List of Titles

Wireless powering internet of things with UAVs : challenges and opportunities

- Liu, Yalin, Dai, Hong-Ning, Wang, Qubeijian, Imran, Muhammad, Guizani, Nadra

Authors: Liu, Yalin , Dai, Hong-Ning , Wang, Qubeijian , Imran, Muhammad , Guizani, Nadra
Date: 2022
Type: Text , Journal article , Review
Relation: IEEE Network Vol. 36, no. 2 (2022), p. 146-152
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Description: Unmanned aerial vehicles (UAVs) have the potential to overcome the deployment constraint of The Internet of Things (IoT) in remote or rural areas. Wirelessly powered communications (WPC) can address the battery limitation of IoT devices through transferring wireless power to IoT devices. The integration of UAVs and WPC, namely UAV-enabled wireless powering IoT (Ue-WPI-o T) can greatly extend the IoT applications from cities to remote or rural areas. In this article, we present a state-of-the-art overview of Ue-WPIoT by first illustrating the working flow of Ue-WPIoT and discussing the challenges. We then introduce the enabling technologies in realizing Ue-WPI-oT. Simulation results validate the effectiveness of the enabling technologies in Ue-WPIoT. We finally outline the future directions and open issues. © 1986-2012 IEEE.

A lightweight cyber security framework with context-awareness for pervasive computing environments

- Al-Muhtadi, Jalal, Saleem, Kashif, Al-Rabiaah, Sumaya, Imran, Muhammad, Gawanmeh, Amjad, Rodrigues, Joel

Authors: Al-Muhtadi, Jalal , Saleem, Kashif , Al-Rabiaah, Sumaya , Imran, Muhammad , Gawanmeh, Amjad , Rodrigues, Joel
Date: 2021
Type: Text , Journal article
Relation: Sustainable Cities and Society Vol. 66, no. (2021), p.
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Description: Internet of things (IoT) plays a key role in enabling smart sustainable cities. Pervasive computing over the IoT platform makes life more convenient by embedding sensors based on context-aware computing devices in the physical environment for the ubiquitous availability of computing resources. The sensors gather contextual information from the physical world and transmit it to receivers as per requirements or in case of environmental changes, such as temperature and humidity. However, the combination of dynamic operation and the need to handle sensitive and private data make the pervasive computing environment and IoT devices vulnerable to numerous attacks. Smart environments require a maximum level of safety assurance, such as trusted context producers and customers, which should protect sensitive information from exposure or monitoring. This paper discusses the major cyber threats in smart environments and proposes a novel lightweight security framework that authenticates and maintains the context providers and receivers. The cloud environment is adopted for user authentication at the user layer to implement access control and role assignment. Finally, the proposed security framework is implemented in the IBM cloud platform with six devices to evaluate its efficiency, sustainability, and secure communication. © 2020 Elsevier Ltd

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A novel collaborative IoD-assisted VANET approach for coverage area maximization

- Ahmed, Gamil, Sheltami, Tarek, Mahmoud, Ashraf, Imran, Muhammad, Shoaib, Muhammad

