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Multi-Think Transformer for Enhancing Emotional Health ACM Trans. Internet Technol. (IF 5.3) Pub Date : 2024-03-18 Jiarong Wang, Jiaji Wu, Shaohong Chen, Xiangyu Han, Mingzhou Tan, Jianguo Yu
The smart healthcare system not only focuses on physical health but also on emotional health. Music therapy, as a non-pharmacological treatment method, has been widely used in clinical treatment, but music selection and generation still require manual intervention. AI music generation technology can assist people in relieving stress and providing more personalized and efficient music therapy support
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Market Manipulation of Cryptocurrencies: Evidence from Social Media and Transaction Data ACM Trans. Internet Technol. (IF 5.3) Pub Date : 2024-03-18 Wen Li, Lingfeng Bao, Jiachi Chen, John Grundy, Xin Xia, Xiaohu Yang
The cryptocurrency market cap has experienced a great increase in recent years. However, large price fluctuations demonstrate the need for governance structures and identify whether there are market manipulations. In this article, we conduct three analyses—social media data analysis, blockchain data analysis, and price bubble analysis—to investigate whether market manipulation exists on Bitcoin, Ethereum
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Distributed Computation Offloading and Power Control for UAV-Enabled Internet of Medical Things ACM Trans. Internet Technol. (IF 5.3) Pub Date : 2024-03-16 Jiakun Gao, Xiaolong Xu, Lianyong Qi, Wanchun Dou, Xiaoyu Xia, Xiaokang Zhou
The advancement of the Internet of Medical Things (IoMT) has led to the emergence of various health and emotion care services, e.g., health monitoring. To cater to increasing computational requirements of IoMT services, Mobile Edge Computing (MEC) has emerged as an indispensable technology in smart health. Benefiting from the cost-effectiveness of deployment, unmanned aerial vehicles (UAVs) equipped
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Audio-Visual Event Localization using Multi-task Hybrid Attention Networks for Smart Healthcare Systems ACM Trans. Internet Technol. (IF 5.3) Pub Date : 2024-03-16 Han Liang, Jincai Chen, Fazlullah Khan, Gautam Srivastava, Jiangfeng Zeng
Human perception heavily relies on two primary senses: vision and hearing, which are closely inter-connected and capable of complementing each other. Consequently, various multimodal learning tasks have emerged, with audio-visual event localization (AVEL) being a prominent example. AVEL is a popular task within the realm of multimodal learning, with the primary objective of identifying the presence
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Open Set Dandelion Network for IoT Intrusion Detection ACM Trans. Internet Technol. (IF 5.3) Pub Date : 2024-02-22 Jiashu Wu, Hao Dai, Kenneth B. Kent, Jerome Yen, Chengzhong Xu, Yang Wang
As Internet of Things devices become widely used in the real-world, it is crucial to protect them from malicious intrusions. However, the data scarcity of IoT limits the applicability of traditional intrusion detection methods, which are highly data-dependent. To address this, in this article, we propose the Open-Set Dandelion Network (OSDN) based on unsupervised heterogeneous domain adaptation in
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ADTO: A Trust Active Detecting-based Task Offloading Scheme in Edge Computing for Internet of Things ACM Trans. Internet Technol. (IF 5.3) Pub Date : 2024-02-22 Xuezheng Yang, Zhiwen Zeng, Anfeng Liu, Neal N. Xiong, Shaobo Zhang
In edge computing, Internet of Things devices with weak computing power offload tasks to nearby edge servers for execution, so the task completion time can be reduced and delay-sensitive tasks can be facilitated. However, if the task is offloaded to malicious edge servers, then the system will suffer losses. Therefore, it is significant to identify the trusted edge servers and offload tasks to trusted
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SDN-enabled Quantized LQR for Smart Traffic Light Controller to Optimize Congestion ACM Trans. Internet Technol. (IF 5.3) Pub Date : 2024-02-22 Anuj Sachan, Neetesh Kumar
Existing intersection management systems, in urban cities, lack in meeting the current requirements of self-configuration, lightweight computing, and software-defined control, which are necessarily required for congested road-lane networks. To satisfy these requirements, this work proposes effective, scalable, multi-input and multi-output, and congestion prevention-enabled intersection management system
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DxHash: A Memory-saving Consistent Hashing Algorithm ACM Trans. Internet Technol. (IF 5.3) Pub Date : 2024-02-22 Chao Dong, Fang Wang, Dan Feng
