Security enabled UAVs for Tech-Agriculture monitoring rice crops using FIBOR architecture

2021 ◽  
pp. 119-126
Author(s):  
J V N Lakshmi
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Continuous Monitoring ◽  
Security And Privacy ◽  
Security Model ◽  
Indian Agriculture ◽  
Collaborative Environment ◽  
Design Flexibility ◽  
Proposed Model ◽  
Farming Industry ◽  
Technical Collaboration

Unmanned Aerial Vehicles usage has significantly improved in all the sectors. Various industries are using drones as a platform for development with eco- nomic investment. Drastic advancement in design, flexibility, equipment and technical improvements has a great impact in creating airborne domain of IoT. Hence, drones have become a part of farming industry. Indian agriculture economy concentrates more on producing rice as this is considered as a staple food in various states. For increasing the production of rice sensors are equipped in the fields to track the water supply and humidity components. Whereas, identifying weeds, early stages of disease detection, recognizing failed crops, spraying fertilizers and continuous monitoring from bleats, locust and other dangerous insects are some of the technical collaboration with UAVs with respect farming sector. However, use of UAVs in real time environment involves many security and privacy challenges. In order to preserve UAVs from external vulnerabilities and hacking the collaborative environment requires a tough security model. In this proposed article a framework is implemented applying FIBOR security model on UAVs to suppress the threats from data hackers and protect the data in cloud from attackers. This proposed model enabled with drone technology provides a secured framework and also improves the crop yield by 15% by adapting a controlled network environment.

scholarly journals Multi-Layer Blockchain-Based Security Architecture for Internet of Things

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 772 ◽  
Author(s):  
Houshyar Honar Pajooh ◽  
Mohammad Rashid ◽  
Fakhrul Alam ◽  
Serge Demidenko
Keyword(s):  
Internet Of Things ◽  
Clustering Algorithm ◽  
Model Development ◽  
Base Stations ◽  
Smart Devices ◽  
Security Model ◽  
Cluster Heads ◽  
Authentication Mechanism ◽  
Proposed Model ◽  
Authentication And Authorization

The proliferation of smart devices in the Internet of Things (IoT) networks creates significant security challenges for the communications between such devices. Blockchain is a decentralized and distributed technology that can potentially tackle the security problems within the 5G-enabled IoT networks. This paper proposes a Multi layer Blockchain Security model to protect IoT networks while simplifying the implementation. The concept of clustering is utilized in order to facilitate the multi-layer architecture. The K-unknown clusters are defined within the IoT network by applying techniques that utillize a hybrid Evolutionary Computation Algorithm while using Simulated Annealing and Genetic Algorithms. The chosen cluster heads are responsible for local authentication and authorization. Local private blockchain implementation facilitates communications between the cluster heads and relevant base stations. Such a blockchain enhances credibility assurance and security while also providing a network authentication mechanism. The open-source Hyperledger Fabric Blockchain platform is deployed for the proposed model development. Base stations adopt a global blockchain approach to communicate with each other securely. The simulation results demonstrate that the proposed clustering algorithm performs well when compared to the earlier reported approaches. The proposed lightweight blockchain model is also shown to be better suited to balance network latency and throughput as compared to a traditional global blockchain.

Proposed Back Propagation Deep Neural Network for Intrusion Detection in Internet of Things Fog Computing

2021 ◽  
Vol 9 (4) ◽  
pp. 464-469
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Intrusion Detection ◽  
Fog Computing ◽  
Denial Of Service ◽  
Back Propagation ◽  
Security And Privacy ◽  
Brute Force ◽  
Iot Platform ◽  
Proposed Model