Authors: Ahmed, Gamil , Sheltami, Tarek , Mahmoud, Ashraf , Imran, Muhammad , Shoaib, Muhammad
Date: 2021
Type: Text , Journal article
Relation: IEEE Access Vol. 9, no. (2021), p. 61211-61223
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Description: Internet of Drones (IoD) is an efficient technique that can be integrated with vehicular ad-hoc networks (VANETs) to provide terrestrial communications by acting as an aerial relay when terrestrial infrastructure is unreliable or unavailable. To fully exploit the drones' flexibility and superiority, we propose a novel dynamic IoD collaborative communication approach for urban VANETs. Unlike most of the existing approaches, the IoD nodes are dynamically deployed based on current locations of ground vehicles to effectively mitigate inevitable isolated cars in conventional VANETs. For efficiently coordinating IoD, we model IoD to optimize coverage based on the location of vehicles. The goal is to obtain an efficient IoD deployment to maximize the number of covered vehicles, i.e., minimize the number of isolated vehicles in the target area. More importantly, the proposed approach provides sufficient interconnections between IoD nodes. To do so, an improved version of succinct population-based meta-heuristic, namely Improved Particle Swarm Optimization (IPSO) inspired by food searching behavior of birds or fishes flock, is implemented for IoD assisted VANET (IoDAV). Moreover, the coverage, received signal quality, and IoD connectivity are achieved by IPSO's objective function for optimal IoD deployment at the same time. We carry out an extensive experiment based on the received signal at floating vehicles to examine the proposed IoDAV performance. We compare the results with the baseline VANET with no IoD (NIoD) and Fixed IoD assisted (FIoD). The comparisons are based on the coverage percentage of the ground vehicles and the quality of the received signal. The simulation results demonstrate that the proposed IoDAV approach allows finding the optimal IoD positions throughout the time based on the vehicle's movements and achieves better coverage and better quality of the received signal by finding the most appropriate IoD position compared with NIoD and FIoD schemes. © 2013 IEEE.

A policy-based solution for the detection of colluding GPS-Spoofing attacks in FANETs

- Bada, Mousaab, Boubiche, Djallel, Lagraa, Nasreddine, Kerrache, Chaker, Imran, Muhammad, Shoaib, Muhammad

Authors: Bada, Mousaab , Boubiche, Djallel , Lagraa, Nasreddine , Kerrache, Chaker , Imran, Muhammad , Shoaib, Muhammad
Date: 2021
Type: Text , Journal article
Relation: Transportation Research Part A: Policy and Practice Vol. 149, no. (2021), p. 300-318
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Description: Most of Flying Adhoc Networks (FANETs) applications consume GPS based location information for their services, which are also shared in real-time with other UAVs, ground control stations and centralized service operators. GPS spoofing is among the most popular attacks in FANETs that lead the Global Navigation Satellite System (GNSS) receivers to generate false navigation solutions. Several anti-spoofing techniques have been proposed in the literature. However, Conventional detection methods present vulnerabilities against Colluding GPS Spoofing Attack where multiple GPS spoofing signal sources are used. In this paper, we propose a policy-based distributed detection mechanism to face colluding GPS-Spoofing attack in FANETs. Based on Burglary scene and the location of each UAV at the time of the attack, we can distinguish between Active and Passive witnesses that are respectively used to help the target to detect and confirm the presence of GPS spoofing signal using respectively Absolute power and Carrier-to-Noise density ratio. A trust model based on Beta and Weibull Distribution has been adopted as a combination technique of different testimonies to both mitigate the spread of false rumors and classify the different signals. Simulation results depict that our proposal is able to detect and revoke the GPS Spoofing signal with high accuracy reaching the 99% and low communication overhead. © 2021 Elsevier Ltd

Advertising through UAVs : optimized path system for delivering smart real-estate advertisement materials

- Ullah, Fahim, Al-Turjman, Fadi, Qayyum, Siddra, Inam, Hina, Imran, Muhammad

Authors: Ullah, Fahim , Al-Turjman, Fadi , Qayyum, Siddra , Inam, Hina , Imran, Muhammad
Date: 2021
Type: Text , Journal article
Relation: International Journal of Intelligent Systems Vol. 36, no. 7 (2021), p. 3429-3463
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Description: Real-estate advertisements through electronic and print media are bringing considerable fortune to the global real-estate sector. However, innovative advertisement methods must be adopted if real estate aims to transform into smart real estate. The current study, which is based on a systematic literature review of 58 articles published in the last decade, identifies key media for real-estate advertisements as print media (e.g., magazines, brochures, newspapers, and digests), electronic media (e.g., websites, social media, and other digital tools), and mixed methods (e.g., billboards, signs and banners, and personalized messaging). This study takes the case of Kingsford suburb in the eastern Sydney area, and investigates the performance of the Australian real-estate industry in general and lists the key dynamics of properties in Kingsford and its prominent real-estate agencies. An unmanned aerial vehicle (UAV)-based smart real-estate advertisement material delivery system is proposed to deliver advertisement materials and gifts to the potential customers of these agencies. The system paths are optimized through four Java-run algorithms: greedy, interroute, intraroute, and Tabu. Results based on six cases, three each for rent and sales with varying numbers of customers and UAVs and an 8-h operating time, indicate that the Tabu algorithm provides the best-optimized paths in all cases, followed by the interroute, intraroute, and greedy algorithms. However, the inter- and intraroute algorithms show superior performance in terms of computation speed. The proposed framework is a practical approach in disrupting the real-estate advertising sector, thereby helping this sector transform into a smart real estate consistent with industry 4.0 goals. © 2021 Wiley Periodicals LLC

