Volume-11 , Special Issue-01 , Nov - 2023

Distributed Denial of Service (DDoS) attacks pose significant threats to online services and networks by overwhelming targeted systems with malicious traffic. This paper provides a comprehensive review of DDoS attacks and explores various mitigation strategies employed by organizations to defend against these attacks. The study focuses on recent developments in attack techniques and discusses the effectiveness of different mitigation approaches. By understanding the evolving landscape of DDoS attacks and the corresponding countermeasures, organizations can enhance their resilience and minimize the impact of such attacks.

DDOS, mitigation strategies, characteristics, traffic, attacks, countermeasures

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Amit Dogra, Taqdir, "DDoS Attacks: Trends, Mitigation Strategies, and Future Directions," International Journal of Computer Sciences and Engineering, Vol.11, Issue.01, pp.221-230, 2023.

T Efficient attendance management plays a crucial role in the success of educational institutions. This paper proposes a novel approach to enhance attendance management through the utilization of the Model-View-Controller (MVC) architecture. Traditional manual methods for attendance calculation are prone to errors and time-consuming. To address these challenges, an effective web application is designed to electronically monitor student activity in the classroom and store attendance records in a database. The application leverages the power of the Laravel Framework and incorporates JavaScript for improved usability. By implementing the MVC architecture, the system enables easy manipulation of attendance data through a user-friendly graphical user interface (GUI). Moreover, the system takes into account the distinction between theoretical and practical teaching hours, facilitating accurate calculation of student absences. The successful implementation and testing of the system demonstrate its readiness to manage student attendance in any department of a university. This paper provides valuable insights into leveraging MVC architecture for attendance management and offers a practical solution to enhance efficiency and accuracy in educational institutions.

Attendance management, Model-View-Controller (MVC), Web application, Electronic monitoring, Attendance records, Laravel Framework.

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Rudra Pratap Singh, Madhav Arora, Gurwinder Singh, "Improving Attendance Management in Educational Institutions: A Model View Controller Approach," International Journal of Computer Sciences and Engineering, Vol.11, Issue.01, pp.231-235, 2023.

This study delves further into the design and analysis of an Automatic Sun Tracking Solar Panel based on the open loop concept. The primary goal of this project is to maximise solar energy utilisation by effectively capturing sunlight and converting it into electrical energy for a variety of purposes. The method increases power output by putting the solar panel perpendicular to the sun`s rays, which maximises sunlight absorption. Moreover, this tracking system operates independently of the intensity of the sunrays, accurately determining the sun`s coordinates and automatically adjusting its position accordingly. This method ensures the solar panel`s excellent efficiency and dependability. This project`s main advantage is its capacity to provide access to a sustainable and ecologically favourable source of energy. This solar tracking system can be integrated into local communities and, when connected to large-scale battery banks, can cater to their energy requirements independently. Overall, this research advances renewable energy technologies, allowing for the broad deployment of solar power systems.

Sun tracking, Solar panel, Solar energy, Electricity generation, Environment friendly, Battery, Open loop, Everlasting, Decentralized

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[10] B. O. Anyaka, D. C. Ahiabuike, and M. J. Mbunwe, "Improvement of PV Systems Power Output Using Sun-Tracking Techniques," International Journal of Computational Engineering Research, vol. 3, no. 9, pp. 80-98, 2013.

P Roy, A Das, A Simlai, I Mondol, T Nag, J Ghosh, S Bhowmik, A Bhowmik, P Sarkar, S Majumdar, "Sun Trailing Solar Panel System for Improving Energy Efficiency," International Journal of Computer Sciences and Engineering, Vol.11, Issue.01, pp.236-242, 2023.

Numerous applications are possible for Wireless Sensor Networks (WSNs). However, there are a number of implementations where the sensor data is useless and may lead to an false analysis of the provided information, especially if the coordinates information is unknown. Because of this, localization is crucial to many WSN operations. The problems and difficulties preventing the position of the sensor nodes in WSNs are thoroughly examined in this research. The fundamental concept behind a sensor network is to disperse tiny sensing devices which is capable of detecting changes in incidents or parameters and interacting with other devices over a defined geographic area for a variety of objectives, such as target tracking, vigilance, and environmental tracking. It is profitable to be utilized in great abundance in the future by integrating sensor technologies with computing power and wireless connectivity. A variety of security risks are also brought on by the use of wireless communication technology. In this essay, issues and difficulties with wireless sensor networks are surveyed.

