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Smart farming has the potential to overcome the challenge of 2050 to feed 10 billion people. Both artificial intelligence (AI) and the internet of things (IoT) have become critical prerequisites to smart farming due to their high interoperability, sensors, and cutting-edge technologies. Extending the role of responsible leadership, this paper proposes an AI and IoT based smart farming system in Bangladesh. With a comprehensive literature review, this paper counsels the need to go beyond the simple application of traditional farming and irrigation practices and recommends implementing smart farming enabling responsible leadership to uphold sustainable agriculture. It contributes to the current literature of smart farming in several ways. First, this paper helps to understand the prospect and challenges of both AI and IoT and the requirement of smart farming in a nonwestern context. Second, it clarifies the interventions of responsible leadership into Bangladesh’s agriculture sector and justifies the demand for sustainable smart farming. Third, this paper is a step forward to explore future empirical studies for the effective and efficient use of AI and IoT to adopt smart farming. Finally, this paper will help policymakers to take responsible initiatives to plan and apply smart farming in a developing economy like Bangladesh.
Amlan Haque; Nahina Islam; Nahidul Samrat; Shuvashis Dey; Biplob Ray. Smart Farming through Responsible Leadership in Bangladesh: Possibilities, Opportunities, and Beyond. Sustainability 2021, 13, 4511 .
AMA StyleAmlan Haque, Nahina Islam, Nahidul Samrat, Shuvashis Dey, Biplob Ray. Smart Farming through Responsible Leadership in Bangladesh: Possibilities, Opportunities, and Beyond. Sustainability. 2021; 13 (8):4511.
Chicago/Turabian StyleAmlan Haque; Nahina Islam; Nahidul Samrat; Shuvashis Dey; Biplob Ray. 2021. "Smart Farming through Responsible Leadership in Bangladesh: Possibilities, Opportunities, and Beyond." Sustainability 13, no. 8: 4511.
IEC 61850 is one of the most prominent communication standards adopted by the smart grid community due to its high scalability, multi-vendor interoperability, and support for several input/output devices. Generic Object-Oriented Substation Events (GOOSE), which is a widely used communication protocol defined in IEC 61850, provides reliable and fast transmission of events for the electrical substation system. This paper investigates the security vulnerabilities of this protocol and analyzes the potential impact on the smart grid by rigorously analyzing the security of the GOOSE protocol using an automated process and identifying vulnerabilities in the context of smart grid communication. The vulnerabilities are tested using a real-time simulation and industry standard hardware-in-the-loop emulation. An in-depth experimental analysis is performed to demonstrate and verify the security weakness of the GOOSE publish-subscribe protocol towards the substation protection within the smart grid setup. It is observed that an adversary who might have familiarity with the substation network architecture can create falsified attack scenarios that can affect the physical operation of the power system. Extensive experiments using the real-time testbed validate the theoretical analysis, and the obtained experimental results prove that the GOOSE-based IEC 61850 compliant substation system is vulnerable to attacks from malicious intruders.
Haftu Reda; Biplob Ray; Pejman Peidaee; Adnan Anwar; Abdun Mahmood; Akhtar Kalam; Nahina Islam. Vulnerability and Impact Analysis of the IEC 61850 GOOSE Protocol in the Smart Grid. Sensors 2021, 21, 1554 .
AMA StyleHaftu Reda, Biplob Ray, Pejman Peidaee, Adnan Anwar, Abdun Mahmood, Akhtar Kalam, Nahina Islam. Vulnerability and Impact Analysis of the IEC 61850 GOOSE Protocol in the Smart Grid. Sensors. 2021; 21 (4):1554.
Chicago/Turabian StyleHaftu Reda; Biplob Ray; Pejman Peidaee; Adnan Anwar; Abdun Mahmood; Akhtar Kalam; Nahina Islam. 2021. "Vulnerability and Impact Analysis of the IEC 61850 GOOSE Protocol in the Smart Grid." Sensors 21, no. 4: 1554.
To reach the goal of sustainable agriculture, smart farming is taking advantage of the Unmanned Aerial Vehicles (UAVs) and Internet of Things (IoT) paradigm. These smart farms are designed to be run by interconnected devices and vehicles. Some enormous potentials can be achieved by the integration of different IoT technologies to achieve automated operations with minimum supervision. This paper outlines some major applications of IoT and UAV in smart farming, explores the communication technologies, network functionalities and connectivity requirements for Smart farming. The connectivity limitations of smart agriculture and it’s solutions are analysed with two case studies. In case study-1, we propose and evaluate meshed Long Range Wide Area Network (LoRaWAN) gateways to address connectivity limitations of Smart Farming. While in case study-2, we explore satellite communication systems to provide connectivity to smart farms in remote areas of Australia. Finally, we conclude the paper by identifying future research challenges on this topic and outlining directions to address those challenges.