An intelligent content caching protocol for connected vehicles

- Rahim, Muddasir, Ali, Shaukat, Alvi, Ahmad, Javed, Muhammad, Imran, Muhammad, Azad, Muhammad, Chen, Dong

Authors: Rahim, Muddasir , Ali, Shaukat , Alvi, Ahmad , Javed, Muhammad , Imran, Muhammad , Azad, Muhammad , Chen, Dong
Date: 2021
Type: Text , Journal article
Relation: Transactions on Emerging Telecommunications Technologies Vol. 32, no. 4 (2021), p.
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Description: In the future smart cities, connected vehicles provide various infotainment and nonsafety services using vehicle to vehicle and vehicle to road side units (RSUs) communications. To enable these infotainment services, content providers cache their popular data on the RSU storage to make it quickly accessible for the vehicles. In this article, we propose a novel content caching protocol used by mobile network operators. The proposed protocol uses knapsack optimization algorithm to allocate the variable-sized contents to the RSUs based on their utility. Results show that the proposed protocol provides 13% and 70% approximately higher download data than the market matching and random caching, respectively. © 2021 John Wiley & Sons, Ltd.

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An investigation of the drivers of social commerce and e-word-of-mouth intentions : elucidating the role of social commerce in e-business

- Goraya, M. Awals, Jing, Zhu, Shareef, Mahmud, Imran, Muhammad, Malik, Aneela, Akram, M. Shakaib

Authors: Goraya, M. Awals , Jing, Zhu , Shareef, Mahmud , Imran, Muhammad , Malik, Aneela , Akram, M. Shakaib
Date: 2021
Type: Text , Journal article
Relation: Electronic Markets Vol. 31, no. 1 (2021), p. 181-195
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Description: Building on social commerce (s-commerce) perspectives and the trust transfer theory, this study develops a theoretical model that explains the indirect effects of two types of s-commerce attributes (community and platform) on behavioral outcomes (s-commerce intentions and e-Word-of-Mouth (e-WOM) intentions) through trust in community and platform. We analyze data collected from s-commerce users on travel booking websites using structural equation modeling technique. Results confirm that s-commerce intentions and e-WOM intentions are contingent upon s-commerce community and platform attributes. Moreover, the results provide evidence for the mediating effects of trust in community and platform on the relationship between s-commerce attributes and behavioral outcomes. The study provides further insights about the impact of s-commerce experience on s-commerce intention and e-WOM intention. Moreover, this study contributes to s-commerce research and practice by developing and validating the role of s-commerce community and platform attributes in forming consumers’ s-commerce behavioral outcomes. © 2019, Institute of Applied Informatics at University of Leipzig.

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Assessing nitrate contamination risks in groundwater : a machine learning approach