Consistent Hashing (CH) algorithms are widely adopted in networks and distributed systems for their ability to achieve load balancing and minimize disruptions. However, the rise of the Internet of Things (IoT) has introduced new challenges for existing CH algorithms, characterized by high memory usage and update overhead. This article presents DxHash, a novel CH algorithm based on repeated pseudo-random
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A Novel Cross-Domain Recommendation with Evolution Learning ACM Trans. Internet Technol. (IF 5.3) Pub Date : 2024-02-22 Yi-Cheng Chen, Wang-Chien Lee
In this “info-plosion” era, recommendation systems (or recommenders) play a significant role in finding interesting items in the surge of online digital activities and e-commerce. Several techniques have been widely applied for recommendation systems, but the cold-start and sparsity problems remain a major challenge. The cold-start problem occurs when generating recommendations for new users and items
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AI-assisted Blockchain-enabled Smart and Secure E-prescription Management Framework ACM Trans. Internet Technol. (IF 5.3) Pub Date : 2024-01-23 Siva Sai, Vinay Chamola
Traditional medical prescriptions based on physical paper-based documents are prone to manipulation, errors, and unauthorized reproduction due to their format. Addressing the limitations of the traditional prescription system, e-prescription systems have been introduced in several countries. However, e-prescription systems lead to several concerns like the risk of privacy loss, the problem of double-spending
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Atrial Fibrillation Detection from Compressed ECG Measurements for Wireless Body Sensor Network ACM Trans. Internet Technol. (IF 5.3) Pub Date : 2024-01-10 Yongyong Chen, Junxin Chen, Shuang Sun, Jingyong Su, Qiankun Li, Zhihan Lyu
Recent years have witnessed an increasing prevalence of wearable devices in the public, where atrial fibrillation (AF) detection is a popular application in these devices. Generally, AF detection is performed on cloud whereas this paper describes an on-device AF detection method. Technically, compressed sensing (CS) is first used for electrocardiograph (ECG) acquisition. Then QRS detection is proposed
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Federated Learning-based Information Leakage Risk Detection for Secure Medical Internet of Things ACM Trans. Internet Technol. (IF 5.3) Pub Date : 2024-01-09 Tingting Wang, Tao Tang, Zhen Cai, Kai Fang, Jinyu Tian, Jianqing Li, Wei Wang, Feng Xia
The Medical Internet of Things (MIoT) requires extreme information and communication security, particularly for remote consultation systems. MIoT’s integration of physical and computational components creates a seamless network of medical devices providing high-quality care via continuous monitoring and treatment. However, traditional security methods such as cryptography cannot prevent privacy compromise
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EtherShield: Time-interval Analysis for Detection of Malicious Behavior on Ethereum ACM Trans. Internet Technol. (IF 5.3) Pub Date : 2024-01-08 Bofeng Pan, Natalia Stakhanova, Zhongwen Zhu
Advances in blockchain technology have attracted significant attention across the world. The practical blockchain applications emerging in various domains, ranging from finance, healthcare, and entertainment, have quickly become attractive targets for adversaries. The novelty of the technology coupled with the high degree of anonymity it provides made malicious activities even less visible in the blockchain
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Positional Encoding-based Resident Identification in Multi-resident Smart Homes ACM Trans. Internet Technol. (IF 5.3) Pub Date : 2023-12-22 Zhiyi Song, Dipankar Chaki, Abdallah Lakhdari, Athman Bouguettaya
We propose a novel resident identification framework to identify residents in a multi-occupant smart environment. The proposed framework employs a feature extraction model based on the concepts of positional encoding. The feature extraction model considers the locations of homes as a graph. We design a novel algorithm to build such graphs from layout maps of smart environments. The Node2Vec algorithm
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ML-Based Identification of Neuromuscular Disorder Using EMG Signals for Emotional Health Application ACM Trans. Internet Technol. (IF 5.3) Pub Date : 2023-12-14 Abdelouahad Achmamad, Mohamed Elfezazi, Abdellah Chehri, Imran Ahmed, Atman Jbari, Rachid Saadane
Abstract: The electromyogram (EMG), also known as an EMG, is used to assess nerve impulses in motor nerves, sensory nerves, and muscles. EMS is a versatile tool used in various biomedical applications. It is commonly employed to determine physical health, but it also finds utility in evaluating emotional well-being, such as through facial electromyography. Classification of EMG signals has attracted
