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Securing Cloud-based Data Sharing with Accountable Proxy Re-Encryption 4

Securing Cloud-based Data Sharing with Accountable Proxy Re-...

引用

4th International Conference on Intelligent Technologies, CONIT 2024

作者： Mahalakshmi, E. Vaidhegi, A. Jayakumar, D. Ramkumar, M.O. Rajmohan, R. Department of Computer Science and Engineering Villupuram India Srm Institute of Science and Technology Department of Computing Technologies Kattankulathur India

ISBN: (纸本)9798350349900

Cloud computing has been a considerable way to store and share data among different communities in the past few decades. However, it has always been a challenge to ensure that the data is secured during cloud data transfer. The proposed paper resolves the major challenges being faced in cloud data sharing with the new approach of Accountable Proxy-ReEncryption (APRE). The proposed paper deals with protocols and anticipates cryptography measures, namely homomorphic encryption, by ensuring two things: confidentiality and integrity. Both work on the shared data of the cloud. The major aspect of homomorphic encryption is that it has an inbuilt feature of function execution over the encrypted data without decryption. So, it communicates the data confidentially by maintenance. Thus, re-encryption of the proxy used in this research would also allow for safe delegation to the proxy servers. The APRE protocol brings about different accountability mechanisms. In this case, it deals with the aspect of transparency and data supervision in communication. The homomorphic signatures in the paper enable the data owner to monitor and audit the proxy functions. It strictly enforces the decryption policies and minimizes the rate of mishandling of shared information. In so doing, this layer boosts the trust of cloud data sharing, especially in terms of provision of confidentiality, preservation of privacy, and the allowance of the robustness of behaviour in verifying and tracking data access. Finally, this proposed system uses a comprehensive assessment framework to check the effectiveness and efficiency of the APRE protocol. It can, therefore, be inferred that from the outcome obtained from the results, this proposed system outperforms the other existing systems in security, performance, and effectiveness. © 2024 IEEE.

关键词： Cloud platforms

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Minimization of Energy Consumption in Cloud 3

Minimization of Energy Consumption in Cloud

引用

3rd International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies, ICAECT 2023

作者： Kirti Smriti, Manu Shaily, Kumud Sudha, Danthuluri CMR Institute of Technology Department of Computer Science & Engineering Karnataka Bangalore India

ISBN: (纸本)9781665494007

With advancement in technology and the internet Cloud computing is becoming more popular and hence the number of datacentres is increasing which causes the amount of power consumption to increase and more cooling equipment are required. How to efficiently distribute Virtual Machines (VMs) to the Physical Machines (PMs) or hosts in order to conserve power is the task. There are numerous existing energy-conscious methods which concentrate on reducing energy use in a cloud environment. Here two models, a gradient regression-based method and a maximum percentage of correlation-based method are proposed;these can significantly minimize use of energy in cloud computing. CloudSim is a simulation tool for simulating cloud computation environments. The VM migration policy has been modified to give more energy efficient results. © 2023 IEEE.

关键词： Electric power utilization

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The Voiceless Assistant for the Specially Abled 1

The Voiceless Assistant for the Specially Abled

引用

1st IEEE International Conference on Applied Intelligence and Sustainable Computing, ICAISC 2023

作者： Vijaya Shetty, S. Ram, Ajith Bhargav, Arjun Harshinee, A. Pathak, Kanchan Nitte Meenakshi Institute of Technology Department of Computer Science Engineering Bengaluru India

ISBN: (纸本)9798350323795

A novel system aimed at bridging the communication gap between deaf and blind individuals and those who are not familiar with sign language or Braille is proposed. Google's Speech Recognition library is used to convert speech to text and the pyttsx3 library is used to convert text to speech. The system is designed to interconvert between Indian sign language, Braille, and English text, creating a unified platform for individuals with different disabilities to communicate effectively. The sign language recognition component of the system was trained with a training accuracy of 97.73 percent and test accuracy of 98 percent. The Braille recognition component was trained with a training accuracy of 97 percent and test accuracy of 95.5 percent. The integration of sign language and Braille into one platform is a unique feature that sets this system apart from existing solutions. © 2023 IEEE.