- Awais, Muhammad, Aslam, Bilal, Maqsoom, Ahsen, Khalil, Umer, Imran, Muhammad

Authors: Awais, Muhammad , Aslam, Bilal , Maqsoom, Ahsen , Khalil, Umer , Imran, Muhammad
Date: 2021
Type: Text , Journal article
Relation: Applied Sciences (Switzerland) Vol. 11, no. 21 (2021), p.
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Description: Groundwater is one of the primary sources for the daily water requirements of the masses, but it is subjected to contamination due to the pollutants, such as nitrate, percolating through the soil with water. Especially in built-up areas, groundwater vulnerability and contamination are of major concern, and require appropriate consideration. The present study develops a novel framework for assessing groundwater nitrate contamination risk for the area along the Karakoram Highway, which is a part of the China Pakistan Economic Corridor (CPEC) route in northern Pakistan. A groundwater vulnerability map was prepared using the DRASTIC model. The nitrate concentration data from a previous study were used to formulate the nitrate contamination map. Three machine learning (ML) models, i.e., Support Vector Machine (SVM), Multivariate Discriminant Analysis (MDA), and Boosted Regression Trees (BRT), were used to analyze the probability of groundwater contamination incidence. Furthermore, groundwater contamination probability maps were obtained utilizing the ensemble modeling approach. The models were calibrated and validated through calibration trials, using the area under the receiver operating characteristic curve method (AUC), where a minimum AUC threshold value of 80% was achieved. Results indicated the accuracy of the models to be in the range of 0.82–0.87. The final groundwater contamination risk map highlights that 34% of the area is moderately vulnerable to groundwater contamination, and 13% of the area is exposed to high groundwater contamination risk. The findings of this study can facilitate decision-making regarding the location of future built-up areas properly in order to mitigate the nitrate contamination that can further reduce the associated health risks. © 2021 by the authors. Licensee MDPI, Basel, Switzerland. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Muhammad Imran” is provided in this record**

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Cloudlet computing : recent advances, taxonomy, and challenges

- Babar, Mohammad, Khan, Muhammad, Ali, Farman, Imran, Muhammad, Shoaib, Muhammad

Authors: Babar, Mohammad , Khan, Muhammad , Ali, Farman , Imran, Muhammad , Shoaib, Muhammad
Date: 2021
Type: Text , Journal article
Relation: IEEE Access Vol. 9, no. (2021), p. 29609-29622
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Description: A cloudlet is an emerging computing paradigm that is designed to meet the requirements and expectations of the Internet of things (IoT) and tackle the conventional limitations of a cloud (e.g., high latency). The idea is to bring computing resources (i.e., storage and processing) to the edge of a network. This article presents a taxonomy of cloudlet applications, outlines cloudlet utilities, and describes recent advances, challenges, and future research directions. Based on the literature, a unique taxonomy of cloudlet applications is designed. Moreover, a cloudlet computation offloading application for augmenting resource-constrained IoT devices, handling compute-intensive tasks, and minimizing the energy consumption of related devices is explored. This study also highlights the viability of cloudlets to support smart systems and applications, such as augmented reality, virtual reality, and applications that require high-quality service. Finally, the role of cloudlets in emergency situations, hostile conditions, and in the technological integration of future applications and services is elaborated in detail. © 2013 IEEE.

CRT-BIoV : a cognitive radio technique for blockchain-enabled internet of vehicles

- Rathee, Geetanjali, Ahmad, Farhan, Kurugollu, Fatih, Azad, Muhammad, Iqbal, Razi, Imran, Muhammad

Authors: Rathee, Geetanjali , Ahmad, Farhan , Kurugollu, Fatih , Azad, Muhammad , Iqbal, Razi , Imran, Muhammad
Date: 2021
Type: Text , Journal article
Relation: IEEE Transactions on Intelligent Transportation Systems Vol. 22, no. 7 (2021), p. 4005-4015
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Description: Cognitive Radio Network (CRN) is considered as a viable solution on Internet of Vehicle (IoV) where objects equipped with cognition make decisions intelligently through the understanding of both social and physical worlds. However, the spectrum availability and data sharing/transferring among vehicles are critical improving services and driving safety metrics where the presence of Malicious Devices (MD) further degrade the network performance. Recently, a blockchain technique in CRN-based IoV has been introduced to prevent data alteration from these MD and allowing the vehicles to track both legal and illegal activities in the network. In this paper, we provide the security to IoV during spectrum sensing and information transmission using CRN by sensing the channels through a decision-making technique known as Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS), a technique that evokes the trust of its Cognitive Users (CU) by analyzing certain predefined attributes. Further, blockchain is maintained in the network to trace every activity of stored information. The proposed mechanism is validated rigorously against several security metrics using various spectrum sensing and security parameters against a baseline solution in IoV. Extensive simulations suggest that our proposed mechanism is approximately 70% more efficient in terms of malicious nodes identification and DoS threat against the baseline mechanism. © 2000-2011 IEEE.

