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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Giri, Rakesh Kumar Vittapu, Mani Sarma Dev, Anoop Shewale, Chaitali R. Majid, Mohd Aliff Abdul Kulkarni, Nandini Sunrise University Alwar Department of Computer Science and Engineering India Mallareddy Engineering College and Management Sciences Department of Computer Science and Engineering Kistapur Village Medchal Telangana Hyderabad India Chitkara University Centre of Research Impact and Outcome Punjab Rajpura India Vishwakarma Institute of Technology Department of Information Technology Pune India University Teknology MARA Faculty of Hotel and Tourism Management Department of Foodservice Management Malaysia Symbiosis International University Department of Symbiosis School of Planning Architecture and Design Nagpur Nagpur India

ISBN: (纸本)9798350370249

Cross-layer Protocols for proper resource Allocation in Mobile Networks are a singular technique to enhance the efficiency of wireless networks. The method utilizes multiple layers of the radio protocol stack better to coordinate cell node scheduling and resource allocation. Using combining communication, routing, and scheduling functionalities in an unmarried protocol, pass-Layer Protocols for proper resource Allocation can offer a sizable will increase in the number of facts that may be transferred and the overall latency and throughput of the community. This technique can also enhance the radio interface's operation by lowering interference and encouraging collaborative communications. Eventually, by using facts and managing records from the communique and routing layers, go-Layer Protocols for proper resource Allocation can reduce the complexity of the community, even offering greater scalability. This paper affords unique cross-Layer Protocols for resource Allocation in Cellular Networks. The proposed protocol permits integrated resource allocation in the cell network environment, considering communication and computation layers. © 2024 IEEE.

关键词： Network layers

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LowResIR-Net: Lightweight Residual Network for ADL Recognition Using Low-Resolution Infrared Sensor Data 16

LowResIR-Net: Lightweight Residual Network for ADL Recogniti...

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16th International Conference on ENTERprise information Systems, CENTERIS 2024 - 12th International Conference on Project MANagement, ProjMAN 2024 - 14th International Conference on Health and Social Care information Systems and Technologies, HCist 2024

作者： Mekruksavanich, Sakorn Phaphan, Wikanda Jitpattanakul, Anuchit Department of Computer Engineering School of Information and Communication Technology University of Phayao Phayao56000 Thailand Research Group in Statistical Learning and Inference Department of Applied Statistics Faculty of Applied Science King Mongkut's University of Technology North Bangkok Bangkok10800 Thailand Intelligent and Nonlinear Dynamic Innovations Research Center Department of Mathematics Faculty of Applied Science King Mongkut's University of Technology North Bangkok Bangkok10800 Thailand

Detecting activities of daily living (ADL) is crucial for supported living and medical monitoring. Traditional approaches rely on high-resolution sensors and computationally intensive algorithms, limiting their scalability and practical use in real-world settings. This research introduces LowResIR-Net, a compact deep residual network architecture specifically tailored for recognizing ADL utilizing low-resolution infrared sensor data. LowResIR-Net efficiently extracts key features from low-dimensional data by leveraging the advantages of infrared sensing, such as privacy protection and light resilience. Its architecture combines residual connections with depth-wise convolutions, enhancing feature learning while maintaining a compact model size. The model’s performance is evaluated using the Coventry-2018 dataset, containing low-resolution infrared data from three residential sensor locations. Our tests have shown that in all three cases, LowResIR-Net consistently achieves superior performance compared to other cutting-edge deep learning models, such as CNN, LSTM, BiLSTM, GRU, and BiGRU. LowResIR-Net attains the most excellent accuracies of 90.18%, 93.75%, and 93.30%, and F1-scores of 81.81%, 89.55%, and 88.92% for scenarios I, II, and III, respectively. Furthermore, it achieves these results with fewer parameters than most other models. LowResIR-Net’s strong performance highlights its ability to accurately capture complex patterns in low-resolution infrared data for ADL detection. This study demonstrates the potential of lightweight deep learning and low-resolution infrared sensors in developing privacy-focused and computationally efficient wellness monitoring systems. © 2025 The Author(s).

