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Preserving Service Availability Under DDoS Attack in Micro-Service Based Cloud Infrastructure 16

Preserving Service Availability Under DDoS Attack in Micro-S...

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16th International Conference on Security of Information and Networks, SIN 2023

作者： Kumar, Anmol Agarwal, Mayank Indian Institute of Technology Department of Computer Science & Engineering Patna801103 India

ISBN: (纸本)9798350343212

Distributed denial of service (DDoS) attacks target the availability of the victim's services. DDoS attacks, being resource-consumption attacks, create heavy resource contention. In the state of the art, we found that resource isolation for legitimate users assisted in maintaining service availability even in the presence of DDoS attacks. As the networks are moving towards micro-service architecture, DDoS attack on these architecture can lead to disruption of services. In this work, we implement a micro-service architecture using container based environment. We use the threshold connection and micro-service architecture to preserve service availability under DDoS attack. The threshold connection will check for the active connection of distinct web pages, and micro-service architecture helps in serving those different requests on different containers. We classify those users whose number of requests is greater than the threshold connection as attacker and the rest of them as benign users. Also, we classify the target web page into two categories: high resource consumption web pages and low resource consumption web pages based on their resource consumption. We serve the requests for both pages in different containers. Our experimental results show that even in the presence of a massive DDoS attack, our proposed mechanism is able to preserve the availability of the target service. The proposed methodology leads to failure of only 8 benign requests as compared to 499 under state-of-the-art. It is imperative to emphasize that the proposed technique should not be regarded as a DDoS detection instrument but rather as a supplementary component to an existing detection solutions. © 2023 IEEE.

关键词： Network security

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Utilizing Machine Learning Models to Determine the Security Level of Different Cryptosystems 7

Utilizing Machine Learning Models to Determine the Security ...

引用

7th International Conference on Trends in Electronics and informatics, ICOEI 2023

作者： Pranathi, Kantipudi Priya, Bodepudi Lakshmi Felix, A. Yovan Sathyabama Institute of Science and Technology Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350397284

Due to recent developments in multimedia technology, digital data security has emerged as an important concern. To improve upon the state of the art in terms of security, researchers often recommend modifications to procedures that have previously been implemented. However, many suggested encryption algorithms have proved unsafe over the previous several decades, putting sensitive data at risk. It is crucial to use the most suitable encryption strategy to defend against such attacks;nevertheless, the type of data being protected might affect the method that is most appropriate for each given situation. However, systematically evaluating various cryptosystems to choose the optimal one may consume significant computational effort. To rapidly and reliably choose the appropriate algorithm, an SVM (support vector machine) is proposed as a security-level identification tool for photo encryption algorithms. In this research, a dataset was compiled with the help of common encryption security criteria, including Security, Peak signal to noise ratio, Homogeneity, Correlation, Contrast, Energy, Entropy, and Mean Square Error. These values are used as extracted characteristics from various cypher pictures. There are three tiers of security for dataset labels: strong, acceptable, and weak. For evaluating the effectiveness of the proposed model, the calculated accuracy and results demonstrate the value of this SVM system. © 2023 IEEE.

关键词： Support vector machines

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ACR2UNet: Semantic Segmentation of Remotely Sensed Images using Residual-Recurrent UNet and Asymmetric Convolutions

ACR2UNet: Semantic Segmentation of Remotely Sensed Images us...

引用

2023 IEEE Applied Sensing Conference, APSCON 2023

作者： Putty, Aarabhi Annappa, B. National Institute of Technology Karnataka Department of Computer Science and Engineering Surathkal India

ISBN: (纸本)9781665461634

Land-use and land-cover (LULC) mapping is one of the significant components in environmental monitoring. LULC mapping, necessary to manage the vital resource of land, has been achieved, in recent years, by segmenting remotely sensed images (RSIs). A standard paradigm for segmentation is UNet, and this paper proposes a novel asymmetric convolutional residualrecurrent UNet architecture, which utilizes the power of asymmetric convolutions as well as residual and recurrent techniques for mapping RSIs. The proposed methodology has a couple of additional advantages. First, asymmetric convolution operations strengthen the square kernels and enhance the semantic feature space. Further, a recurrent network assists in providing rich local contextual information with the help of residual inputs. The presented model is evaluated on the WHDLD dataset for LULC segmentation and is found to achieve an improvement of 1-2% in the mIoU score compared to state-of-the-art methods. © 2023 IEEE.

关键词： Convolution

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Predicting Density in Post-Rift Lithologic Sequence from Well Log Data Using Multilayer Perceptron Neural Network 2

Predicting Density in Post-Rift Lithologic Sequence from Wel...

