Modelling Features-Based Birthmarks for Security of End-to-End Communication System by Meilian Li (733635)

Improving the security of SNMP in wireless networks by Otrok, H.

“…Simple network management protocol (SNMP) is widely used for monitoring and managing computers and network devices on wired and wireless network. …”
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Features-Based IoT Security Authentication Framework Using Statistical Aggregation, Entropy, and MOORA Approaches by Habib Ullah Khan (12024579)

Automated Deep Learning BLACK-BOX Attack for Multimedia P-BOX Security Assessment by Zakaria Tolba (16904718)

Attack-Specific Feature Selection for Anomaly Detection in Software-Defined Networks by Abbas, Nadine

“…Due to the rapid advancement of technologies including the tremendous growth of multimedia content, cloud computing and mobile usage, conventional networks are not able to meet the demands. …”
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Engineering the advances of the artificial neural networks (ANNs) for the security requirements of Internet of Things: a systematic review by Yasir Ali (799969)

TIDCS: A Dynamic Intrusion Detection and Classification System Based Feature Selection by Zina Chkirbene (16869987)

“…In this paper, we propose two models for intrusion detection and classification scheme Trust-based Intrusion Detection and Classification System (TIDCS) and Trust-based Intrusion Detection and Classification System- Accelerated (TIDCS-A) for secure network. TIDCS reduces the number of features in the input data based on a new algorithm for feature selection. …”

AI-powered malware detection with Differential Privacy for zero trust security in Internet of Things networks by Faria Nawshin (21841598)

A Features-Based Privacy Preserving Assessment Model for Authentication of Internet of Medical Things (IoMT) Devices in Healthcare by Habib Ullah Khan (12024579)

PAST-AI: Physical-Layer Authentication of Satellite Transmitters via Deep Learning by Gabriele Oligeri (14151426)

Subjects:

A novel intrusion detection framework for optimizing IoT security by Abdul Qaddos (20748779)

LLMs Have Rhythm: Fingerprinting Large Language Models Using Inter-Token Times and Network Traffic Analysis by Saeif Alhazbi (17058108)

Subjects:

Fast Text Classification using Lean Gradient Descent Feed Forward Neural Network for Category Feature Augmentation by Attieh, Joseph

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Static Video Summarization Using Video Coding Features with Frame-level Temporal Sub-Sampling and Deep Learning by Issa, Obada

“…The frame-level temporal subsampling techniques are based on cosine similarity and PCA projections of feature vectors. We create three different learning architectures by utilizing LSTM networks, 1D-CNN networks, and Random Forests. …”
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Toward Adaptive Intrusion Detection Systems for UAVs Using Cyber-Physical Image Analysis by Hanane Amirat (23126110)

Subjects: “…Information and computing sciences…”

A FeedForward–Convolutional Neural Network to Detect Low-Rate DoS in IoT by Harun Surej Ilango (17545728)

LLM-Driven Multi-Agent Architectures for Intelligent Self-Organizing Networks by Adnan Qayyum (16875936)

Cryptomining makes noise: Detecting cryptojacking via Machine Learning by Maurantonio Caprolu (16928412)

Optimizing energy efficiency through precise occupancy detection: A tailored CNN architecture for smart buildings and beyond by Aya Nabil Sayed (17317006)

“…<p dir="ltr">Occupancy detection is crucial for various applications, including smart buildings, security systems, and energy management. This paper introduces a novel convolutional neural network (CNN) architecture based on an image encoding approach for accurate occupancy detection. …”

A Survey on the Integration of Blockchain With IoT to Enhance Performance and Eliminate Challenges by Al Sadawi, Alia

“…Finally, this research proposes an architectural design to integrate IoT with blockchain in two layers using dew and cloudlet computing. Our aim is to benefit from blockchain features and services to guarantee a decentralized data storage and processing and address security and anonymity challenges and achieve transparency and efficient authentication service.…”
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