Wireless Sensor Network, Localization, Sensor node, Network, Sensing devices, Environment monitoring

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Sucheta Panda, Sushree Bibhuprada B. Priyadarshini, "A Comprehensive Study of Various Challenges and Constraints in Wireless Sensor Networks (WSNs)," International Journal of Computer Sciences and Engineering, Vol.11, Issue.01, pp.243-248, 2023.

The use of deep learning technology in the domain of biodiversity has been expanding over the past few years, with applications in wildlife and vegetation monitoring. The Convolutional (CNN) is a powerful tool that has enabled new feature extraction methods in computer vision. Remote sensing techniques, such as satellite and drone-assisted images, have also contributed to the development of vegetation cover assessment. This study focuses on detecting changes in vegetation cover in the Sundarbans mangrove forest, which is the world`s largest mangrove and a heritage site that supports over 4.37 million people and reduces 45 million tons of CO2. The study Neural Network used a deep learning model to analyze time-series data and achieved an accuracy score of 99.85% and a value of 1 for the other three metrics - precision, recall, and F1-Score. The study also includes a review of previous work in the field and proposes a novel model for vegetation cover assessment. This study emphasizes the importance of sustaining the ecology of the Sundarbans and provides valuable insights for future research in this field.

Mangrove Forest; Deep Learning; Convolutional Neural Network; Remote Sensing Images.

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S. Chakraborty, S. Nandi, S. Ahmed, N. Adhikari, M. Sultana, S. Bhattacharya, "Detecting Density Changes of Mangrove Forest in India using Remotely Sensed Images," International Journal of Computer Sciences and Engineering, Vol.11, Issue.01, pp.249-256, 2023.

The rapid advancement of the Internet of Things (IoT) has sparked a paradigm shift across industries, revolutionizing traditional approaches to data collection, analysis, and utilization. In particular, the integration of IoT technologies within the healthcare domain has ushered in transformative possibilities that hold the potential to enhance patient care, improve clinical outcomes, and optimize healthcare operations. This research paper aims to comprehensively explore the multifaceted landscape of IoT in healthcare, delving into the benefits, challenges, and untapped avenues of future research. The primary objective of this research is to provide a thorough examination of the advantages offered by IoT applications in healthcare, ranging from empowering real-time patient monitoring to enabling predictive analytics for disease management. IoT`s seamless amalgamation with healthcare has paved the way for remote patient monitoring, where wearable devices and sensors continuously collect and transmit vital signs, fostering proactive interventions and personalized healthcare. This real-time health tracking not only empowers patients to actively engage in their well-being but also equips healthcare providers with timely data for informed decision-making. Predictive analytics powered by IoT further elevates disease management by utilizing data-driven insights to anticipate outbreaks, detect anomalies, and enhance preventive strategies. The interconnectedness of IoT devices ensures that patient care is finely tuned and tailored, ultimately contributing to improved patient outcomes and an elevated quality of care. Additionally, the marriage of IoT with healthcare operations manifests in optimized hospital efficiency, streamlining inventory management, resource allocation, and energy consumption. However, alongside these transformative benefits, the assimilation of IoT into healthcare presents a spectrum of challenges that necessitate careful consideration. Data security and privacy concerns loom large, as the constant stream of sensitive health data creates vulnerabilities that must be fortified through robust encryption mechanisms and access controls. The interoperability puzzle also emerges as a critical challenge, demanding standardized protocols to seamlessly integrate diverse IoT devices and systems within complex healthcare ecosystems. Ethical dilemmas entwined with patient consent and the responsible use of data surface prominently, requiring a balance between innovation and safeguarding patient autonomy. Moreover, the regulatory landscape introduces its own complexities, where adherence to frameworks such as the Health Insurance Portability and Accountability Act (HIPAA) and the General Data Protection Regulation (GDPR) is paramount. The integration of IoT with established healthcare infrastructure poses integration challenges, necessitating thoughtful strategies to harmonize new technologies with legacy systems. Looking ahead, the future scope of research in IoT-driven healthcare holds immense promise and potential. The paper underscores several avenues for further exploration. Advanced data analytics emerges as a fertile ground, where the synergy of machine learning and AI algorithms can extract intricate insights from the deluge of IoT-generated healthcare data, facilitating early disease detection and personalized treatment pathways. The application of blockchain technology surfaces as a means to bolster data security, privacy, and interoperability, providing a decentralized and tamper-proof framework for health data exchange. Integrating AI and machine learning with IoT extends the boundaries of predictive analytics, enabling more accurate prognostications and informed clinical decisions. The development of standardized protocols specifically tailored for healthcare IoT is essential to ensure harmonious coexistence of devices and systems while upholding data integrity and security. Addressing the ethical and legal conundrums intrinsic to IoT in healthcare warrants interdisciplinary research efforts to devise frameworks that strike a balance between innovation and ethical imperatives. This research paper navigates the dynamic realm of IoT in healthcare, charting its benefits, confronting its challenges, and illuminating the path for future research. IoT`s integration with healthcare is a cornerstone of innovation that has the potential to revolutionize patient care, redefine healthcare operations, and drive data-driven insights. By addressing the challenges and exploring the promising future avenues, this research contributes to the growing body of knowledge that shapes the future of healthcare, where IoT emerges as a beacon of transformative potential.

