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Addressing the Rising Challenge of Malware Innovative Detection and Mitigation Techniques

Addressing the Rising Challenge of Malware Innovative Detect...

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2024 International Conference on Communication, computer sciences and engineering, IC3SE 2024

作者： Balaram, A. Umashankari, E. Dutt, Amit Bharadwaj, Garima Revathi, V. Albawi, Ali Mlr Institute Of Technology Department Of Computer Science And Engineering Telangana Hyderabad India Institute Of Aeronautical Engineering Department Of Computer Science And Engineering Telangana Hyderabad India Lovely Professional University Phagwara India Amity Business School Amity University Greater Noida India New Horizon College Of Engineering Department Of Applied Sciences Bangalore India College Of Medical Technology The Islamic University Radiology Techniques Department Najaf Iraq

ISBN: (纸本)9798350366846

This research talks about Hybrid Anomaly Detection (HAD), a complex technology for finding and stopping malware. There are four different methods to apply the approach. The following are a few examples: EDR, DBA, TIS, and EML. The goal of the ablation specialists is to enhance the HAD structure in whatever way possible. With a success rate of 99.5% and only one false positive, DBA starts monitoring the process the second it starts. EML makes the system more flexible and useful by finding malware using probability estimates and weighted voting. TIS protects against new threats and motivates people to work together by sharing and prioritizing threat information. EDR is all about computer security by evaluating and reducing risks. The ablation study focuses on how well each algorithm can identify things, how flexible it is, how well it can work with others, and how safe it keeps endpoints safe. Since these algorithms work well together, the HAD framework offers a complete answer that performs better than other approaches in many ways. This study suggests a good way for everyone to work together to fight modern computer risks, which will improve cybersecurity. © 2024 IEEE.

关键词： Malware

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A Novel Approach to Detect Face Mask in Real Time 3rd

A Novel Approach to Detect Face Mask in Real Time

引用

3rd International Conference on Artificial Intelligence and Speech technology, AIST 2021

作者： Gupta, Sumita Majumdar, Rana Deswal, Shivam Department of CSE Amity School of Engineering and Technology Amity University Noida India School of Computer Science and Engineering Swami Vivekananda University Kolkata India

ISBN: (纸本)9783030957100

COVID-19, a deadly virus outbreak in the entire world, infected countless number of people and leads to death of millions of people. Economy of countries halted, people are stuck up, the situation is becoming worse day by day that no one expected. The COVID-19 can be spread through airborne droplets, aerosols and other carriers. So, the guidelines are released which promotes 3 key points for its prevention: (a) maintain social distancing, (b) sanitization, and (c) most important, wearing of mask in public places. But unfortunately, people are avoiding these measures leading to spread of the disease. So, there is need of some sort of security guards on ground that ensures people would strictly follow the guidelines. But, it’s too risky for the lives of security guards. Fortunately, we live in 21st century. There are so powerful technologies like Machine Learning, Artificial Intelligence, Deep Learning and many more. So, it is possible to develop a way where machines will help us to ensure the guidelines to be followed. There is no need for a physical person to watch over crowd. This research paper proposed a work to implement machine-learning algorithm to ensure people wear the proper face mask or not. It can be used in public places like airports, railway stations or at main gate of societies to ensure that no one without mask may enter the society and similarly can be used at stores. © 2022, Springer Nature Switzerland AG.

关键词： Face recognition

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Legal Considerations for Artificial Intelligence and Machine Learning 15

Legal Considerations for Artificial Intelligence and Machine...

引用

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

作者： Bhatnagar, Gunjan Verma, Alpika Chakraborty, Nilanjan Suman Kumar, Ashwini Mittal, Aman Dev Bhoomi Uttarakhand University School of Engineering and Computer Uttarakhand 248007 India Invertis University Department of LAW Uttar Pradesh Bareilly243123 India Amity University Amity Law School Kolkata India K. R. Mangalam University School of Engineering & Technology Department of Computer Science & Engineering Haryana Gurugram122103 India ARKA JAIN University Department of Engineering and Information Technology Jharkahnd Jamshedpur India Chitkara University Institute of Engineering and Technology Chitkara University Centre for Interdisciplinary Research in Business and Technology Punjab India

ISBN: (纸本)9798350370249

Artificial intelligence (AI) and gadgets gaining knowledge of (ML) have revolutionized organizations' overall performance, leading to accelerated performance and productivity. This era has become a fundamental part of our daily lives, from personal assistants to self-using vehicles. However, as AI and ML continue to improve and become more pervasive, it's crucial to undergo the prison implications that would stand up. One of the primary criminal considerations for AI and ML is record privacy and safety. With the sizeable series and processing of extensive records, the danger of fact breaches and privacy violations increases. Corporations should follow applicable legal suggestions and policies, the overall records protection law (GDPR), and the California Purchaser Privacy Act (CCPA). Another interest is a legal responsibility. As AI and ML become more impartial, questions arise about who is responsible for any damage or harm because of those structures. This trouble has become more complicated, even as a few events concern improving and deploying AI and ML technologies. © 2024 IEEE.

