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Autonomous Search and Rescue Agent Using Deep Reinforcement Learning

Autonomous Search and Rescue Agent Using Deep Reinforcement ...

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2023 International Conference on Recent Advances in Science and engineering technology, ICRASET 2023

作者： Rampriya, R.S. Alam, Mohammed Junaid Jayan, Sri Vellore Institute of Technology School of Computer Science Engineering and Information Systems Tamilnadu Vellore India Madras Institute of Technology Department of Computer Technology Tamilnadu Chennai India

ISBN: (纸本)9798350306927

Disaster management is one of the areas of paramount importance for any government or organization. This process gets very tedious and tricky for some specific type of disasters. Deploying manpower for mitigating the disaster and saving the victims is a risky decision because the life of the people in the disaster management team is put to risk, which is a very unfortunate thing. So instead of using manpower, we can deploy intelligent machine agents, which are equivalent or sometimes more efficient than human beings for such highly risky tasks and avert the loss of lives. In our case, we have specifically considered the disaster wherein fire breaks out in a building and people get trapped inside due to the dangerous situation. In this case, where deploying manpower to rescue them requires a high quality protective gear and can even put their lives on risk, we have proposed to deploy intelligent machine agents that are trained to figure out the path on their own and find their way to the victims after which a rescue operation can be performed by safely escorting the victims to a nearby exit in the building. The agent in the proposed application has been evaluated by the metrics such as the time taken to reach the victims and come back to the exit, the total rewards gathered by the agent during its exploration in the environment and the number of correct decisions it made during its journey. The agent takes an average time of 145.6 seconds to complete its operation in the real-time environment. It gathered an average peak cumulative reward value of -0.2 in the real time environment. The agent on an average, records 67.3% chance of making a correct decision (that gets a positive reward) given a state vector. © 2023 IEEE.

关键词： Autonomous agents

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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 ...

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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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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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Generalizing a Secure Framework for Domain Transfer Network for Face Anti-spoofing 18th

Generalizing a Secure Framework for Domain Transfer Network ...

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18th International Conference on Data Science and Artificial Intelligence, ICDSAI 2022

作者： Chandavarkar, B.R. Rana, Ayushman Ketkar, Mihir M. Pai, Priyanka G. Department of Computer Science and Engineering National Institute of Technology Karnataka Mangalore India

ISBN: (纸本)9783031161773

An essential field in cyber-security is the technology behind the authentication of users. In the contemporary era, alphanumeric passwords have been the primary tool used. A password is easy to understand but theoretically complex to brute force and is very easy to store in large databases since, in essence, they are an array of characters. In practical use, however, passwords tend to be very ineffective as the attributes that make for "strong" passwords are generally really abstract and random. However, human memories tend to remember constructed language, which can be intelligently guessed with sufficient information regarding the person. A widely accepted remedy to this problem is to replace passwords with face recognition software which involves minimal effort for the user and, though not completely immune, is quite challenging to misuse. Misuse is often done by spoofing faces. Spoofing faces means presenting a 2D or even a 3D copy of a face to the camera, pretending it is the real face. Many discovered spoofing methods are taken into consideration and protected against in most software. Even though various methods have been suggested for anti-spoofing, there are challenges that these methods go through, e.g., washed-out images, lack of colour, poor illumination. Our proposal involves the use of OpenCV and deep learning to accurately colourize the image pre-processing and put it through the GAN framework (Wang et al., From RGB to Depth: Domain Transfer Network for Face Anti-Spoofing (2021). https://***/document/9507460. Accessed 07 Feb 2022). Furthermore, to secure the image to prevent ill use, the final generated image pair will be encrypted so that only the user can access it. The aim is to combine the power of re-colourization with the GAN framework’s strong anti-spoofing capabilities and make the whole framework secure for the user. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Cryptography

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A Lightweight Authentication and Key Agreement Protocol for IoT-Based Smart Healthcare System

A Lightweight Authentication and Key Agreement Protocol for ...

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2023 IEEE World Conference on Communication and Computing, WCONF 2023

作者： Das, Sangjukta Singh, Maheshwari Prasad Namasudra, Suyel National Institute of Technology Patna Department of Computer Science and Engineering Bihar India

ISBN: (纸本)9798350311204

Nowadays, the enormous advantages of the Internet of Things (IoT) are being used in a variety of fields, including, but not limited to, transportation, healthcare, and traffic monitoring. However, the lack of strong security in IoT devices can put both the devices and the data at risk, which can be life-threatening in healthcare. Authentication of network devices is identified as a major security concern, particularly in the context of smart healthcare systems. This paper discusses a privacy-preserving authentication technique that provides session key agreement for smart healthcare systems. This scheme is developed by using simple cryptographic operations to cope with resource-constrained IoT devices. The proposed scheme aims to establish a secure session for authorized devices. Security analysis and performance analysis are conducted to evaluate the effectiveness of the proposed scheme, which is found to be more effective than existing schemes. © 2023 IEEE.

关键词： Internet of things

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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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Advancing Spelling Correction through Natural Language Processing and TextBlob: A Context-Aware Approach

Advancing Spelling Correction through Natural Language Proce...

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2023 International Conference on the Confluence of Advancements in Robotics, Vision and Interdisciplinary technology Management, IC-RVITM 2023

作者： Singh, Nongmeikapam Thoiba Mishra, Aditya Mohan Singh, Ankit Chanu, Asem Debala Chandigarh University Department of Computer Science and Engineering Punjab India Indian Institute of Information Technology Department of Computer Science and Engineering Assam Guwahati India

ISBN: (纸本)9798350306088

This study explores the development of an advanced spelling correction system using Natural Language Processing (NLP) and the TextBlob library. It addresses the prevalent issue of spelling errors in written text and aims to create a system that not only corrects typographical errors but also considers the contextual nuances in which words are used. The paper begins by explaining key NLP concepts, including tokenization, part-of-speech tagging, and contextual analysis, which form the foundation of the spelling correction process. These techniques are crucial for systematically identifying and rectifying spelling errors. Furthermore, the research focuses on integrating TextBlob's dictionary-based correction mechanism with contextual awareness to improve precision, particularly in context-dependent correction scenarios. The study rigorously evaluates the system's performance through real-world testing and transparently discusses potential limitations and challenges encountered during development. Overall, the research paper highlights the transformative impact of NLP and TextBlob on spelling correction, demonstrating substantial improvements in correction accuracy and contextual comprehension. It emphasizes the wide-ranging applications of this technology, extending its influence beyond spelling correction to various domains, including word processing software, search engines, and virtual assistants. The findings endorse the effectiveness of this approach and call for continued research and development efforts to advance language processing technologies and enhance written communication across diverse applications. © 2023 IEEE.

关键词： Machine learning

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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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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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