Artificial intelligent smart home automation with secured camera management-based GSM, cloud computing, and arduino

oai:ojs.pen.ius.edu.ba:article/1718Home management and controlling have seen a great introduction to network that enabled digital technology, especially in recent decades. For the purpose of home automation, this technique offers an exciting capability to enhance the connectivity of equipment within the home. Also, with the rapid expansion of the Internet, there are potentials that added to the remote control and monitoring of such network-enabled devices. In this paper, we had been designed and implemented a fully manageable and secure smart home automation system based on a cloud computing system with an ESP Arduino system. The security of home had been improved by adding a complete camera system with a GSM communication technique to connect the Arduino output data to an external specified number if there is no internet provider. We used three sensors for temperature, gas, and motion measurements. The ESP8226 Wi-Fi device programmed the sensors to maintain the sensors measurements and transfer them to the cloud server database which is programmed to the web server via Appatshy and Mysql formats. The system implemented with high time response so that all readings updated and appeared spontaneously. The designed system should be effective, a secure, and rapid response real-time smart home system should be achieved

Data protection based neural cryptography and deoxyribonucleic acid

The need to a robust and effective methods for secure data transferring makes the more credible. Two disciplines for data encryption presented in this paper: machine learning and deoxyribonucleic acid (DNA) to achieve the above goal and following common goals: prevent unauthorized access and eavesdropper. They used as powerful tool in cryptography. This paper grounded first on a two modified Hebbian neural network (MHNN) as a machine learning tool for message encryption in an unsupervised method. These two modified Hebbian neural nets classified as a: learning neural net (LNN) for generating optimal key ciphering and ciphering neural net CNN) for coding the plaintext using the LNN keys. The second granulation using DNA nucleated to increase data confusion and compression. Exploiting the DNA computing operations to upgrade data transmission security over the open nets. The results approved that the method is effective in protect the transferring data in a secure manner in less tim

ARTIFICIAL INTELLIGENCE IN BLOCKCHAIN-PROVIDE DIGITAL TECHNOLOGY

Artificial intelligence technologies, today, are rapidly developing and are an important branch of Computer Science. Artificial intelligence is at the heart of research and development of theory, methods, technologies, and applications for modeling and expanding human intelligence. Artificial intelligence technology has three key aspects, namely data, algorithm, and computing power, in the sense that training an algorithm to produce a classification model requires significant data, and the learning process requires improved computing capabilities. In the age of big data, information can come from a variety of sources (such as sensor systems, Internet of Things (IoT) devices and systems, as well as social media platforms) and/or belong to different stakeholders. This mostly leads to a number of problems. One of the key problems is isolated data Islands, where data from a single source/stakeholder is not available to other parties or training an artificial intelligence model, or it is financially difficult or impractical to collect a large amount of distributed data for Centralized Processing and training. There is also a risk of becoming a single point of failure in centralized architectures, which can lead to data intrusion. In addition, data from different sources may be unstructured and differ in quality, and it may also be difficult to determine the source and validity of the data. There is also a risk of invalid or malicious data. All these restrictions may affect the accuracy of the forecast. In practice, artificial intelligence models are created, trained, and used by various subjects. The learning process is not transparent to users, and users may not fully trust the model they are using. In addition, as artificial intelligence algorithms become more complex, it is difficult for people to understand how the result of training is obtained. So, recently there has been a tendency to move away from centralized approaches to artificial intelligence to decentralized ones

Cloud security: literature survey

Today, the growth of digitalization has made the ease for livelihood for all the organizations. Cloud computing the storage provider for all the computer resources has made it easy for accessing the data from anywhere anytime. But at the same time the security for cloud data storage is the major drawback which is provided by various cryptographic algorithms. These algorithms convert the data into unreadable format, known as cipher text, Rivest, Shamir and Adleman (RSA) one of the most popularly used asymmetric algorithm. This paper gives detailed review about such different cryptographic algorithms used for the cloud data security. The comparison study is also made for the size of data and to analyze the encryption time and decryption time, which concludes that to enhance the cloud data security some addon techniques are to be used along with these cryptographic algorithms. To increase the security level and to increase the transmission speed of plaintext, integrated method will be proposed by encoding the plaintext to intermediate plaintext and then intermediate plaintext will be compressed using any one of the compression techniques to increase the compression ratio, lastly the compressed file is encrypted to further enhance the security level