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Deep learning-based approach for detecting trajectory modifications of cassini-huygens spacecraft

- Aldabbas, Ashraf, Gal, Zoltan, Ghori, Khawaja, Imran, Muhammad, Shoaib, Muhammad

Authors: Aldabbas, Ashraf , Gal, Zoltan , Ghori, Khawaja , Imran, Muhammad , Shoaib, Muhammad
Date: 2021
Type: Text , Journal article
Relation: IEEE Access Vol. 9, no. (2021), p. 39111-39125
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Description: There were necessary trajectory modifications of Cassini spacecraft during its last 14 years movement cycle of the interplanetary research project. In the scale 1.3 hour of signal propagation time and 1.4-billion-kilometer size of Earth-Cassini channel, complex event detection in the orbit modifications requires special investigation and analysis of the collected big data. The technologies for space exploration warrant a high standard of nuanced and detailed research. The Cassini mission has accumulated quite huge volumes of science records. This generated a curiosity derives mainly from a need to use machine learning to analyze deep space missions. For energy saving considerations, the communication between the Earth and Cassini was executed in non-periodic mode. This paper provides a sophisticated in-depth learning approach for detecting Cassini spacecraft trajectory modifications in post-processing mode. The proposed model utilizes the ability of Long Short Term Memory (LSTM) neural networks for drawing out useful data and learning the time series inner data pattern, along with the forcefulness of LSTM layers for distinguishing dependencies among the long-short term. Our research study exploited the statistical rates, Matthews correlation coefficient, and F1 score to evaluate our models. We carried out multiple tests and evaluated the provided approach against several advanced models. The preparatory analysis showed that exploiting the LSTM layer provides a notable boost in rising the detection process performance. The proposed model achieved a number of 232 trajectory modification detections with 99.98% accuracy among the last 13.35 years of the Cassini spacecraft life. © 2013 IEEE.

Device-centric adaptive data stream management and offloading for analytics applications in future internet architectures

- Rehman, Muhammad, Liew, Chee, Wah, Teh, Imran, Muhammad, Salah, Khaled, Nasser, Nidal, Svetinovic, Davor

Authors: Rehman, Muhammad , Liew, Chee , Wah, Teh , Imran, Muhammad , Salah, Khaled , Nasser, Nidal , Svetinovic, Davor
Date: 2021
Type: Text , Journal article
Relation: Future Generation Computer Systems Vol. 114, no. (2021), p. 155-168
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Description: Information-Centric Networking (ICN) enables in-network data management and communication between multiple parties by replicating data and activating interactions between decoupled senders and receivers. Existing data management and offloading schemes in ICNs primarily use the transport layer hence it becomes inefficient to actively develop and update the ICN standards because of continuously evolving heterogeneous future internet architectures such as mobile edge cloud computing (MECC) architectures. In this paper, we present an adaptive execution model for mobile data stream mining (MDSM) applications in MECC environments to enable device-centric adaptive data management and offloading. We designed the proposed execution model considering multiple factors of complexity such as volume and velocity of continuously streaming data, the selection of data fusion and data preprocessing methods, the choice of learning models, learning rates, learning modes, mobility, limited computational and memory resources in mobile devices, the high coupling between application components, and dependency over Internet connections. We integrated the proposed execution model with multiple MDSM applications mapping to a real-word use-case for activity detection using MECC as a future network architecture. We thoroughly evaluated the proposed execution model in terms of battery power consumption, memory utilization, makespan, accuracy, and the amount of data reduced during in-network communication. The comparison showed that our proposed adaptive execution model outperformed the static and dynamic execution models which were deployed in the same ICN architecture. © 2020 Elsevier B.V.

