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Smart devices have accentuated the importance of geolocation information. Geolocation identification using smart devices has paved the path for incentive-based location-based services (LBS). However, a user’s full control over a smart device can allow tampering of the location proof. Witness-oriented location proof systems (LPS) have emerged to resist the generation of false proofs and mitigate collusion attacks. However, witness-oriented LPS are still susceptible to three-way collusion attacks (involving the user, location authority, and the witness). To overcome the threat of three-way collusion in existing schemes, we introduce a decentralized consensus protocol called MobChain in this paper. In this scheme the selection of a witness and location authority is achieved through a distributed consensus of nodes in an underlying P2P network that establishes a private blockchain. The persistent provenance data over the blockchain provides strong security guarantees; as a result, the forging and manipulation of location becomes impractical. MobChain provides secure location provenance architecture, relying on decentralized decision making for the selection of participants of the protocol thereby addressing the three-way collusion problem. Our prototype implementation and comparison with the state-of-the-art solutions show that MobChain is computationally efficient and highly available while improving the security of LPS.
Faheem Zafar; Abid Khan; Saif Malik; Mansoor Ahmed; Carsten Maple; Adeel Anjum. MobChain: Three-Way Collusion Resistance in Witness-Oriented Location Proof Systems Using Distributed Consensus. Sensors 2021, 21, 5096 .
AMA StyleFaheem Zafar, Abid Khan, Saif Malik, Mansoor Ahmed, Carsten Maple, Adeel Anjum. MobChain: Three-Way Collusion Resistance in Witness-Oriented Location Proof Systems Using Distributed Consensus. Sensors. 2021; 21 (15):5096.
Chicago/Turabian StyleFaheem Zafar; Abid Khan; Saif Malik; Mansoor Ahmed; Carsten Maple; Adeel Anjum. 2021. "MobChain: Three-Way Collusion Resistance in Witness-Oriented Location Proof Systems Using Distributed Consensus." Sensors 21, no. 15: 5096.
Drones, also known as Unmanned Aerial Vehicles (UAVs), are one of the highly emerging technologies of the modern day. Due to their small size, flying capabilities, and complex machinery, drones can be deployed in diverse fields, including agriculture, sports, entertainment, parcel delivery, disaster management, search and rescue, emergency medicine, and healthcare. In case of medical emergency, timely delivery of the required emergency kit is very important. This is often not possible in many underdeveloped countries due to lack of resources, traffic jams, congestion or challenging routes. Also, in times like today’s when the world is hit with COVID-19 pandemic, the movement is very limited due to lockdowns and emergency. In such case, drones can be deployed to deliver the emergency kits and collect samples for tests. This may save someones life as well as time and financial resources. In third world countries, the COVID-19 has spread chaos because of very limited hospitals, resources and staff. Therefore, it is difficult for the government and health officials to accommodate every patient or give him/her the care that he/she needs. Amidst the fear of pandemic, everyone is trying to undergo tests for COVID-19 which is difficult to handle In our research, we have proposed a solution that comprises smartphone application with the help of a patient sending a call to a healthcare centre for delivering emergency kit. The kit contains equipment with the help of which a person can collect swab. The drone takes the swab samples back to the healthcare centre for tests. We have introduced an optimization factor as a baseline for future studies of this kind. We have further conducted field experiments to test our proposed scheme. The results have shown that drones can be quite efficient in collecting samples and delivering emergency kits.
Fahad Saeed; Amjad Mehmood; Muhammad Faran Majeed; Carsten Maple; Khalid Saeed; Muhammad Kashif Khattak; Huihui Wang; Gregory Epiphaniou. Smart delivery and retrieval of swab collection kit for COVID-19 test using autonomous Unmanned Aerial Vehicles. Physical Communication 2021, 48, 101373 .
AMA StyleFahad Saeed, Amjad Mehmood, Muhammad Faran Majeed, Carsten Maple, Khalid Saeed, Muhammad Kashif Khattak, Huihui Wang, Gregory Epiphaniou. Smart delivery and retrieval of swab collection kit for COVID-19 test using autonomous Unmanned Aerial Vehicles. Physical Communication. 2021; 48 ():101373.
Chicago/Turabian StyleFahad Saeed; Amjad Mehmood; Muhammad Faran Majeed; Carsten Maple; Khalid Saeed; Muhammad Kashif Khattak; Huihui Wang; Gregory Epiphaniou. 2021. "Smart delivery and retrieval of swab collection kit for COVID-19 test using autonomous Unmanned Aerial Vehicles." Physical Communication 48, no. : 101373.