关键词： Infrared detectors

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Blockchain-based security solutions for IOT networks: Analysing efficacy and implementation challenges

Blockchain-based security solutions for IOT networks: Analys...

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2025 International Conference on Pervasive Computational Technologies, ICPCT 2025

作者： Kumar, Gotte Ranjith Chamaraju, Y.S. Mulani, Umar M Naveenkumar, R. Datta, Auadhati Kanwer, Budesh Sr University School of Cs & Ai Telangana Warangal India Govt Cpc Polytechnic Department of Electronics & Communication Engineering Karnataka Mysore570007 India Kj College of Engineering and Management Research Pune India Chandigarh Group of Colleges Jhanjeri Chandigarh Colleges of Engineering Department of Computer Science and Engineering Punjab Mohali140307 India Vignan's Institute of Information Technology Department of Management Studies Andhra Pradesh Duvvada India Poornima Institute of Engineering and Technology Rajasthan Jaipur India

ISBN: (纸本)9798331508685

Blockchain innovation has gathered significant attention from both scholars and industry professionals after years of development. This technology enables the creation of smart contracts, which facilitate automated deal execution among users. Today, blockchain is also employed as a specialized infrastructure in some IT applications, helping prevent data duplication, similar to how Bitcoin and other cryptocurrencies manage transaction records. Bitcoin records, for instance, are exceptionally secure as the currency circulates across hundreds of thousands of servers, making it nearly impossible to alter. For a successful breach, an attacker would need to manipulate records on 51% of these servers simultaneously. In contrast, private data stored on single servers, such as those managed by Amazon and Google, are more vulnerable to cyberattacks. In this paper, the study propose leveraging blockchain to address security concerns in the Internet of Things. The study identifies and categorizes common security challenges, with a focus on data privacy issues, as well as the protocols used for network organization, communication, and management. Following this, the study outline security solutions for IoT and illustrate scenarios in which blockchain is applied within IoT applications. © 2025 IEEE.

关键词： Smart contract

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TG-LLaVA: Text Guided LLaVA via Learnable Latent Embeddings 39

TG-LLaVA: Text Guided LLaVA via Learnable Latent Embeddings

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39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Yan, Dawei Li, Pengcheng Li, Yang Chen, Hao Chen, Qingguo Luo, Weihua Dong, Wei Yan, Qingsen Zhang, Haokui Shen, Chunhua School of Cybersecurity Northwestern Polytechnical University China AI Business Alibaba Group China College of Computer Science and Technology Zhejiang University China College of Information and Control Engineering Xi’an University of Architecture and Technology China School of Computer Science Northwestern Polytechnical University China

ISBN: (纸本)157735897X

Currently, inspired by the success of vision-language models (VLMs), an increasing number of researchers are focusing on improving VLMs and have achieved promising results. However, most existing methods concentrate on optimizing the connector and enhancing the language model component, while neglecting improvements to the vision encoder itself. In contrast, we propose Text Guided LLaVA (TG-LLaVA) in this paper, which optimizes VLMs by guiding the vision encoder with text, offering a new and orthogonal optimization direction. Specifically, inspired by the purpose-driven logic inherent in human behavior, we use learnable latent embeddings as a bridge to analyze textual instruction and add the analysis results to the vision encoder as guidance, refining it. Subsequently, another set of latent embeddings extracts additional detailed text-guided information from high-resolution local patches as auxiliary information. Finally, with the guidance of text, the vision encoder can extract text-related features, similar to how humans focus on the most relevant parts of an image when considering a question. This results in generating better answers. Experiments on various datasets validate the effectiveness of the proposed method. Remarkably, without the need for additional training data, our proposed method can bring more benefits to the baseline (LLaVA-1.5) compared with other concurrent methods. Furthermore, the proposed method consistently brings improvement in different settings. Copyright © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

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The Power of Bamboo: On the Post-Compromise Security for Searchable Symmetric Encryption 30

The Power of Bamboo: On the Post-Compromise Security for Sea...