Internet of things (IoT) is an emerging concept which aims to connect billions of devices with each other anytime regardless of their location. Sadly, these IoT devices do not have enough computing resources to process huge amount of data. Therefore, Cloud computing is relied on to provide these resources. However, cloud computing based architecture fails in applications that demand very low and predictable latency, therefore the need for fog computing which is a new paradigm that is regarded as an extension of cloud computing to provide services between end users and the cloud user. Unfortunately, Fog-IoT is confronted with various security and privacy risks and prone to several cyberattacks which is a serious challenge. The purpose of this work is to present security and privacy threats towards Fog-IoT platform and discuss the security and privacy requirements in fog computing. We then proceed to propose an Intrusion Detection System (IDS) model using Standard Deep Neural Network's Back Propagation algorithm (BPDNN) to mitigate intrusions that attack Fog-IoT platform. The experimental Dataset for the proposed model is obtained from the Canadian Institute for Cybersecurity 2017 Dataset. Each instance of the attack in the dataset is separated into separate files, which are DoS (Denial of Service), DDoS (Distributed Denial of Service), Web Attack, Brute Force FTP, Brute Force SSH, Heartbleed, Infiltration and Botnet (Bot Network) Attack. The proposed model is trained using a 3-layer BP-DNN

scholarly journals Blockchain-Based Security Model for LoRaWAN Firmware Updates

2022 ◽  
Vol 11 (1) ◽  
pp. 5
Author(s):  
Njabulo Sakhile Mtetwa ◽  
Paul Tarwireyi ◽  
Cecilia Nombuso Sibeko ◽  
Adnan Abu-Mahfouz ◽  
Matthew Adigun
Keyword(s):  
Use Cases ◽  
Smart Devices ◽  
Area Network ◽  
Sensitive Information ◽  
Security Model ◽  
Functional Requirements ◽  
Wide Area Network ◽  
Proposed Model ◽  
Attack Surface ◽  
Iot Devices

The Internet of Things (IoT) is changing the way consumers, businesses, and governments interact with the physical and cyber worlds. More often than not, IoT devices are designed for specific functional requirements or use cases without paying too much attention to security. Consequently, attackers usually compromise IoT devices with lax security to retrieve sensitive information such as encryption keys, user passwords, and sensitive URLs. Moreover, expanding IoT use cases and the exponential growth in connected smart devices significantly widen the attack surface. Despite efforts to deal with security problems, the security of IoT devices and the privacy of the data they collect and process are still areas of concern in research. Whenever vulnerabilities are discovered, device manufacturers are expected to release patches or new firmware to fix the vulnerabilities. There is a need to prioritize firmware attacks, because they enable the most high-impact threats that go beyond what is possible with traditional attacks. In IoT, delivering and deploying new firmware securely to affected devices remains a challenge. This study aims to develop a security model that employs Blockchain and the InterPlanentary File System (IPFS) to secure firmware transmission over a low data rate, constrained Long-Range Wide Area Network (LoRaWAN). The proposed security model ensures integrity, confidentiality, availability, and authentication and focuses on resource-constrained low-powered devices. To demonstrate the utility and applicability of the proposed model, a proof of concept was implemented and evaluated using low-powered devices. The experimental results show that the proposed model is feasible for constrained and low-powered LoRaWAN devices.

scholarly journals A New Secure Model for Data Protection over Cloud Computing

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Amr M. Sauber ◽  
Passent M. El-Kafrawy ◽  
Amr F. Shawish ◽  
Mohamed A. Amin ◽  
Ismail M. Hagag
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Data Protection ◽  
Cloud Services ◽  
Security And Privacy ◽  
Storage Model ◽  
Cloud Data ◽  
Security Issues ◽  
Data Owner ◽  
Proposed Model

The main goal of any data storage model on the cloud is accessing data in an easy way without risking its security. A security consideration is a major aspect in any cloud data storage model to provide safety and efficiency. In this paper, we propose a secure data protection model over the cloud. The proposed model presents a solution to some security issues of cloud such as data protection from any violations and protection from a fake authorized identity user, which adversely affects the security of the cloud. This paper includes multiple issues and challenges with cloud computing that impairs security and privacy of data. It presents the threats and attacks that affect data residing in the cloud. Our proposed model provides the benefits and effectiveness of security in cloud computing such as enhancement of the encryption of data in the cloud. It provides security and scalability of data sharing for users on the cloud computing. Our model achieves the security functions over cloud computing such as identification and authentication, authorization, and encryption. Also, this model protects the system from any fake data owner who enters malicious information that may destroy the main goal of cloud services. We develop the one-time password (OTP) as a logging technique and uploading technique to protect users and data owners from any fake unauthorized access to the cloud. We implement our model using a simulation of the model called Next Generation Secure Cloud Server (NG-Cloud). These results increase the security protection techniques for end user and data owner from fake user and fake data owner in the cloud.

