Article
Computer Science, Hardware & Architecture
Mohamad Amar Irsyad Mohd Aminuddin, Zarul Fitri Zaaba, Azman Samsudin, Faiz Zaki, Nor Badrul Anuar
Summary: This survey paper provides a systematic and thorough review of various website fingerprinting (WF) on Tor techniques. The study finds that most of the reviewed studies make assumptions that limit the practicality of WF on Tor in real-world scenarios. The paper calls for further research and classification of WF on Tor techniques to provide more accurate practical guidelines.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2023)
Article
Computer Science, Information Systems
Xi Xiao, Xiang Zhou, Zhenyu Yang, Le Yu, Bin Zhang, Qixu Liu, Xiapu Luo
Summary: This paper surveys and analyzes existing website fingerprinting (WF) defense schemes. It categorizes WF defenses into four categories and explains their principles and characteristics. The effectiveness of WF defenses is evaluated on a public dataset using a new experimental setting, finding that many defenses are not as effective as claimed. Deployment issues of WF defenses are discussed, and suggestions are provided for researchers and users.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Marco Simioni, Pavel Gladyshev, Babak Habibnia, Paulo Roberto Nunes de Souza
Summary: Anonymity networks, such as Tor and I2P, aim to protect privacy and promote freedom of speech, but they can also be used for criminal activities. A general method for effectively identifying candidate nodes responsible for delivering services in anonymity networks remains an open research problem. This paper describes the infrastructure designed for monitoring the I2P network and how its output can enable such a general method.
FORENSIC SCIENCE INTERNATIONAL-DIGITAL INVESTIGATION
(2021)
Article
Computer Science, Information Systems
Ishan Karunanayake, Nadeem Ahmed, Robert Malaney, Rafiqul Islam, Sanjay K. Jha
Summary: This paper investigates the identification of Onion Service traffic, and finds that modifications to Tor traffic can make Onion Service traffic less distinguishable.
Article
Computer Science, Hardware & Architecture
Qingfeng Tan, Xuebin Wang, Wei Shi, Jian Tang, Zhihong Tian
Summary: This paper presents a new type of attack for deanonymizing user activities in Tor network, which can be used by both AS-level adversaries and Node-level adversaries. By exploiting the occasional failures of censored network and the poor reliability of Tor communication, the adversaries can gain control of the routes and reveal user activity information. The proposed attacks are shown to be effective and scalable in real-world Tor networks through experiments and evaluations.
IEEE-ACM TRANSACTIONS ON NETWORKING
(2022)
Article
Chemistry, Analytical
Xiance Meng, Mangui Liang
Summary: This paper proposes a port-based anonymous communication network (PBACN) that reduces latency and improves anonymity compared to Tor. By using a path construction algorithm and a port-based source routing addressing method, the proposed PBACN achieves a higher level of anonymity while simplifying routing complexity.
Article
Physics, Multidisciplinary
Xiance Meng, Mangui Liang
Summary: As the most popular anonymous communication system, Tor provides anonymous protection for users by sending their messages through a series of relays. However, the use of bandwidth-weighted path selection algorithm results in higher congestion risk for routers with high bandwidth. To address this issue, we propose a circuit construction method with multiple parallel middle relays and a dynamic load allocation method.
Article
Agronomy
Kambiz Mootab Laleh, Majid Ghorbani Javid, Iraj Alahdadi, Elias Soltani, Saeid Soufizadeh, Jose Luis Gonzalez-Andujar
Summary: Diminishing yield gaps is a crucial issue in developing nations. This study evaluated the yield gap of wheat fields using comparative performance analysis techniques and identified contributing factors and potential yield. The results showed a yield gap of 3748 kg/ha, which accounted for 40.23% of the potential yield. Factors such as leaf chlorophyll, irrigation, and soil salinity contributed to the yield gap. Therefore, developing nations can effectively utilize these techniques to increase crop production.
Article
Computer Science, Information Systems
Malak Alfosail, Peter Norris
Summary: This paper discusses how the memory residue of the client affects anonymity when using Tor, analyzing artifacts related to Tor usage through digital forensics tactics. The findings suggest that the Tor browser retains a plethora of details about client activities, potentially compromising user privacy and anonymity.