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An IoT and Deep Learning-Based Smart Healthcare Framework for Thyroid Cancer Detection ACM Trans. Internet Technol. (IF 5.3) Pub Date : 2023-12-11 Rohit Sharma, Gautam Kumar Mahanti, Chinmay Chakraborty, Ganapati Panda, Adyasha Rath
A world of healthcare possibilities has been opened with the development of the Internet of Medical Things and related machine learning, deep learning, and artificial intelligence approaches. It has a broad range of uses: when linked to the Internet, common medical equipment and sensors may gather important data; deep learning and artificial intelligence algorithms use this data to understand symptoms
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A Softwarized Intrusion Detection System for IoT-Enabled Smart Healthcare System ACM Trans. Internet Technol. (IF 5.3) Pub Date : 2023-11-27 Danish Javeed, Tianhan Gao, Muhammad Shahid Saeed, Prabhat Kumar, Randhir Kumar, Alireza Jolfaei
The Internet of Things-enabled Smart Healthcare System (IoT-SHS) is a networked infrastructure of intelligent wearables, software applications, health systems, and services that continuously monitors and transmits patient-sensitive data using an open wireless channel. The conventional security mechanisms are unsuitable for detecting attacks in the dynamic IoT-SHS context due to resource limitations
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Tolerance Analysis of Cyber-Manufacturing Systems to Cascading Failures ACM Trans. Internet Technol. (IF 5.3) Pub Date : 2023-11-17 Xiuwen Fu, Pasquale Pace, Gianluca Aloi, Antonio Guerrieri, Wenfeng Li, Giancarlo Fortino
In practical cyber-manufacturing systems (CMS), the node component is the forwarder of information and the provider of services. This dual role makes the whole system have the typical physical-services interaction characteristic, making CMS more vulnerable to cascading failures than general manufacturing systems. In this work, in order to reasonably characterize the cascading process of CMS, we first
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Digital Twin of Intelligent Small Surface Defect Detection with Cyber-manufacturing Systems ACM Trans. Internet Technol. (IF 5.3) Pub Date : 2023-11-17 Yirui Wu, Hao Cao, Guoqiang Yang, Tong Lu, Shaohua Wan
With the remarkable technological development in cyber-physical systems, industry 4.0 has evolved by use of a significant concept named digital twin (DT). However, it is still difficult to construct a relationship between twin simulation and a real scenario considering dynamic variations, especially when dealing with small surface defect detection tasks with high performance and computation resource
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Malicious Account Identification in Social Network Platforms ACM Trans. Internet Technol. (IF 5.3) Pub Date : 2023-11-17 Loredana Caruccio, Gaetano Cimino, Stefano Cirillo, Domenico Desiato, Giuseppe Polese, Genoveffa Tortora
Today, people of all ages are increasingly using Web platforms for social interaction. Consequently, many tasks are being transferred over social networks, like advertisements, political communications, and so on, yielding vast volumes of data disseminated over the network. However, this raises several concerns regarding the truthfulness of such data and the accounts generating them. Malicious users
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Unpaired Self-supervised Learning for Industrial Cyber-Manufacturing Spectrum Blind Deconvolution ACM Trans. Internet Technol. (IF 5.3) Pub Date : 2023-11-17 Lizhen Deng, Guoxia Xu, Jiaqi Pi, Hu Zhu, Xiaokang Zhou
Cyber-Manufacturing combines industrial big data with intelligent analysis to find and understand the intangible problems in decision-making, which requires a systematic method to deal with rich signal data. With the development of spectral detection and photoelectric imaging technology, spectral blind deconvolution has achieved remarkable results. However, spectral processing is limited by one-dimensional
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Offering Two-way Privacy for Evolved Purchase Inquiries ACM Trans. Internet Technol. (IF 5.3) Pub Date : 2023-11-17 Jan Pennekamp, Markus Dahlmanns, Frederik Fuhrmann, Timo Heutmann, Alexander Kreppein, Dennis Grunert, Christoph Lange, Robert H. Schmitt, Klaus Wehrle
Dynamic and flexible business relationships are expected to become more important in the future to accommodate specialized change requests or small-batch production. Today, buyers and sellers must disclose sensitive information on products upfront before the actual manufacturing. However, without a trust relation, this situation is precarious for the involved companies as they fear for their competitiveness
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Exploring the Potential of Cyber Manufacturing System in the Digital Age ACM Trans. Internet Technol. (IF 5.3) Pub Date : 2023-11-17 Usman Ahmed, Jerry Chun-Wei Lin, Gautam Srivastava
