Article
Computer Science, Theory & Methods
Kinza Sarwar, Sira Yongchareon, Jian Yu, Saeed Ur Rehman
Summary: Despite the challenges in adopting IoT due to data privacy concerns, the introduction of fog computing can address some of the issues and provide improvements for preserving data privacy in IoT applications. Future research directions in this area are also discussed.
ACM COMPUTING SURVEYS
(2023)
Article
Computer Science, Information Systems
Abdulmalik Alwarafy, Khaled A. Al-Thelaya, Mohamed Abdallah, Jens Schneider, Mounir Hamdi
Summary: This article conducts a comprehensive survey on security and privacy issues in the context of EC-assisted IoT, including definitions, attack classifications, solutions, and open challenges. Furthermore, it provides future research directions for the secure EC-assisted IoT paradigm.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Computer Science, Information Systems
Marc Jayson Baucas, Petros Spachos, Konstantinos N. Plataniotis
Summary: The number of embedded devices connecting to wireless networks has increased, leading to the need for secure fog-based IoT networks. This study proposes a platform that uses public-key encryption and permissioned blockchains to protect network endpoints and track encryption processes, ultimately fortifying the network against malicious attacks.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Review
Computer Science, Hardware & Architecture
Mohammad Nikravan, Mostafa Haghi Kashani
Summary: This paper presents a systematic review of trust management in Fog and Edge Computing (FEC), categorizing and comparing different trust management approaches. It also discusses evaluation techniques, tools and simulation environments, and important trust metrics. The paper highlights open issues and future trends for further studies in this field.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2022)
Article
Computer Science, Hardware & Architecture
Savio Sciancalepore
Summary: This paper introduces PARFAIT, a framework for secure and low-delay access to services in fog-enabled IoT ecosystems. PARFAIT uses rolling ephemeral identities to provide unlinkability among access requests, preventing tracking of mobile IoT devices by compromised fog nodes.
Review
Computer Science, Interdisciplinary Applications
Rohit Kumar, Neha Agrawal
Summary: Cloud computing is transforming traditional computing methods through various forms and architectural types, such as Edge and Fog computing. These extensions of the basic cloud computing model promise improved network performance. Industrial applications rely on cloud resources to process a large volume of power-sensitive Industrial IoT (IIoT) data, which requires careful analysis to enhance system performance. This paper explores the Edge-Fog-Cloud architectural frameworks, compares their advantages and disadvantages, and delves into the scientific side of multi-dimensional IIoT data. It also highlights the current state-of-the-art and implementation challenges.
JOURNAL OF INDUSTRIAL INFORMATION INTEGRATION
(2023)
Article
Computer Science, Information Systems
Huifeng Wu, Yi Yan, Baiping Chen, Feng Hou, Danfeng Sun
Summary: This article introduces an ontology and a three-layer cloud-fog-edge architecture (FADA) for large and complex machines to address issues such as data quality and data extraction. Experimental results prove the feasibility and performance advantages of FADA in different scenarios.
IEEE TRANSACTIONS ON CLOUD COMPUTING
(2022)
Article
Computer Science, Information Systems
Soumya Banerjee, Ashok Kumar Das, Samiran Chattopadhyay, Sajjad Shaukat Jamal, Joel J. P. C. Rodrigues, Youngho Park
Summary: In this work, a new security mechanism was proposed for ensuring security during failover among fog nodes in IoT. The scheme achieves fast lightweight secondary authentication leveraging initial authentication. The research demonstrates the security of the proposed scheme through formal security analysis, informal security analysis, and comparative analysis with other schemes.
Article
Chemistry, Analytical
Ahmed M. Alwakeel
Summary: With the advancement of technologies, cloud computing becomes essential. Fog computing and edge computing are emerging cloud technologies aiming to simplify complexities of cloud computing and utilize local network computing capabilities. However, using these technologies introduces security and privacy challenges which require countermeasures to mitigate their impact.
Review
Computer Science, Information Systems
Muhammad Burhan, Hina Alam, Ahmad Arsalan, Rana Asif Rehman, Muhammad Anwar, Muhammad Faheem, Muhammad Waqar Ashraf
Summary: The Internet of Things enables seamless communication between countless objects, but faces challenges such as latency, limited processing power, and network failures. The concept of fog computing integrates cloud resources closer to IoT devices, extending computing, storage, and networking capabilities to the network edge. However, fog-based IoT networks still have real-time security challenges that need to be addressed.
