent years, the rapid development in the field of wireless technologies led to the appearance of a new topic, known as the Internet of things (IoT). The IoT applications can be found in various fields of our life, such as smart home, health care, smart building, and etc. In all these applications, the data collected from the real world are transmitted through the Internet; therefore, these data have become a target of many attacks and hackers. Hence, a secure communication must be provided to protect the transmitted data from unauthorized access. This paper focuses on designing a secure IoT system to protect the sensing data. In this system, the security is provided by the use of Lightweight AES encryption algorithm to encrypt the data received from physical environment. The hardware used in this proposal is the Raspberry Pi 3 model B and two types of sensors. The LAES algorithm was embedded inside the Raspberry in order to protect the sensing data, that come from sensors connected to the Raspberry Pi, before sending them through the network. The analysis results show that the proposed IoT security system consumes less time in encryption/decryption and has high throughput when compared with others from related work. Its throughput is higher in about 19.24% than the value reported for one system in the related studies.

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Publication Date
Sat Jun 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
The Role of Green Human Resources Management in Achieving Sustainable Development
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The research aims at clarifying the role of green human resource management practices in achieving sustainable development. The research problem is that the health sector is less concerned with environmental aspects, specifically green human resource management practices, Which are reflected on sustainable development with their economic, environmental and social dimensions as well as reducing costs, waste minimization and recycling, And the research started from two main hypotheses to explore the correlation and influence between the variables of the research by analyzing the answers of the research sample, which included (136) employees of the Al-Imamein Al-kadhemein medical city, Data and information were collected using quest

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