Road traffic flow forecasting is among the most important use case associated with smart cities. Traffic forecasting allows drivers to select the fastest route towards their target destinations. A prerequisite for traffic flow management is accurate traffic forecasting. In this study, we introduce a framework for traffic forecasting that uses data on air pollution. The reason to select that data is air pollution rates are often associated with traffic congestion, and there is intensive research that exists to forecast air pollution by road traffic. To the best of our knowledge, any effort to enhance road traffic prediction through air quality and ensemble regression model techniques is not yet been proposed. In this research, our contribution is twofold. Firstly, we have performed a comparative analysis of 7 different regression models to find out which model gives better accuracy. Secondly, we propose a framework using regression models in which the first regression model's result is boosted using boosting ensemble method and is passed to the next regression model which shows that the proposed framework gives more satisfying results than the above 7 regression models. The experimental findings show the effectiveness of the proposed framework which decreases the error rate by 2.47 %.
Nimra Shahid; Munam Ali Shah; Abid Khan; Carsten Maple; Gwanggil Jeon. Towards greener smart cities and road traffic forecasting using air pollution data. Sustainable Cities and Society 2021, 72, 103062 .
AMA StyleNimra Shahid, Munam Ali Shah, Abid Khan, Carsten Maple, Gwanggil Jeon. Towards greener smart cities and road traffic forecasting using air pollution data. Sustainable Cities and Society. 2021; 72 ():103062.
Chicago/Turabian StyleNimra Shahid; Munam Ali Shah; Abid Khan; Carsten Maple; Gwanggil Jeon. 2021. "Towards greener smart cities and road traffic forecasting using air pollution data." Sustainable Cities and Society 72, no. : 103062.
Federated learning (FL) has attracted increasing attention as a promising approach to driving a vast number of end devices with artificial intelligence. However, it is very challenging to guarantee the efficiency of FL considering the unreliable nature of end devices while the cost of device-server communication cannot be neglected. In this paper, we propose SAFA, a semi-asynchronous FL protocol, to address the problems in federated learning such as low round efficiency and poor convergence rate in extreme conditions (e.g., clients dropping offline frequently). We introduce novel designs in the steps of model distribution, client selection and global aggregation to mitigate the impacts of stragglers, crashes and model staleness in order to boost efficiency and improve the quality of the global model. We have conducted extensive experiments with typical machine learning tasks. The results demonstrate that the proposed protocol is effective in terms of shortening federated round duration, reducing local resource wastage, and improving the accuracy of the global model at an acceptable communication cost.
Wentai Wu; Ligang He; Weiwei Lin; Rui Mao; Carsten Maple; Stephen A. Jarvis. SAFA: A Semi-Asynchronous Protocol for Fast Federated Learning With Low Overhead. IEEE Transactions on Computers 2021, 70, 655 -668.
AMA StyleWentai Wu, Ligang He, Weiwei Lin, Rui Mao, Carsten Maple, Stephen A. Jarvis. SAFA: A Semi-Asynchronous Protocol for Fast Federated Learning With Low Overhead. IEEE Transactions on Computers. 2021; 70 (5):655-668.
Chicago/Turabian StyleWentai Wu; Ligang He; Weiwei Lin; Rui Mao; Carsten Maple; Stephen A. Jarvis. 2021. "SAFA: A Semi-Asynchronous Protocol for Fast Federated Learning With Low Overhead." IEEE Transactions on Computers 70, no. 5: 655-668.
Location privacy is a critical problem in the vehicular communication networks. Vehicles broadcast their road status information to other entities in the network through beacon messages. The beacon message content consists of the vehicle ID, speed, direction, position, and other information. An adversary could use vehicle identity and positioning information to determine vehicle driver behavior and identity at different visited location spots. A pseudonym can be used instead of the vehicle ID to help in the vehicle location privacy. These pseudonyms should be changed in appropriate way to produce uncertainty for any adversary attempting to identify a vehicle at different locations. In the existing research literature, pseudonyms are changed during silent mode between neighbors. However, the use of a short silent period and the visibility of pseudonyms of direct neighbors provides a mechanism for an adversary to determine the identity of a target vehicle at specific locations. Moreover, privacy is provided to the driver, only within the RSU range; outside it, there is no privacy protection. In this research, we address the problem of location privacy in a highway scenario, where vehicles are traveling at high speeds with diverse traffic density. We propose a Dynamic Grouping and Virtual Pseudonym-Changing (DGVP) scheme for vehicle location privacy. Dynamic groups are formed based on similar status vehicles and cooperatively change pseudonyms. In the case of low traffic density, we use a virtual pseudonym update process. We formally present the model and specify the scheme through High-Level Petri Nets (HLPN). The simulation results indicate that the proposed method improves the anonymity set size and entropy, provides lower traceability, reduces impact on vehicular network applications, and has lower computation cost compared to existing research work.
Ikram Ullah; Munam Shah; Abid Khan; Carsten Maple; Abdul Waheed. Virtual Pseudonym-Changing and Dynamic Grouping Policy for Privacy Preservation in VANETs. Sensors 2021, 21, 3077 .
AMA StyleIkram Ullah, Munam Shah, Abid Khan, Carsten Maple, Abdul Waheed. Virtual Pseudonym-Changing and Dynamic Grouping Policy for Privacy Preservation in VANETs. Sensors. 2021; 21 (9):3077.