COMPUTERS & SECURITY
(2021)
Article
Computer Science, Theory & Methods
Javier Pastor-Galindo, Felix Gomez Marmol, Gregorio Martinez Perez
Summary: This study explores methods for acquiring onion network addresses and analyzes various strategies, evaluating their effectiveness and relevance. The results indicate that Tor crawling and repositories are the most commonly used methods, while relay injection, repositories, and Tor crawling are the most effective approaches. The study also reveals that previous research only explored a small portion of the Tor network and highlights the challenges for future studies in providing more representative datasets for dark web exploration.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2023)
Article
Computer Science, Information Systems
Kanika Goel, Arthur H. M. Ter Hofstede
Summary: NoSQL databases have disrupted the database market and become increasingly relevant in the era of big data due to their ability to meet demands for performance, availability, scalability, and storage solutions. However, compromises have been made in terms of security and privacy, leading to growing awareness and unease within the community. This paper systematically examines privacy weaknesses in NoSQL databases and provides a repository of knowledge for future research in this area.
Article
Computer Science, Information Systems
Mahdieh Zabihimayvan, Derek Doran
Summary: This research addresses the information leakage caused by links from Tor hidden services to the surface web and evaluates the impact of these links on Tor's network. The results reveal that a majority of Tor hidden services have at least one link to the surface web, and Tor directories play a significant role in network communication and information dissemination.
INTERNATIONAL JOURNAL OF INFORMATION SECURITY
(2022)
Article
Telecommunications
Syed Jawad Hussain, Muhammad Irfan, N. Z. Jhanjhi, Khalid Hussain, Mamoona Humayun
Summary: The performance of devices used for collecting sensitive medical information has significantly improved over the years. However, security and privacy concerns have also become greater, with various techniques being applied to secure data in Wireless Body Area Networks. While the latest authentication schemes provide privacy and security, they come with a tradeoff of increased time and processing cost due to the limited computation capacity of WBAN devices.
WIRELESS PERSONAL COMMUNICATIONS
(2021)
Article
Mathematics
Huwei Liu, Fan Wang, Junhui Zhao, Jianglong Yang, Chunqiao Tan, Li Zhou
Summary: This paper investigates the order picking problem with multiple picking locations and proposes the Cuckoo Search algorithm to optimize the picking walking distance. Experimental results show that the Mixed-type path strategy is superior to the Return-type and S-type path strategies in a Chevron layout warehouse.
Article
Computer Science, Information Systems
Lamiaa Basyoni, Aiman Erbad, Mashael Alsabah, Noora Fetais, Amr Mohamed, Mohsen Guizani
Summary: The internet has become the fastest way to access information, but it also poses challenges to users' privacy. Anonymity networks like Tor have been developed to address this issue, with new designs like QuicTor showing significant performance improvements without compromising user anonymity.
Article
Biology
Adnan Qayyum, Waqas Sultani, Fahad Shamshad, Rashid Tufail, Junaid Qadir
Summary: This paper proposes a single-shot deep image prior (DIP)-based approach for enhancing retinal images without requiring training data. The method is time and memory-efficient, making it suitable for resource-constrained environments. The proposed approach is evaluated quantitatively on multiple datasets and is found to be effective.
COMPUTERS IN BIOLOGY AND MEDICINE
(2022)
Article
Biology
Khansa Rasheed, Adnan Qayyum, Mohammed Ghaly, Ala Al-Fuqaha, Adeel Razi, Junaid Qadir
Summary: With the increasing use of machine learning and deep learning in healthcare, the issues of liability, trust, and interpretability of model outputs are becoming more important. The black-box nature of these models hinders their clinical utilization, requiring explanations of model decisions to gain trust from clinicians and patients. The development of explainable machine learning improves model transparency and reliability, and can address ethical problems arising from the use of machine learning in healthcare.
COMPUTERS IN BIOLOGY AND MEDICINE
(2022)
Article
Engineering, Electrical & Electronic
Hafsa Benaddi, Khalil Ibrahimi, Abderrahim Benslimane, Mohammed Jouhari, Junaid Qadir
Summary: This paper proposes a DRL-based IDS for network traffics using MDP and analyzes the IDS behavior through modeling the interaction between the IDS and attacker players. The proposed DRL-IDS outperforms existing models in terms of detection rate, accuracy, and false alarms reduction.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2022)
Review
Computer Science, Artificial Intelligence
Muhammad Huzaifa Bashir, Aqil M. Azmi, Haq Nawaz, Wajdi Zaghouani, Mona Diab, Ala Al-Fuqaha, Junaid Qadir
Summary: The Qur'an is a sacred religious text read and followed by almost two billion Muslims worldwide. With the popularity of Islam, Arabic became a widely spoken language. Recently, there has been a growing interest in studying religious texts, including the Qur'an, using computational and natural language processing techniques. This paper surveys the efforts in Qur'anic NLP, covering automated morphological analysis, correction of Qur'anic recitation, and outlines future research directions in this field.
