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Privacy-preserving multi-keyword hybrid search over encrypted data in cloud

Journal of Ambient Intelligence and Humanized Computing 2024年第1期15卷 261-274页

作者： Singh, Niharika Kumar, Jitendra Singh, Ashutosh Kumar Mohan, Anand School of Computer Sciences Bennett University Uttar Pradesh Noida India CISIR Department of Electrical and Electronics Engineering University Teknologi Petronas Perak Seri Iskandar Malaysia Department of Computer Applications National Institute of Technology Tiruchirappalli Tamilnadu Tiruchirappalli India Department of Computer Applications National Institute of Technology Kurukshetra Haryana Kurukshetra India Department of Electronics Engineering Indian Institute of Technology-BHU Uttar Pradesh Varanasi India

Data outsourcing to the cloud is gaining popularity day by day in cloud computing. It requires a dynamic architecture that avoids loopholes and stops intruders from entering the cloud environment. To retrieve the enciphered documents from the cloud, the latest technique that is enrolled effectively is multi-keyword fuzzy search. The proposed research work uses this technique along with the n-gram corpus algorithm that helps to achieve relevancy score and sub-linear search time. This algorithmic combination is able to predict the privacy ranking measure of the retrieved data. To validate the opposed approach, simulation analysis has been performed to preserve user-oriented privacy in a cloud environment. The ranking precision of the proposed method is compared with (Fu et al. in IEEE Trans Inf Forensics Secur 12(8):1874–1884. https://***/10.1109/TIFS.2017.2692728, 2017) which uses a stemming algorithm and a matching algorithm based on the inner product. The results express the efficiency of the proposed approach by showing a relative improvement in security precision up to 55%. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022.

关键词： Privacy-preserving techniques

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TCP-Cubiwood: Enhanced Cubic Congestion Control for mmWave and Future Networks 17

TCP-Cubiwood: Enhanced Cubic Congestion Control for mmWave a...

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17th International Conference on COMmunication Systems and NETworkS, COMSNETS 2025

作者： Prakash, Ujjayant Baswade, Anand M. Indian Institute of Technology Department of Computer Science and Engineering Bhilai India

ISBN: (纸本)9798331531195

The rise in mobile internet usage especially using cellular networks demands efficient performance for web traffic, primarily made up of short TCP flows. For TCP, Cubic is the most widely deployed congestion control algorithm. mmWave and THz offer very high bandwidth and low latency, enabling faster speeds and reduced delay for companies deploying innovative applications, positioning them as the future of wireless technology. As such, we are compelled to thoroughly evaluate the performance of Cubic in various mmWave specific NLoS/LoS scenarios. In the process, we find Cubic really struggling when it comes to static NLoS scenarios and long connections particularly because Cubic keeps on attempting recovery from slow-start but fails due to the NLoS condition. This is where TCP Cubiwood comes to the rescue with an improvement of 189%in a simulated static NLoS scenario with results comparable to Cubic in wired conditions as well, thus becoming a suitable contender for replacing the historical algorithm. Delayed Congestion Response (DCR) tries to make TCP more robust towards channel errors in wireless networks so we also propose an additional flavor of Cubiwood, called Cubiwood-DCR which increases performance slightly in both wired and wireless high frequency scenarios. We extensively evaluate Cubiwood against Cubic, both with and without DCR enabled and make our code available for reproducibility and further research in the same direction. Moreover, the simplicity of this method makes our proposal a much more attractive solution. We believe the proposed solution is easy to implement, can replace Cubic and has the potential to improve performance in THz communication as well which is one of the competing spectrum bands for 6G networks. © 2025 IEEE.

关键词： Congestion control (communication)

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Enabling LoRa energy awareness: A Multihop One-Hop Routing Protocol for Prolonging Network Lifetime 19

Enabling LoRa energy awareness: A Multihop One-Hop Routing P...