Cyber-manufacturing Systems (CMS) have been growing in popularity, transitioning from conventional manufacturing to an innovative paradigm that emphasizes innovation, automation, better customer service, and intelligent systems. A new manufacturing model can improve efficiency and productivity, and provide better customer service and response times. In addition, it may revolutionize the way products
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Collaborative Hotspot Data Collection with Drones and 5G Edge Computing in Smart City ACM Trans. Internet Technol. (IF 5.3) Pub Date : 2023-11-17 Pei-Cheng Song, Jeng-Shyang Pan, Han-Chieh Chao, Shu-Chuan Chu
The construction and governance of smart cities require the collaboration of different systems and different regions. How to realize the monitoring of abnormal hot spots through the collaboration of subsystems with limited resources is related to the stability and efficiency of the city. This work constructs a hot data processing framework for drones and 5G edge computing infrastructure, as well as
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Providing Realtime Support for Containerized Edge Services ACM Trans. Internet Technol. (IF 5.3) Pub Date : 2023-11-17 Wenzhao Zhang, Yi Gao, Wei Dong
Containers have emerged as a popular technology for edge computing platforms. Although there are varieties of container orchestration frameworks, e.g., Kubernetes to provide high-reliable services for cloud infrastructure, providing real-time support at the containerized edge systems (CESs) remains a challenge. In this paper, we propose EdgeMan, a holistic edge service management framework for CESs
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Polarized Communities Search via Co-guided Random Walk in Attributed Signed Networks ACM Trans. Internet Technol. (IF 5.3) Pub Date : 2023-11-17 Fanyi Yang, Huifang Ma, Cairui Yan, Zhixin Li, Liang Chang
Polarized communities search aims at locating query-dependent communities, in which mostly nodes within each community form intensive positive connections, while mostly nodes across two communities are connected by negative links. Current approaches towards polarized communities search typically model the network topology, while the key factor of node, i.e., the attributes, are largely ignored. Existing
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UNION: Fault-tolerant Cooperative Computing in Opportunistic Mobile Edge Cloud ACM Trans. Internet Technol. (IF 5.3) Pub Date : 2023-11-17 Wenhua Xiao, Xudong Fang, Bixin Liu, Ji Wang, Xiaomin Zhu
Opportunistic Mobile Edge Cloud in which opportunistically connected mobile devices run in a cooperative way to augment the capability of a single device has become a timely and essential topic due to its widespread prospect under resource-constrained scenarios (e.g., disaster rescue). Because of the mobility of devices and the uncertainty of environments, it is inevitable that failures occur among
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Designing and Developing a Weed Detection Model for California Thistle ACM Trans. Internet Technol. (IF 5.3) Pub Date : 2023-08-21 Hossein Chegini, Fernando Beltran, Aniket Mahanti
With a great percentage of farms in New Zealand as pastures, they are mainly important in contributing to the milk and meat industries. Pasture quality is highly affected by weeds. Weeds grow fast and invade pastures by seed pollination. They consume the nutrients, water, and other minerals, and once they are bitter, cattle do not eat them. Therefore, dairy farmers have to allocate a significant portion
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Three-tier Storage Framework Based on TBchain and IPFS for Protecting IoT Security and Privacy ACM Trans. Internet Technol. (IF 5.3) Pub Date : 2023-08-21 Ying Li, Yaxin Yu, Xingwei Wang
Recently, most of the Internet of things (IoT) infrastructures are highly centralized with single points of failure, which results in serious security and privacy issues of IoT data. Fortunately, blockchain technique can provide a decentralized and secure IoT framework to deal with security issues based on the characteristics of decentralization, non-tampering, openness, transparency, and traceability
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A Blockchain-Based Access Control Scheme for Zero Trust Cross-Organizational Data Sharing ACM Trans. Internet Technol. (IF 5.3) Pub Date : 2023-08-21 Keke Gai, Yufeng She, Liehuang Zhu, Kim-Kwang Raymond Choo, Zhiguo Wan
Multi-organization data sharing is becoming increasingly prevalent due to the interconnectivity of systems and the need for collaboration across organizations (e.g., exchange of data in a supply chain involving multiple upstream and downstream vendors). There are, however, data security concerns due to lack of trust between organizations that may be located in jurisdictions with varying security and