ARTIFICIAL INTELLIGENCE REVIEW
(2023)
Article
Computer Science, Information Systems
Muhammad Atif Butt, Adnan Qayyum, Hassan Ali, Ala Al-Fuqaha, Junaid Qadir
Summary: The use of AI at the edge is transforming human lives, but the security and trustworthiness of edge AI applications are not foolproof or ethical. This paper analyzes the application of edge AI through a human-centric perspective, discussing the challenges and possible solutions in terms of privacy, trustworthiness, robustness, and security. A case study on human facial emotion recognition is presented to illustrate the issues caused by widely used input quantization.
COMPUTERS & SECURITY
(2023)
Article
Telecommunications
Wajid Rafique, Abdelhakim Senhaji Hafid, Junaid Qadir
Summary: Smart cities are urban areas that use ICT to efficiently and sustainably solve city problems. Within ICT, Intent-aware Recommender Systems (IARS) play a crucial role in filtering information and assisting in decision-making in smart city platforms based on user demands. This paper provides a detailed literature survey of IARS and its application in developing smart city services.
TRANSACTIONS ON EMERGING TELECOMMUNICATIONS TECHNOLOGIES
(2023)
Article
Social Issues
Osama Nasir, Rana Tallal Javed, Shivam Gupta, Ricardo Vinuesa, Junaid Qadir
Summary: Artificial Intelligence (AI) should aim at benefiting society by supporting all 17 UN Sustainable Development Goals (SDGs). This study provides insight into AI in terms of curricula, frameworks, projects, and research papers. The findings reveal an imbalance in the coverage of SDGs, with SDG 9 having the highest representation and SDGs 5, 6, 14, and 15 having the lowest representation. This suggests a focus on economic growth while neglecting important societal and environmental issues.
TECHNOLOGY IN SOCIETY
(2023)
Correction
Computer Science, Artificial Intelligence
Muhammad Huzaifa Bashir, Aqil M. Azmi, Haq Nawaz, Wajdi Zaghouani, Mona Diab, Ala Al-Fuqaha, Junaid Qadir
ARTIFICIAL INTELLIGENCE REVIEW
(2023)
Article
Biology
Nazish Khalid, Adnan Qayyum, Muhammad Bilal, Ala Al-Fuqaha, Junaid Qadir
Summary: There is a growing interest in translating AI research into clinically-validated applications for healthcare services. However, the widespread adoption of AI-based applications faces barriers such as non-standardized medical records, limited availability of datasets, and privacy concerns. This study provides a summary of state-of-the-art privacy-preserving techniques for AI-based healthcare applications.
COMPUTERS IN BIOLOGY AND MEDICINE
(2023)
Editorial Material
Education & Educational Research
Aditya Johri, Andrew S. Katz, Junaid Qadir, Ashish Hingle
JOURNAL OF ENGINEERING EDUCATION
(2023)
Article
Chemistry, Analytical
Azka Rehman, Muhammad Usman, Abdullah Shahid, Siddique Latif, Junaid Qadir
Summary: Brain tumors are highly deadly and their manual segmentation is time-consuming and prone to errors. This study proposes an automatic method called SDS-MSA-Net for brain tumor segmentation using a multi-scale attention network and novel selective deep supervision mechanisms. The method extracts global and local features from 3D and 2D inputs, filters out redundant information, and produces segmentations of the whole, enhanced, and core tumor regions. Evaluation on the BraTS2020 dataset demonstrates improved performance, especially in segmenting the core and enhancing tumor regions, validating the effectiveness of the proposed approach.
Article
Computer Science, Artificial Intelligence
Siddique Latif, Rajib Rana, Sara Khalifa, Raja Jurdak, Junaid Qadir, Bjorn Schuller
Summary: Traditionally, speech emotion recognition (SER) relied on manual feature engineering, but this approach requires significant manual effort and impedes innovation. Representation learning techniques have been adopted to automatically learn intermediate representations without manual engineering, leading to improved SER performance and rapid innovation. Deep learning further enhances the effectiveness of representation learning by enabling the automatic learning of hierarchical representations. This article presents a comprehensive survey on deep representation learning for SER, highlighting techniques, challenges, and future research areas.