Analysis of Computer Network Security Storage System Based on Cloud Computing Environment

A fundamental component of cloud computers from a business perspective is that users are allowed to use any desire and pay with a product that desire. Its cloud services were accessible anytime and anywhere consumers needed them. As a result, consumers are free to purchase whatever IT services they want, and they don't have to worry about how easy things can be managed. The remote server is used in a new information storage computing architecture that is considered an Internet generation. Ensuring security, material at resource providers' sites is a challenge that must be addressed in cloud technology. Thus, rather than reliance on a single provider for knowledge storing, this research implies developing construction for protection of knowledge stockpiling with a variation of operations, in which knowledge is scrambled and divided into numerous cipher frames and distributed across a large number of provider places. This support was applied to provide greater security, scalability, or reliability that was suggested according to the new structure. This paper, presented an encoded model for the cloud environment to improve security. The proposed model comprises the parity metadata for the database management provision to the provider. In the developed encoder chunks parity is not stored within the single resources with the provision of the available information chunks. The constructed security architecture in the RAID layer increases the dependability of the data with the deployment of the RAID 10 deployment. The developed RAID-based encoder chunks exhibit improved efficiency for the higher uptime at a minimal cost

Artificial intelligent smart home automation with secured camera management-based GSM, cloud computing and arduino

Home management and controlling have seen a great introduction to network that enabled digital technology, especially in recent decades. For the purpose of home automation, this technique offers an exciting capability to enhance the connectivity of equipment within the home. Also, with the rapid expansion of the Internet, there are potentials that added to the remote control and monitoring of such network-enabled devices. In this paper, we had been designed and implemented a fully manageable and secure smart home automation system based on a cloud computing system with an ESP Arduino system. The security of home had been improved by adding a complete camera system with a GSM communication technique to connect the Arduino output data to an external specified number if there is no internet provider. We used three sensors for temperature, gas, and motion measurements. The ESP8226 Wi-Fi device programmed the sensors to maintain the sensors measurements and transfer them to the cloud server database which is programmed to the web server via Appatshy and Mysql formats. The system implemented with high time response so that all readings updated and appeared spontaneously. The designed system should be effective, a secure, and rapid response real-time smart home system should be achieved

Blockchain technology and internet of things: review, challenge and security concern

Blockchain (BC) has received high attention from many researchers recently because it has decentralization, trusted auditability, and transparency as its main properties. BC has contributed fundamentally to the development of applications like cryptocurrencies, health care, the internet of things (IoT), and so on. The IoT is envisioned to include billions of pervasive and mission-critical sensors and actuators connected to the internet. This network of smart devices is expected to generate and have access to vast amounts of information, creating unique opportunities for new applications, but significant security and privacy issues emerge concurrently because it does not contain robust security systems. BC provides many services like privacy, security, and provenance to the systems that depends on. This research includes analyzing and a comprehensive review of BC technologies. Moreover, the proposed solutions in academia with the methodologies that used to integrate blockchain with IoT are presented. Also, the types of attacks on blockchain are collected and classified. Furthermore, the main contributions and challenges that are included in the literature are explored, then the relevant recommendations for solving the explored challenges are proposed. In conclusion, the integration of BC with IoT could produce promising results in enhancing the security and privacy of IoT environment

Assessment of the status and factors influencing the adoption of cloud computing in knowledge-based companies Case Study: Kerman Science and Technology Park

