IJARCCE adheres to the suggestive parameters outlined by the University Grants Commission (UGC) for peer-reviewed journals, upholding high standards of research quality, ethical publishing, and academic excellence.
NATIONAL CONFERENCE ON INNOVATION IN OPEN SOURCE CIRCUITS on
th, th & th September, CISC, ECHO (Electronics and Communication Heuristics Organization) in, association with the Centre for Collaborative Research in Robotics and, AI and the e- Yantra Project, IIT Bombay
NATIONAL CONFERENCE ON INNOVATION IN OPEN SOURCE CIRCUITS on
th, th & th September, CISC, ECHO (Electronics and Communication Heuristics Organization) in, association with the Centre for Collaborative Research in Robotics and, AI and the e- Yantra Project, IIT Bombay
Open Source Software Licenses: A Comparative Analysis of GPL, MIT, and Apache Manjunath S Rakaraddi, Bhairam V Pawar, Rahul M, Raviteja Javali,
Muhibur Rahman T. R
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Department of Computer Science and Engineering, Arasu Engineering College Prevention and Detection of Botnet Attacks using Double layered machine learning Technique
S. Parvathy, S. Mounika, M. Nihidha, M. Sruthi
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Detection of Blackhole and Sinkhole Attacks in Wireless Sensor Networks Using a Lightweight Secure Protocol
C. Karthika and Dr. P. E. Irin Dorathy
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Abstract
NATIONAL CONFERENCE ON INNOVATION IN OPEN SOURCE CIRCUITS on
th, th & th September, CISC, ECHO (Electronics and Communication Heuristics Organization) in, association with the Centre for Collaborative Research in Robotics and, AI and the e- Yantra Project, IIT Bombay
NATIONAL CONFERENCE ON INNOVATION IN OPEN SOURCE CIRCUITS on
th, th & th September, CISC, ECHO (Electronics and Communication Heuristics Organization) in, association with the Centre for Collaborative Research in Robotics and, AI and the e- Yantra Project, IIT Bombay
Open Source Software Licenses: A Comparative Analysis of GPL, MIT, and Apache Manjunath S Rakaraddi, Bhairam V Pawar, Rahul M, Raviteja Javali,
Muhibur Rahman T. R
Abstract: Open-source software licensing plays a vital role in modern software development by defining the legal permissions, responsibilities, and limitations associated with the use, modifi-cation, and distribution of software. Among the numerous open-source licenses available, the GNU General Public License (GPL), MIT License, and Apache License 2.0 are widely adopted due to their distinct licensing models and practical significance in both academic and industrial environments. This paper presents a comparative study of these three major open-source licenses by analyzing their features, permissions, restrictions, distribution policies, and patent considerations. The GPL license emphasizes software freedom through its copyleft approach, requiring deriva-tive works to remain open source, whereas the MIT License pro-vides maximum flexibility with minimal restrictions. The Apache License 2.0 combines permissive licensing with explicit patent protection, making it suitable for commercial and enterprise applications. The study highlights the advantages, limitations, and real-world applications of each license to help developers, researchers, and organizations select appropriate licensing strate-gies for software projects. The analysis demonstrates that the choice of an open-source license significantly impacts software collaboration, legal compliance, commercial adoption, and long-term project sustainability.
Department of Computer Science and Engineering, Arasu Engineering College Prevention and Detection of Botnet Attacks using Double layered machine learning Technique
S. Parvathy, S. Mounika, M. Nihidha, M. Sruthi
Abstract: In multi level botnet attack in prevailing cyber attacks in the IoT environment starts and ends detection activities. In existing detection of botnet attacks compromising the IoT devices initially performs ddos attacks. According to the various performances of existing machine learning botnet detection model is limited to the trained data which are already specified. The consequences towards the datasets according to the diversified attack patterns that performs perfectly will be questionable. In our proposed methodology the generalized scanning of datasets in DDoS attacks generates 33 varieties of detection patterns. Integration of detecting samples of DDoS at tacks with publicly available datasets within the limit of more attacks. Proposed prevention and detection of double layered machine learning techniques helps in training the dataset models. Prior to the attacking stage the IoT botnet attacks identifies from the trained double layered attack identification and detection models. In the next layer efficiency of datasets detection approach with more accuracy and precise training models will be provided.
Detection of Blackhole and Sinkhole Attacks in Wireless Sensor Networks Using a Lightweight Secure Protocol
C. Karthika and Dr. P. E. Irin Dorathy
Abstract: Wireless Sensor Networks (WSNs) are widely used in critical applications such as environmental monitoring, healthcare, and industrial automation, where secure and reliable data transmission is essential. However, due to resource constraints and unattended deployment, WSNs are highly vulnerable to routing attacks such as blackhole and sinkhole attacks. This paper proposes a simple and lightweight trust-based security protocol designed to detect and isolate malicious nodes with minimal computational and communication overhead. The protocol operates in three key stages: neighbour monitoring, trust evaluation, and secure route selection. In the monitoring phase, nodes locally observe the packet forwarding behaviour of their one-hop neighbours. A combined trust score is then computed using forwarding reliability and traffic consistency metrics to accurately identify malicious behaviour. Nodes with low trust scores are isolated through a distributed blacklist mechanism. Finally, secure routing decisions are made by selecting nodes with high trust values and sufficient residual energy, ensuring both reliability and energy efficiency. The proposed approach effectively detects both blackhole and sinkhole attacks while maintaining low overhead, making it suitable for resource- constrained WSN environments.