scholarly journals Considering business perception in assessing e-service quality in the Jordanian government

2021 ◽  
pp. 1591-1600
Author(s):  
Wesam Alabdallat ◽  
Omar Alhawari
Keyword(s):  
Service Quality ◽  
Conceptual Framework ◽  
Security And Privacy ◽  
Business Sector ◽  
Government Service ◽  
Five Dimensions ◽  
Government Services ◽  
Proposed Model ◽  
Business Perspective

Considering the speedy developments of e-services usages, countries are thriving to present better e-government services; particularly, regarding the business sector. Therefore, the matter of evaluating e-government service quality from the business perspective has become an important issue to study. This paper discussed how the business sector perceive the e-services provided by Jordanian government, which is basically derived based on the lack of literature and models addressing such issue. In this regard, this study aims to fill this existed gap. To tackle this problem, a conceptual framework of SERVQUAL questionnaire was developed and proposed. Then, the proposed model was verified and validated. The results of this paper concluded that business perceives different gaps between the actual and anticipated e-services in which the actual recorded less than the anticipated. Additionally, the gaps revealed in the developed SERVQUAL model, which included five dimensions showed, that only one element was found to be statistically insignificant and that is the Security and Privacy. Finally, the proposed model was revised and modified.

Automated monitoring and assessment of productivity in earthmoving projects

2018 ◽  
Vol 45 (11) ◽  
pp. 958-972 ◽  
Author(s):  
Ashraf Salem ◽  
Osama Moselhi
Keyword(s):  
Data Fusion ◽  
Continuous Monitoring ◽  
Research Work ◽  
Sensor Data ◽  
Fusion Algorithm ◽  
Cost Overruns ◽  
Knowledge Based ◽  
Monitoring Model ◽  
Multi Sensor Data Fusion ◽  
Proposed Model

Continuous monitoring of productivity and assessment of its variations are crucial processes that significantly contribute to success of earthmoving projects. Numerous factors may lead to productivity variations. However, these factors are subjectively identified using manual knowledge-based expert judgment. Such manual recognition process is not only subject to errors but also time-consuming. There is a lack of research work that focuses on near real-time assessment of productivity variation and its effect on cost, schedule and effective utilization of resources in earthmoving projects. This paper presents a customized multi-source automated data acquisition model that acquires data from a variety of wireless sensing technologies. The acquired multi-sensor data are transmitted to a central MySQL database. Then a newly developed data fusion algorithm is applied for truck state recognition, and hence the duration of each earthmoving state. Multi-sensor data fusion facilitates measurement of actual productivity, and consequently the assessment of productivity ratios that support continuous monitoring of productivity variation in earthmoving operations. The developed tracking and monitoring model generates an early warning that supports proactive decisions to avoid schedule delays, cost overruns, and inefficient depletion of resources. A case study is used to reveal the applicability of the proposed model in monitoring and assessing actual productivity and its deviations from planned productivity. Finally, results are discussed and conclusions are drawn highlighting the features of the proposed model.

Dynamic FCFS ACM Model for Risk Assessment on Real Time Unix File System

2015 ◽  
pp. 551-571
Author(s):  
Prashant Kumar Patra ◽  
Padma Lochan Pradhan
Keyword(s):  
Risk Assessment ◽  
Access Control ◽  
Security Policy ◽  
Security Requirements ◽  
Management Policy ◽  
Security Model ◽  
Distributed Environment ◽  
Web Portal ◽  
Proposed Model ◽  
The Right