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19th Annual International Conference on Distributed Computing in Smart Systems and the Internet of Things, DCOSS-IoT 2023

作者： Katsidimas, Ioannis Manolopoulos, Alexandros-Ioannis Nikoletseas, Sotiris University of Patras Department of Computer Engineering and Informatics Patras Greece University of Athens Department of Physics National and Kapodistrian Athens Greece University of Patras and Computer Technology Institute and Press Diophantus Department of Computer Engineering and Informatics Patras Greece

ISBN: (纸本)9798350346497

IoT applications often rely on battery-powered nodes that may be challenging to recharge, making energy efficiency a crucial concern. In this context, routing protocols play a vital role as they dictate the paths data packets take between nodes, directly influencing the energy consumption of IoT networks. Energy-aware routing protocols have been proposed to address this issue, with the aim of optimizing energy consumption by selecting paths that minimize the energy required for data transmission and reception. These protocols employ various strategies, such as distance-based, traffic-based, and hybrid schemes, to achieve energy efficiency in IoT networks. LoRaWAnprotocol has been adopted for various IoT applications with requirements in low-power and extended coverage. Over the recent years attempts have been made to replace the typical star topology employed by LoRa with multihop solutions, in an effort to further increase its capabilities. In this paper, we present a multihop algorithm that is based on an energy-balanced routing scheme adopted by LoRa nodes to increase energy efficiency and network lifetime. Multiple one-hop routes are configured for critical nodes and a different route is selected in each transmission. Additionally, critical nodes adjust their Spreading Factor and Transmission Power according to the distance of intermediate nodes. Simulation testing results verify the improved performance of our algorithm over the direct link approach. © 2023 IEEE.

关键词： Energy efficiency

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A Novel Combination of PCA and LSTM for Multi-Carrier Modulation Signals Classification 5

A Novel Combination of PCA and LSTM for Multi-Carrier Modula...

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5th International Conference on Circuits, Control, Communication and Computing, I4C 2024

作者： Sejal, K.M. Dua, Mohit National Institute of Technology Department of Computer Engineering Kurukshetra India

ISBN: (纸本)9798331528539

Fast communication is essential in today's world, and signal demodulation is a key factor affecting latency. Traditional demodulation methods are complex and time-consuming, making Automatic Modulation Classification (AMC) crucial for modern communication systems, particularly in wireless communication and signal processing. This paper presents a novel approach to classify five types of Multicarrier Modulation (MCM) signals. It also analyzes two subcarrier waveforms for each signal type, resulting in 10 unique MCM signals. This paper is divided into 2 parts -feature extraction from signals and classification of signals using those extracted features. To extract relevant features, Principal Component Analysis (PCA) and Recursive Feature Elimination (RFE) are applied. A Long Short-Term Memory (LSTM) network is then used to classify the MCM signals. Our results show that the combination of PCA and RFE. LSTM achieves superior performance in categorizing the MCM signals, making it a promising approach for efficient and accurate AMC. This paper is classifying MCM signals of range - 16dB to 16dB with the accuracy of 91% to 97%. © 2024 IEEE.

关键词： Multicarrier modulation

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Image Forensics—Analysis of Manipulated Images 4th

Image Forensics—Analysis of Manipulated Images

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4th International Conference on Innovations in Computational Intelligence and computer Vision, ICICV 2024

作者： Mamidwar, Aryan Mugalikar, Atharva Ghuge, Vivek Godse, Divija Department of Computer Engineering Vishwakarma Institute of Technology Pune India

