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

作者： Kaushik, Keshav Negi, Rahul Dev, Prabhav University of Petroleum and Energy Studies School of Computer Science Dehradun India University of Petroleum and Energy Studies B.Tech Computer Science and Engineering Dehradun India

ISBN: (纸本)9798350398267

Some prominent instances have been centered on electronic warfare. For example, the American military has made significant investments in automation through UAV programs, only for competitors like the Iranians to create strategies to interfere with these systems. Iran managed to capture a top-secret U.S. surveil-lance drone by fooling it into descending in the incorrect place by jamming its control signals and providing it with bogus GPS data. In this paper, the authors have focused on the electronic warfare approach for deploying a software-based Wi-Fi jammer. The software-based Wi-Fi jammer can disconnect the targets using the DoS pursuit mode. The paper describes the unique methodology of how software can also be used for jamming wireless signals. © 2022 IEEE.

关键词： Wi-Fi

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bioCrypt: Gradient-based facial encoding for key generation to encrypt and decrypt multimedia data

arXiv

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arXiv 2024年

作者： Patel, Ankit Kumar Paul, Dewanshi Giri, Sarthak Chaudhary, Sneha Gautam, bikalpa B.Tech Electronics & Computer Engineering Graduated from VIT University Chennai India B.Tech Computer Science & Engineering Graduated from VIT University Vellore India

Security systems relying on passwords are vulnerable to being forgotten, guessed, or breached. Likewise, biometric systems that operate independently are at risk of template spoofing and replay incidents. This paper introduces a biocryptosystem utilizing face recognition techniques to address these issues, allowing for the encryption and decryption of various file types through the Advanced Encryption Standard (AES). The proposed system creates a distinct 32-bit encryption key derived from facial features identified by Histogram of Oriented Gradients (HOG) and categorized using Support Vector Machines (SVM). HOG efficiently identifies edge-aligned facial features, even in dim lighting, ensuring that reliable biometric keys can be generated. This key is then used with AES to encrypt and decrypt a variety of data formats, such as text, audio, and video files. This encryption key, derived from an individual’s distinctive facial traits, is exceedingly challenging for adversaries to reproduce or guess. The security and performance of the system have been validated through experiments using several metrics, including correlation analysis, Shannon entropy, normalized Hamming distance, and the avalanche effect on 25 different file types. Potential uses for the proposed system include secure file sharing, online transactions, and data archiving, making it a strong and trustworthy approach to safeguarding sensitive information by integrating the uniqueness of facial biometrics with the established security of AES encryption. © 2024, CC bY.

关键词： Hamming distance

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Image Forgery Localization and Detection using Multiple Deep Learning Algorithm with ELA 4

Image Forgery Localization and Detection using Multiple Deep...

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International Conference on 4th Industrial Revolution based technology and Practices, ICFIRTP 2022

作者： Singh, Anshul Kumar Sharma, Chandani Kumar Singh, brajesh Quantum University Department of Computer Science and Engineering Roorkee India R. B. S. Engg. Tech. Campus Department of Computer Science and Engineering Agra India

ISBN: (纸本)9798350345919

In today's technical world, social media may help an individual grow significantly. On the other side, we must not overlook the reality that it is also a large platform for criticism. With recent advancements, approaches for creating and manipulating multimedia information may now deliver a highly sophisticated level of realism. There has been a blurring of the line between real media and fake media in recent years. Creative arts, film production, advertising, and video gaming are among the industries that could benefit from this technology. However, it poses significant security risks. Software tools freely accessible on the internet enable anybody, with no particular abilities, to generate extremely convincing phony images and films. A dataset composed of real photographs and false images is used in this article to identify images of modifications using Deep Learning algorithms with Error Level Analysis on each image. Our experiment yielded the accuracies of 93.5%, 89.1 and 92.4% in ResNet50, Vgg16 and CNN respectively for 50 epochs. © 2022 IEEE.