关键词： Answerable California Concern Implications Privateness Revolutionized

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Commodity Price Prediction for making informed Decisions while trading using Long Short-Term Memory (LSTM) Algorithm 5

Commodity Price Prediction for making informed Decisions whi...

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5th International Conference on Contemporary Computing and Informatics, IC3I 2022

作者： Suman, Shashikant Kaushik, Prakarsh Challapalli, Sai Sri Nandan Lohani, Bhanu Prakash Kushwaha, Pradeep Gupta, Amar Deep Amity School of Engineering and Technology Dept. of Computer Science Greater Noida India

ISBN: (纸本)9798350398267

Commodity markets are physical or virtual marketplaces where market players meet to buy or sell positions in commodities such as crude oil, gold, copper, silver, cotton, and wheat. People invest their hard-earned money based on some predictions to gain some profit from commodity market. Although, traditional methods such as technical analysis & fundamental analysis are very popular among traders, they are not as accurate as analysis by long short-term memory (LSTM) algorithm. In this paper, we have developed a model of well-known efficient LSTM algorithm to predict the commodity market price by utilizing a freely accessible dataset for commodity markets having open, high, low, and closing prices from historical data. © 2022 IEEE.

关键词： Long short-term memory

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Comparative Analysis of Cloud Computing Based Face Recognition Services

Comparative Analysis of Cloud Computing Based Face Recogniti...

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2022 International Conference on Machine Learning, Big Data, Cloud and Parallel Computing, COM-IT-CON 2022

作者： Jha, Soumya Arora, Manya Sharma, Yashica Anand, Ashish Sharma, Dolly Amity University Amity School of Engineering and Technology Uttar Pradesh Noida India Amity University Department of Computer Science and Engineering Uttar Pradesh Noida India

ISBN: (数字)9781665496025

ISBN: (纸本)9781665496025

With growing crime rate around the world, it has become essential to have security surveillance systems that uses evolved mix of advanced technologies to provide a robust and a holistic approach to mitigating security risks. On the other hand, there have been rapid advancement in technologies which have led to the progress of security awareness and embedded system to cope up with the higher demand of the security surveillance. With immense variety of systems available nowadays, this paper aims to compare the various existing facial recognition cloud services used for real time security and surveillance with main focus on cloud-based architecture. © 2022 IEEE.

关键词： Face recognition

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AI Based Data Augmentation Process Used to Find the Defect in Injection Molding

AI Based Data Augmentation Process Used to Find the Defect i...

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2023 International Conference on New Frontiers in Communication, Automation, Management and Security, ICCAMS 2023

作者： Rebekah, Repalle Deepthi Crestose Laxmaiah, G. Raj, S Solomon Singh, Samit Kumar Hazela, Bramah Verma, Manish Kumar Ravindra College of Engineering for Women Department of Computer Science and Engineering Andhra Pradesh Kurnool India Chaitanya Bharathi Institute of Technology Department of Mechanical Engineering Hyderabad India Bhoj Reddy Engineering College for Women Department of Mechanical Engineering Hyderabad India Amity University Amity School of Engineering & Technology Department of Computer Science and Engineering Lucknow India Lovely Professional University Department of Psychology Phagwara India

ISBN: (纸本)9798350317060

Automatic quality examination is now receiving attention as a vital element of the industry 4.o. However, because of the variety of products, challenges associated with creating uniformly high-quality product pictures, and short cycle durations, injection molding technologies have not gotten much attention in this field of study. In this work, we suggested an injection molding defect inspection method for edge intelligence. The data imbalance and scarcity issues faced by small and medium-sized businesses (SMEs) are addressed via data augmentation, implemented the unique technique of the injection process, and evaluated effectiveness of the created AI model. The suggested model's accuracy was more than 90%, demonstrating the system's viability for use in the real world. © 2023 IEEE.

关键词： Injection molding

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Leveraging Deep Learning Architectures for Accurate Wind Speed and Power Prediction in Renewable Energy Systems 7

Leveraging Deep Learning Architectures for Accurate Wind Spe...