Nahina Islam; Mamunur Rashid; Faezeh Pasandideh; Biplob Ray; Steven Moore; Rajan Kadel. A Review of Applications and Communication Technologies for Internet of Things (IoT) and Unmanned Aerial Vehicle (UAV) Based Sustainable Smart Farming. Sustainability 2021, 13, 1821 .
AMA StyleNahina Islam, Mamunur Rashid, Faezeh Pasandideh, Biplob Ray, Steven Moore, Rajan Kadel. A Review of Applications and Communication Technologies for Internet of Things (IoT) and Unmanned Aerial Vehicle (UAV) Based Sustainable Smart Farming. Sustainability. 2021; 13 (4):1821.
Chicago/Turabian StyleNahina Islam; Mamunur Rashid; Faezeh Pasandideh; Biplob Ray; Steven Moore; Rajan Kadel. 2021. "A Review of Applications and Communication Technologies for Internet of Things (IoT) and Unmanned Aerial Vehicle (UAV) Based Sustainable Smart Farming." Sustainability 13, no. 4: 1821.
The cloud resource allocation for jobs must be further optimized and prioritised due to ever increasing demand for cloud computing resources to handle big data. In this research, we have examined the relationship between resource allocation, usages, and priority of tasks to reveal the influence of priority in resource allocation and resource usages. The analysis and modeling of this paper have used the Google cloud public dataset of 2011 and 2019. After processing and cleaning of one month data of Google cloud, we have revealed, the tasks are classified in 12 priorities in the 2011 cluster model whereas 500 priorities in the 2019 cluster model. However, both models have grouped these priorities into five groups. Therefore, we have modeled resource allocation versus usages based on five main priority groups using XGBoost (Extreme Gradient Boosting) and correlation coefficient. The comparative study on the developed models shows, the priority grouping of 2019 has better evenly distribution of resources for jobs but less efficient in most of the priority groups for resource allocation. Based on the performance parameters of the developed models, the resource allocation works more efficiently for most of the 2011 priority groups except `other'. These findings are useful for researchers to develop a balanced priority-based resource allocation-usages model to further optimise resources to reduce the management cost of cloud clusters.
Dimuth Lasantha; Biplob Ray. Priority Based Modeling and Comparative Study of Google Cloud Resources between 2011 and 2019. 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom) 2020, 1310 -1317.
AMA StyleDimuth Lasantha, Biplob Ray. Priority Based Modeling and Comparative Study of Google Cloud Resources between 2011 and 2019. 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom). 2020; ():1310-1317.
Chicago/Turabian StyleDimuth Lasantha; Biplob Ray. 2020. "Priority Based Modeling and Comparative Study of Google Cloud Resources between 2011 and 2019." 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom) , no. : 1310-1317.
Solar power forecasting is critical to ensure the safety and stability of the power grid with high photovoltaic power penetration. Machine learning methods are compelling in solar forecasting. These methods can capture the complex coupling relationship between different meteorological factors without physical modeling. Most of the existing machine learning based forecasts follow the batch learning manner. Once the training is completed, the structure and parameters of the model are usually no longer adjusted. However, the climate is complex and dynamic. It is difficult for a fixed model to adapt to the climate characteristics of different regions or periods. Therefore, an online domain adaptive learning approach is proposed in this paper. Knowledge can be selectively accumulated or forgotten in its iterative process. As weather changes, the model can dynamically adjust its structure to adapt to the latest weather conditions. Unlike existing adaptive iterative methods, the proposed adaptive learning approach does not rely on the labels of the test data in the updating process. Experiments show that this method can effectively track changes in data distribution and obtain reliable prediction results.
Hanmin Sheng; Biplob Ray; Kai Chen; Yuhua Cheng. Solar Power Forecasting Based on Domain Adaptive Learning. IEEE Access 2020, 8, 198580 -198590.
AMA StyleHanmin Sheng, Biplob Ray, Kai Chen, Yuhua Cheng. Solar Power Forecasting Based on Domain Adaptive Learning. IEEE Access. 2020; 8 ():198580-198590.