关键词： CNN ELA Image Forgery Real vs. Fake detection ResNet50 Vgg16

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An Innovative Method for Mobile Network Payment Security System based on hybrid LSTM-Ensemble Learning-based Model 3

An Innovative Method for Mobile Network Payment Security Sys...

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3rd International Conference for Advancement in technology, ICONAT 2024

作者： Sujatha, N. Pramod, S. Aravindh, S. babu, balagopala Ramesh Devi, S. Rukmani Ananthi, M. B. M. S. College of Engineering Department of Mathematics Karnataka Bengaluru India Nitte Meenakshi Institute of Technology Yelahanka Department of Mathematics Karnataka Bangalore India Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Department of Computer Science and Engineering Tamilnadu Chennai India SRKR Engineering College Department of Computer Science and Engineering Andhra Pradesh Bhimavaram India SIMATS Deemed to Be University Saveetha College of Liberal Arts and Sciences Department of Computer Science Tamilnadu Chennai India KGiSL Institute of Technology Department of Computer Science and Business Systems Tamilnadu Coimbatore India

ISBN: (纸本)9798350354171

It is common practice in many industries to use cash since it accounts for more than 85% of payments in almost all developing countries. A cell phone is become an everyday item. Mobile phones have practically become people's constant companions due to the plethora of other uses they offer beyond just communicating. Since they are both cheap and multipurpose, soon everyone will be utilizing them. In an ideal world, everyone would use their cell phone for everything. Verification, preprocessing, and training the model are the three parts that make up the method. In order to confirm the payment, the customer's biometric template is checked during the verification procedure. The three stages of fingerprint preparation include matching fingerprint templates, extracting fingerprint minutiae, and fingerprint preprocessing. The training of the model was carried out using a Hybrid LSTM-Ensemble Learning. The average accuracy of the suggested method is 92.76%, which is higher than LSTM and Ensemble Learning. © 2024 IEEE.

关键词： Contrastive Learning

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IoT Enabled Anti-Child Trafficking System Using Data Analysis

IoT Enabled Anti-Child Trafficking System Using Data Analysi...

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Communication, Computing and Signal Processing (IICCCS), IEEE International Conference on

作者： Rittika Paul Zarin Tasnim Mim Alex Mathew Roy Piyush Chauhan Dewan Ahanaf Tahsen B-Tech of Computer Science and Engineering-IoT Jain (Deemed-to-be University) Bangalore India Computer Science and Engineering-IoT Jain (Deemed-to-be University) Bangalore India

ISBN: (数字)9798350390759

ISBN: (纸本)9798350390766

The increasing prevalence of child trafficking in the South particularly in bangladesh, India, and Nepal requires a creative solution that can go beyond the orthodox preventative techniques. This continuously growing issue mainly violates the fundamental rights of children, for example liberty, education, social support, and economic opportunities. Trafficked children must go through physical and sexual abuse, which turns into slavery, forced labor, and committing crimes like begging, theft, and delivering drugs. To create a definitive system that targets detecting and response for stopping child abduction and trafficking, this research provides an anti-child trafficking device that is embedded with different types of sensors and location trackers. These sensors are used to collect accurate data or information for real-time child monitoring. The collected data can be used for detecting potential trafficking routes and predicting future circumstances. Using these technologies, it is possible to create a protective boundary for children. This research paper presents a model of combined sensors of our proposed wearable device. It can be considered a resolver in the prevention of child trafficking and abduction, by providing any alert or messages to the parents now.

关键词： Data analysis Accuracy Target tracking Web services Signal processing Real-time systems Telecommunication computing Wearable devices Monitoring Wearable sensors

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Particle Swarm Optimization for Efficient brain Tumor Classification Using InceptionV3 Deep Learning Model 9

Particle Swarm Optimization for Efficient Brain Tumor Classi...

