Optimization of Security as an Enabler for Cloud Services and Applications

Deshpande, Varun; Nair, Mydhili K.; Bihani, Ayush

doi:10.1007/978-3-319-73676-1_10

Cited by 3 publications

(4 citation statements)

References 3 publications

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“…The network segment should be kept under monitoring for any potential unexpected traffic and be subjected to the necessary response [26]. The study in [8] focused on efficient message filtering for privacy-preserving authentication and secure packet forwarding for aggregated transmission evidence generation. Privacy of identification, location, input, output privacy, and function privacy is required for IoT security.…”

Section: Literature Reviewmentioning

confidence: 99%

“…According to the report "State of IoT Security" a 22% increase has been observed in cyber attacks on IoT applications. In addition, such attacks being highly graded and sophisticated indicate serious concerns [8,9]. As devices have limited processing and storage capabilities, smart devices are vulnerable to assaults as these devices violate many policies regarding security [10,11].…”

Section: Introductionmentioning

confidence: 99%

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Blockchain-Modeled Edge-Computing-Based Smart Home Monitoring System with Energy Usage Prediction

Iqbal

Altaf

Waris

et al. 2023

Sensors

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Internet of Things (IoT) has made significant strides in energy management systems recently. Due to the continually increasing cost of energy, supply–demand disparities, and rising carbon footprints, the need for smart homes for monitoring, managing, and conserving energy has increased. In IoT-based systems, device data are delivered to the network edge before being stored in the fog or cloud for further transactions. This raises worries about the data’s security, privacy, and veracity. It is vital to monitor who accesses and updates this information to protect IoT end-users linked to IoT devices. Smart meters are installed in smart homes and are susceptible to numerous cyber attacks. Access to IoT devices and related data must be secured to prevent misuse and protect IoT users’ privacy. The purpose of this research was to design a blockchain-based edge computing method for securing the smart home system, in conjunction with machine learning techniques, in order to construct a secure smart home system with energy usage prediction and user profiling. The research proposes a blockchain-based smart home system that can continuously monitor IoT-enabled smart home appliances such as smart microwaves, dishwashers, furnaces, and refrigerators, among others. An approach based on machine learning was utilized to train the auto-regressive integrated moving average (ARIMA) model for energy usage prediction, which is provided in the user’s wallet, to estimate energy consumption and maintain user profiles. The model was tested using the moving average statistical model, the ARIMA model, and the deep-learning-based long short-term memory (LSTM) model on a dataset of smart-home-based energy usage under changing weather conditions. The findings of the analysis reveal that the LSTM model accurately forecasts the energy usage of smart homes.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Blockchain-Modeled Edge-Computing-Based Smart Home Monitoring System with Energy Usage Prediction

Iqbal

Altaf

Waris

et al. 2023

Sensors

View full text Add to dashboard Cite

show abstract

“…Cloud computing has mainly faced security challenges on four levels which are network level, data level, user authentication level, and generic level [22,[62][63][64][65]. These above mentioned security challenges which big data faces on cloud are discussed in detail below: Distributed Nodes: this is a network level issue where all the nodes are connected with each other and data flow can be occurred any-where across the nodes.…”

Section: Introductionmentioning

confidence: 99%

Analyzing and Evaluating Critical Challenges and Practices for Software Vendor Organizations to Secure Big Data on Cloud Computing: An AHP-Based Systematic Approach

Khan

et al. 2021

IEEE Access

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Recently, its becomes easy to track down the data due to its availability in a large number. Although for data management, processing, and obtainability, cloud computing is considered a well-known approach for organizational development on the internet. Despite many advantages, cloud computing has still numerous security challenges that can affect the big-data usage on cloud computing. To find the security issues/challenges that are faced by software vendors' organizations we conducted a systematic literature review (SLR) through which we have find out 103 relevant research publications by developing a search string that is inspired by the research questions. This relevant data was comprised from different databases e.g. Google Scholar, IEEE Explore, ScienceDirect, ACM Digital Library, and SpringerLink. Furthermore, for the detailed literature review, we have accomplished all the steps in SLR, for example, development of SLR protocol, Initials and final assortment of the relevant data, data extraction, data quality assessment, and data synthesis. We identified fifteen (15) critical security challenges which are: data secrecy, geographical data location, unauthorized data access, lack of control, lack of data management, network-level issues, data integrity, data recovery, lack of trust, data sharing, data availability, asset issues, legal amenabilities, lack of quality, and lack of consistency. Furthermore, sixty four (64) standard practices are identified for these critical security challenges using the proposed SLR that could help vendor organizations to overcome the security challenges for big data. The findings of our research study demonstrate the resemblances and divergences in the identified security challenges in different periods, continents, databases, and methods. The proposed SLR will also support software vendor organizations for securing big data on the cloud computing platforms.

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“…Authors of [49] consider security policy implementation as the most challenging task in cloud computing for service providers. The key challenges include also:…”

mentioning

confidence: 99%

IoT Security Challenges: Cloud and Blockchain, Postquantum Cryptography, and Evolutionary Techniques

et al. 2021

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Internet of Things connects the physical and cybernetic world. As such, security issues of IoT devices are especially damaging and need to be addressed. In this treatise, we overview current security issues of IoT with the perspective of future threats. We identify three main trends that need to be specifically addressed: security issues of the integration of IoT with cloud and blockchains, the rapid changes in cryptography due to quantum computing, and finally the rise of artificial intelligence and evolution methods in the scope of security of IoT. We give an overview of the identified threats and propose solutions for securing the IoT in the future.

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Optimization of Security as an Enabler for Cloud Services and Applications

Cited by 3 publications

References 3 publications

Blockchain-Modeled Edge-Computing-Based Smart Home Monitoring System with Energy Usage Prediction

Blockchain-Modeled Edge-Computing-Based Smart Home Monitoring System with Energy Usage Prediction

Analyzing and Evaluating Critical Challenges and Practices for Software Vendor Organizations to Secure Big Data on Cloud Computing: An AHP-Based Systematic Approach

IoT Security Challenges: Cloud and Blockchain, Postquantum Cryptography, and Evolutionary Techniques

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