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BACKM-EHA: A Novel Blockchain-enabled Security Solution for IoMT-based E-healthcare Applications ACM Trans. Internet Technol. (IF 5.3) Pub Date : 2023-08-21 Mohammad Wazid, Prosanta Gope
E-health is the use of information and communication technology (ICT) for the healthcare-related services. It uses various types of digital technologies and telecommunications, such as computers, sensing devices, Internet, and mobile devices to deliver medical services. Internet of Medical Things (IoMT) is a communication environment optimized for low-power devices (for example, health sensors and
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V-Gas: Generating High Gas Consumption Inputs to Avoid Out-of-Gas Vulnerability ACM Trans. Internet Technol. (IF 5.3) Pub Date : 2023-08-21 Fuchen Ma, Meng Ren, Fu Ying, Wanting Sun, Houbing Song, Heyuan Shi, Yu Jiang, Huizhong Li
Out-of-gas errors occur when smart contract programs are provided with inputs that cause excessive gas consumption and which will be easily exploited to perform Denial-of-Service attacks. Various approaches have been proposed to estimate the gas limit of a function in smart contracts to avoid such error. However, underestimation often occurs when the contract is complex In this work, we propose V-Gas
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A Highly Compatible Verification Framework with Minimal Upgrades to Secure an Existing Edge Network ACM Trans. Internet Technol. (IF 5.3) Pub Date : 2023-08-21 Zhenyu Li, Yong Ding, Honghao Gao, Bo Qu, Yujue Wang, Jun Li
Edge networks are providing services for an increasing number of companies, and they can be used for communication between edge devices and edge gateways. However, the performance of edge devices varies greatly, and it is not easy to upgrade low-performance edge devices. Therefore, cyber attackers can use the vulnerability of edge devices to implement advanced persistent threat attacks. This article
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S-BDS: An Effective Blockchain-based Data Storage Scheme in Zero-Trust IoT ACM Trans. Internet Technol. (IF 5.3) Pub Date : 2023-08-21 Jin Wang, Jiahao Chen, Neal Xiong, Osama Alfarraj, Amr Tolba, Yongjun Ren
With the development of the Internet of Things (IoT), a large-scale, heterogeneous, and dynamic distributed network has been formed among IoT devices. There is an extreme need to establish a trust mechanism between devices, and blockchain can provide a zero-trust security framework for IoT. However, the efficiency of the blockchain is far from meeting the application requirements of the IoT, which
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Securing Low-Power Blockchain-enabled IoT Devices against Energy Depletion Attack ACM Trans. Internet Technol. (IF 5.3) Pub Date : 2023-08-21 Amjad Alsirhani, Muhammad Ali Khan, Abdullah Alomari, Sauda Maryam, Aiman Younas, Muddesar Iqbal, Muhammad Hameed Siqqidi, Amjad Ali
Blockchain-enabled Internet of Things (IoT) envisions a world with rapid development and implementations to change our everyday lives based on smart devices. These devices are attached to the internet that can communicate with each other without human interference. A well-known wireless network in blockchain-enabled IoT frameworks is the Low Power and Lossy Network (LLN) that uses a novel protocol
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Privacy-Aware Traffic Flow Prediction Based on Multi-Party Sensor Data with Zero Trust in Smart City ACM Trans. Internet Technol. (IF 5.3) Pub Date : 2023-08-21 Fan Wang, Guangshun Li, Yilei Wang, Wajid Rafique, Mohammad R. Khosravi, Guanfeng Liu, Yuwen Liu, Lianyong Qi
With the continuous increment of city volume and size, a number of traffic-related urban units (e.g., vehicles, roads, buildings, etc.) are emerging rapidly, which plays a heavy burden on the scientific traffic control of smart cities. In this situation, it is becoming a necessity to utilize the sensor data from massive cameras deployed at city crossings for accurate traffic flow prediction. However
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i-DarkVec: Incremental Embeddings for Darknet Traffic Analysis ACM Trans. Internet Technol. (IF 5.3) Pub Date : 2023-08-21 Luca Gioacchini, Luca Vassio, Marco Mellia, Idilio Drago, Zied Ben Houidi, Dario Rossi
Darknets are probes listening to traffic reaching IP addresses that host no services. Traffic reaching a darknet results from the actions of internet scanners, botnets, and possibly misconfigured hosts. Such peculiar nature of the darknet traffic makes darknets a valuable instrument to discover malicious online activities, e.g., identifying coordinated actions performed by bots or scanners. However
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An End-to-end Trust Management Framework for Crowdsourced IoT Services ACM Trans. Internet Technol. (IF 5.3) Pub Date : 2023-08-21 Mohammed Bahutair, Athman Bouguettaya