Article
Computer Science, Information Systems
Yongkai Fan, Guanqun Zhao, Xia Lei, Wei Liang, Kuan-Ching Li, Kim-Kwang Raymond Choo, Chunsheng Zhu
Summary: The article proposes a secure Blockchain-based scheme to guarantee the credibility of nodes and data in IoT and fog environments, demonstrating its feasibility through experiments.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Computer Science, Information Systems
Ali Akbar Sadri, Amir Masoud Rahmani, Morteza Saberikamarposhti, Mehdi Hosseinzadeh
Summary: This paper highlights the importance of cloud computing and fog computing in the Internet of Things, the critical role of data management, and the essential techniques for data size reduction in fog computing. The study focuses on classifying and analyzing FDR studies from 2016 to 2022, presenting relevant topics and methods, and identifying open issues and challenges for future research.
INTERNET OF THINGS
(2022)
Article
Computer Science, Information Systems
Ismael Martinez, Abdelhakim Senhaji Hafid, Abdallah Jarray
Summary: The increasing demand for Internet-of-Things applications has led to an overreliance on cloud computing, resulting in network congestion and unreliable response delays. Fog computing, as an alternative to cloud, offers low-latency services by bringing processing and storage resources to the network edge.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Review
Computer Science, Information Systems
Mohammed Laroui, Boubakr Nour, Hassine Moungla, Moussa A. Cherif, Hossam Afifi, Mohsen Guizani
Summary: The Internet of Things (IoT) enables communication between devices and digital assets over a network without human intervention. Traditional cloud computing is not efficient in analyzing large amounts of data quickly, prompting the proposal of edge computing to decentralize data processing to solve this issue. Edge computing supports IoT applications requiring quick response times, leading to improved energy consumption and resource utilization.
COMPUTER COMMUNICATIONS
(2021)
Article
Computer Science, Information Systems
Cong Peng, Min Luo, Huaqun Wang, Muhammad Khurram Khan, Debiao He
Summary: This article proposes an efficient privacy-preserving multidimensional data aggregation scheme called PMDA for IoT. Through the use of homomorphic encryption method and signature mechanism, the scheme ensures nonrepudiation of device data and verification efficiency at edge nodes.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Agriculture, Multidisciplinary
Lesia Kinach, Kate Parizeau, Evan D. G. Fraser
AGRICULTURE AND HUMAN VALUES
(2020)
Article
Multidisciplinary Sciences
Lee Hannah, Patrick R. Roehrdanz, Krishna K. C. Bahadur, Evan D. G. Fraser, Camila Donatti, Leonardo Saenz, Timothy Max Wright, Robert J. Hijmans, Mark Mulligan, Aaron Berg, Arnout van Soesbergen
Article
Psychology, Biological
Evan D. G. Fraser
PHYSIOLOGY & BEHAVIOR
(2020)
Letter
Multidisciplinary Sciences
Gael Grenouillet, Kevin S. McCann, Bailey C. McMeans, Evan Fraser, Nam So, Zeb S. Hogan, Sovan Lek, Peng Bun Ngor
SCIENTIFIC REPORTS
(2021)
Article
Green & Sustainable Science & Technology
Poritosh Roy, Lisa Ashton, Maria G. Corradini, Evan D. G. Fraser, Mahendra Thimmanagari, Mike Tiessan, Atul Bali, Khurshid M. Saharan, Amar K. Mohanty, Manjusri Misra
Summary: Plastic waste issue has gained global attention, efforts are being made to replace single-use plastic straws, yet the potential impacts on environment, economy, and society need further analysis.
JOURNAL OF CLEANER PRODUCTION
(2021)
Review
Chemistry, Multidisciplinary
Abbas Yazdinejad, Behrouz Zolfaghari, Amin Azmoodeh, Ali Dehghantanha, Hadis Karimipour, Evan Fraser, Arthur G. Green, Conor Russell, Emily Duncan
Summary: Smart Farming and Precision Agriculture have attracted attention in recent years for their potential to improve efficiency in agriculture. However, they also introduce new security threats that require awareness and proper countermeasures. This paper categorizes security threats within the SF/PA areas and provides a taxonomy for detecting cyber threats in SF and PA environments.