Chicago/Turabian StyleHanmin Sheng; Biplob Ray; Kai Chen; Yuhua Cheng. 2020. "Solar Power Forecasting Based on Domain Adaptive Learning." IEEE Access 8, no. : 198580-198590.
Historical data offers a wealth of knowledge to the users. However, often restrictively mammoth that the information cannot be fully extracted, synthesized, and analyzed efficiently for an application such as the forecasting of variable generator outputs. Moreover, the accuracy of the prediction method is vital. Therefore, a trade-off between accuracy and efficacy is required for the data-driven energy forecasting method. It has been identified that the hybrid approach may outperform the individual technique in minimizing the error while challenging to synthesize. A hybrid deep learning-based method is proposed for the output prediction of the solar photovoltaic systems (i.e. proposed PV system) in Australia to obtain the trade-off between accuracy and efficacy. The historical dataset from 1990-2013 in Australian locations (e.g. North Queensland) are used to train the model. The model is developed using the combination of multivariate long and short-term memory (LSTM) and convolutional neural network (CNN). The proposed hybrid deep learning (LSTM-CNN) is compared with the existing neural network ensemble (NNE), random forest, statistical analysis, and artificial neural network (ANN) based techniques to assess the performance. The proposed model could be useful for generation planning and reserve estimation in power systems with high penetration of solar photovoltaics (PVs) or other renewable energy sources (RESs).
Biplob Ray; Rakibuzzaman Shah; Rabiul Islam; Syed Islam. A New Data Driven Long-Term Solar Yield Analysis Model of Photovoltaic Power Plants. IEEE Access 2020, 8, 136223 -136233.
AMA StyleBiplob Ray, Rakibuzzaman Shah, Rabiul Islam, Syed Islam. A New Data Driven Long-Term Solar Yield Analysis Model of Photovoltaic Power Plants. IEEE Access. 2020; 8 (99):136223-136233.
Chicago/Turabian StyleBiplob Ray; Rakibuzzaman Shah; Rabiul Islam; Syed Islam. 2020. "A New Data Driven Long-Term Solar Yield Analysis Model of Photovoltaic Power Plants." IEEE Access 8, no. 99: 136223-136233.
The “Internet of things” (IoT) creating a perfect storm in the smart world. Due to the availability of internet and capabilities of devices, sensors-based technologies becoming popular day by day. It now opens the opportunities for overcoming many new challenges. Any device with on/off capability connecting through the internet via sensor can be an IoT device which includes a coffee machine, light, hand watch, headphones, washing machine, mobile phones, car, CCTV camera and so on. Simply we can say connecting things to people via the internet and controlling remotely is the great advantage of IoT. In our daily life, the IoT is widely used which includes transportation, health, education, security and so on. Imagine how IoT can make our life easier, based on your set alarm when you wake up if it can notify your coffee machine to prepare coffee for you that will save you time. Despite those advantages, the IoT based system is not free from vulnerabilities. Different types of attacks make the system vulnerable and tried to exploit the system and creating obstacles from its growth. Here we will explore IoT attacks and the relevant technologies associated along with machine learning strategies that exist to overcome those obstacles.
Morshed U. Chowdhury; Robin Doss; Biplob Ray; Sutharshan Rajasegarar; Sujan Chowdhury. IoT Insider Attack - Survey. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2020, 28 -41.
AMA StyleMorshed U. Chowdhury, Robin Doss, Biplob Ray, Sutharshan Rajasegarar, Sujan Chowdhury. IoT Insider Attack - Survey. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. 2020; ():28-41.
Chicago/Turabian StyleMorshed U. Chowdhury; Robin Doss; Biplob Ray; Sutharshan Rajasegarar; Sujan Chowdhury. 2020. "IoT Insider Attack - Survey." Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering , no. : 28-41.
Operational and planning modules of energy systems heavily depend on the information of the underlying topological and electric parameters, which are often kept in database within the operation centre. Therefore, these operational and planning modules are vulnerable to cyber anomalies due to accidental or deliberate changes in the power system database model. To validate, we have demonstrated the impact of cyber-anomalies on the database model used for operation of energy systems. To counter these cyber-anomalies, we have proposed a defence mechanism based on widely accepted classification techniques to identify the abnormal class of anomalies. In this study, we find that our proposed method based on multilayer perceptron (MLP), which is a special class of feedforward artificial neural network (ANN), outperforms other exiting techniques. The proposed method is validated using IEEE 33-bus and 24-bus reliability test system and analysed using ten different datasets to show the effectiveness of the proposed method in securing the Optimal Power Flow (OPF) module against data integrity anomalies. This paper highlights that the proposed machine learning-based anomaly detection technique successfully identifies the energy database manipulation at a high detection rate allowing only few false alarms.