Chicago/Turabian StyleIkram Ullah; Munam Shah; Abid Khan; Carsten Maple; Abdul Waheed. 2021. "Virtual Pseudonym-Changing and Dynamic Grouping Policy for Privacy Preservation in VANETs." Sensors 21, no. 9: 3077.
Computation offloading is a process that provides computing services to vehicles with computation sensitive jobs. Volunteer Computing-Based Vehicular Ad-hoc Networking (VCBV) is envisioned as a promising solution to perform task executions in vehicular networks using an emerging concept known as vehicle-as-a-resource (VaaR). In VCBV systems, offloading is the primary technique used for the execution of delay-sensitive applications which rely on surplus resource utilization. To leverage the surplus resources arising in periods of traffic congestion, we propose a hybrid VCBV task coordination model which performs the resource utilization for task execution in a multi-hop fashion. We propose an algorithm for the determination of boundary relay vehicles to minimize the requirement of placement for multiple road-side units (RSUs). We propose algorithms for primary and secondary task coordination using hybrid VCBV. Extensive simulations show that the hybrid technique for task coordination can increase the system utility, while the latency constraints are addressed.
Abdul Waheed; Munam Shah; Abid Khan; Carsten Maple; Ikram Ullah. Hybrid Task Coordination Using Multi-Hop Communication in Volunteer Computing-Based VANETs. Sensors 2021, 21, 2718 .
AMA StyleAbdul Waheed, Munam Shah, Abid Khan, Carsten Maple, Ikram Ullah. Hybrid Task Coordination Using Multi-Hop Communication in Volunteer Computing-Based VANETs. Sensors. 2021; 21 (8):2718.
Chicago/Turabian StyleAbdul Waheed; Munam Shah; Abid Khan; Carsten Maple; Ikram Ullah. 2021. "Hybrid Task Coordination Using Multi-Hop Communication in Volunteer Computing-Based VANETs." Sensors 21, no. 8: 2718.
Driven by recent advances in object detection with deep neural networks, the tracking-by-detection paradigm has gained increasing prevalence in the research community of multi-object tracking (MOT). It has long been known that appearance information plays an essential role in the detection-to-track association, which lies at the core of the tracking-by-detection paradigm. While most existing works consider the appearance distances between the detections and the tracks, they ignore the statistical information implied by the historical appearance distance records in the tracks, which can be particularly useful when a detection has similar distances with two or more tracks. In this work, we propose a hybrid track association (HTA) algorithm that models the historical appearance distances of a track with an incremental Gaussian mixture model (IGMM) and incorporates the derived statistical information into the calculation of the detection-to-track association cost. Experimental results on three MOT benchmarks confirm that HTA effectively improves the target identification performance with a small compromise to the tracking speed. Additionally, compared to many state-of-the-art trackers, the DeepSORT tracker equipped with HTA achieves better or comparable performance in terms of the balance of tracking quality and speed.
Xufeng Lin; Chang-Tsun Li; Victor Sanchez; Carsten Maple. On the detection-to-track association for online multi-object tracking. Pattern Recognition Letters 2021, 146, 200 -207.
AMA StyleXufeng Lin, Chang-Tsun Li, Victor Sanchez, Carsten Maple. On the detection-to-track association for online multi-object tracking. Pattern Recognition Letters. 2021; 146 ():200-207.
Chicago/Turabian StyleXufeng Lin; Chang-Tsun Li; Victor Sanchez; Carsten Maple. 2021. "On the detection-to-track association for online multi-object tracking." Pattern Recognition Letters 146, no. : 200-207.
In a smart grid, efficient load management can help balance and reduce the burden on the national power grid and also minimize local operational electricity cost. Robust optimization is a technique that is increasingly used in home energy management systems, where it is applied in the scheduling of household loads through demand side control. In this work, interruptible loads and thermostatically controlled loads are analyzed to obtain optimal schedules in the presence of uncertainty. Firstly, the uncertain parameters are represented as different intervals, and then in order to control the degree of conservatism, these parameters are divided into various robustness levels. The conventional scheduling problem is transformed into a deterministic scheduling problem by translating the intervals and robustness levels into constraints. We then apply Harris’ hawk optimization together with integer linear programming to further optimize the load scheduling. Cost and trade-off schemes are considered to analyze the financial consequences of several robustness levels. Results show that the proposed method is adaptable to user requirements and robust to the uncertainties.
Malik Ali Judge; Awais Manzoor; Carsten Maple; Joel J.P.C. Rodrigues; Saif Ul Islam. Price-based demand response for household load management with interval uncertainty. Energy Reports 2021, 1 .
AMA StyleMalik Ali Judge, Awais Manzoor, Carsten Maple, Joel J.P.C. Rodrigues, Saif Ul Islam. Price-based demand response for household load management with interval uncertainty. Energy Reports. 2021; ():1.
Chicago/Turabian StyleMalik Ali Judge; Awais Manzoor; Carsten Maple; Joel J.P.C. Rodrigues; Saif Ul Islam. 2021. "Price-based demand response for household load management with interval uncertainty." Energy Reports , no. : 1.