We propose a novel end-to-end trust management framework for crowdsourced Internet of Things (IoT) services. The framework targets three main aspects: trust assessment, trust information credibility and accuracy, and trust information storage. We harness the usage patterns of IoT consumers to offer a trust assessment that adapts to IoT consumers’ uses. Additionally, our framework ascertains the credibility
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DisguisedNets: Secure Image Outsourcing for Confidential Model Training in Clouds ACM Trans. Internet Technol. (IF 5.3) Pub Date : 2023-08-21 Keke Chen, Yuechun Gu, Sagar Sharma
Large training data and expensive model tweaking are standard features of deep learning with images. As a result, data owners often utilize cloud resources to develop large-scale complex models, which also raises privacy concerns. Existing cryptographic solutions for training deep neural networks (DNNs) are too expensive, cannot effectively utilize cloud GPU resources, and also put a significant burden
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DisguisedNets: Secure Image Outsourcing for Confidential Model Training in Clouds ACM Trans. Internet Technol. (IF 5.3) Pub Date : 2023-07-15 Keke Chen, Yuechun Gu, Sagar Sharma
Large training data and expensive model tweaking are standard features of deep learning with images. As a result, data owners often utilize cloud resources to develop large-scale complex models, which also raises privacy concerns. Existing cryptographic solutions for training deep neural networks (DNNs) are too expensive, cannot effectively utilize cloud GPU resources, and also put a significant burden
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An End-to-End Trust Management Framework for Crowdsourced IoT Services ACM Trans. Internet Technol. (IF 5.3) Pub Date : 2023-06-01 Mohammed Bahutair, Athman Bouguettaya
We propose a novel end-to-end trust management framework for crowdsourced IoT services. The framework targets three main aspects: trust assessment, trust information credibility and accuracy, and trust information storage. We harness the usage patterns of IoT consumers to offer a trust assessment that adapts to IoT consumers’ uses. Additionally, our framework ascertains the credibility and accuracy
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Offering Two-Way Privacy for Evolved Purchase Inquiries ACM Trans. Internet Technol. (IF 5.3) Pub Date : 2023-05-25 Jan Pennekamp, Markus Dahlmanns, Frederik Fuhrmann, Timo Heutmann, Alexander Kreppein, Dennis Grunert, Christoph Lange, Robert H. Schmitt, Klaus Wehrle
Dynamic and flexible business relationships are expected to become more important in the future to accommodate specialized change requests or small-batch production. Today, buyers and sellers must disclose sensitive information on products upfront before the actual manufacturing. However, without a trust relation, this situation is precarious for the involved companies as they fear for their competitiveness
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Personalized Individual Semantics Learning to Support a Large-Scale Linguistic Consensus Process ACM Trans. Internet Technol. (IF 5.3) Pub Date : 2023-05-19 Yucheng Dong, Qin Ran, Xiangrui Chao, Congcong Li, Shui Yu
When making decisions, individuals often express their preferences linguistically. The computing with words methodology is a key basis for supporting linguistic decision making, and the words in that methodology may mean different things to different individuals. Thus, in this article, we propose a continual personalized individual semantics learning model to support a consensus-reaching process in
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Taming Internet of Things Application Development with the IoTvar Middleware ACM Trans. Internet Technol. (IF 5.3) Pub Date : 2023-05-19 Pedro Victor Borges, Chantal Taconet, Sophie Chabridon, Denis Conan, Everton Cavalcante, Thais Batista
In the last years, Internet of Things (IoT) platforms have been designed to provide IoT applications with various services such as device discovery, context management, and data filtering. The lack of standardization has led each IoT platform to propose its own abstractions, APIs, and data models. As a consequence, programming interactions between an IoT consuming application and an IoT platform is
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A Highly Stable Fusion Positioning System of Smartphone under NLoS Acoustic Indoor Environment ACM Trans. Internet Technol. (IF 5.3) Pub Date : 2023-05-19 Hucheng Wang, Zhi Wang, Lei Zhang, Xiaonan Luo, Xinheng Wang
Fusion positioning technology requires stable and effective positioning data, but this is often challenging to achieve in complex Non-Line-of-Sight (NLoS) environments. This paper proposes a fusion positioning method that can achieve stable and no hop points by adjusting parameters and predicting trends, even with a one-sided lack of fusion data. The method combines acoustic signal and Inertial Measurement