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2nd International Conference on informatics, ICI 2023

作者： Roy, Avik Arora, Anuja Jaypee Institute of Information Technology Department of Computer Science Engineering and IT Noida India

ISBN: (纸本)9798350343830

Estimating the density log is essential in analyzing reservoir characterization of oil and gas exploration. Density and Sonic logs assist in generating the acoustic impedance logs that further help in the impedance volume generation and inversion analysis. In the past different empirical methods (such as Gardner's equation, and Faust Equation) have been proposed to estimate density logs from the other recorded well log data like Sonic and Resistivity Logs. The current study demonstrates that if the Gamma Ray (GR) log is present in a well in addition to the Sonic log, it may be applied to estimate the density logs, improving the acceptance and accuracy of the prediction. The approach takes data from the F3 North field of the Netherlands and estimates density using both gamma and sonic logs. Data from four wells have been used in the study. The model is prepared using training data of three wells and one well is used for testing purposes. The result shows significant improvement by adding GR logs instead of using only Sonic logs while predicting Density with the Neural Network Algorithm. The study gives confidence in using GR logs in addition to Sonic logs for better predictability of Density with Neural Network Algorithms. © 2023 IEEE.

关键词： Acoustic impedance

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Image Classification of Ischemic Stroke Blood Clot Origin using Stacked EfficientNet-B0, VGG19 and ResNet-152 3

Image Classification of Ischemic Stroke Blood Clot Origin us...

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3rd International Conference on Secure Cyber Computing and Communications, ICSCCC 2023

作者： Rao, Masabathula V S Raghavendra Puligundla, Surya Ekkala, Nikhil Sai Chebrolu, Srilatha National Institute of Technology Department of Computer Science and Engineering Andhra Pradesh India

ISBN: (纸本)9798350300710

Stroke continues to be the second-leading cause of mortality globally. Over 700,000 Americans suffer from an ischemic stroke every year as a result of a blood clot clogging a brain artery. The chances of the patient surviving a second stroke where recurrent strokes account for 23% of all incidents, are decreased. The motivation of this work is to help physicians better understand the causes of blood clots in fatal strokes, making it simpler for doctors to recommend the most effective post-stroke therapeutic management and lowering the risk of a second stroke. Whole slide digital pathology images capture the blood clot of the patient who has suffered from ischemic stroke. The objective of this work is to classify the blood clot origin in the case of ischemic stroke. Its a binary classification problem where the classes are Cardioembolism and Large artery atherosclerosis. Deep learning models can be applied to classify the stroke origin efficiently. This work proposes a stacked deep learning model with VGG19, ResNet-152, EfficientNet-B0 to classify the stroke origin. Experiments have been conducted on Mayo Clinic - Strip AI dataset from Kaggle. Comparisons have been made with these individual models and also combinations of these models and found that the proposed model is achieving lower loss value. © 2023 IEEE.

关键词： computer vision

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An Intelligent Air Defense Recommendation Model based on Fuzzy Inference System 26

An Intelligent Air Defense Recommendation Model based on Fuz...

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26th International Conference on computer and Information technology, ICCIT 2023

作者： Islam Arif, Md. Ariful Islam, Zohirul Sharmee, Sharmin Sultana Akhtaruzzaman, M. Military Institute of Science and Technology Department of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9798350359015

Securing the nation's airspace demands the integration of an advanced air defense system. Automation technology can be incorporated to deploy anti-missile rockets, acting as a deterrent against various air-missile threats. This research aims to identify potential threats within a protected area and integrate an automatic system into the air defense measures based on detection. In the event of identifying incoming missiles, decisions will be made by gathering and validating information on specific issues through dedicated radars. Special emphasis is placed on utilizing a Fuzzy system to determine the nature of the threat, distinguishing between scrambling or surface-to-air missile launches based on distance, secondary radar input, and the speed of the airborne object. The paper provides a comprehensive comparison of defuzzification methods, demonstrating their effectiveness in modern air defense systems. The chosen method proves suitable, emphasizing its pertinence to contemporary air defense needs. The Fuzzy system offers insights into optimal times, types, and launch locations for interceptors or surface-to-air missiles (SAMs) within an integrated air defense system. The research evaluates the defuzzification process using five different methods, with MoM method yielding notably superior results. The incorporation of technology is crucial for ensuring the safety of protected areas, key installations, and the dynamic decision-making processes inherent in air defense systems, necessitating the use of fuzzy logic-based systems. © 2023 IEEE.

关键词： Air defense fuzzy inference system fuzzy logic integrated system intelligent system

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Decentralized Blockchain based Online Voting System with Biometric Authentication 8

Decentralized Blockchain based Online Voting System with Bio...