The COVID-19 pandemic was a remarkable, unprecedented event which altered the lives of billions of citizens globally resulting in what became commonly referred to as the new-normal in terms of societal norms and the way we live and work. Aside from the extraordinary impact on society and business as a whole, the pandemic generated a set of unique cyber-crime related circumstances which also affected society and business. The increased anxiety caused by the pandemic heightened the likelihood of cyber-attacks succeeding corresponding with an increase in the number and range of cyber-attacks. This paper analyses the COVID-19 pandemic from a cyber-crime perspective and highlights the range of cyber-attacks experienced globally during the pandemic. Cyber-attacks are analysed and considered within the context of key global events to reveal the modus-operandi of cyber-attack campaigns. The analysis shows how following what appeared to be large gaps between the initial outbreak of the pandemic in China and the first COVID-19 related cyber-attack, attacks steadily became much more prevalent to the point that on some days, three or four unique cyber-attacks were being reported. The analysis proceeds to utilise the UK as a case study to demonstrate how cyber-criminals leveraged salient events and governmental announcements to carefully craft and execute cyber-crime campaigns.
Harjinder Singh Lallie; Lynsay A. Shepherd; Jason R.C. Nurse; Arnau Erola; Gregory Epiphaniou; Carsten Maple; Xavier Bellekens. Cyber security in the age of COVID-19: A timeline and analysis of cyber-crime and cyber-attacks during the pandemic. Computers & Security 2021, 105, 102248 .
AMA StyleHarjinder Singh Lallie, Lynsay A. Shepherd, Jason R.C. Nurse, Arnau Erola, Gregory Epiphaniou, Carsten Maple, Xavier Bellekens. Cyber security in the age of COVID-19: A timeline and analysis of cyber-crime and cyber-attacks during the pandemic. Computers & Security. 2021; 105 ():102248.
Chicago/Turabian StyleHarjinder Singh Lallie; Lynsay A. Shepherd; Jason R.C. Nurse; Arnau Erola; Gregory Epiphaniou; Carsten Maple; Xavier Bellekens. 2021. "Cyber security in the age of COVID-19: A timeline and analysis of cyber-crime and cyber-attacks during the pandemic." Computers & Security 105, no. : 102248.
Supply chains (SC) present performance bottlenecks that contribute to a high level of costs, infiltration of product quality, and impact productivity. Examples of such inhibitors include the bullwhip effect, new product lines, high inventory, and restrictive data flows. These bottlenecks can force manufacturers to source more raw materials and increase production significantly. Also, restrictive data flow in a complex global SC network generally slows down the movement of goods and services. The use of distributed ledger technologies (DLT) in SC management (SCM) demonstrates the potentials to reduce these bottlenecks through transparency, decentralization, and optimizations in data management. These technologies promise to enhance the trustworthiness of entities within the SC, ensure the accuracy of data-driven operations, and enable existing SCM processes to migrate from a linear to a fully circular economy. This article presents a comprehensive review of 111 articles published in the public domain in the use and efficacy of DLT in SC. It acts as a roadmap for current and future researchers who focus on SC security management to better understand the integration of digital technologies such as DLT. We clustered these articles using standard descriptors linked to trustworthiness, namely, immutability, transparency, traceability, and integrity.
Mary Asante; Gregory Epiphaniou; Carsten Maple; Haider Al-Khateeb; Mirko Bottarelli; Kayhan Zrar Ghafoor. Distributed Ledger Technologies in Supply Chain Security Management: A Comprehensive Survey. IEEE Transactions on Engineering Management 2021, PP, 1 -27.
AMA StyleMary Asante, Gregory Epiphaniou, Carsten Maple, Haider Al-Khateeb, Mirko Bottarelli, Kayhan Zrar Ghafoor. Distributed Ledger Technologies in Supply Chain Security Management: A Comprehensive Survey. IEEE Transactions on Engineering Management. 2021; PP (99):1-27.
Chicago/Turabian StyleMary Asante; Gregory Epiphaniou; Carsten Maple; Haider Al-Khateeb; Mirko Bottarelli; Kayhan Zrar Ghafoor. 2021. "Distributed Ledger Technologies in Supply Chain Security Management: A Comprehensive Survey." IEEE Transactions on Engineering Management PP, no. 99: 1-27.
