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361 results on '"Kumari, Sneha"'

4. Leveraging LSTM and GAN for Modern Malware Detection

Author

Gupta, Ishita, Kumari, Sneha, Jha, Priya, and Ghosh, Mohona

Subjects
Computer Science - Cryptography and Security, Computer Science - Artificial Intelligence
Abstract

The malware booming is a cyberspace equal to the effect of climate change to ecosystems in terms of danger. In the case of significant investments in cybersecurity technologies and staff training, the global community has become locked up in the eternal war with cyber security threats. The multi-form and changing faces of malware are continuously pushing the boundaries of the cybersecurity practitioners employ various approaches like detection and mitigate in coping with this issue. Some old mannerisms like signature-based detection and behavioral analysis are slow to adapt to the speedy evolution of malware types. Consequently, this paper proposes the utilization of the Deep Learning Model, LSTM networks, and GANs to amplify malware detection accuracy and speed. A fast-growing, state-of-the-art technology that leverages raw bytestream-based data and deep learning architectures, the AI technology provides better accuracy and performance than the traditional methods. Integration of LSTM and GAN model is the technique that is used for the synthetic generation of data, leading to the expansion of the training datasets, and as a result, the detection accuracy is improved. The paper uses the VirusShare dataset which has more than one million unique samples of the malware as the training and evaluation set for the presented models. Through thorough data preparation including tokenization, augmentation, as well as model training, the LSTM and GAN models convey the better performance in the tasks compared to straight classifiers. The research outcomes come out with 98% accuracy that shows the efficiency of deep learning plays a decisive role in proactive cybersecurity defense. Aside from that, the paper studies the output of ensemble learning and model fusion methods as a way to reduce biases and lift model complexity., Comment: 11 pages

Published
2024

26. Systematic Review on Growth of E-Agriculture in Context of Android-Based Mobile Applications

Author

Kumbhar, Vidya, Patil, Ashwini, Kumari, Sneha, Bharti, Nisha, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Tuba, Milan, editor, Akashe, Shyam, editor, and Joshi, Amit, editor

Published
2023
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27. Assessment of Risks and Risk Management for Agriculture Supply Chain

Author

Kumari, Sneha, Venkatesh, V. G., Shi, Yangyan, Sushil, Series Editor, Chroust, Gerhard, Editorial Board Member, Connell, Julia, Editorial Board Member, Evans, Stuart, Editorial Board Member, Fujiwara, Takao, Editorial Board Member, C. Jackson OBE, Mike, Editorial Board Member, Jain, Rashmi, Editorial Board Member, Palanisamy, Ramaraj, Editorial Board Member, A. Stohr, Edward, Editorial Board Member, Paul, Sanjoy Kumar, editor, Agarwal, Renu, editor, Sarker, Ruhul Amin, editor, and Rahman, Towfique, editor

Published
2023
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40. Mn and Zn-Doped Multivariate Metal-Organic Framework as a Metalloimmunological Adjuvant to Promote Protection Against Tuberculosis Infection

Author

Howlett, Thomas S., primary, Kumari, Sneha, additional, Ehrman, Ryanne, additional, Masson, Jesse, additional, Izzo, Linda, additional, Wang, Trixie, additional, Gull, Humera, additional, Tang, Wendy, additional, Trashi, Orikeda, additional, Satish, Neha, additional, Wijesundara, Yalini, additional, Herbert, Fabian, additional, Izzo, Angelo, additional, and Gassensmith, Jeremiah, additional

Published
2024
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49. Impact of corporate social responsibility on sustainable agriculture and livelihood of farmers.

Author

Misra, Shuchi Benara, Kumari, Sneha, and Miglani, Varun

Subjects
SOCIAL responsibility of business, SUSTAINABLE agriculture, AGRICULTURE, RURAL development, TRADITIONAL farming
Abstract

Rural areas have low levels of advancement and access to resources compared to urban regions, and elevating these regions is fundamental for accomplishing balanced and sustainable development. Rural uplifting typically includes a range of interventions, and by drawing in local stakeholders, rural uplifting projects can make sustainable arrangements that are custom‐made for each community's unique difficulties and opportunities. Corporate social responsibility (CSR) can contribute to and aid the government's efforts in rural development. CybageAsha's (CSR department of Cybage Software) flagship programs seek to improve rural communities through sustainable solutions. These encompass income‐generating interventions using contemporary agricultural methods as well as infrastructure development. This article analyses the impact of agricultural interventions on the farmers' livelihoods carried out by CybageAsha in 19 villages across the Pune district (India) by using the t‐test and difference‐in‐difference approach. Findings reveal that the shift from traditional farming methods to adopting new farming methods among beneficiaries has added value in improving the beneficiaries' yields, incomes, skills, and livelihood. CybageAsha's interventions positively impacted the beneficiaries, contributing to agricultural development, livelihood improvement, income generation, and a decline in migration. However, there is a need for continuous support and improvement to sustain the benefits for farmers. The article provides a new understanding for researchers and practitioners about the CSR approaches towards agricultural development. Addressing the challenges and concerns identified in the data analysis will further enhance the effectiveness of rural uplifting initiatives. [ABSTRACT FROM AUTHOR]

Published
2024
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