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Concept Drift in Software Defect Prediction: A Method for Detecting and Handling the Drift ACM Trans. Internet Technol. (IF 5.3) Pub Date : 2023-05-19 Arvind Kumar Gangwar, Sandeep Kumar
Software Defect Prediction (SDP) is crucial towards software quality assurance in software engineering. SDP analyzes the software metrics data for timely prediction of defect prone software modules. Prediction process is automated by constructing defect prediction classification models using machine learning techniques. These models are trained using metrics data from historical projects of similar
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Dynamic Personalized POI Sequence Recommendation with Fine-Grained Contexts ACM Trans. Internet Technol. (IF 5.3) Pub Date : 2023-05-19 Jing Chen, Wenjun Jiang, Jie Wu, Kenli Li, Keqin Li
The Point Of Interest (POI) sequence recommendation is the key task in itinerary and travel route planning. Existing works usually consider the temporal and spatial factors in travel planning. However, the external environment, such as the weather, is usually overlooked. In fact, the weather is an important factor because it can affect a user’s check-in behaviors. Furthermore, most of the existing
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Securing Scalable Real-time Multiparty Communications with Hybrid Information-centric Networking ACM Trans. Internet Technol. (IF 5.3) Pub Date : 2023-05-19 Luca Muscariello, Michele Papalini, Olivier Roques, Mauro Sardara, Arthur Tran Van
In this article, we consider security aspects of online meeting applications based on protocols such as WebRTC that leverage the Information-centric Networking (ICN) architecture to make the system fundamentally more scalable. If the scalability properties provided by ICN have been proved in recent literature, the security challenges and implications for real-time applications have not been reviewed
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IRGA: An Intelligent Implicit Real-time Gait Authentication System in Heterogeneous Complex Scenarios ACM Trans. Internet Technol. (IF 5.3) Pub Date : 2023-05-19 Li Yang, Xi Li, Zhuoru Ma, Lu Li, Neal Xiong, Jianfeng Ma
Gait authentication as a technique that can continuously provide identity recognition on mobile devices for security has been investigated by academics in the community for decades. However, most of the existing work achieves insufficient generalization to complex real-world environments due to the complexity of the noisy real-world gait data. To address this limitation, we propose an intelligent Implicit
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Using Deep Learning Models to Detect Fake News about COVID-19 ACM Trans. Internet Technol. (IF 5.3) Pub Date : 2023-05-18 Mu-Yen Chen, Yi-Wei Lai, Jiunn-Woei Lian
The proliferation of mobile networked devices has made it easier and faster than ever for people to obtain and share information. However, this occasionally results in the propagation of erroneous information, which may be difficult to distinguish from the truth. The widespread diffusion of such information can result in irrational and poor decision making on potentially important issues. In 2020,
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Stance-level Sarcasm Detection with BERT and Stance-centered Graph Attention Networks ACM Trans. Internet Technol. (IF 5.3) Pub Date : 2023-05-18 Yazhou Zhang, Dan Ma, Prayag Tiwari, Chen Zhang, Mehedi Masud, Mohammad Shorfuzzaman, Dawei Song
Computational Linguistics (CL) associated with the Internet of Multimedia Things (IoMT)-enabled multimedia computing applications brings several research challenges, such as real-time speech understanding, deep fake video detection, emotion recognition, home automation, and so on. Due to the emergence of machine translation, CL solutions have increased tremendously for different natural language processing
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VoiceTalk: Multimedia-IoT Applications for Mixing Mandarin, Taiwanese, and English ACM Trans. Internet Technol. (IF 5.3) Pub Date : 2023-05-18 Yi-Bing Lin, Yuan-Fu Liao, Sin-Horng Chen, Shaw-Hwa Hwang, Yih-Ru Wang
The voice-based Internet of Multimedia Things (IoMT) is the combination of IoT interfaces and protocols with associated voice-related information, which enables advanced applications based on human-to-device interactions. An example is Automatic Speech Recognition (ASR) for live captioning and voice translation. Three major issues of ASR for IoMT are IoT development cost, speech recognition accuracy
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MWPoW+: A Strong Consensus Protocol for Intra-Shard Consensus in Blockchain Sharding ACM Trans. Internet Technol. (IF 5.3) Pub Date : 2023-05-18 Yibin Xu, Jianhua Shao, Tijs Slaats, Boris Düdder