In intelligent transportation systems (ITS), communications between vehicles, i.e. vehicle-to-vehicle (V2V) communications are of greatest importance to facilitate autonomous driving. The current state-of-the-art for secure data exchange in V2V communications relies on public-key cryptography (PKC) consuming significant computational and energy resources for the encryption/decryption process and large bandwidth for the key distribution. To overcome these limitations, physical-layer security (PLS) has emerged as a lightweight solution by exploiting the physical characteristics of the V2V communication channel to generate symmetric cryptographic keys. Currently, key-generation algorithms are designed via empirical parameter settings, without resulting in optimum key-generation performance. In this paper, we devise a key-generation algorithm for PLS in V2V communications by introducing a novel channel response quantisation method that results in optimum performance via analytical parameter settings. Contrary to the current state-of-the-art, the channel responses incorporate all V2V channel attributes that contribute to temporal variability, such as three dimensional (3D) scattering and scatterers' mobility. An extra functionality, namely, Perturbe-Observe (PO), is further incorporated that enables the algorithm to adapt to the inherent non-reciprocity of the V2V channel responses at the legitimate entities. Optimum performance is evidenced via maximisation of the key bit generation rate (BGR) and key entropy (H) and minimisation of the key bit mismatch rate (BMR). A new metric is further introduced, the so-called secret-bit generation rate (SBGR), as the ratio of the number of bits which are successfully used to compose keys to the total amount of channel samples. SBGR unifies BGR and BMR and is thus maximised by the proposed algorithmic process.
Mirko Bottarelli; Petros Karadimas; Gregory Epiphaniou; Dhouha Kbaier Ben Ismail; Carsten Maple. Adaptive and Optimum Secret Key Establishment for Secure Vehicular Communications. IEEE Transactions on Vehicular Technology 2021, 70, 2310 -2321.
AMA StyleMirko Bottarelli, Petros Karadimas, Gregory Epiphaniou, Dhouha Kbaier Ben Ismail, Carsten Maple. Adaptive and Optimum Secret Key Establishment for Secure Vehicular Communications. IEEE Transactions on Vehicular Technology. 2021; 70 (3):2310-2321.
Chicago/Turabian StyleMirko Bottarelli; Petros Karadimas; Gregory Epiphaniou; Dhouha Kbaier Ben Ismail; Carsten Maple. 2021. "Adaptive and Optimum Secret Key Establishment for Secure Vehicular Communications." IEEE Transactions on Vehicular Technology 70, no. 3: 2310-2321.
Traffic accidents have become a major issue for researchers, academia, government and vehicle manufacturers over the last few years. Many accidents and emergency situations frequently occur on the road. Unfortunately, accidents lead to health injuries, destruction of some infrastructure, bad traffic flow, and more importantly these events cause deaths of hundreds of thousands of people due to not getting treatment in time. Thus, we need to develop an efficient and smart emergency system to ensure the timely arrival of an ambulance service to the place of the accident in order to provide timely medical help to those injured. In addition, we also need to communicate promptly with other entities such as hospitals so that they can make appropriate arrangements and provide timely medical information to emergency personnel on the scene including alerting those related to the injured person(s). In this paper, we have developed an intelligent protocol that uses connected and autonomous vehicles’ scenarios in Intelligent Transportation System (ITS) so that prompt emergency services can be provided to reduce the death rate caused. The proposed protocol smartly connects with all the relevant entitles during the emergency while maintaining a smooth traffic flow for the arrival of the ambulance service. Moreover, our protocol also mitigates the broadcasting of messages circulating over the network for delay sensitive tasks. The evaluation results, based on the performance metrics such as channel collision, average packet delay, packet loss, and routing-overhead demonstrate that our proposed protocol outperforms previously proposed protocols such as Emergency Message Dissemination for Vehicular (EMDV), Contention Based Broadcasting (CBB), and Particle Swarm Optimization Contention-based Broadcast (PCBB) protocols. Finally, we discuss several issues and challenges that need to be addressed in the network in order to achieve more a reliable, efficient, connected, and autonomous vehicular network.
Bushra Feroz; Amjad Mehmood; Hafsa Maryam; Sherali Zeadally; Carsten Maple; Munam Ali Shah. Vehicle-Life Interaction in Fog-Enabled Smart Connected and Autonomous Vehicles. IEEE Access 2021, 9, 7402 -7420.
AMA StyleBushra Feroz, Amjad Mehmood, Hafsa Maryam, Sherali Zeadally, Carsten Maple, Munam Ali Shah. Vehicle-Life Interaction in Fog-Enabled Smart Connected and Autonomous Vehicles. IEEE Access. 2021; 9 ():7402-7420.
Chicago/Turabian StyleBushra Feroz; Amjad Mehmood; Hafsa Maryam; Sherali Zeadally; Carsten Maple; Munam Ali Shah. 2021. "Vehicle-Life Interaction in Fog-Enabled Smart Connected and Autonomous Vehicles." IEEE Access 9, no. : 7402-7420.
Digital twins (DT) have been proposed to support and enhance manufacturing processes of the industries. The outcome of adopting DT is so encouraging that it is hoped that more than 50% of the large industries will benefit from DT by the end of 2021. There are different narratives of researchers about DT. This paper presents DT as a novel six dimensional framework. Furthermore, we propose an efficient blockchain for DT, namely twinchain. The twin creation process is a multi-phase multidisciplinary process which urges for auditing, tracking, immutability and accountability. The blockchain technology is envisioned to help for attaining the said goals. Twinchain allows efficient management of DT data w.r.t storage, sharing and authenticity. Another salient feature is that all of the cryptographic schemes used in the construction of twinchain are quantum resilient. The paper also presents a framework for deployment of twinchain for manufacturing of a robot surgical machine.