IoT, healthcare system, IoT security, data security, data privacy, security challenges

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Srikanta Kolay, Tryambak Hiwarkar, "IoT in Healthcare: Benefits, Challenges and Future Scope of Research," International Journal of Computer Sciences and Engineering, Vol.11, Issue.01, pp.257-265, 2023.

An application called WhatsApp has emerged as the most popular and effective means of communication in recent years. The heroku web application called WhatsApp Chat analyzer provides analysis of WhatsApp groups. In this paper authors applied matplotlib, streamlit, seaborn, re, pandas, and certain NLP concepts for analyzing WhatsApp chart. Here authors combine machine learning with NLP. This WhatsApp conversation analyzer imports a user`s WhatsApp chat file, analyses it, and produces various visualizations as a consequence.

WhatsApp chat analyzer, NumPy , Pandas , NLP, Matplotlib

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Amrut Ranjan Jena, Pratyush Kumar, Rafiqul Islam, "WhatsApp Analyzer: A Tool to Measure the User Performance in Social Platform," International Journal of Computer Sciences and Engineering, Vol.11, Issue.01, pp.266-269, 2023.

This increase in data is not going to slow down anytime soon. Data too large or complex for traditional database systems can be ingested, processed, and analyzed using a big data architecture. Depending on the capabilities of a company`s users and tools, the threshold for entering into the big data realm may differ. This paper is mainly focuses on essential questions for Big Data Architecture – What is Big Data Architecture, Big Data Architecture Layers, Types of Big Data Architecture, Big Data Architecture Application, Benefits of Big Data Architecture and Big Data Architecture Challenges.

Big Data Architecture, Data Lake, Lambda Architecture, Kappa Architecture, Data Ingestion, Data Visualization.

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Srinjoy Saha, Sneha Nej, Rupa Saha, Debmitra Ghosh, Anal Rauth, "A Review on Big Data Architecture and It`s Application for Future Aspect," International Journal of Computer Sciences and Engineering, Vol.11, Issue.01, pp.270-276, 2023.

An abstract is a short summary of your research paper, usually about a paragraph (150-300 words) long. A well-written abstract can let readers get the essence of your paper, prepare readers to follow the detailed information, analyses, and arguments in your full paper, and help readers remember the key points. Note: -Special symbols, mathematical formulas, and equations are not allowed in the "Abstract" section. References should not be cited in the abstract

The authors must provide up to 6-8 keywords for indexing purposes (vital words of the article)

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Sucheta Panda, Sushree Bibhuprada B. Priyadarshini, "A Review on Localization Strategies in Wireless Sensor Networks using Beacon nodes," International Journal of Computer Sciences and Engineering, Vol.11, Issue.01, pp.277-283, 2023.

This paper presents a blockchain-based mailing service designed to enhance email communication security, privacy, and accountability while effectively preventing spam through the application of machine learning techniques. By leveraging blockchain technology, the proposed system ensures verification and authentication of user identities, granting access to messages solely to authorized parties. A robust anti-spam system is established by utilizing blockchain`s capabilities, effectively filtering out unwanted emails and reducing the risk of phishing attacks. The integration of machine learning algorithms and natural language processing enables the analysis of email content for identification of potential spam mails. Furthermore, the blockchain serves as a transparent and auditable record of all sent and received emails, promoting greater accountability. Nevertheless, challenges related to maintaining user anonymity, achieving verification and authentication, and addressing scalability concerns require careful consideration. The proposed system incorporates a spam mail detection mechanism, integrating blockchain technology to secure email communication and prevent spam while utilizing machine learning-based algorithms to filter unwanted emails. Experimental results demonstrate the effectiveness of the system in spam detection, highlighting its ability to provide a secure and reliable mailing service.

Blockchain-based mailing service, Email communication, Spam prevention, Machine learning.

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