Adnan Anwar; Abdun Mahmood; Biplob Ray; Apel Mahmud; Zahir Tari. Machine Learning to Ensure Data Integrity in Power System Topological Network Database. Electronics 2020, 9, 693 .
AMA StyleAdnan Anwar, Abdun Mahmood, Biplob Ray, Apel Mahmud, Zahir Tari. Machine Learning to Ensure Data Integrity in Power System Topological Network Database. Electronics. 2020; 9 (4):693.
Chicago/Turabian StyleAdnan Anwar; Abdun Mahmood; Biplob Ray; Apel Mahmud; Zahir Tari. 2020. "Machine Learning to Ensure Data Integrity in Power System Topological Network Database." Electronics 9, no. 4: 693.
The growing popularity of electric vehicles (EV) is creating an increasing burden on the power grid in Bangladesh due to massive energy consumption. Due to this uptake of variable energy consumption, environmental concerns, and scarcity of energy lead to investigate alternative energy resources that are readily available and environment friendly. Bangladesh has enormous potential in the field of renewable resources, such as biogas and biomass. Therefore, this paper proposes a design of a 20 kW electric vehicle charging station (EVCS) using biogas resources. A comprehensive viability analysis is also presented for the proposed EVCS from technological, economic, and environmental viewpoints using the HOMER (Hybrid Optimization of Multiple Energy Resources) model. The viability result shows that with the capacity of 15–20 EVs per day, the proposed EVCS will save monthly $16.31 and $29.46, respectively, for easy bike and auto-rickshaw type electric vehicles in Bangladesh compare to grid electricity charging. Furthermore, the proposed charging station can reduce 65.61% of CO2 emissions than a grid-based charging station.
Ashish Kumar Karmaker; Alamgir Hossain; Nallapaneni Manoj Kumar; Vishnupriyan Jegadeesan; ArunKumar Jayakumar; Biplob Ray. Analysis of Using Biogas Resources for Electric Vehicle Charging in Bangladesh: A Techno-Economic-Environmental Perspective. Sustainability 2020, 12, 2579 .
AMA StyleAshish Kumar Karmaker, Alamgir Hossain, Nallapaneni Manoj Kumar, Vishnupriyan Jegadeesan, ArunKumar Jayakumar, Biplob Ray. Analysis of Using Biogas Resources for Electric Vehicle Charging in Bangladesh: A Techno-Economic-Environmental Perspective. Sustainability. 2020; 12 (7):2579.
Chicago/Turabian StyleAshish Kumar Karmaker; Alamgir Hossain; Nallapaneni Manoj Kumar; Vishnupriyan Jegadeesan; ArunKumar Jayakumar; Biplob Ray. 2020. "Analysis of Using Biogas Resources for Electric Vehicle Charging in Bangladesh: A Techno-Economic-Environmental Perspective." Sustainability 12, no. 7: 2579.
Water gives life to our parks and helps them to be lush and green. However, over-irrigation in parks has the potential to waste substantial amounts of water and may also result in seepage and leakage of nutrients into nearby streams. Therefore, it is important to implement a smart water management system in parks to conserve water resources. This paper presents a multidisciplinary approach to use the latest irrigation technologies, Internet of Things (IoT) communication system, sensor technologies, and machine learning model for better water management of parklands by optimising the irrigation requirement and operating conditions. The project uses Dual Electromagnetic (DUAL-EM) sensor to scan the parkland to visualise the distribution of moisture content in a contour map which helps in identifying the location of interest to install moisture sensors to build the park's realtime watering profile. The IoT system uses a Low Power Wide Area Network (LoRaWAN) to connect moisture sensors (MP640), and micro-weather station (ATMOS 41) to automate the data collection on the cloud for real-time data storage and monitoring. The live data of the IoT system is used with laboratory testing data to prepare a smarter decision system for irrigation via machine learning. The sprinklers that are controlled by the smarter decision system helps to dispense irrigation water as per the needs of the parkland thus, reducing wastage of water and minimising nutrients leaching into streams to protect natural habitats.