Abid Khan; Furqan Shahid; Carsten Maple; Awais Ahmad; Gwanggil Jeon. Towards Smart Manufacturing Using Spiral Digital Twin Framework and Twinchain. IEEE Transactions on Industrial Informatics 2020, PP, 1 -1.
AMA StyleAbid Khan, Furqan Shahid, Carsten Maple, Awais Ahmad, Gwanggil Jeon. Towards Smart Manufacturing Using Spiral Digital Twin Framework and Twinchain. IEEE Transactions on Industrial Informatics. 2020; PP (99):1-1.
Chicago/Turabian StyleAbid Khan; Furqan Shahid; Carsten Maple; Awais Ahmad; Gwanggil Jeon. 2020. "Towards Smart Manufacturing Using Spiral Digital Twin Framework and Twinchain." IEEE Transactions on Industrial Informatics PP, no. 99: 1-1.
Reducing the number of road accidents is a key agenda item for governments across the world. This has led to an increase in the amount of attention given to Vehicular Communication Systems (VCS), which are seen as an important technology that can offer significant improvements in road safety. Using VCS, vehicles can form a dynamic self-configuring network that enables a vehicle to communicate with other vehicles (V2V) and roadside infrastructure (V2I). However, such wireless communication channels are vulnerable to attacks, and therefore an authentication scheme for communications should be designed before the deployment. Prior work has focused on utilising digital signature approaches to achieve the security requirements, but due to the special characteristics of VCS, such approaches are not well suited for safety related applications of VCS, since they incur high communication and computation overheads. To combat this issue, we propose a certificateless and lightweight authentication scheme to provide means of secure communications for VCS. In this work we introduce authentication tokens, which replace digital certificates to reduce the burden of certificate management on a Trusted Authority (TA). In addition, the utilisation of tokens ensures that mutual authentication is achieved for V2I communication. Moreover, we employ TESLA as the underlying broadcast authentication protocol to achieve the required security goals for safety message broadcasting. According to the security analysis and extensive simulation of our scheme, the results show that it can withstands various types of attacks. Also it has better performance in term of verification delay, scalability and communication overhead compared to lightweight authentication schemes that are based on similar techniques. Therefore, the scheme is well suited for VCS
Waleed Hathal; Haitham Cruickshank; Zhili Sun; Carsten Maple. Certificateless and Lightweight Authentication Scheme for Vehicular Communication Networks. IEEE Transactions on Vehicular Technology 2020, 69, 16110 -16125.
AMA StyleWaleed Hathal, Haitham Cruickshank, Zhili Sun, Carsten Maple. Certificateless and Lightweight Authentication Scheme for Vehicular Communication Networks. IEEE Transactions on Vehicular Technology. 2020; 69 (12):16110-16125.
Chicago/Turabian StyleWaleed Hathal; Haitham Cruickshank; Zhili Sun; Carsten Maple. 2020. "Certificateless and Lightweight Authentication Scheme for Vehicular Communication Networks." IEEE Transactions on Vehicular Technology 69, no. 12: 16110-16125.
Future Intelligent Transport Systems (ITS) will require that vehicles are equipped with Dedicated Short Range Communications (DSRC). With these DSRC capabilities, new privacy threats are emerging that can be taken advantage of by threat actors with little experience and cheap components. However, the origins of these privacy threats are not limited to the vehicle and its communications, but extend to non-vehicular devices carried by the driver and passengers. A shortcoming of existing work is that it tends to focus on a specific aspect of privacy leakage when attempting to protect location privacy. In doing so, interactions between privacy threats are not considered. In this work, we investigate the privacy surface of a vehicle by considering the many different ways in which location privacy can be leaked. Following this, we identify techniques to protect privacy and that it is insufficient to provide location privacy against a single threat vector. A methodology to calculate the interactions of privacy preserving techniques is used to highlight the need to consider the wider threat landscape and for techniques to collaborate to ensure location privacy is provided against multiple sources of privacy threats where possible.
Matthew Bradbury; Phillip Taylor; Ugur Ilker Atmaca; Carsten Maple; Nathan Griffiths. Privacy Challenges With Protecting Live Vehicular Location Context. IEEE Access 2020, 8, 207465 -207484.
AMA StyleMatthew Bradbury, Phillip Taylor, Ugur Ilker Atmaca, Carsten Maple, Nathan Griffiths. Privacy Challenges With Protecting Live Vehicular Location Context. IEEE Access. 2020; 8 ():207465-207484.
Chicago/Turabian StyleMatthew Bradbury; Phillip Taylor; Ugur Ilker Atmaca; Carsten Maple; Nathan Griffiths. 2020. "Privacy Challenges With Protecting Live Vehicular Location Context." IEEE Access 8, no. : 207465-207484.