ISBN: (纸本)9789819769940

With the emergence of low-cost internet connections, there has been significant growth in internet usage, and people are using social media to a larger extent. Social media forms a major part in human-to-human communication in the twenty-first century. Enormous number of images are shared and circulated on the social media platforms. Tampering and editing of the images are done even though internet and social media platforms like Facebook, Instagram, and Twitter connect people all over the world;evils in a society corrupt them. Small errors in information or manipulated images can wreak havoc and have unintended repercussions. Altered photos are a major source of misinformation/fake news and are frequently used maliciously, such as for mob provocation. Cases of similar incidents have grown during the previous decade. So, there should be one system which will filter this manipulated image before it leads to some major destruction. In the system mentioned in this paper, use of Error Level Analysis has been employed along with Convoluted Neural Network (CNN). The motive of this research work is to develop a system that will detect the manipulated image and verify its authenticity. By utilizing the machine learning algorithm ELA to detect changed photographs, the research helps reduce the dangers that edited images pose to society by keeping an eye on them. With a 98.5% accuracy rate, the Xception CNN model presented in this study performs well on the dataset. The dataset used is CASIA II, and it contains a total of 12,323 images and is furthermore divided into subsets. These folders consist of 7200 authentic images and 5123 tampered images. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Convolutional neural networks

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A Comprehensive Analysis of Dithering Algorithms and GPU Implementations 3

A Comprehensive Analysis of Dithering Algorithms and GPU Imp...

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3rd International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2024

作者： Kulkarni, Radhika V. Deshpande, Aaditya Dagale, Pratik Manmode, Devyani Vishwakarma Institute of Technology Department of Computer Engineering Pune India

ISBN: (纸本)9798350375190

This research paper conducts a thorough comparative analysis of various dithering algorithms, prioritizing the GPU-optimized Floyd-Steinberg algorithm. Dithering plays a crucial role in improving image quality in constrained display scenarios. The study evaluates popular algorithms, including Bayer matrix, Ordered dithering, and Error Diffusion, while specifically exploring enhancements in the Floyd-Steinberg algorithm through GPU optimization. Quantitative metrics such as MSE, PSNR, and SSI are employed, alongside subjective assessments, to gauge algorithmic performance. The research delves into adaptability across color spaces and image types, providing insights for algorithm selection. Emphasizing real-time applications, the study offers developers valuable guidance in choosing efficient dithering techniques. The GPU-optimized Floyd-Steinberg algorithm emerges as a promising solution, showcasing its potential for accelerated computing environments and resource-intensive tasks. © 2024 IEEE.

关键词： Graphics processing unit

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Mathematical Equation Identification and Solving System 15

Mathematical Equation Identification and Solving System

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15th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2024

作者： Tambe, Riya Bharadwaj, Rakhi Vaze, Sanaya Uttarwar, Varad Urane, Samarth Department of Computer Engineering Vishwakarma Institute of Technology Pune India

ISBN: (纸本)9798331300579

The rapid advancements in deep learning techniques have significantly impacted various fields, including mathematics and natural language processing. Mathematical equation identification and solving is a challenging task that has been studied by researchers for many years. Traditional approaches to this task typically rely on rule-based systems, hand-crafted features or manual work. However, these approaches are often limited in their ability to handle complex equations and there are also chances of error in it. The survey begins by discussing the challenges associated with mathematical equation identification and solving, such as the complexity of mathematical notation, variable representation, and equation structure. The paper provides an overview of the existing methodologies, algorithms, and frameworks employed in the development of systems capable of identifying and solving mathematical equations using deep learning techniques. © Grenze Scientific Society, 2024.

关键词： Deep learning

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Building a Compassionate GenAI-integrated ASL Translator for YouTube Video 4

Building a Compassionate GenAI-integrated ASL Translator for...