IEEE TRANSACTIONS ON AFFECTIVE COMPUTING
(2023)
Review
Computer Science, Information Systems
Raihan Ur Rasool, Hafiz Farooq Ahmad, Wajid Rafique, Adnan Qayyum, Junaid Qadir, Zahid Anwar
Summary: The field of quantum computing has rapidly developed in recent years and attracted significant attention from academia and industry. Quantum computing has the potential to process information in fundamentally different ways, enabling previously unattainable computational capabilities. However, its impact on healthcare remains largely unexplored. This survey presents a systematic analysis of quantum computing's capabilities in enhancing healthcare, focusing on areas such as drug discovery, personalized medicine, DNA sequencing, medical imaging, and operational optimization.
Article
Computer Science, Information Systems
Hassan Ali, Muhammad Suleman Khan, Amer AlGhadhban, Meshari Alazmi, Ahmed Alzamil, Khaled Al-utaibi, Junaid Qadir
Summary: Deep learning algorithms have shown great performance in various NLP tasks, but they are susceptible to adversarial attacks. This paper proposes an unsupervised detection method for identifying adversarial inputs to NLP classifiers. Experimental results demonstrate that the proposed method can significantly reduce the success rate of different attacks.
COMPUTERS & SECURITY
(2023)
Article
Computer Science, Artificial Intelligence
Adnan Qayyum, Inaam Ilahi, Fahad Shamshad, Farid Boussaid, Mohammed Bennamoun, Junaid Qadir
Summary: In recent years, deep learning techniques have made significant progress in solving inverse imaging problems, outperforming hand-crafted approaches. Deep learning models make use of large datasets to predict unknown solutions to the inverse problems. A new paradigm called untrained neural network prior (UNNP) has been proposed, which utilizes a single image for deep model training in various inverse tasks. This article comprehensively reviews studies on UNNP and its applications for different tasks, highlighting open research problems that require further investigation.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2023)
Article
Computer Science, Hardware & Architecture
Zihang Zhen, Xiaoding Wang, Hui Lin, Sahil Garg, Prabhat Kumar, M. Shamim Hossain
Summary: In this paper, a blockchain architecture based on dynamic state sharding (DSSBD) is proposed to solve the problems caused by cross-shard transactions and reconfiguration. By utilizing deep reinforcement learning, the number of shards, block spacing, and block size can be dynamically adjusted to improve the performance of the blockchain. The experimental results show that the crowdsourcing system with DSSBD has better performance in terms of throughput, latency, balancing, cross-shard transaction proportion, and node reconfiguration proportion, while ensuring security.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Gabriel F. C. de Queiroz, Jose F. de Rezende, Valmir C. Barbosa
Summary: Multi-access Edge Computing (MEC) is a technology that enables faster task processing at the network edge by deploying servers closer to end users. This paper proposes the FlexDO algorithm to solve the DAG application partitioning and offloading problem, and compares it with other solutions to demonstrate its superior performance in various test scenarios.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Shahid Latif, Wadii Boulila, Anis Koubaa, Zhuo Zou, Jawad Ahmad
Summary: In the field of Industrial Internet of Things (IIoT), networks are increasingly vulnerable to cyberattacks. This research introduces an optimized Intrusion Detection System based on Deep Transfer Learning (DTL) for heterogeneous IIoT networks, combining Convolutional Neural Networks (CNNs), Genetic Algorithms (GA), and ensemble techniques. Through rigorous evaluation, the framework achieves exceptional performance and accurate detection of various cyberattacks.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Rongji Liao, Yuan Zhang, Jinyao Yan, Yang Cai, Narisu Tao
Summary: This paper proposes a joint control approach called STOP to guarantee user-perceived deadline using curriculum-guided deep reinforcement learning. Experimental results show that the STOP scheme achieves a significantly higher average arrival ratio in NS-3.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Miguel Rodriguez-Perez, Sergio Herreria-Alonso, J. Carlos Lopez-Ardao, Raul F. Rodriguez-Rubio
Summary: This paper presents an implementation of an active queue management (AQM) algorithm for the Named-Data Networking (NDN) architecture and its application in congestion control protocols. By utilizing the congestion mark field in NDN packets, information about each transmission queue is encoded to achieve a scalable AQM solution.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Angel Canete, Mercedes Amor, Lidia Fuentes
Summary: This paper proposes an energy-aware placement of service function chains of Virtual Network Functions (VNFs) and a resource-allocation solution for heterogeneous edge infrastructures. The solution has been integrated with an open source management and orchestration project and has been successfully applied to augmented reality services, achieving significant reduction in power consumption and ensuring quality of service compliance.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Sachin Kadam, Kaustubh S. Bhargao, Gaurav S. Kasbekar