关键词： Speech recognition

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XAI: An Explainable AI Model for the Diagnosis of COPD from CXR Images 2

XAI: An Explainable AI Model for the Diagnosis of COPD from ...

引用

2nd IEEE International Conference on Data, Decision and Systems, ICDDS 2023

作者： Ikechukwu, Agughasi Victor Murali, S. Maharaja Institute of Technology Mysore Department of Computer Science and Engineering Mysuru India

ISBN: (纸本)9798350314168

Chronic Obstructive Pulmonary Disease (COPD) is a major health concern worldwide, the third leading cause of death. However, it often goes unnoticed until it reaches severe stages. Although spirometry tests are the definitive method for COPD diagnosis, their accessibility is limited in under-resourced regions. In contrast, Chest X-rays (CXRs) are more universally available, suggesting their potential utility as preliminary screening tools for COPD. This study applies deep learning algorithms to the large-scale VinDR-CXR dataset to identify early-stage COPD using CXRs. The research employs the ChestX-ray14 dataset for model pre-Training and then utilizes VinDR-CXR for model development and validation. Through transfer learning, it was observed that the Xception base model with a recall of 98.2% obtained via fine-Tuning was better than the ResNet50 model. Grad-CAM (Gradient Class Activation Mapping) heatmaps and SHAP (SHapley Additive exPlanations) offer explainability for true positive cases on the Xception model from both datasets. The findings underscore the potential of DL models in facilitating early COPD detection via CXRs, especially where spirometry remains less accessible. Further exploration into multimodal-based COPD diagnosis is recommended for subsequent research. © 2023 IEEE.

关键词： Large datasets

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An Integrated and Optimized Fog Computing enabled Framework to minimize Time Complexity in Smart Grids 6

An Integrated and Optimized Fog Computing enabled Framework ...

引用

6th International Conference on Contemporary Computing and informatics, IC3I 2023

作者： Nag, Rohan Samantraj, Adhinayak S. Mishra, Sushruta Sharma, Vandana School of Computer Engineering Kalinga Institute of Industrial Technology Bhubaneswar India Computer Science Department Delhi NCR India

ISBN: (纸本)9798350304480

A distributed computing paradigm known as 'cloud computing'works as a connection between IoT devices and cloud data centres. The environment system model in this work is on basis of clouds and fog and includes smart grids, which we explore. Prior to understanding the use of fog computing in smart grids we discuss about various features of cloud computing and talk about how to manage the connection between fog and cloud computing. Along with the usual performance of low latency, low cost, and high intelligence, the distinctive characteristics and service scenarios are also explored. Based on the outcome of the simulation, it appears that our suggested PSO-SA algorithm outperforms other optimization algorithms. It recorded a least mean response time of 3.86 seconds only. While the model build up delay was 4.6 seconds, the model execution delay was also found to be only 4.9 seconds with PSO-SA method. The improved efficiency of the technique can be credited to the best aspects of particle swarm optimisation (PSO) and a modified inertia weight obtained by simulated annealing. © 2023 IEEE.

关键词： Cloud Computing Edge Computing Fog Computing Smart Grid

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Detection of Asperger Syndrome at Early Stages in Children using Deep Neural Networks 8

Detection of Asperger Syndrome at Early Stages in Children u...