Blockchain sharding splits a blockchain into several shards where consensus is reached at the shard level rather than over the entire blockchain. It improves transaction throughput and reduces the computational resources required of individual nodes. But a derivation of trustworthy consensus within a shard becomes an issue as the longest chain based mechanisms used in conventional blockchains can no
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Exploring the Potential of Cyber Manufacturing Systems in the Digital Age ACM Trans. Internet Technol. (IF 5.3) Pub Date : 2023-05-08 Usman Ahmed, Jerry Chun-Wei Lin, Gautam Srivastava
Cyber-manufacturing Systems (CMS) have been growing in popularity. Transitioning from conventional manufacturing to an innovative paradigm that emphasizes innovation, automation, better customer service, and intelligent systems. A new manufacturing model can improve efficiency and productivity, and provide better customer service and response times. In addition, it may revolutionize the way products
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Unpaired Self-supervised Learning for Industrial Cyber-Manufacturing Spectrum Blind Deconvolution ACM Trans. Internet Technol. (IF 5.3) Pub Date : 2023-05-03 Lizhen Deng, Guoxia Xu, Jiaqi Pi, Hu Zhu, Xiaokang Zhou
Cyber-Manufacturing combines industrial big data with intelligent analysis to find and understand the intangible problems in decision-making, which requires a systematic method to deal with rich signal data. With the development of spectral detection and photoelectric imaging technology, spectral blind deconvolution has achieved remarkable results. However, spectral processing is limited by one-dimensional
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i-DarkVec: Incremental Embeddings for Darknet Traffic Analysis ACM Trans. Internet Technol. (IF 5.3) Pub Date : 2023-05-03 Luca Gioacchini, Luca Vassio, Marco Mellia, Idilio Drago, Zied Ben Houidi
Darknets are probes listening to traffic reaching IP addresses that host no services. Traffic reaching a darknet results from the actions of internet scanners, botnets and possibly misconfigured hosts. Such peculiar nature of the darknet traffic makes darknets a valuable instrument to discover malicious online activities, e.g., identifying coordinated actions performed by bots or scanners. However
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Real-time Pricing-based Resource Allocation in Open Market Environments ACM Trans. Internet Technol. (IF 5.3) Pub Date : 2023-04-05 Pankaj Mishra, Ahmed Moustafa, Takayuki Ito
Open market environments consist of a set of participants (vendors and consumers) that dynamically leave or join the market. As a result, the arising dynamism leads to uncertainties in supply and demand of the resources in these open markets. In specific, in such uncertain markets, vendors attempt to maximise their revenue by dynamically changing their selling prices according to the market demand
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A Multi-type Classifier Ensemble for Detecting Fake Reviews Through Textual-based Feature Extraction ACM Trans. Internet Technol. (IF 5.3) Pub Date : 2023-04-05 Gregorius Satia Budhi, Raymond Chiong
The financial impact of online reviews has prompted some fraudulent sellers to generate fake consumer reviews for either promoting their products or discrediting competing products. In this study, we propose a novel ensemble model—the Multi-type Classifier Ensemble (MtCE)—combined with a textual-based featuring method, which is relatively independent of the system, to detect fake online consumer reviews
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Finding the Source in Networks: An Approach Based on Structural Entropy ACM Trans. Internet Technol. (IF 5.3) Pub Date : 2023-03-27 Chong Zhang, Qiang Guo, Luoyi Fu, Jiaxin Ding, Xinde Cao, Fei Long, Xinbing Wang, Chenghu Zhou
The popularity of intelligent devices provides straightforward access to the Internet and online social networks. However, the quick and easy data updates from networks also benefit the risk spreading, such as rumor, malware, or computer viruses. To this end, this article studies the problem of source detection, which is to infer the source node out of an aftermath of a cascade, that is, the observed
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SAM: Multi-turn Response Selection Based on Semantic Awareness Matching ACM Trans. Internet Technol. (IF 5.3) Pub Date : 2023-03-23 Rongjunchen Zhang, Tingmin Wu, Sheng Wen, Surya Nepal, Cecile Paris, Yang Xiang
Multi-turn response selection is a key issue in retrieval-based chatbots and has attracted considerable attention in the NLP (Natural Language processing) field. So far, researchers have developed many solutions that can select appropriate responses for multi-turn conversations. However, these works are still suffering from the semantic mismatch problem when responses and context share similar words