APPLIED SCIENCES-BASEL
(2021)
Article
Green & Sustainable Science & Technology
Addisalem (Addis) Benyam, Tammara Soma, Evan Fraser
Summary: Agricultural digitization has the potential to reduce food loss and waste, but current primary drivers are economic gains and cost reduction, rather than food loss prevention. The prohibitive investment costs and digital divide between technology adaptors limit the broad uptake of digital agricultural technologies in addressing food loss and waste.
JOURNAL OF CLEANER PRODUCTION
(2021)
Review
Food Science & Technology
Alesandros Glaros, Sarah Marquis, Chelsea Major, Philip Quarshie, Lisa Ashton, Arthur G. Green, Krishna B. Kc, Lenore Newman, Robert Newell, Rickey Y. Yada, Evan D. G. Fraser
Summary: This paper critically reviews five food frontiers and assesses their potential in reducing environmental footprints and enhancing food system sustainability. The findings suggest that cellular agriculture, controlled environment agriculture, entomophagy, and seaweed aquaculture have similar positive impacts, with controlled environment agriculture appearing to be the most feasible technology for large-scale implementation. The potential impacts of climate-driven northern agricultural expansion are mixed and may pose multiple risks to the global food system.
TRENDS IN FOOD SCIENCE & TECHNOLOGY
(2022)
Article
Biodiversity Conservation
E. M. Bennett, P. Morrison, J. M. Holzer, K. J. Winkler, E. D. G. Fraser, S. J. Green, B. E. Robinson, K. Sherren, J. Botzas-Coluni, W. Palen
Summary: Place-based social-ecological research aims to improve local environmental governance while also providing insights for decision-making on larger scales or in other locations. However, transferring local perspectives and aggregating understanding to larger scales poses challenges.
ECOSYSTEMS AND PEOPLE
(2021)
Article
Food Science & Technology
Philip Tetteh Quarshie, Abdul-Rahim Abdulai, Evan D. G. Fraser
Summary: The study highlights how constraints in the Early Generation Seeds value chain in Ghana hinder the commercialization and adoption of High Yielding Varieties (HYV) among smallholders, affecting trust and limiting the availability of improved seeds. To address these issues, targeted public and private sector relationships that recognize the critical roles of diverse actors in the value chain must be pursued.
FRONTIERS IN SUSTAINABLE FOOD SYSTEMS
(2021)
Correction
Food Science & Technology
Brajesh K. Singh, Tom Arnold, Patricia Biermayr-Jenzano, Jacqueline Broerse, Gianluca Brunori, Patrick Caron, Olivier De Schutter, Shenggen Fan, Jessica Fanzo, Evan Fraser, Mirjana Gurinovic, Marta Hugas, Jacqueline McGlade, Christine Nellemann, Jemimah Njuki, Roberta Sonnino, Hanna L. Tuomisto, Seta Tutundjian, Patrick Webb, Justus Wesseler
Article
Multidisciplinary Sciences
Krishna K. C. Bahadur, Danielle Montocchio, Aaron Berg, Evan D. G. Fraser, Bahram Daneshfar, Catherine Champagne
SN APPLIED SCIENCES
(2020)
Article
Public, Environmental & Occupational Health
Shannon Millar, Kate Parizeau, Evan D. G. Fraser
JOURNAL OF HUNGER & ENVIRONMENTAL NUTRITION
(2020)
Article
Area Studies
Y. K. Eugenia Kwok, Krishna Bahadur Kc, Jennifer J. Silver, Evan Fraser
ASIA PACIFIC VIEWPOINT
(2020)
Article
Computer Science, Information Systems
Kashan Ahmed, Syed Khaldoon Khurshid, Sadaf Hina
Summary: This paper mainly introduces the construction of the cyber threat intelligence knowledge graph and the information extraction technique. By using joint extraction technique, it solves the problem of traditional techniques becoming ineffective due to the increasing size of CTI data. Experimental results show that this technique outperforms state-of-the-art models in knowledge triple extraction on CTI data and improves the F1 score.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Xinlong He, Yang Xu, Sicong Zhang, Weida Xu, Jiale Yan
Summary: This paper proposes a new membership inference attack method in federated learning, which utilizes data poisoning and sequence prediction confidence. The attack is effective and results in minimal overall model performance degradation.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Tieming Chen, Huan Zeng, Mingqi Lv, Tiantian Zhu
Summary: In this paper, the authors propose a deep learning based dynamic malware detection method called CTIMD, which integrates threat knowledge from CTIs into the learning process of API call sequences with runtime parameters. Experimental results show that CTIMD outperforms existing methods in terms of performance.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Wonwoo Choi, Minjae Seo, Seongman Lee, Brent Byunghoon Kang
Summary: This paper proposes SUM, a backward-edge control flow protection scheme for ARM Cortex-M processors. It combines MPU and the overlooked hardware feature FaultMask to achieve efficient and robust protection. The empirical evaluation shows minimal runtime overhead for the proposed solution.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Liliana Ribeiro, Ines Sousa Guedes, Carla Sofia Cardoso