The access control is a mechanism that a system grants, revoke the right to access the object. The subject and object can able to integrate, synchronize, communicate and optimize through read, write and execute over a UFS. The access control mechanism is the process of mediating each and every request to system resources, application and data maintained by a operating system and determining whether the request should be approve, created, granted or denied as per top management policy. The AC mechanism, management and decision is enforced by implementing regulations established by a security policy. The management has to investigate the basic concepts behind access control design and enforcement, point out different security requirements that may need to be taken into consideration. The authors have to formulate and implement several ACM on normalizing and optimizing them step by step, that have been highlighted in proposed model for development and production purpose. This research paper contributes to the development of an optimization model that aims and objective to determine the optimal cost, time and maximize the quality of services to be invested into security model and mechanisms deciding on the measure components of UFS. This model has to apply to ACM utilities over a Web portal server on object oriented and distributed environment. This ACM will be resolve the uncertainty, un-order, un formal and unset up (U^4) problems of web portal on right time and right place of any where & any time in around the globe. It will be more measurable and accountable for performance, fault tolerance, throughput, bench marking and risk assessment on any application.

Dynamic FCFS ACM Model for Risk Assessment on Real Time Unix File System

2013 ◽  
Vol 5 (4) ◽  
pp. 41-62
Author(s):  
Prashant Kumar Patra ◽  
Padma Lochan Pradhan
Keyword(s):  
Risk Assessment ◽  
Access Control ◽  
Security Policy ◽  
Security Requirements ◽  
Management Policy ◽  
Security Model ◽  
Distributed Environment ◽  
Web Portal ◽  
Proposed Model ◽  
The Right

The access control is a mechanism that a system grants, revoke the right to access the object. The subject and object can able to integrate, synchronize, communicate and optimize through read, write and execute over a UFS. The access control mechanism is the process of mediating each and every request to system resources, application and data maintained by a operating system and determining whether the request should be approve, created, granted or denied as per top management policy. The AC mechanism, management and decision is enforced by implementing regulations established by a security policy. The management has to investigate the basic concepts behind access control design and enforcement, point out different security requirements that may need to be taken into consideration. The authors have to formulate and implement several ACM on normalizing and optimizing them step by step, that have been highlighted in proposed model for development and production purpose. This research paper contributes to the development of an optimization model that aims and objective to determine the optimal cost, time and maximize the quality of services to be invested into security model and mechanisms deciding on the measure components of UFS. This model has to apply to ACM utilities over a Web portal server on object oriented and distributed environment. This ACM will be resolve the uncertainty, un-order, un formal and unset up (U^4) problems of web portal on right time and right place of any where & any time in around the globe. It will be more measurable and accountable for performance, fault tolerance, throughput, bench marking and risk assessment on any application.

scholarly journals Extraction of Fetal Heart Rate from Maternal ECG—Non Invasive Approach for Continuous Monitoring during Labor

Proceedings ◽  
2018 ◽  
Vol 2 (13) ◽  
pp. 1009 ◽  
Author(s):  
Tashreque Mohammed Haq ◽  
Safkat Arefin ◽  
Shamiur Rahman ◽  
Tanzilur Rahman
Keyword(s):  
Heart Rate ◽  
Fetal Heart Rate ◽  
Continuous Monitoring ◽  
Good Accuracy ◽  
Fetal Heart ◽  
Signal Separation ◽  
Invasive Approach ◽  
Non Invasive ◽  
Proposed Model ◽  
Fetal Scalp

Here, we propose a signal processing based approach for the extraction of the fetal heart rate (FHR) from Maternal Abdominal ECG (MAECG) in a non-invasive way. Datasets from a Physionet database has been used in this study for evaluating the performance of the proposed model that performs three major tasks; preprocessing of the MAECG signal, separation of Fetal QRS complexes from that of maternal and estimation of Fetal R peak positions. The MAECG signal is first preprocessed with improved multistep filtering techniques to detect the Maternal QRS (MQRS) complexes, which are dominant in the MAECG. A reference template is then reconstructed based on MQRS locations and removed from the preprocessed signal resulting in the raw FECG. This extracted FECG is further corrected and enhanced before obtaining the Fetal R peaks. The detection of FQRS and calculation of FHR has been compared against the reference Fetal Scalp ECG. Results indicate that the approach achieved good accuracy.

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