On-line detection of anomalies in time series is a key technique used in various event-sensitive scenarios such as robotic system monitoring, smart sensor networks and data center security. However, the increasing diversity of data sources and the variety of demands make this task more challenging than ever. Firstly, the rapid increase in unlabeled data means supervised learning is becoming less suitable in many cases. Secondly, a large portion of time series data have complex seasonality features. Thirdly, on-line anomaly detection needs to be fast and reliable. In light of this, we have developed a prediction-driven, unsupervised anomaly detection scheme, which adopts a backbone model combining the decomposition and the inference of time series data. Further, we propose a novel metric, Local Trend Inconsistency (LTI), and an efficient detection algorithm that computes LTI in a real-time manner and scores each data point robustly in terms of its probability of being anomalous. We have conducted extensive experimentation to evaluate our algorithm with several datasets from both public repositories and production environments. The experimental results show that our scheme outperforms existing representative anomaly detection algorithms in terms of the commonly used metric, Area Under Curve (AUC), while achieving the desired efficiency.
Wentai Wu; Ligang He; Weiwei Lin; Yi Su; Yuhua Cui; Carsten Maple; Stephen A. Jarvis. Developing an Unsupervised Real-time Anomaly Detection Scheme for Time Series with Multi-seasonality. IEEE Transactions on Knowledge and Data Engineering 2020, PP, 1 -1.
AMA StyleWentai Wu, Ligang He, Weiwei Lin, Yi Su, Yuhua Cui, Carsten Maple, Stephen A. Jarvis. Developing an Unsupervised Real-time Anomaly Detection Scheme for Time Series with Multi-seasonality. IEEE Transactions on Knowledge and Data Engineering. 2020; PP (99):1-1.
Chicago/Turabian StyleWentai Wu; Ligang He; Weiwei Lin; Yi Su; Yuhua Cui; Carsten Maple; Stephen A. Jarvis. 2020. "Developing an Unsupervised Real-time Anomaly Detection Scheme for Time Series with Multi-seasonality." IEEE Transactions on Knowledge and Data Engineering PP, no. 99: 1-1.
Detection of Black Hole attacks is one of the most challenging and critical routing security issues in vehicular ad hoc networks (VANETs) and autonomous and connected vehicles (ACVs). Malicious vehicles or nodes may exist in the cyber-physical path on which the data and control packets have to be routed converting a secure and reliable route into a compromised one. However, instead of passing packets to a neighbouring node, malicious nodes bypass them and drop any data packets that could contain emergency alarms. We introduce an intelligent black hole attack detection scheme (IDBA) tailored to ACV. We consider four key parameters in the design of the scheme, namely, Hop Count, Destination Sequence Number, Packet Delivery Ratio (PDR), and End-to-End delay (E2E). We tested the performance of our IDBA against AODV with Black Hole (BAODV), Intrusion Detection System (IdsAODV), and EAODV algorithms. Extensive simulation results show that our IDBA outperforms existing approaches in terms of PDR, E2E, Routing Overhead, Packet Loss Rate, and Throughput.
Zohaib Hassan; Amjad Mehmood; Carsten Maple; Muhammad Altaf Khan; Abdulaziz Aldegheishem. Intelligent Detection of Black Hole Attacks for Secure Communication in Autonomous and Connected Vehicles. IEEE Access 2020, 8, 199618 -199628.
AMA StyleZohaib Hassan, Amjad Mehmood, Carsten Maple, Muhammad Altaf Khan, Abdulaziz Aldegheishem. Intelligent Detection of Black Hole Attacks for Secure Communication in Autonomous and Connected Vehicles. IEEE Access. 2020; 8 ():199618-199628.
Chicago/Turabian StyleZohaib Hassan; Amjad Mehmood; Carsten Maple; Muhammad Altaf Khan; Abdulaziz Aldegheishem. 2020. "Intelligent Detection of Black Hole Attacks for Secure Communication in Autonomous and Connected Vehicles." IEEE Access 8, no. : 199618-199628.
In the current hyper-connected, data-driven era, smart devices are providing access to geolocation information, enabling a paradigm shift in diverse domains. Location proof systems utilize smart devices to provide witnessed proof of location to enable secure location-based services (LBS). Applications of location proof systems include safety, asset management and operations monitoring in health care, supply chain tracking, and Internet-of-Things (IoT)-based location intelligence in businesses. In this paper, we investigate the state of the art in location proof systems, examining design challenges and implementation considerations for application in the real world. To frame the analysis, we have developed a taxonomy of location proof systems and performed a comparative analysis over the common attributes, highlighting their strength and weaknesses. Furthermore, we have identified future trends for this increasingly important area of investigation and development.
Faheem Zafar; Abid Khan; Adeel Anjum; Carsten Maple; Munam Ali Shah. Location Proof Systems for Smart Internet of Things: Requirements, Taxonomy, and Comparative Analysis. Electronics 2020, 9, 1776 .
AMA StyleFaheem Zafar, Abid Khan, Adeel Anjum, Carsten Maple, Munam Ali Shah. Location Proof Systems for Smart Internet of Things: Requirements, Taxonomy, and Comparative Analysis. Electronics. 2020; 9 (11):1776.