引用

8th International Conference on Communication and Electronics Systems, ICCES 2023

作者： Battu, Vishnu Vardhan Vinay Kumar, B. Boddapati, Chaitanya Sreya Chaparala, Pujitha Chava, Sri Harsha Damisetty, Leela Hemanth Pvp Siddhartha Institute of Technology Department of Computer Science and Engineering Vijayawada India

ISBN: (纸本)9798350396638

ASD (Autism Spectrum Disorder) is behavioral and considered to be a developmental disorder found in human beings. It includes disorders in brain development, eventually affecting functional brain capabilities. It also affects how a person converses with others and causes problems in interaction and communication. The vast range of symptoms, abilities, and functioning levels in ASD patients is known as the "spectrum."It is essential to diagnose ASD at early stages so that autistic child can reach their full *** some cases, parents cannot accept that their child's mental growth is not developing along with physical development. With early diagnosis, children with autism can lead fulfilling and joyful lives through the provision of appropriate medication. Screening tests are used to diagnose this type of disorder but are time-consuming and costly. This research study has employed a convolutional neural network to detect the likelihood of ASD in young children at an early stage. Deep Neural Networks function well in many applications. This study has used Xception and Resnet50 model to predict ASD based on static facial images, especially in children. According to the results obtained, ResNet50's performance is better than Xception in Autism detection. © 2023 IEEE.

关键词： Deep neural networks

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Efficient Prediction and Analysis of Monkeypox Skin Lesion: A Comparative Study for Web based Application 2

Efficient Prediction and Analysis of Monkeypox Skin Lesion: ...

引用

2nd Edition of IEEE Delhi Section Owned Conference, DELCON 2023

作者： Gupta, Piyush Mittal, Uday Jha, Tushar Agarwal, Mini Tiwari, Ajay Maharaja Agrasen Institute of Technology Department of Computer Science and Engineering Delhi India

ISBN: (纸本)9798350322064

After the coronavirus pandemic, another deadly disease, known as monkeypox, began to spread. This was so alarming that the World Health Organization declared it a global public health emergency. As of 31st January 2023, there have been 85449 cases of monkeypox reported in 110 countries worldwide. It is difficult to diagnose because its symptoms resemble those of chicken pox, small-pox, etc. The clinical diagnosis of monkeypox is performed using the Polymerase chain reaction (PCR) test, which takes a considerable amount of time to determine the result. Any non-clinical test that could aid in identifying monkeypox in suspected patients would be advantageous. Various deep learning models were found to be useful for this purpose, provided sufficient training data is available. We've used already existing datasets and extended them to have a sufficiently large dataset. This dataset is then fed to pre-trained deep-learning models, including ResNet50, EfficientNetB3, InceptionV3, and MobileNetV2. It has aided in comparing the accuracy of these models. Based on our analysis, we have employed best performing model i.e., EfficientNetB3 in a web application with a user-friendly interface to interact with it. © 2023 IEEE.

关键词： Polymerase chain reaction

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Hybrid Cryptographic Algorithm to Secure Internet of Things 7

Hybrid Cryptographic Algorithm to Secure Internet of Things

引用

7th International Conference on Intelligent Computing and Control Systems, ICICCS 2023

作者： Amala Nikitha, G. Kathrine, G. Jaspher W. Duthie, Christina Rajesh Ebenezer, V. Silas, Salaja Karunya Institute of Technology and Sciences Department of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350397253

Small IoT devices can only support light protocols since they lack significant processing or storage power. Lightweight encryption standards or techniques will be utilized for encryption and decryption to prevent hackers from accessing the data in order to increase the security of IoT devices' network connections and commands. The encryption has to be robust enough to safeguard and lightweight enough to enable light processing hardware. There aren't many standards for lightweight cryptography that are used to safeguard devices in an existing network. If the network is not secured properly, an intruder can get in and take control of the devices without making a visible appearance. A hybrid lightweight cryptographic methodology have been proposed to address this problem. LWC algorithms are designed to provide strong security while minimizing the computational and memory resources required for encryption and decryption. This is particularly important for IoT devices, which often have limited processing power, storage capacity, and battery life. LWC algorithms offer a range of benefits for IoT devices, including improved security, reduced power consumption, and increased battery life. They are also designed to be easy to implement and integrate with existing IoT platforms and protocols. Proposed system's analytical work implementation will combine Salsa20 and AES algorithms to provide greater security and making it well-suited for real-time cryptography. © 2023 IEEE.