Ear in the sky : terrestrial mobile jamming to prevent aerial eavesdropping

- Wang, Qubeijian, Liu, Yalin, Dai, Hong-Ning, Imran, Muhammad, Nasser, Nidal

Authors: Wang, Qubeijian , Liu, Yalin , Dai, Hong-Ning , Imran, Muhammad , Nasser, Nidal
Date: 2021
Type: Text , Conference paper
Relation: 2021 IEEE Global Communications Conference, GLOBECOM 2021, Madrid, 7-11 December 2021, 2021 IEEE Global Communications Conference, GLOBECOM 2021 - Proceedings
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Description: The emerging unmanned aerial vehicles (UAVs) pose a potential security threat for terrestrial communications when UAVs can be maliciously employed as UAV-eavesdroppers to wiretap confidential communications. To address such an aerial security threat, we present a friendly jamming scheme named terrestrial mobile jamming (TMJ) to protect terrestrial confidential communications from UAV eavesdropping. In our TMJ scheme, a jammer moving along the protection area can emit jamming signals toward the UAV-eavesdropper so as to reduce the eavesdropping risk. We evaluate the performance of our scheme by analyzing a secrecy-capacity maximization problem subject to the legitimate connectivity and eavesdropping probability. In addition, we investigate the optimized position for the jammer as well as its jamming power. Simulation results verify the effectiveness of the proposed scheme. © 2021 IEEE.

Friendly-jamming schemes to secure ultra-reliable and low-latency communications in 5G and beyond communications

- Li, Xuran, Dai, Hong-Ning, Shukla, Mahendra, Li, Dengwang, Xu, Huaqiang, Imran, Muhammad

Authors: Li, Xuran , Dai, Hong-Ning , Shukla, Mahendra , Li, Dengwang , Xu, Huaqiang , Imran, Muhammad
Date: 2021
Type: Text , Journal article
Relation: Computer Standards and Interfaces Vol. 78, no. (2021), p.
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Description: The security vulnerabilities are becoming the major obstacle to prevent the wide adoption of ultra-reliable and low latency communications (URLLC) in 5G and beyond communications. Current security countermeasures based on cryptographic algorithms have a stringent requirement on the centralized key management as well as computational capabilities of end devices while it may not be feasible for URLLC in 5G and beyond communications. In contrast to cryptographic approaches, friendly jamming (FJ) as a promising physical layer security method can enhance wireless communications security while it has less resource requirement on end devices and it can be applied to the full distribution environment. In order to protect wireless communications, FJ signals are introduced to degrade the decoding ability of eavesdroppers who maliciously wiretap confidential information. This article presents a state-of-the-art survey on FJ schemes to enhance network security for IoT networks with consideration of various emerging wireless technologies and different types of networks. First, we present various secrecy performance metrics and introduce the FJ method. The interference caused by FJ signals on legitimate communication is the major challenge of using FJ schemes. In order to overcome this challenge, we next introduce the integration of FJ schemes with various communication technologies, including beamforming, multiple-input multiple-output, full duplex, and relay selection. In addition, we also integrate FJ schemes with different types of communication networks. Finally, a case study of FJ schemes is illustrated and future research directions of FJ schemes have been outlined. © 2021 Elsevier B.V.

Handwriting dynamics assessment using deep neural network for early identification of Parkinson's disease

- Kamran, Iqra, Naz, Saeeda, Razzak, Imran, Imran, Muhammad

Authors: Kamran, Iqra , Naz, Saeeda , Razzak, Imran , Imran, Muhammad
Date: 2021
Type: Text , Journal article
Relation: Future Generation Computer Systems Vol. 117, no. (2021), p. 234-244
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Description: The etiology of Parkinson's disease (PD) remains unclear. Symptoms usually appear after approximately 70% of dopamine-producing cells have stopped working normally. PD cannot be cured, but its symptoms can be managed to delay its progression. Evidence suggests that early diagnosis is important in establishing an effective pathway for management of symptoms. However, PD diagnosis is challenging, particularly in the early stages of the disease. In this paper, we present a method for early diagnosis of PD using patients’ handwriting samples. To improve performance, we combined multiple PD handwriting datasets and used deep transfer learning-based algorithms to overcome the challenge of high variability in the handwritten material. Our approach achieved excellent PD identification performance with 99.22% accuracy on illuminated task of combined HandPD, NewHandPD and Parkinson's Drawing datasets, demonstrating the superiority of our approach over current state-of-the-art methods. © 2020 Elsevier B.V.