Varun Yarehalli Chandrappa; Biplob Ray; Nanjappa Ashwath; Pramod Shrestha. Application of Internet of Things (IoT) to Develop a Smart Watering System for Cairns Parklands – A Case Study. 2020 IEEE Region 10 Symposium (TENSYMP) 2020, 1118 -1122.
AMA StyleVarun Yarehalli Chandrappa, Biplob Ray, Nanjappa Ashwath, Pramod Shrestha. Application of Internet of Things (IoT) to Develop a Smart Watering System for Cairns Parklands – A Case Study. 2020 IEEE Region 10 Symposium (TENSYMP). 2020; ():1118-1122.
Chicago/Turabian StyleVarun Yarehalli Chandrappa; Biplob Ray; Nanjappa Ashwath; Pramod Shrestha. 2020. "Application of Internet of Things (IoT) to Develop a Smart Watering System for Cairns Parklands – A Case Study." 2020 IEEE Region 10 Symposium (TENSYMP) , no. : 1118-1122.
Radio frequency identification (RFID) technology has many applications such as supply chain management, asset tracking, healthcare and logistics. Since RFID tags and readers communicate through a wireless medium, they are prone to a wide range of attacks. There are a number of measures to safeguard the security of RFID device operations and communications: mutual authentication, confidentiality, indistinguishability, forward security, and desynchronisation resilience. Due to limited computational power and memory, heavy-weight encryption functions cannot be performed in the RFID tags to execute the security protocols. Therefore, RFID security protocols are restricted to light-weight encryption functions such as simple one-way hash function, cyclic redundancy check (CRC), pseudorandom number generator (PRNG) and exclusive-OR (XOR). This paper develops a lightweight secure authentication protocol to mutually authenticate the RFID tag and the reader through an insecure radio communication channel. The protocol assumes that each RFID tag pre-shares a secret key with the reader. The protocol uses two random values to guarantee the freshness of the messages in order to outwit any replay attack. An analysis of the protocol using Scyther verification tool shows that the protocol ensures secure communication between the reader and the RFID tag provided the communication channel between the backend server and the reader is protected.
Salahuddin Azad; Biplob Ray. A Lightweight Protocol for RFID Authentication. 2019 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE) 2019, 1 -6.
AMA StyleSalahuddin Azad, Biplob Ray. A Lightweight Protocol for RFID Authentication. 2019 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE). 2019; ():1-6.
Chicago/Turabian StyleSalahuddin Azad; Biplob Ray. 2019. "A Lightweight Protocol for RFID Authentication." 2019 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE) , no. : 1-6.
This paper has presented three insiders attacks on Zigbee protocol – a protocol used for wireless communication for the Internet of Thing (IoT) devices. The end- user’s communication in IoT networks are sensor oriented as the user objects in IoT networks are embedded with sensors and actuators. Most of the sensors communicate with wireless medium among which many of them use Zigbee protocol. Security is an important element of IoT objects to protect user’s privacy and counter malicious attacks but difficult to guarantee due to its limited capabilities, wireless communication and unpredicted users’ actions. In this paper, we have evaluated Zigbee protocol stack for security vulnerabilities which revealed security weakness of remote AT commands. By using remote AT commands in an IoT network, we have devised three successful insider attacks to make unauthorized change of the destination address of a packet, change of node ID, and the change of PAN ID. These attacks detail will be very useful for IoT researches and practitioners in the security domain to design appropriate countermeasures for Zigbee IoT networks.
Waqas Ahmad Piracha; Morshed Chowdhury; Biplob Ray; Sutharshan Rajasegarar; Robin Doss. Insider Attacks on Zigbee Based IoT Networks by Exploiting AT Commands. Communications in Computer and Information Science 2019, 77 -91.
AMA StyleWaqas Ahmad Piracha, Morshed Chowdhury, Biplob Ray, Sutharshan Rajasegarar, Robin Doss. Insider Attacks on Zigbee Based IoT Networks by Exploiting AT Commands. Communications in Computer and Information Science. 2019; ():77-91.
Chicago/Turabian StyleWaqas Ahmad Piracha; Morshed Chowdhury; Biplob Ray; Sutharshan Rajasegarar; Robin Doss. 2019. "Insider Attacks on Zigbee Based IoT Networks by Exploiting AT Commands." Communications in Computer and Information Science , no. : 77-91.