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

作者： Waniya, Joel Sanjeev Palmer, Matthew Kathrine, G Jaspher W. Basil Xavier, S. Aarthi, Shilpa Karunya Institute of Technology and Sciences Department of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350396638

Online voting system using blockchain with integration of biometric authentication have emerged as a promising solution to address the challenges of online voting such as preventing fraud and maintaining the integrity of the voting results. Blockchain technology provides a high level of security and transparency, making it difficult for hackers to manipulate or alter the voting results. Biometric authentication, on the other hand, ensures that only eligible voters can cast their votes, preventing double voting and other forms of fraud. Despite the potential benefits of using blockchain technology and biometric authentication for online voting, there are still challenges that need to be addressed. These challenges include ensuring that the system is accessible and user-friendly to all voters, protecting against cyberattacks, ensuring compliance with legal and regulatory requirements, and maintaining voter privacy. The objective of this proposed online voting system using blockchain with biometric authentication is to create a secure and reliable voting system that is accessible and user-friendly to all voters, while maintaining the privacy and integrity of the voting process. The system will use blockchain technology to create a tamper-proof and auditable record of the votes, and biometric authentication to ensure that only eligible voters can cast their votes. The system will also incorporate additional security measures such as encryption and multifactor authentication to protect against cyberattacks and ensure compliance with legal and regulatory requirements. By addressing these challenges, this proposed online voting system using blockchain with biometric authentication has the potential to increase voter confidence and trust in the election process. © 2023 IEEE.

关键词： Cryptography

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Image-based Ransomware Detection for Social Media Post Using Structural Similarity Index 20

Image-based Ransomware Detection for Social Media Post Using...

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20th IEEE India Council International Conference, INDICON 2023

作者： Panchal, Henil Shalin Kumar Jadav, Nilesh Chaturvedi, Pooja Gupta, Rajesh Tanwar, Sudeep Nirma University Institute of Technology Department of Computer Science and Engineering Ahmedabad India

ISBN: (纸本)9798350305593

The rapid advancement of digital technologies allowed people to interact with different social media platforms for communicating and sharing their feeds with their friends and communities. However, sharing and posting on social media are imperiled by various privacy-related issues, such as tampering with the uploaded images. Malicious individuals use manipulated images to exploit users and spread false information. Motivated by the aforesaid issue in this paper, we proposed a framework that can effectively detect manipulated images on social media platforms, specifically tackling image-based ransomware attacks. The proposed framework combines several image processing algorithms, including the Structural Similarity Index, Correlation Coefficient, Image Histogram Comparison, and Image Feature Comparison algorithms, to detect the manipulated images. Through experimentation and performance analysis, it is determined that the proposed framework has varying sensitivity levels to induced noise and manipulation. The results demonstrated the effectiveness of the proposed framework in detecting manipulated images, with the SSIM achieving the highest accuracy and the histogram comparison algorithm being the fastest. © 2023 IEEE.

关键词： Image manipulation Image Processing Moderation Algorithm Social media Trustworthiness

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Improving Software Effort Estimation with Heterogeneous Stacked Ensemble Using SMOTER over ELM and SVR Base Learners 16th

Improving Software Effort Estimation with Heterogeneous Stac...

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16th International Conference on Multi-disciplinary Trends in Artificial Intelligence, MIWAI 2023

作者： Durgesh, D.V.S. Saket, M.V.S. Ramana Reddy, B. Department of Computer Science and Engineering Chaitanya Bharathi Institute of Technology Hyderabad India

ISBN: (纸本)9783031364013

Software engineering projects can be complex and involve many different tasks and activities, such as collecting requirements, design, coding, testing, and deployment. Estimating the effort needed for the project is one of the first phases in the creation of software projects. For a software engineering project to be successfully completed, the amount of work needed to execute it must be precisely estimated. The paper suggests a novel method to calculate the effort needed to construct a software project by employing a heterogeneous stacked ensemble comprising of two base learners, namely Extreme Learning Machine (ELM) and Support Vector Regressor (SVR) and it also aims to investigate the effectiveness of Synthetic Minority Over-Sampling Technique for Regression (SMOTER) in predicting software project effort. The results indicate that the proposed model enhances the performance of the base models, resulting in a reduction of 35.7% in MAE, 24.1% in RMSE, and 18.3% in R-value. After the implementation of SMOTER, a noteworthy reduction in the error of the proposed model has been observed. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Software testing

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Enhancement in IoT through Custom Instruction Set Architectures and TinyML: Review

Enhancement in IoT through Custom Instruction Set Architectu...

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2023 International Conference on computer, Electronics and Electrical engineering and their Applications, IC2E3 2023

作者： Sandhya, P. Chandran, Priya National Institute of Technology Calicut Department of Computer Science and Engineering Calicut India

ISBN: (纸本)9798350338003

The Internet of Things or IoT means to the confluence of the network of interconnected devices, the technologies that enable communication among these devices, and between these devices and the cloud. IoT contains embedded CPUs for performing a variety of functions. The processors for enhancing IoT applications form an active area of research in the domain of computer Architecture. Embedded processors are resource and power-constrained challenging the execution of deep learning and machine learning algorithms. One proposed solution in literature is TinyML (Tiny Machine Learning) to overcome this limitation. TinyML architecture for IoT aims to deliver low latency, and effective bandwidth usage, reinforce data security, enhance privacy, and save costs. TinyML enables IoT devices to perform ML computations to be performed in the edge and avoid frequent access to the cloud which increases the performance. This paper presents a review of processor designs that are designed for TinyML architecture. For addressing other important issues in IoT a review of custom ISAs (Instruction Set Architectures) developed is also presented in this review. © 2023 IEEE.

关键词： Network architecture

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