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9th International Conference on Communication and Electronics Systems, ICCES 2024

作者： Akhila, P. Prabaharan, G. Pandiiyan, K. Swarna, S.L. Hussain, A. Sakthivelu, U. B V Raju Institute of Technology Department of Artificial Intelligence and Machine Learning Telangana Narsapur India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Avadi Chennai India Srm Arts and Science College Department of Computer Science with Artificial Intelligence Kattankulathur Chengalpattu India Sona College of Technology Department of Computer Science Science and Engineering Junction Main Road Tamil Nadu Salem India College of Engineering and Technology Srm Institute of Science and Technology Department of Networking and Communications Tamil Nadu Kattankulathur India

ISBN: (纸本)9798350377972

This research proposes a novel framework for brain tumor classification utilizing a combination of deep learning and optimization techniques. The framework employs an autoencoder network for image preprocessing, followed by SegNet for accurate tumor segmentation. The core classification is performed using the InceptionV3 model, further optimized through Particle Swarm Optimization (PSO) to enhance predictive performance. The proposed system achieved a classification accuracy of 98.75% on a dataset of 7,023 MRI images, demonstrating its effectiveness in accurately classifying brain tumors. This research contributes to the advancement of medical image analysis and provides a valuable tool for supporting clinicians in the early diagnosis and treatment of brain tumors. © 2024 IEEE.

关键词： Particle swarm optimization (PSO)

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An approach for exploiting and mitigating Log4J using Log4Shell vulnerability 3

An approach for exploiting and mitigating Log4J using Log4Sh...

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3rd International Conference on Computation, Automation and Knowledge Management, ICCAKM 2022

作者： Kaushik, Keshav Dass, Alpana Dhankhar, Ayush University of Petroleum and Energy Studies School of Computer Science Dehradun India University of Petroleum and Energy Studies Student B.Tech Computer Science and Engineering Dehradun India

ISBN: (数字)9781665453196

ISBN: (纸本)9781665453196

A new serious flaw has been discovered in log4j, a popular open-source tool used to produce logs within Java programs. The Log4Shell vulnerability, also referred as CVE-2021-44228, enables Remote Code Execution (RCE), enabling attackers to run obfuscated code on the host. A large number of programmes and businesses, including the well-known game Minecraft, employ the well-known utility log4j. Additionally, it is utilised in numerous commercial products as well as several Apache frameworks including Struts2, Kafka, Druid, and Flink. In this paper, the authors have used an approach to exploit the Log4Shell vulnerability and then provided the mitigation methods for the same. © 2022 IEEE.

关键词： Open source software

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Resonating Silence: Music Perception in the Deaf and Hard of Hearing

Resonating Silence: Music Perception in the Deaf and Hard of...

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IEEE UP Section Conference on Electrical computer and Electronics (UPCON)

作者： Mahak Garg Akanksha Yadav Kiran Singh B.Tech Computer Science and Engineering Galgotias University Greater Noida India School of Computer Science & Engineering Galgotias University Greater Noida India

ISBN: (数字)9798350378726

ISBN: (纸本)9798350378733

Music is traditionally considered an auditory experience; however, the perception of music by Deaf and hard-of-hearing individuals challenges this assumption. This paper examines how people who are Deaf engage with music through a multisensory approach, emphasizing vibration, touch, and visual elements. by analyzing data from the Frontier and Kaggle database, the study explores how hearing-impaired individuals interpret and emotionally respond to rhythmic vibrations. Participants, aged 10–40, interacted with a haptic device that produced both musical and non-musical vibrations. Age-based trends emerged: older participants often associated vibrations with musical instruments, while younger participants connected them to common household objects. Emotional responses varied, with younger individuals showing heightened excitement and older participants experiencing greater relaxation. Findings indicate that tactile rhythms can foster meaningful associations and emotions across age groups, providing insights into sensory-based musical experiences for those who are hearing-impaired. This paper synthesizes literature, case studies, and data from the Frontier database to highlight the various ways music can be felt and comprehended beyond hearing. by underscoring the holistic and multisensory dimensions of music, it argues for appreciating sound and music through a broader understanding of sensory experiences.