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4th IEEE Asian Conference on Innovation in technology, ASIANCON 2024

作者： Uke, Shailaja Godse, Shreyas Giramkar, Anshuman Gupta, Snehal Indulkar, Pooja Vishwakarma Institute of Technology Department of Computer Engineering Pune India

ISBN: (纸本)9798350354218

Video streaming is crucial for modern entertainment, education, and communication, providing accessible content to a wide audience globally. However, deaf and hard of hearing communities may face barriers due to lack of or inadequate closed captioning, hindering their ability to fully engage with and comprehend streamed content. Our paper navigates through a transformative project centered on the development of a Generative AI for YouTube video translation, integrating Google Cloud with a compassionate approach to enhance accessibility for the Deaf and Hard of Hearing community through American Sign Language (ASL) translations. Leveraging cutting-edge technologies such as Google Cloud's Gen-AI and the Palm 2.0 Text Bison model, the project aims to revolutionize the landscape of YouTube video content by providing ASL translations for a more inclusive user experience. Key objectives include the creation of an ASL Translation Tool for YouTube videos, emphasizing inclusivity beyond mere translation to engage ASL users effectively. By harnessing Google Cloud technologies and APIs in a seamless and compassionate manner, the project ensures a thoughtful code structure and organized outputs that reflect its commitment to fostering inclusivity, understanding, and accessibility for all, particularly for the ASL community. Through this endeavor, the project endeavors to showcase how technology, when employed with empathy and foresight, can serve as a catalyst for positive change in promoting inclusivity and accessibility for diverse communication needs. © 2024 IEEE.

关键词： Video streaming

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Real-time Air Quality Monitoring and Context-aware Alert System 17

Real-time Air Quality Monitoring and Context-aware Alert Sys...

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17th International Conference on COMmunication Systems and NETworkS, COMSNETS 2025

作者： Kakde, Anuj Pagoti, Yashwant Krishna Nikumbh, Sarthak Karmakar, Prasenjit Chakraborty, Sandip Indian Institute of Technology Department of Computer Science and Engineering Kharagpur India

ISBN: (纸本)9798331531195

Air quality monitoring is gaining increasing importance as awareness about the health impacts of air pollution continues to grow. These monitors typically track air pollutants to give users a clearer picture of their environment. Accurate and real-time monitoring increases our understanding of the surrounding air we breathe and allows us to improve it. The proposed system helps users minimize their exposure to harmful pollutants by providing real-time data on the concentration of various gases. The system triggers alerts directly to the subscribed user's mobile phones in case of any hazardous situations so that the user can take appropriate actions immediately to resolve the issue. Our extensive data collection and evaluation with off-the-shelf machine learning models indicated an overall F1-score of 99.54 (±0.5)% with a simple random forest model in classifying burning, cooking, occupancy in a closed room, using aerosol products, based on the sensor's readings. © 2025 IEEE.

关键词： Indoor air pollution

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A Framework for Privacy-Preserving Multiparty Computation with Homomorphic Encryption and Zero-Knowledge Proofs

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Informatica (Slovenia) 2024年第21期48卷 1-13页

作者： Dhokrat, Janak Pulgam, Namita Maktum, Tabassum Mane, Vanita Department of Computer Engineering Ramrao Adik Institute of Technology D Y Patil Deemed to be University Maharashtra Navi Mumbai India Department of Computer Engineering School of Engineering & Technology Anjuman I Islam’s Kalsekar Technical Campus Maharashtra New Panvel India

In digital landscape of today’s ongoing world the imperative for enhanced security in cloud-based data processing is paramount. This paper introduces an innovative framework that seamlessly integrates Homomorphic Encryption and Zero-Knowledge Proofs (ZKPs) to bolster data privacy and confidentiality. This paper explores the technical intricacies, real-world applications, and potential implications of this fusion framework. Homomorphic Encryption empowers computations on encrypted data without compromising privacy while Zero-Knowledge Proofs offer a mechanism to verify computations without exposing sensitive details. The effectiveness and adaptability of the proposed framework is demonstrated through meticulous analysis and practical deployment in safeguarding cloud-based data processing. The proposed framework marks a significant stride towards creating an environment where data security is unequivocally prioritized. Extensive computational experiments with quantitative results demonstrate substantial improvements in secure data processing, accuracy and efficiency confirming the frameworks effectiveness in preserving privacy while maintaining computational performance. © 2024 Slovene Society Informatika. All rights reserved.

关键词： Differential privacy

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