Titlebook: Machine Learning for Networking; Third International Éric Renault,Selma Boumerdassi,Paul Mühlethaler Conference proceedings 2021 Springer

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Improving Android Malware Detection Through Dimensionality Reduction Techniques,gorously to find optimal detection solutions, mobile malware is becoming more sophisticated and its writers are getting more and more skilled in hiding malicious code. In this paper, we examine the usefulness of two known dimensionality reduction transformations namely, Principal Component Analysis

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A Regret Minimization Approach to Frameless Irregular Repetition Slotted Aloha: IRSA-RM,munications systems for IoT, including cellular networks. For many use cases, such as massive machine-type communications (mMTC), performance can be gained by going out of the classical model of connection establishment and adopting the random access methods. Associated with physical layer technique

Mri485

Mobility Based Genetic Algorithm for Heterogeneous Wireless Networks,rgy savings) ensured by the mobile elements of the data collected with precision by the static elements. In this article, we focus on this collaboration. We base our study on genetic algorithms to select the best next destination from the event area according to different criteria, such as the amoun

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Geographical Information Based Clustering Algorithm for Internet of Vehicles,IoV are characterized by a high nodes’ mobility, high nodes’ number and high data storage. However, IoV suffer from many challenges in order to achieve robust communication between vehicles such as frequent link disconnection, delay, and network overhead. In the traditional Vehicular Ad hoc NETworks

Cardioversion

Active Probing for Improved Machine-Learned Recognition of Network Traffic, via optimization through protocol selection (OPS) or through other forms of parameter tuning, a machine-learned classifier is one tool to identifying background traffic protocols. Unfortunately, global knowledge can be difficult to obtain in a dynamic distributed system like a shared, wide-area net

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A Dynamic Time Warping and Deep Neural Network Ensemble for Online Signature Verification,erates in a writer-dependent manner and its algorithm outputs unbounded distance values. The introduction of bounded outputs offers the prospect of cross pollination with other regression models which provide normalized outputs. Writer-dependent methods are heavily influenced by the richness of the

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Performance Evaluation of Some Machine Learning Algorithms for Security Intrusion Detection,ncreasing, in the design of communication protocols as well as in their implementation. On another side, the knowledge, tools and scripts, to launch attacks, become readily available and more usable. Hence, the need for an intrusion detection system (IDS) is also more apparent. This technology consi

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Nmda-Receptor

Improving Android Malware Detection Through Dimensionality Reduction Techniques,x ensemble that can use multiple and possibly heterogeneous base models. The experimental results in contemporary Androzoo benchmark corpora verify the suitability of ensembles for this task and clearly demonstrate the effectiveness of our method.

简洁

Geographical Information Based Clustering Algorithm for Internet of Vehicles, we propose a new Geo-graphical Information based Clustering Algorithm “GICA” destined to IoV environment. The proposal aims to maintain the cluster structure while respecting the quality of service requirements as the network evolves. We evaluated our proposed approach using the NS3 simulator and the realistic mobility model SUMO.