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Intelligent energy prediction techniques for fog computing networks

- Farooq, Umar, Shabir, Muhammad, Javed, Muhammad, Imran, Muhammad

Authors: Farooq, Umar , Shabir, Muhammad , Javed, Muhammad , Imran, Muhammad
Date: 2021
Type: Text , Journal article
Relation: Applied Soft Computing Vol. 111, no. (2021), p.
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Description: Energy Efficiency is a key concern for future fog-enabled Internet of Things (IoT). Since Fog Nodes (FNs) are energy-constrained devices, task offloading techniques must consider the energy consumption of the FNs to maximize the performance of IoT applications. In this context, accurate energy prediction can enable the development of intelligent energy-aware task offloading techniques. In this paper, we present two energy prediction techniques, the first one is based on the Recursive Least Square (RLS) filter and the second one uses the Artificial Neural Network (ANN). Both techniques use inputs such as the number of tasks and size of the tasks to predict the energy consumption at different fog nodes. Simulation results show that both techniques have a root mean square error of less than 3%. However, the ANN-based technique shows up to 20% less root mean square error as compared to the RLS-based technique. © 2021 Elsevier B.V.

Intelligent IoT framework for indoor healthcare monitoring of Parkinson's disease patient

- Raza, Mohsina, Awais, Muhammad, Singh, Nishant, Imran, Muhammad, Hussain, Sajjad

Authors: Raza, Mohsina , Awais, Muhammad , Singh, Nishant , Imran, Muhammad , Hussain, Sajjad
Date: 2021
Type: Text , Journal article
Relation: IEEE Journal on Selected Areas in Communications Vol. 39, no. 2 (2021), p. 593-602
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Description: Parkinson's disease is associated with high treatment costs, primarily attributed to the needs of hospitalization and frequent care services. A study reveals annual per-person healthcare costs for Parkinson's patients to be $21,482, with an additional $29,695 burden to society. Due to the high stakes and rapidly rising Parkinson's patients' count, it is imperative to introduce intelligent monitoring and analysis systems. In this paper, an Internet of Things (IoT) based framework is proposed to enable remote monitoring, administration, and analysis of patient's conditions in a typical indoor environment. The proposed infrastructure offers both static and dynamic routing, along with delay analysis and priority enabled communications. The scheme also introduces machine learning techniques to detect the progression of Parkinson's over six months using auditory inputs. The proposed IoT infrastructure and machine learning algorithm are thoroughly evaluated and a detailed analysis is performed. The results show that the proposed scheme offers efficient communication scheduling, facilitating a high number of users with low latency. The proposed machine learning scheme also outperforms state-of-the-art techniques in accurately predicting the Parkinson's progression. © 1983-2012 IEEE.

Is blockchain for internet of medical things a panacea for COVID-19 pandemic?

- Li, Xuran, Tao, Bishenghui, Dai, Hong-Ning, Imran, Muhammad, Wan, Dehuan, Li, Dengwang

Authors: Li, Xuran , Tao, Bishenghui , Dai, Hong-Ning , Imran, Muhammad , Wan, Dehuan , Li, Dengwang
Date: 2021
Type: Text , Journal article
Relation: Pervasive and Mobile Computing Vol. 75, no. (2021), p.
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Description: The outbreak of the COVID-19 pandemic has deeply influenced the lifestyle of the general public and the healthcare system of the society. As a promising approach to address the emerging challenges caused by the epidemic of infectious diseases like COVID-19, Internet of Medical Things (IoMT) deployed in hospitals, clinics, and healthcare centers can save the diagnosis time and improve the efficiency of medical resources though privacy and security concerns of IoMT stall the wide adoption. In order to tackle the privacy, security, and interoperability issues of IoMT, we propose a framework of blockchain-enabled IoMT by introducing blockchain to incumbent IoMT systems. In this paper, we review the benefits of this architecture and illustrate the opportunities brought by blockchain-enabled IoMT. We also provide use cases of blockchain-enabled IoMT on fighting against the COVID-19 pandemic, including the prevention of infectious diseases, location sharing and contact tracing, and the supply chain of injectable medicines. We also outline future work in this area. © 2021 Elsevier B.V.