Chicago/Turabian StyleFaheem Zafar; Abid Khan; Adeel Anjum; Carsten Maple; Munam Ali Shah. 2020. "Location Proof Systems for Smart Internet of Things: Requirements, Taxonomy, and Comparative Analysis." Electronics 9, no. 11: 1776.
Electric power grids are lagging in flexibility and time-response. A smart grid is an improved version of electrical grids that leverages Internet of Things (IoT) based devices to improve the overall infrastructure from the grid stations to intelligent appliances. It provides better understanding of supply and demand and overall flow of data depending based upon the requirements. Modern approach towards Smart grid envisions to provide electricity consumers with the opportunity to manage their respective power usage. Population increase has played a major role in the adoption of smart grid as a lot of electrical energy is consumed in the residential sector and a lot of architectures have been proposed for better flow of information from the smart meter to connectors and devices for improved customer participation. Customer needs have been very important in the smart grid. However, the customers have never been provided with the ease of choosing their own kind of benefits from the smart grid. In this work, we propose an enhanced architecture working effectively for multiple users based on their requirements. The users would be able to choose their type of scheduling techniques based on their requirements. These requirements may include cost reduction and increasing user comfort for better consumption of electricity and reliable systems. These requirements can be achieved using different Bio inspired computing based scheduling algorithms. Furthermore, in this work, we provide a comparison of these bio inspired scheduling techniques, i.e., Enhanced Differential Evolution, Bacterial Foraging Algorithm and Grey Wolf Optimization integrated in smart grid architecture for providing better consumption of electricity and achieving reliable systems. These algorithms mainly aim to schedule load, minimize electricity bills and maximize the user comfort depending on user demand. .
Zunaira Amjad; Munam Ali Shah; Carsten Maple; Hasan Ali Khattak; Zoobia Ameer; Muhammad Nabeel Asghar; Shafaq Mussadiq. Towards Energy Efficient Smart Grids Using Bio-Inspired Scheduling Techniques. IEEE Access 2020, 8, 158947 -158960.
AMA StyleZunaira Amjad, Munam Ali Shah, Carsten Maple, Hasan Ali Khattak, Zoobia Ameer, Muhammad Nabeel Asghar, Shafaq Mussadiq. Towards Energy Efficient Smart Grids Using Bio-Inspired Scheduling Techniques. IEEE Access. 2020; 8 (99):158947-158960.
Chicago/Turabian StyleZunaira Amjad; Munam Ali Shah; Carsten Maple; Hasan Ali Khattak; Zoobia Ameer; Muhammad Nabeel Asghar; Shafaq Mussadiq. 2020. "Towards Energy Efficient Smart Grids Using Bio-Inspired Scheduling Techniques." IEEE Access 8, no. 99: 158947-158960.
The world is experiencing a rapid growth of smart cities accelerated by Industry 4.0, including the Internet of Things (IoT), and enhanced by the application of emerging innovative technologies which in turn create highly fragile and complex cyber–physical–natural ecosystems. This paper systematically identifies peer-reviewed literature and explicitly investigates empirical primary studies that address cyber resilience and digital forensic incident response (DFIR) aspects of cyber–physical systems (CPSs) in smart cities. Our findings show that CPSs addressing cyber resilience and support for modern DFIR are a recent paradigm. Most of the primary studies are focused on a subset of the incident response process, the “detection and analysis” phase whilst attempts to address other parts of the DFIR process remain limited. Further analysis shows that research focused on smart healthcare and smart citizen were addressed only by a small number of primary studies. Additionally, our findings identify a lack of available real CPS-generated datasets limiting the experiments to mostly testbed type environments or in some cases authors relied on simulation software. Therefore, contributing this systematic literature review (SLR), we used a search protocol providing an evidence-based summary of the key themes and main focus domains investigating cyber resilience and DFIR addressed by CPS frameworks and systems. This SLR also provides scientific evidence of the gaps in the literature for possible future directions for research within the CPS cybersecurity realm. In total, 600 papers were surveyed from which 52 primary studies were included and analysed.
Gabriela Ahmadi-Assalemi; Haider Al-Khateeb; Gregory Epiphaniou; Carsten Maple. Cyber Resilience and Incident Response in Smart Cities: A Systematic Literature Review. Smart Cities 2020, 3, 894 -927.
AMA StyleGabriela Ahmadi-Assalemi, Haider Al-Khateeb, Gregory Epiphaniou, Carsten Maple. Cyber Resilience and Incident Response in Smart Cities: A Systematic Literature Review. Smart Cities. 2020; 3 (3):894-927.
Chicago/Turabian StyleGabriela Ahmadi-Assalemi; Haider Al-Khateeb; Gregory Epiphaniou; Carsten Maple. 2020. "Cyber Resilience and Incident Response in Smart Cities: A Systematic Literature Review." Smart Cities 3, no. 3: 894-927.