With the evolution of wireless communication in Internet of Things (IoT) networks, Low Power Wide Area Network (LPWAN) has attracted a lot of attention due to its low cost and low power usages. Some of the LPWAN offerings are mainly proprietary but Long-Range Wide Area Network (LoRaWAN) is an open standard communication protocol (ALOHA-based) for a network using the Long Range (LoRa) in the physical layer. Due to its bi-directional communication and Adaptive Data Rate (ADR) capability, the LoRaWAN gateways are adopted in various IoT networks, like smart city, smart farming, worldwide. However, for wider adoption of LoRaWAN in mission-critical applications, it must be tested for scalability and reliability in various practical scenarios to reduce adverse impact in the system. This paper has conducted an evaluation of scalability and reliability of LoRaWAN using three practical scenarios of IoT systems. The evaluation has considered throughput performance, spreading factor statistics, gateway coverage assessment, and success probability performance of the protocol to reveal the performance of the protocol. The evaluation result shows that LoRaWAN networks are decidedly scalable supporting hundreds or thousands of end devices; however, on the other hand, there is an impression where scalability could be inversely proportional to performance only with an increased number of nodes and not gateways, thus requires a solution at the nodes. Our evaluated result can be very useful not only for designing the LoRaWAN based IoT network but also for improving LoRaWAN data transmission techniques for more reliable data transfer between sensor nodes and gateway.
Ansa Iftikhar Ahmad; Biplob Ray; Morshed Chowdhury. Performance Evaluation of LoRaWAN for Mission-Critical IoT Networks. Communications in Computer and Information Science 2019, 37 -51.
AMA StyleAnsa Iftikhar Ahmad, Biplob Ray, Morshed Chowdhury. Performance Evaluation of LoRaWAN for Mission-Critical IoT Networks. Communications in Computer and Information Science. 2019; ():37-51.
Chicago/Turabian StyleAnsa Iftikhar Ahmad; Biplob Ray; Morshed Chowdhury. 2019. "Performance Evaluation of LoRaWAN for Mission-Critical IoT Networks." Communications in Computer and Information Science , no. : 37-51.
Large-scale renewable energy, especially solar photovoltaic (PV), is increasing into the Australian power network (known as NEM) due to sustainability and environmental benefits. The analysis of energy yield and variability for solar PV at different locations is essential for transmission system operator(s) when making long-term planning for cross-border transmission system design. This work presents the large-scale PV regional models for various potential locations in Queensland (QLD) and New South Wales (NSW) according to the integrated development plan for Australia. The model gives an estimation of PV production with one-hour resolution. The correlation among the variability of PV production at different locations has been established which can be useful for the transmission system operator(s) for future planning of reserve margin for the system.
Biplob Ray; Rakibuzzaman Shah. Performance Assessment of Prospective PV Systems in Queensland and New South Wales of Australia. 2019 IEEE PES GTD Grand International Conference and Exposition Asia (GTD Asia) 2019, 200 -205.
AMA StyleBiplob Ray, Rakibuzzaman Shah. Performance Assessment of Prospective PV Systems in Queensland and New South Wales of Australia. 2019 IEEE PES GTD Grand International Conference and Exposition Asia (GTD Asia). 2019; ():200-205.
Chicago/Turabian StyleBiplob Ray; Rakibuzzaman Shah. 2019. "Performance Assessment of Prospective PV Systems in Queensland and New South Wales of Australia." 2019 IEEE PES GTD Grand International Conference and Exposition Asia (GTD Asia) , no. : 200-205.