Cloud computing is one of the most important topics in knowledge-based companies. Small and medium-sized enterprises with a low budget and few human resources are one of the major groups tending to use cloud computing to benefit from this technology. Several components affect the adoption of cloud in these companies, which should be evaluated before making the decision. This study aimed to identify these components and determine how much each component impacts the adoption of cloud in small and medium-sized companies. Accordingly, based on the diffusion of innovation theory and technology-organization-environment (TOE) framework as well as the previous studies, a conceptual model with twelve components was presented. Data were collected via a questionnaire using the descriptive survey method from 59 knowledge-based companies of Kerman Science and Technology Park. In this study, the “need” factor was selected as the desired state and “use” as the current state; then, the mean of the other components was compared with the mean of these two factors. The results of this study showed that based on the gap between the desired state and the current state, the employees’ knowledge of cloud computing, compatibility, complexity, and security and privacy require more attention. Innovation factors, decision makers’ knowledge of cloud computing, benefits, and costs have a better position than other components. Finally, factors effective in the compliance of knowledge-based companies of Kerman Science and Technology Park with cloud computing were ranked using the Vikor method. The need factor (information need), decision makers’ innovation, and benefits were ranked first to third, respectively, and the complexity factor was ranked last among the indicators. Therefore, identifying the current state (not using cloud computing based on the needs or not matching with cloud) and the desired state (using cloud computing based on the needs or matching with the cloud) in knowledge-based companies, based on the criteria or factors whose usefulness was investigated in this study, can be an important step in joining these companies into the cloud, and thus bringing the benefits of this new technology to knowledge-based companies

Enhanced grey wolf optimisation algorithm for feature selection in anomaly detection

Anomaly detection deals with identification of items that do not conform to an expected pattern or items present in a dataset. The performance of different mechanisms utilized to perform the anomaly detection depends heavily on the group of features used. Thus, not all features in the dataset can be used in the classification process since some features may lead to low performance of classifier. Feature selection (FS) is a good mechanism that minimises the dimension of high-dimensional datasets by deleting the irrelevant features. Modified Binary Grey Wolf Optimiser (MBGWO) is a modern metaheuristic algorithm that has successfully been used for FS for anomaly detection. However, the MBGWO has several issues in finding a good quality solution. Thus, this study proposes an enhanced binary grey wolf optimiser (EBGWO) algorithm for FS in anomaly detection to overcome the algorithm issues. The first modification enhances the initial population of the MBGWO using a heuristic based Ant Colony Optimisation algorithm. The second modification develops a new position update mechanism using the Bat Algorithm movement. The third modification improves the controlled parameter of the MBGWO algorithm using indicators from the search process to refine the solution. The EBGWO algorithm was evaluated on NSL-KDD and six (6) benchmark datasets from the University California Irvine (UCI) repository against ten (10) benchmark metaheuristic algorithms. Experimental results of the EBGWO algorithm on the NSL-KDD dataset in terms of number of selected features and classification accuracy are superior to other benchmark optimisation algorithms. Moreover, experiments on the six (6) UCI datasets showed that the EBGWO algorithm is superior to the benchmark algorithms in terms of classification accuracy and second best for the number of selected features. The proposed EBGWO algorithm can be used for FS in anomaly detection tasks that involve any dataset size from various application domains

The Challenges of Adopting Cloud Computing in Nigerian Government Organizations

Several technical challenges prevent the adoption of cloud computing by government organizations in Nigeria. Information technology (IT) leaders in the Nigerian government are concerned about this problem because the lack of cloud computing adoption may prevent the Nigerian government from taking advantage of cloud-based information systems to improve its service delivery to citizens and businesses. Grounded in the technology acceptance model, the purpose of this quantitative correlational study was to examine if IT administrators’ perception of data security and perception of fault tolerance can predict their intentions to adopt cloud computing. Data were collected from 79 IT administrators in government organizations in Nigeria. The results of the multiple regression were significant, F(2, 76) = 31.58, p \u3c .001, R2 = 0.45, with IT administrators’ perception of data security (β = .72, p \u3c .001) being the only significant predictor of IT administrators’ intention to adopt cloud computing; IT administrators’ perception of fault tolerance (β = .09, p = .37) was not a significant predictor of IT administrators’ intention to adopt cloud computing. The Nigerian government may use this study as a pedestal to measure cloud computing practice and maturity in all its organizations, improve existing cloud computing policies, and increase cloud computing training programs for its IT administrators. This study’s results might contribute to positive social change by helping the Nigerian government improve its service delivery to citizens and businesses through the increased adoption of cloud computing-based information systems