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7th International Conference on Contemporary Computing and Informatics, IC3I 2024

作者： Alekhya, V. Anandhi, R.J. Jain, Alok Gupta, Navya Singh, S. Vikram Begum, Rowsonara Institute of Aeronautical Engineering Telangana Hyderabad50043 India New Horizon College of Engineering Department of Information Science Engineering Bangalore India Lovely Professional University Phagwara India Lloyd Law College Uttar Pradesh Greater Noida India Amity University Amity School of Engineering & Technology Uttar Pradesh Greater Noida India Mlr Institute of Technology Department of Computer Science and Engineering Telangana Hyderabad India

ISBN: (纸本)9798350350067

The advanced deep learning models that are incorporated in this paper present strategies on the forecasting of Wind velocity and wind power. While metaheuristic strategies do not define the system and work to establish that the given inputs and outputs can be linked, deep learning models render a higher capacity to capture temporal and spatial dependencies in wind data. It is expected that through dealing with big data to recognize complex relations, the improvements in wind speed and power prediction would be immensely increased. Thus, this approach allows for more accurate and specific forecasting favoring the efficient functioning of wind energy and its incorporation into the electricity grid. The performance of these deep learning models is tested through New Delhi, India specific case incrementally showing that these models are very computationally efficient and have better prediction capabilities. © 2024 IEEE.

关键词： Wind forecasting

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SkinSage - Lesion Diagnosis Using Deep Learning Techniques

SkinSage - Lesion Diagnosis Using Deep Learning Techniques

引用

International Conference on Confluence The Next Generation Information technology Summit (Confluence)

作者： Geetika Paarth Bhardwaj Nimish Vaibhav Bhargava Shivendra Singh Department of Computer Science and Engineering Amity School of Engineering and Technology Noida India

The alarming rise in instances of skin cancer in recent years, one of the most prevalent malignancies worldwide, emphasises how important early and accurate identification is. The SkinSage project, which combines the precision of deep learning models and technologies. Earlier, dermatologists relied on eye exams to spot skin lesions. But with datasets like HAM10000 and digital photography, it became easy to record a variety of skin conditions. SkinSage uses cutting-edge neural architectures like CNN, ResNet, DenseNet, and InceptionV3 to recognise patterns and nuances that are much above the capabilities of the human eye. In addition to being a computational marvel, the SkinSage project also exemplifies accessibility by making its analytical capabilities available via a smartphone application in future. High-quality skin lesion diagnostics will be accessible to everyone thanks to this platform, regardless of location or degree of training. With the confluence of these developments, SkinSage becomes more than just a tool for diagnosing skin cancer; it signals a paradigm shift that has the potential to democratise early detection and save countless lives in the future.

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Machine Learning Classification of Shoulder Pain Pathologies: A Scoping Review

Machine Learning Classification of Shoulder Pain Pathologies...

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International Conference on Computing and Networking technology (ICCNT)

作者： Garima Shukla Khushi Bhagat Vedant Chaudhari E Navaneeth Krishnan Mansi Chauhan Bhadauria Yash Chouksey Department of Computer Science and Engineering Amity School of Engineering and Technology Amity University Mumbai Mumbai India

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

Shoulder problem is a widely known musculoskeletal disorder that impacts heavily on the life of patients. Effective treatment for this must be preceded by accurate and timely diagnosis but traditional diagnostic techniques have always been subjective and less reliable. In recent years, machine learning (ML) techniques have shown promising results in improving the accuracy of diagnosing shoulder pain, addressing the limitations of traditional diagnostic methods. Nonetheless, there is a failure to translate these ML models into practical clinical tools that can easily be employed by healthcare professionals. In addition, this paper will present an overview of current understanding and methodologies employed for diagnosing and managing shoulder pain along with reviewing the use of ML techniques in medical image diagnostics. It also suggests development of a user-friendly and accessible diagnosis tool for shoulder pathologies aimed at linking modern research and daily practice in the medical field.

关键词： Pathology Accuracy Pain Reviews Shoulder Standardization Medical services Feature extraction Data models Medical diagnostic imaging

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Statistical Exploration and Sentiment Analysis of WhatsApp Chats using Supervised Learning 23

Statistical Exploration and Sentiment Analysis of WhatsApp C...

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Proceedings of the 5th International Conference on Information Management & Machine Intelligence

作者： Aakarsh Sharma Shweta Sinha Amity School of Engineering and Technology Amity University Gurugram India Computer Science & Engineering Amity University Haryana India

ISBN: (纸本)9798400709418

This paper presents the sentiment analysis of WhatsApp chat data while also evaluating user activity, employing VADER and supervised learning. The study encompasses both sentiment classification utilizing VADER's lexicon-based approach and supervised sentiment analysis using the Naive Bayes and SVM model. The research extends to statistical exploration like identifying the most active user within the group chat dataset and other statistical information. By contrasting the efficiency and accuracy of these techniques, the paper aids in method selection based on specific analysis goals. Results offer insights into sentiment trends and user engagement for informed decision-making.

关键词： Keywords. Naïve Bayes

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