BACKGROUND Personal electronic health devices, such as fitness trackers, heart rate monitors, blood glucose meters, blood pressure monitors and stress level meters, and related smartphone-based health applications are increasing in usage and popularity. These Internet-based medical technologies, which this paper refers to as mHealth systems, may be prescribed by a healthcare professional or purchased over-the-counter and make it easier for an individual to collect, access and monitor information relevant to their own health and well-being. However, as with many Internet-based technologies, and especially so with sensitive, personal health information, privacy is a significant concern. Actual or a perceived risk of privacy intrusions may delay the wider adoption of mHealth systems and even generate mistrust that reduces their long-term effectiveness. This paper contributes to the understanding of users’ perspectives on information privacy in mHealth systems. OBJECTIVE To gain an understanding of current usage patterns and how important users perceive privacy, we have conducted a national survey in Australia. Understanding consumers’ preferences and expectations provide directions for developers, lawmakers and researchers in creating an improved mHealth ecosystem. METHODS As part of the National Social Survey by Population Research Laboratory of CQUniversity, participants who were 18 years or older were randomly selected from across Australia for telephone interviews. The participants were asked 10 questions about usage and privacy of mobile health systems. The collected data was tabulated, cleaned and analysed using SPSS and the resultant data set contained 1,225 cases with a total of 187 variables for each case. RESULTS The survey reveals users of mHealth systems have a strong desire for privacy, e.g. more than 80% rate privacy important or very important and more than 60% think no personal information should be released to developers. The survey also shows around 70% of users never or rarely review privacy policies, and that they perceive the significant potential impact of intrusions, including increased health insurance costs, embarrassment and financial loss. CONCLUSIONS While the survey results show users desire privacy and have low trust of telecommunications and IT organisations, this conflicts with the technical design of mHealth systems: in many cases application developers, device manufacturers and telecommunication companies may have access to sensitive health information. The lack of standardization and guidelines for data processing by mHealth systems, as well as ineffectiveness of privacy policies, need to be addressed to avoid users’ confusion and potential invasions of privacy. CLINICALTRIAL This research is undertaken as part of our CQUniversity Population Research Grant Scheme (PRGS). NSS-2016 received approval by the Human Ethics Research Review Panel at CQUniversity before administration to the general public....
Biplob Ray; Steven Gordon; Sue Hunt. Privacy of mHealth Systems: A national survey on user perspectives (Preprint). 2018, 1 .
AMA StyleBiplob Ray, Steven Gordon, Sue Hunt. Privacy of mHealth Systems: A national survey on user perspectives (Preprint). . 2018; ():1.
Chicago/Turabian StyleBiplob Ray; Steven Gordon; Sue Hunt. 2018. "Privacy of mHealth Systems: A national survey on user perspectives (Preprint)." , no. : 1.
Biplob Ray; Jemal Abawajy; Morshed Chowdhury; Abdulhameed Alelaiwi. Universal and secure object ownership transfer protocol for the Internet of Things. Future Generation Computer Systems 2018, 78, 838 -849.
AMA StyleBiplob Ray, Jemal Abawajy, Morshed Chowdhury, Abdulhameed Alelaiwi. Universal and secure object ownership transfer protocol for the Internet of Things. Future Generation Computer Systems. 2018; 78 ():838-849.
Chicago/Turabian StyleBiplob Ray; Jemal Abawajy; Morshed Chowdhury; Abdulhameed Alelaiwi. 2018. "Universal and secure object ownership transfer protocol for the Internet of Things." Future Generation Computer Systems 78, no. : 838-849.
In recent years big data has emerged as a universal term and its management has become a crucial research topic. The phrase ‘big data’ refers to data sets so large and complex that the processing of them requires collaborative High Performance Computing (HPC). How to effectively allocate resources is one of the prime challenges in HPC. This leads us to the question: are the existing HPC resource allocation techniques effective enough to support future big data challenges? In this context, we have investigated the effectiveness of HPC resource allocation using the Google cluster dataset and a number of data mining tools to determine the correlational coefficient between resource allocation, resource usages and priority. Our analysis initially focused on correlation between resource allocation and resource uses. The finding shows that a high volume of resources that are allocated by the system for a job are not being used by that same job. To investigate further, we analyzed the correlation between resource allocation, resource usages and priority. Our clustering, classification and prediction techniques identified that the allocation and uses of resources are very loosely correlated with priority of the jobs. This research shows that our current HPC scheduling needs improvement in order to accommodate the big data challenge efficiently.
Biplob R. Ray; Morshed Chowdhury; Usman Atif. Is High Performance Computing (HPC) Ready to Handle Big Data? Communications in Computer and Information Science 2017, 759, 97 -112.
AMA StyleBiplob R. Ray, Morshed Chowdhury, Usman Atif. Is High Performance Computing (HPC) Ready to Handle Big Data? Communications in Computer and Information Science. 2017; 759 ():97-112.
Chicago/Turabian StyleBiplob R. Ray; Morshed Chowdhury; Usman Atif. 2017. "Is High Performance Computing (HPC) Ready to Handle Big Data?" Communications in Computer and Information Science 759, no. : 97-112.