Summary: Phishing susceptibility is influenced by individual and contextual factors. The study found that individuals who perceive themselves as capable of detecting phishing and those who use online services more frequently are more susceptible to phishing. However, technology competencies and other individual variables do not predict phishing susceptibility.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Wenjie Wang, Yuanhai Shao, Yiju Wang
Summary: In this paper, we investigate the adversarial perturbations of twin support vector machines (TWSVMs) and propose an optimization framework, which provides explicit solutions to increase the interpretability of the conclusion and convenience for calculation.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Snofy D. Dunston, V. Mary Anita Rajam
Summary: This paper proposes a novel adversarial attack technique that can synthesize adversarial images to mislead deep learning models, and also studies interpretability plots. The research findings show that the proposed attack technique influences the interpretability plots, regardless of the success of the attack.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Junchen Li, Guang Cheng, Zongyao Chen, Peng Zhao
Summary: Protocol Reverse Engineering (PRE) is a direct approach for analyzing unknown traffic. This paper proposes a method for clustering unknown traffic based on private protocol labels, and the experimental results demonstrate its advantages on real-world network traffic.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Rafal Kozik, Massimo Ficco, Aleksandra Pawlicka, Marek Pawlicki, Francesco Palmieri, Michal Choras
Summary: The inclusion of Explainability of Artificial Intelligence (xAI) has become a mandatory requirement for designing and implementing reliable, interpretable, and ethical AI solutions. However, it has been shown that xAI can enable successful adversarial attacks in the domain of fake news detection, leading to a decrease in AI security. This paper presents an attack scheme that uses an explainable solution to reshape the structure of the original message, allowing the adversary to manipulate the model's prediction while keeping the message's meaning intact.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Benyuan Yang, Lili Luo, Zhimeng Wang
Summary: Interoperation is widely used in practical industrial applications, but merging local access control policies may lead to security violations. Dealing with these issues in a multidomain environment is critical, but finding the maximum secure interoperation among individual systems poses a challenge due to the large number of entities and access involved.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Binghui Zou, Chunjie Cao, Longjuan Wang, Sizheng Fu, Tonghua Qiao, Jingzhang Sun
Summary: The ongoing struggle between security researchers and malware has led to the exploration of using convolutional neural networks and capsule networks for classification and identification of malware. However, training these networks requires a significant amount of data and parameters, and the research on capsule networks is still in its early stages, posing challenges.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Hongsong Chen, Xingyu Li, Wenmao Liu
Summary: Multivariate time-series anomaly detection is crucial for maintaining normal operation of physical equipment. Recent advances have been made in this field, but two challenges have limited the model's ability to generalize. To address these challenges, a multivariate time-series anomaly detection model consisting of a characterization network and a forecasting network is proposed. Experimental results demonstrate that this method outperforms baseline methods in terms of detection performance and robustness.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Roberto Doriguzzi-Corin, Domenico Siracusa
Summary: This paper discusses the application of federated learning in the field of cybersecurity and proposes an adaptive mechanism-based federated learning solution for DDoS attack detection in dynamic cybersecurity scenarios. Through experiments, it is demonstrated that the proposed solution outperforms state-of-the-art federated learning algorithms in terms of convergence time and accuracy.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Antonio Giovanni Schiavone
Summary: The usage of HTTPS protocol is crucial for secure communication with websites, ensuring the confidentiality, integrity, and authenticity of online data transmissions. The Municipality2HTTPS research project analyzed the implementation of HTTPS in Italian municipalities' websites and identified areas for improvement.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Domna Bilika, Nikoletta Michopoulou, Efthimios Alepis, Constantinos Patsakis
Summary: Voice Assistants (VAs) are widely used in smart devices, but are vulnerable to attacks, as shown by experiments with popular VAs revealing successful attack rates exceeding 30% and statistical variations among vendors, calling for additional countermeasures to protect user information.
COMPUTERS & SECURITY
(2024)