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30th Annual Network and Distributed System Security Symposium, NDSS 2023

作者： Chen, Tianyang Xu, Peng Picek, Stjepan Luo, Bo Susilo, Willy Jin, Hai Liang, Kaitai National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab China Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering China Cluster and Grid Computing Lab School of Computer Science and Technology China Huazhong University of Science and Technology Wuhan430074 China Digital Security Group Radboud University Nijmegen Netherlands Department of EECS Institute of Information Sciences The University of Kansas LawrenceKS United States Institute of Cybersecurity and Cryptology School of Computing and Information Technology University of Wollongong WollongongNSW2522 Australia Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology Delft2628 CD Netherlands

ISBN: (纸本)1891562835

Dynamic searchable symmetric encryption (DSSE) enables users to delegate the keyword search over dynamically updated encrypted databases to an honest-but-curious server without losing keyword privacy. This paper studies a new and practical security risk to DSSE, namely, secret key compromise (e.g., a user’s secret key is leaked or stolen), which threatens all the security guarantees offered by existing DSSE schemes. To address this open problem, we introduce the notion of searchable encryption with key-update (SEKU) that provides users with the option of non-interactive key updates. We further define the notion of post-compromise secure with respect to leakage functions to study whether DSSE schemes can still provide data security after the client’s secret key is compromised. We demonstrate that post-compromise security is achievable with a proposed protocol called "Bamboo". Interestingly, the leakage functions of Bamboo satisfy the requirements for both forward and backward security. We conduct a performance evaluation of Bamboo using a real-world dataset and compare its runtime efficiency with the existing forward-and-backward secure DSSE schemes. The result shows that Bamboo provides strong security with better or comparable performance. © 2023 30th Annual Network and Distributed System Security Symposium, NDSS 2023. All Rights Reserved.

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Nanoarchitectonics of point-of-care diagnostics for sweat biomarkers analysis

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Nano Materials Science 2024年第6期6卷 647-671页

作者： Xuan Lin Arya Vasanth Aditya Ashok Hoang-Phuong Phan Kevin M.Koo Mohammed A.Amin Yusuf Valentino Kaneti Carlos Salomon Md Shahriar A.Hossain Yusuke Yamauchi Mostafa Kamal Masud School of Chemistry and Molecular Biosciences The University of QueenslandBrisbaneQLD4072Australia Australian Institute of Bioengineering and Nanotechnology The University of QueenslandBrisbaneQLD4076Australia Graduate School of Biomedical Engineering The University of New South WalesSydneyNSW2052Australia The University of Queensland Centre for Clinical Research(UQCCR) HerstonQueensland4029Australia Department of Chemistry College of ScienceTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Translational Extracellular Vesicles in Obstetrics and Gynae-Oncology Group University of Queensland Centre for Clinical ResearchFaculty of MedicineThe University of QueenslandBrisbaneQLD 4029Australia School of Mechanical and Mining Engineering Faculty of EngineeringArchitecture and Information Technology(EAIT)The University of QueenslandBrisbaneQLD4072Australia Department of Materials Process Engineering Graduate School of EngineeringNagoya UniversityFuro-choChikusa-kuNagoyaAichi464-8603Japan Department of Chemical and Biomolecular Engineering Yonsei UniversitySeoul 03722South Korea

Sweat contains numerous vital biomarkers such as metabolites,electrolytes,proteins,nucleic acids and antigens that reflect hydration status,exhaustion,nutrition,and physiological *** healthcare diagnosis relies on disease diagnostics in sophisticated centralized laboratories with invasive sample collection(e.g.,chemical analyses,plasma separation via centrifugation,tissue biopsy,etc.).Cutting-edge point-of-care diagnostics for sweat biomarker analysis allow for non-invasive monitoring of physiologically related biomarkers in sweat and real-time health status ***,using advanced nanoarchitectures,including nanostructured platforms and nanoparticles,can enhance the specificity,sensitivity,wearability and widen the sensing modality of sweat ***,we comprehensively review the secretory mechanisms,clinical uses of sweat biomarkers,and the design,principle,and latest technologies of sweat *** an emphasis on cutting-edge technologies for sweat biomarker analysis,this review chronicles the issues associated with the current sweat biomarkers analysis of sweat biomarkers and provides insights into strategies for enhancing the translation of such biosensors into routine clinical practice.