关键词： Vibrations Visualization Databases Instruments Music Auditory system Real-time systems Haptic interfaces Emotional responses Artificial intelligence

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Anti-Remote Disk Imaging: A Comprehensive Approach to Prevent Unauthorized Data Access

Anti-Remote Disk Imaging: A Comprehensive Approach to Preven...

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Data science, Agents & Artificial Intelligence (ICDSAAI), International Conference on

作者： K. Venketesh M. Caleb Gunalan Manoj Hariharan R Rahul S Surender R Department of Computer Science and Engineering Kalasalingam Academy of Research and Education Tamilnadu India B.Tech Computer Science and Engineering Kalasalingam Academy of Research and Education Tamilnadu India

ISBN: (数字)9798331537555

ISBN: (纸本)9798331537562

Remote disk imaging is an emerging cybersecurity risk that compromises sensitive information integrity. Malicious actors exploit legitimate tools like dd and Clonezilla to clone and exfiltrate data remotely. This paper introduces a novel anti-remote disk imaging system that integrates process monitoring, dynamic firewall configurations, and full-disk encryption to mitigate unauthorized disk access. Unlike existing singular approaches, our unified solution offers real-time detection, prevention, and administrative alerts. Comparative analyses reveal that our tool outperforms existing techniques with a 92% effectiveness rate and an average response time of 3 seconds while maintaining low resource usage. These results highlight its practicality for safeguarding critical systems in resource-constrained environments. Remote disk imaging poses challenges such as real-time detection, resource constraints, and distinguishing between legitimate and malicious activities. Existing techniques, like full-disk encryption and firewall-based blocking, face limitations in adaptability and performance. This paper introduces a comprehensive system that addresses these challenges by integrating process monitoring, dynamic firewall configurations, and encryption to prevent unauthorized disk imaging.

关键词： Process monitoring Firewalls (computing) Prevention and mitigation Imaging Machine learning Real-time systems Software Encryption Time factors Information integrity

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Enhancing Security in IoT Networks Through RDAD for Attack Detection in RPL-Enabled Environments

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SN computer science 2024年第7期5卷 864页

作者： Sridhar, K. Kumar, b. Anjanee Devi, S. Anjali Raju, Vadali Pitchi Soni, Anita Singh, Pallavi Deore, Shailesh Shivaji Department of Mechanical Engineering Lendi Institute of Engineering and Technology Andhra Pradesh Vizianagaram India Department of Electronic and Communication Engineering Dadi Institute of Engineering and Technology Gavarapalem Andhra Pradesh Anakapalle India Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram Andhra Pradesh Guntur India Indur Institute of Engg. & amp Tech Siddipet India IES University Bhopal India Department of ECE Hindustan Institute of Technology and Science TN Chennai India Department of Computer Engineering SSVPS B S DEORE College of Engineering Maharashtra Dhule India

The “Internet of Things” (IoT) revolutionizes technology integration, enabling interconnected devices to communicate both among themselves and with the online realm. These smart gadgets collect valuable data, facilitating remote sharing via networked connections. Yet, their constrained memory, power, and computational capacities pose challenges. Within IoT, devices vary in functionality, from fully capable to limited subsets. These communication methods are integral to IoT's existence. Security is paramount when deploying IoT applications due to the inevitability of routing attacks aiming to intercept data in transit. To thwart such unauthorized access, Rank Decreased Attack Detection (RDAD) emerges as a crucial solution. Developed with IoT in mind, the Routing Protocol for Low-Power and Lossy Networks (RPL) serves as an anticipatory routing protocol. In an IoT environment, routing flaws can obscure data, thus highlighting the significance of RPL's topology-building process, which prioritizes nodes based on a ranking measure. RDAD proposes a mechanism that considers a parent node's Packet Delivery Ratio (PDR) to select trustworthy routing paths for data packets. Comparative analysis reveals RDAD's superiority over existing detection methods, significantly enhancing packet delivery rates and minimizing losses. With a detection rate of nearly 96.5% for RDA attacks, RDAD emerges as a potent safeguard for IoT routing security. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024.

关键词： INTI IoT PDR RDAD RPL

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