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It's all about perceptions : a DEMATEL approach to exploring user perceptions of real estate online platforms

- Ullah, Fahim, Sepasgozar, Samad, Jamaluddin Thaheem, Muhammad, Cynthia Wang, Changxin, Imran, Muhammad

Authors: Ullah, Fahim , Sepasgozar, Samad , Jamaluddin Thaheem, Muhammad , Cynthia Wang, Changxin , Imran, Muhammad
Date: 2021
Type: Text , Journal article
Relation: Ain Shams Engineering Journal Vol. 12, no. 4 (2021), p. 4297-4317
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Description: Real Estate Online Platforms (REOPs) are used for conveying real estate and property-related information to potential users (buyers, renters, or sellers). The information leveraged through REOPs supports these users in reaching conclusive rent or buy decisions. Despite their promised utility, user perception about accepting online information through REOPs is unexplored. Using a comprehensive questionnaire and data collected from 65 users, the current study captures the users’ perception of REOPs. Risk, service, information, system, technology adoption model (RSISTAM) is proposed comprising of seven users’ perceptions: risk (PR), service quality (PSEQ), information quality (PIQ), and system quality (PSYQ) from the information systems success model, and usefulness (PU), ease of use (PEU) and behaviour to accept (BAU) from TAM. The results are analysed using the decision making trial and evaluation laboratory (DEMATEL) approach, which shows that PIQ, PSEQ and PEU are the causes and PR, PSYQ, PU and BAU are the effects. Among the criteria, the order of prominence is PEU > PSEQ > PIQ, and for net effects, the order is PU > BAU > PSYQ > PR. For addressing the causes, the REOP managers must provide more transparent, high quality and voluminous information to the users, focus on the system, services, and information qualities, and add more enjoyable, immersive and easy-to-use content through REOPs. This study contributes to the body of knowledge by exploring user perceptions and proposing methods to improve the quality and reliability of REOPs in line with Real Estate 4.0 and industry 4.0 aims. © 2021 THE AUTHORS

Lightweight searchable encryption protocol for industrial internet of things

- Zhang, Ke, Long, Jiahuan, Wang, Xiaofen, Dai, Hong-Ning, Liang, Kaitai, Imran, Muhammad

Authors: Zhang, Ke , Long, Jiahuan , Wang, Xiaofen , Dai, Hong-Ning , Liang, Kaitai , Imran, Muhammad
Date: 2021
Type: Text , Journal article
Relation: IEEE Transactions on Industrial Informatics Vol. 17, no. 6 (2021), p. 4248-4259
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Description: Industrial Internet of Things (IoT) has suffered from insufficient identity authentication and dynamic network topology, thereby resulting in vulnerabilities to data confidentiality. Recently, the attribute-based encryption (ABE) schemes have been regarded as a solution to ensure data transmission security and the fine-grained sharing of encrypted IoT data. However, most of existing ABE schemes that bring tremendous computational cost are not suitable for resource-constrained IoT devices. Therefore, lightweight and efficient data sharing and searching schemes suitable for IoT applications are of great importance. To this end, In this article, we propose a light searchable ABE scheme (namely LSABE). Our scheme can significantly reduce the computing cost of IoT devices with the provision of multiple-keyword searching for data users. Meanwhile, we extend the LSABE scheme to multiauthority scenarios so as to effectively generate and manage the public/secret keys in the distributed IoT environment. Finally, the experimental results demonstrate that our schemes can significantly maintain computational efficiency and save the computational cost at IoT devices, compared to other existing schemes. © 2005-2012 IEEE.

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