关键词： Sweat biomarker Nanoarchitectonics Nanostructures Sweat biosensor Point-of-care diagnostics Wearable sweat sensor

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A Privacy-Aware and Time-Limited Data Access Control Scheme with Large Universe and Public Traceability for Cloud-Based IoD 1

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4th EAI International Conference on Security and Privacy in New Computing Environments, SPNCE 2021

作者： Zhang, Jiawei Yang, Yanbo Lu, Ning Liu, Zhiwei Ma, Jianfeng School of Cyber Engineering Xidian University Xi’an China School of Information Engineering Inner Mongolia University of Science and Technology Baotou China College of Computer Science and Engineering Northeastern University Shenyang China The 27th Research Institute of China Electronics Technology Group Corporation Beijing China

ISBN: (数字)9783030967918

ISBN: (纸本)9783030967901

Recently, the rapid development of Internet of things (IoT) and 5G techniques has greatly facilitated the emerging applications of Unmanned Aerial Vehicles (UAVs) and the Internet of Drones (IoD). Moreover, Cloud-based IoD supplies an ideal platform for UAV data outsourcing and sharing services to lower their heavy burden. As UAV data are of high sensitivity, the convincing Ciphertext-Policy Attribute-Based Encryption (CP-ABE) can be employed to provide confidentiality and fine-grained access control for UAV data shared in cloud. However, the access policies related to encrypted UAV data usually consist of much sensitive and private information. Meanwhile, there exist misbehaving insiders of UAV data consumers that conduct unlimited access to disable UAV data sharing services, which is disastrous. Besides, the high computation overhead also extremely hinders resource-limited users in IoD. To seek a solution, we propose a privacy-aware and time-limited data access control (PATLDAC) scheme for secure UAV data sharing in Cloud-based IoD. Specifically, PATLDAC achieves user privacy preserving through partially hidden access policy which conceals the values of attributes while leaves their names with no sensitive information. Moreover, PATLDAC provide public user tracing to prevent user key abuse and limits the access time for each data user to guarantee service provision. In addition, PATLDAC realizes high efficiency in both encryption and decryption. Finally, the performance complexity evaluation indicate that PATLDAC is suitable and feasible for IoD systems. © 2022, ICST Institute for computer Sciences, Social Informatics and Telecommunications engineering.

关键词： Drones

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The Future of Multimedia: Micro Facial Recognition in Advanced Systems 9

The Future of Multimedia: Micro Facial Recognition in Advanc...

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9th IEEE International Conference for Convergence in technology, I2CT 2024

作者： Preethi, Thakkalapally Choudalla, Saila Ram Govathoti, Sudeepthi Rajasri, K. Mohsen, Karrar Shareef Prakash, Dudi Bhanu Sai Kumar, K. And Ai&ds India Andhra Pradesh Surampalem India Gitam Deemed-to-be-University Dept of Cse Gitam School of Technology Telangana Hyderabad India Mlr Institute of Technology Department of Electrical And Electronics Engineering Telangana Hyderabad India Al-Ayen University Information And Communication Technology Research Group Scientific Research Center Thi-Qar Iraq Cvr College of Engineering Department of Ece Hyderabad India Koneru Lakshmaiah Education Foundation Computer Science Green Fields Andhra Pradesh Vaddeswaram522302 India

ISBN: (纸本)9798350394474

Paper attendance systems are still widely used at many universities, consuming significant amounts of valuable classroom time. Furthermore, the system is likely to fail due to the possibility of human mistake and the rising chance of records being misplaced or lost altogether. The authors overcame this issue by automatically posting attendance information using a facial recognition software. This strategy also helps the school take a look at the student's financial situation. Attendance records and a list of slackers might be generated by the system. They can notify students and guardians via email of attendance and financial obligations. Using KNN deep learning methodology, photos taken by a CC camera or cell phone mounted at the door are used to identify students as they enter the classroom. This study incorporates ResNet and KNN-based Deep-learning technologies to extract useful information from low-quality photos. They might also use a video taken using a cell phone to keep track of attendance. The suggested method improves upon the state-of-the-art to the extent that it achieves an accuracy of 97.34 percent, sensitivity of 98.34 percent, recall of 97.23 percent, and an F1 score of 98.23 percent. © 2024 IEEE.

