Towards a minimum universal features set for IoT DDoS attack detection by Osama Ebrahem, Salah Dowaji, Suhel Alhammoud

Get full text

Preventing flow table overflow against denial of service attack in software defined network by Dongbin WANG, Dongzhe WU, Hui ZHI, Kun GUO, Xu ZHANG, Jinqiao SHI, Yu ZHANG, Yueming LU

Subjects: Get full text

Extracting Optimal Number of Features for Machine Learning Models in Multilayer IoT Attacks by Badeea Al Sukhni, Soumya K. Manna, Jugal M. Dave, Leishi Zhang

Subjects: “…IoT attacks…”
Get full text

RF-SFAD: A RANDOM FOREST MODEL FOR SELECTIVE FORWARDING ATTACK DETECTION IN MOBILE WIRELESS SENSOR NETWORKS by N Usha Bhanu, Soubhagya Ranjan Mallick, Sreenivasa Rao Chappidi, K Sangeethalakshmi

Subjects: “…mobile wireless sensor networks, random forest algorithm, selective forwarding attack detection, clustering, feature selection.…”
Get full text

Enhanced Deep Autoencoder-Based Reinforcement Learning Model with Improved Flamingo Search Policy Selection for Attack Classification by Dharani Kanta Roy, Hemanta Kumar Kalita

“…The enhancement of deep reinforcement learning is made by associating a deep autoencoder (AE) and an improved flamingo search algorithm (IFSA) to approximate the Q-function and optimal policy selection. After feature representations, a support vector machine (SVM) classifier, which discriminates the input into normal and attack instances, is employed for classification. …”
Get full text

Optimizing feature selection and deep learning techniques for precise detection of low-rate distributed denial of service (LDDoS) attack by Naeem Ali Al-Shukaili, Miss Laiha M. Kiah, Ismail Ahmedy

“…Low-rate DDoS refers to the small number of requests to overcome the sudden spikes that disrupt the server.This work aims to improve the detection of two common LDDoS attack types, slowloris and slowhttptest simulated attacks, by optimizing feature selection and utilizing deep learning techniques. …”
Get full text

Efficient Distributed Denial of Service Attack Detection in Internet of Vehicles Using Gini Index Feature Selection and Federated Learning by Muhammad Dilshad, Madiha Haider Syed, Semeen Rehman

Subjects: “…DDoS attack detection…”
Get full text

An Immunology Inspired Flow Control Attack Detection Using Negative Selection with -Contiguous Bit Matching for Wireless Sensor Networks by Muhammad Zeeshan, Huma Javed, Amna Haider, Aumbareen Khan

“…An Anomaly Detection System (ADS) framework inspired from the Human Immune System is implemented in this paper for detecting Sybil attacks in WSNs. This paper implemented an improved, decentralized, and customized version of the Negative Selection Algorithm (NSA) for data flow anomaly detection with learning capability. …”
Get full text

Leveraging federated learning for DoS attack detection in IoT networks based on ensemble feature selection and deep learning models by Tasneem Qasem Al-Ghadi, Selvakumar Manickam, I. Dewa Made Widia, Eka Ratri Noor Wulandari, Shankar Karuppayah

“…Detecting Denial-of-Service (DoS) attacks in IoT networks is critical for ensuring cybersecurity. …”
Get full text

An Efficient Approach Based on RAE-GAMI-NET for Long Range Attack Detection on Blockchain by Vasavi Chithanuru, Mangayarkarasi Ramaiah

Subjects: Get full text

Adversarial Threats to Cloud IDS: Robust Defense With Adversarial Training and Feature Selection by Hariprasad Holla, Shashidhar Reddy Polepalli, Arun Ambika Sasikumar

“…To mitigate these vulnerabilities, we explicitly propose a dual-layered defense strategy: (i) adversarial training, explicitly incorporating adversarial examples into model training to improve robustness, and (ii) SHAP-based robust feature selection, explicitly enhancing interpretability and resilience by identifying stable, attack-resistant features. …”
Get full text

A review on recent approaches of Machine Learning, Deep Learning, and Explainable Artificial intelligence in Intrusion Detection Systems by Seshu Bhavani Mallampati, Seetha Hari

Subjects: “…Datasets. Attacks…”
Get full text

Augmenting cybersecurity through attention based stacked autoencoder with optimization algorithm for detection and mitigation of attacks on IoT assisted networks by Kashi Sai Prasad, E. Laxmi Lydia, M. V. Rajesh, K. Radhika, Janjhyam Venkata Naga Ramesh, N. Neelima, Srinivasa Rao Pokuri

Subjects: “…Cybersecurity attack…”
Get full text

Enhancing Cybersecurity Through Fusion of Optimization With Deep Wavelet Neural Networks on Denial of Wallet Attack Detection in Serverless Computing by P. Renukadevi, Sibi Amaran, A. Vikram, T. Prabhakara Rao, Mohamad Khairi Ishak

“…Besides, the pair barracuda swarm optimization (PBSO) method is employed to select features optimally. To recognize a DoW attack, the FODWNN-DoWAD method utilizes a deep wavelet neural network (DWNN) model. …”
Get full text

Improving IoT Network Longevity with Attack Repellent Energy (SARE) Algorithm for Energy-Efficient and Secure Routing by Indra Pandian, Shanthi Thirugnasambantham, Karthikeyan Balasubramaniam, Kirubaburi Ravichandran

“…The proposed Secure Attack Repellent Energy (SARE) algorithm selects CHs based on the K-Nearest Neighbor (KNN) algorithm, which evaluates residual energy by considering the battery voltage attached to each node. …”
Get full text

An explainable analytical approach to heart attack detection using biomarkers and nature-inspired algorithms by Maithri Bairy, Krishnaraj Chadaga, Niranjana Sampathila, R. Vijaya Arjunan, G. Muralidhar Bairy

Subjects: “…Heart attack prediction…”
Get full text

DDoSNet: Detection and prediction of DDoS attacks from realistic multidimensional dataset in IoT network environment by Goda Srinivasa Rao, P. Santosh Kumar Patra, V.A. Narayana, Avala Raji Reddy, G.N.V. Vibhav Reddy, D. Eshwar

“…By integrating ABO with the decision tree, a subset of features is selected that maximizes the discrimination between regular network traffic and DDoS attacks. …”
Get full text

Resource-Efficient Traffic Classification Using Feature Selection for Message Queuing Telemetry Transport-Internet of Things Network-Based Security Attacks by Emmanuel Tuyishime, Marco Martalò, Petru A. Cotfas, Vlad Popescu, Daniel T. Cotfas, Alexandre Rekeraho

Get full text

Layout selection for single-axle forced-steering radial mechanism by JIANG Hui, HUANG Zhihui, LIU Jiahui, YU Hongda

Get full text

Comparison of selected physical fitness components among male football players of different playing positions by Amandeep Sıngh, Sukhdev Sıngh, Vishaw Gaurav

“…The purpose of this study was to examine the level of physical fitness among male football players in relation to their different playing positions i.e. goalkeepers, defenders, midfielders and attackers. A sample of forty (N = 40) male football players (mean ± SD: age 20.45 ± 1.70 years, height 1.84 ± 4.07 m, weight 81.62 ± 5.45 kg, BMI 23.99 ± 1.66m), which includes ten each goalkeepers, defenders, midfielders and attackers, who participated in inter-college competitions of Guru Nanak Dev University, Amritsar, India, was selected. …”
Get full text