关键词： Internet of things

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Quantum Odyssey: Traversing the NISQ Era's Quantum Terrain 3

Quantum Odyssey: Traversing the NISQ Era's Quantum Terrain

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3rd International Conference on Technological Advancements in Computational Sciences, ICTACS 2023

作者： Arya, Swati Ansar, Syed Anas Aggarwal, Shruti Babu Banarsi das University Department of Computer Application Lucknow India Thapar Institute of Engineering and Technology Department of Computer Science and Engineering Punjab India

ISBN: (纸本)9798350342338

The advent of quantum computing has ignited unprecedented anticipation within the realm of IT. This has transcended the limitations of classical computation and revolutionized various facets of technological advancement. At the forefront of this quantum revolution stands the Noisy Intermediate-Scale Quantum (NISQ) era, characterized by a delicate interplay of immense potential and persistent imperfections. This paper delves into the intricacies of NISQ-era quantum computing, unraveling its fundamental principles, challenges, and transformative implications for the IT landscape. Beginning with quantum computing basics-qubits, superposition, entanglement, and gates-the NISQ era's essence addresses error-prone operations and decoherence. Quantum algorithms for NISQ devices, like Grover's search, Shor's factorization, and Variational Quantum Eigensolver (VQE), are scrutinized for their computational potential. Central to NISQ's viability, quantum error correction and mitigation strategies are surveyed, stabilizing quantum computations amidst noise. Examining quantum hardware architectures and performance metrics unveils NISQ devices' potential. Applications of NISQ quantum computing in cryptography, optimization, machine learning, and more are explored, showcasing quantum advantage's real-world potential. This paper embarks on a multidimensional exploration of NISQ quantum computing, illuminating its intricate facets, applications, and ethical implications. As quantum computing evolves from a theoretical notion to a tangible paradigm, the insights gleaned herein contribute to a holistic understanding of its role in shaping the next wave of computing. © 2023 IEEE.

关键词： Ethical Implications Noisy Intermediate-Scale Quantum (NISQ) Era Quantum Algorithms Quantum Computing Quantum Error Correction (QEC)

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Anomaly Detection in the Cloud Environment with Clustering Optimization Model for Attack Detection in IDs

Anomaly Detection in the Cloud Environment with Clustering O...

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2023 International Conference on IoT, Communication and Automation technology, ICICAT 2023

作者： Jain, Ashima Tripathi, Khushboo Jatain, Aman Manju Amity University Department of Computer Science and Engineering Haryana Gurugram India Jaypee Institute of Information Technology Department of Computer Science and Engineering Noida India

ISBN: (纸本)9798350302820

In recent decades the role of the Internet in day-to-day activities are rapidly increased due to the accessibility and completion of tasks with in fraction of a second, as well as the banking and billing process proceeds online. Due to the character of openness in networks, security is the big threat to users. The intruders enter into the network in different manners to get access or change the original contents as well as block the connection, etc. The intrusion detection (IDS) process is a mandate to overcome the issues, the IDS is classified as misuse detection as well as anomaly detection. This paper constructed a framework for anomaly detection in the cloud environment. The constructed framework model uses the Rule-based Bayesian Optimization (RBBO) for the attack and malicious activities detection. The RBBO model uses the weighted rule-based approach with the estimation of mean and standard deviation in the dataset attributed to the attack and anomaly detection. Based on the generated rules the conditions are provided within the Bayesian Network for the dimensionality reduction. Through implementation of the Bayesian Network classification of attacks are performed for the KDD cup and real-time dataset. The comparative analysis expressed that the RBBO model performance is effective for the detection of anomalies and attacks in the cloud with the reduced false positive rate. © 2023 IEEE.

关键词： Bayesian networks

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