关键词： Face recognition

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A Review on the need of Clustering Techniques Used for Wireless Sensor Networks 2

A Review on the need of Clustering Techniques Used for Wirel...

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2nd International Conference on Business Analytics for technology and Security, ICBATS 2023

作者： Bharany, Salil Rehman, Ateeq Ur Tariq Sadiq, M. Farrukh, Muhammad Alharbi, Meshal Hussain, Amjad Issa, Ghassan F. CET and Technology Department Amritsar India Government College University Department of Electrical Engineering Lahore Pakistan University of Brighton School of Architecture & Engineering United Kingdom Minhaj University Department of Computer Science Lahore Pakistan Prince Sattam Bin Abdulaziz University College of Computer Engineering and Sciences Department of Computer Science Alkharj11942 Saudi Arabia School of Computer Science NCBA&E Lahore Pakistan Applied Science Private University Applied Science Research Center Amman11937 Jordan Skyline University College School of Information Technology Sharjah United Arab Emirates

ISBN: (纸本)9798350335644

Wireless sensor networks have been implemented in various software to help gather and analyze data from the physical world. Wireless sensor networks are networks of multiple tiny sensors powered by low-energy batteries (WSNs). WSN lifetime is a critical factor. This is because, after WSNs have been deployed in a given application, the inaccessibility of the sensing nodes makes it impossible to recharge or replace the power source that is limited in energy. Until recently, WSNs were thought to be the same. All the network nodes have the same power, processing speed, and operational capacity. However, scientists have developed heterogeneous WSNs, in which the properties of individual nodes may vary, to extend the lifespan of networks. In order to extend a network's helpful life, energy-efficient protocols must be designed. Even though WSN has its own problems, it has brought a fresh perspective to studying real-time intelligent systems. WSN (Wireless Sensor Network) has gained significant popularity in the recent years, owing to its vast applications in real-time scenarios, such as disaster management, pollution monitoring, temperature monitoring, traffic monitoring, transport monitoring, healthcare monitoring, battlefield monitoring, and border security surveillance, to name a few. Numerous sensor nodes are employed in these applications. They are typically placed in the sensing field, where they automatically transfer data to the base station (BS) through energy transmission (i.e., battery in the sensor). In WSN, clustering is one method for optimizing power consumption at the sensor node. The sensor nodes are grouped and given a leader when they undergo clustering. This study overviews various WSN clustering algorithms, each categorized according to various clustering properties. © 2023 IEEE.

关键词： Sensor nodes

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A Novel Hybrid Clustering Based Transmission Protocol for Wireless Body Area Networks

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computers, Materials & Continua 2021年第11期69卷 2459-2473页

作者： Neelam Sharma Harshita Chadha Karan Singh B.M.Singh Nitish Pathak Research Scholar Computer Science and EngineeringUttarakhand Technical University(UTU)DehradunIndia Computer Science and Engineering Maharaja Agrasen Institute of TechnologyNew DelhiIndia School of Computer&Systems Sciences Jawaharlal Nehru University(JNU)DelhiIndia College of Engineering Roorkee UTUDehradunIndia Department of Information Technology KIET Group of InstitutionsGhaziabadIndia

Wireless sensor networks are a collection of intelligent sensor devices that are connected to one another and have the capability to exchange information packets amongst *** recent years,this field of research has become increasingly popular due to the host of useful applications it can potentially serve.A deep analysis of the concepts associated with this domain reveals that the two main problems that are to be tackled here are throughput enhancement and network security *** present article takes on one of these two issues namely the throughput *** the purpose of improving network productivity,a hybrid clustering based packet propagation protocol has been *** protocol makes use of not only clustering mechanisms of machine learning but also utilizes the traditional forwarding function approach to arrive at an optimum *** result of the simulation is a novel transmission protocol which significantly enhances network productivity and increases throughput value.

关键词： Forwarding function wireless sensor networks WSNs WBANs energy characteristics clustering hybrid mechanism dissipated energy network stability

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