Since the RFID technology has been found couple of decades ago, there was much involvement of this emerging technology in the improvement of supply chain management. As this technology made the industry more reliable and faster to process, yet there were always some technical issues and security threats that emerged from the heavy use of the RFID tags in the SCM, or other industries. Hereby we represent a new protocol based on a new idea that can be used to manage and organize tags as well as the objects attached to them in SCM, to prevent counterfeiting and reduce the security threats taking into consideration the security and privacy concerns that faces the industry today. This new approach will open a new horizon to the supply chain management as well as the RFID systems technology since it will handle multi- tags attached to objects managed in one location as an entity of one in one. We called our approach the MATRYOSHKA approach since it has the same idea of the russian doll, in managing multi-tags as one entity and prevent counterfeiting. We also added extra authentication process based on a mathematical exchange key formation to increase the security during communication to prevent threats and attacks and to provide a secure mutual authentication method.
Gaith Al.; Robin Doss; Morshed Chowdhury; Biplob Ray. Secure RFID Protocol to Manage and Prevent Tag Counterfeiting with Matryoshka Concept. Communications in Computer and Information Science 2016, 126 -141.
AMA StyleGaith Al., Robin Doss, Morshed Chowdhury, Biplob Ray. Secure RFID Protocol to Manage and Prevent Tag Counterfeiting with Matryoshka Concept. Communications in Computer and Information Science. 2016; ():126-141.
Chicago/Turabian StyleGaith Al.; Robin Doss; Morshed Chowdhury; Biplob Ray. 2016. "Secure RFID Protocol to Manage and Prevent Tag Counterfeiting with Matryoshka Concept." Communications in Computer and Information Science , no. : 126-141.
This paper is concerned with false signal injection attack detection mechanism using a novel distributed event-triggered filtering for cyber physical systems over sensor networks. By the Internet of Things, the classic physical systems are transformed to the networked cyber physical systems, which are built with a large number of distributed networked sensors. In order to save the precious network resources, a novel distributed event-triggered strategy is proposed. Under this strategy, to generate the localized residual signals, the event-triggered distributed fault detection filters are proposed. By Lyapunov- Krasovskii functional theory, the distributed fault detection filtering problem can be formulated as stability and an \(H_{\infty }\) performance of the residual system. Furthermore, a sufficient condition is derived such that the resultant residual system is stable while the transmission of the sampled data is reduced. Based on this condition, the codesign method of the fault detection filters and the transmission strategy is proposed. An illustrative example is given to show the effectiveness of the proposed method.
Yufeng Lin; Biplob Ray; Dennis Jarvis; Jia Wang. False Signal Injection Attack Detection of Cyber Physical Systems by Event-Triggered Distributed Filtering over Sensor Networks. Programmieren für Ingenieure und Naturwissenschaftler 2016, 142 -153.
AMA StyleYufeng Lin, Biplob Ray, Dennis Jarvis, Jia Wang. False Signal Injection Attack Detection of Cyber Physical Systems by Event-Triggered Distributed Filtering over Sensor Networks. Programmieren für Ingenieure und Naturwissenschaftler. 2016; ():142-153.
Chicago/Turabian StyleYufeng Lin; Biplob Ray; Dennis Jarvis; Jia Wang. 2016. "False Signal Injection Attack Detection of Cyber Physical Systems by Event-Triggered Distributed Filtering over Sensor Networks." Programmieren für Ingenieure und Naturwissenschaftler , no. : 142-153.
In this paper, we propose a secure object tracking protocol to ensure the visibility and traceability of an object along the travel path to support the Internet of Things (IoT). The proposed protocol is based on radio frequency identification system for global unique identification of IoT objects. For ensuring secure object tracking, lightweight cryptographic primitives and physically unclonable function are used by the proposed protocol in tags. We evaluated the proposed protocol both quantitatively and qualitatively. In our experiment, we modeled the protocol using security protocol description language (SPDL) and simulated SPDL model using automated claim verification tool Scyther. The results show that the proposed protocol is more secure and requires less computation compared to existing similar protocols.
Biplob Ray; Morshed Chowdhury; Jemal H. Abawajy. Secure Object Tracking Protocol for the Internet of Things. IEEE Internet of Things Journal 2016, 3, 544 -553.
AMA StyleBiplob Ray, Morshed Chowdhury, Jemal H. Abawajy. Secure Object Tracking Protocol for the Internet of Things. IEEE Internet of Things Journal. 2016; 3 (4):544-553.
Chicago/Turabian StyleBiplob Ray; Morshed Chowdhury; Jemal H. Abawajy. 2016. "Secure Object Tracking Protocol for the Internet of Things." IEEE Internet of Things Journal 3, no. 4: 544-553.