Summary: This paper discusses the problem of estimating the node cardinality of each node type in a heterogeneous wireless network. Two schemes, HSRC-M1 and HSRC-M2, are proposed to rapidly estimate the number of nodes of each type. The accuracy and efficiency of these schemes are proven through mathematical analysis and simulation experiments.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Jean Nestor M. Dahj, Kingsley A. Ogudo, Leandro Boonzaaier
Summary: The launch of commercial 5G networks has opened up opportunities for heavy data users and highspeed applications, but traditional monitoring and evaluation techniques have limitations in the 5G networks. This paper presents a cost-effective hybrid analytical approach for detecting and evaluating user experience in real-time 5G networks, using statistical methods to calculate the user quality index.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Ali Nauman, Haya Mesfer Alshahrani, Nadhem Nemri, Kamal M. Othman, Nojood O. Aljehane, Mashael Maashi, Ashit Kumar Dutta, Mohammed Assiri, Wali Ullah Khan
Summary: The integration of terrestrial and satellite wireless communication networks offers a practical solution to enhance network coverage, connectivity, and cost-effectiveness. This study introduces a resource allocation framework that leverages local cache pool deployments and non-orthogonal multiple access (NOMA) to improve energy efficiency. Through the use of a multi-agent enabled deep deterministic policy gradient algorithm (MADDPG), the proposed approach optimizes user association, cache design, and transmission power control, resulting in enhanced energy efficiency and reduced time delays compared to existing methods.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Wu Chen, Jiayi Zhu, Jiajia Liu, Hongzhi Guo
Summary: With advancements in technology, large-scale drone swarms will be widely used in commercial and military fields. Current application methods are mainly divided into autonomous methods and controlled methods. This paper proposes a new framework for global coordination through local interaction.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Peiying Zhang, Zhihu Luo, Neeraj Kumar, Mohsen Guizani, Hongxia Zhang, Jian Wang
Summary: With the development of Industry 5.0, the demand for network access devices is increasing, especially in areas such as financial transactions, drone control, and telemedicine where low latency is crucial. However, traditional network architectures limit the construction of low-latency networks due to the tight coupling of control and data forwarding functions. To overcome this problem, researchers propose a constraint escalation virtual network embedding algorithm assisted by Graph Convolutional Networks (GCN), which automatically extracts network features and accelerates the learning process to improve network performance.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Review
Computer Science, Hardware & Architecture
P. Anitha, H. S. Vimala, J. Shreyas
Summary: Congestion control is crucial for maintaining network stability, reliability, and performance in IoT. It ensures that critical applications can operate seamlessly and that IoT devices can communicate efficiently without overwhelming the network. Congestion control algorithms ensure that the network operates within its capacity, preventing network overload and maintaining network performance.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Shunmugapriya Ramanathan, Abhishek Bhattacharyya, Koteswararao Kondepu, Andrea Fumagalli
Summary: This article presents an experiment that achieves live migration of a containerized 5G Central Unit module using modified open-source migration software. By comparing different migration techniques, it is found that the hybrid migration technique can reduce end-user service recovery time by 36% compared to the traditional cold migration technique.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Fatma Foad Ashrif, Elankovan A. Sundararajan, Rami Ahmad, Mohammad Kamrul Hasan, Elaheh Yadegaridehkordi
Summary: This article introduces the development and current status of authentication protocols in 6LoWPAN, and proposes an innovative perspective to fill the research gap. The article comprehensively surveys and evaluates AKA protocols, analyzing their suitability in wireless sensor networks and the Internet of Things, and proposes future research directions and issues.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Pranjal Kumar Nandi, Md. Rejaul Islam Reaj, Sujan Sarker, Md. Abdur Razzaque, Md. Mamun-or-Rashid, Palash Roy
Summary: This paper proposes a task offloading policy for IoT devices to a mobile edge computing system, aiming to balance device utility and execution cost. A meta heuristic approach is developed to solve the offloading problem, and the results show its potential in terms of task execution latency, energy consumption, utility per unit cost, and task drop rate.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
