Browsing by Author "nr 94012793"
Now showing items 1-13 of 13
-
A Weighted Machine Learning-Based Attacks Classification to Alleviating Class Imbalance
Chkirbene Z.; Erbad A.; Hamila R.; Gouissem A.; Mohamed A.; Guizani M.; Hamdi M.... more authors ... less authors ( Institute of Electrical and Electronics Engineers Inc. , 2021 , Article)The Industrial Internet of Things (IIoT) has become very popular in recent years. However, IIoT is still an attractive and vulnerable target for attackers to exploit and experiment with different types of attacks. To ... -
An Intelligent Resource Reservation for Crowdsourced Live Video Streaming Applications in Geo-Distributed Cloud Environment
Baccour E.; Haouari F.; Erbad A.; Mohamed A.; Bilal K.; Guizani M.; Hamdi M.... more authors ... less authors ( Institute of Electrical and Electronics Engineers Inc. , 2021 , Article)Crowdsourced live video streaming (livecast) services such as Facebook Live, YouNow, Douyu, and Twitch are gaining more momentum recently. Allocating the limited resources in a cost-effective manner while maximizing the ... -
CE-D2D: Collaborative and Popularity-aware Proactive Chunks Caching in Edge Networks
Baccour E.; Erbad A.; Mohamed A.; Guizani M.; Hamdi M. ( Institute of Electrical and Electronics Engineers Inc. , 2020 , Conference Paper)Leveraging video caching to collaborative Mobile Edge Computing (MEC) servers is an emerging paradigm, where cloud computing services are extended to edge networks to allocate multimedia contents close to end-users. However, ... -
Collaborative hierarchical caching and transcoding in edge network with CE-D2D communication
Baccour E.; Erbad A.; Mohamed A.; Guizani M.; Hamdi M. ( Academic Press , 2020 , Article)To support multimedia applications, Mobile Edge Computing (MEC) servers offer storage and computing capacities to handle videos close to end-users. However, the high load in peak hours consumes the limited available bandwidth ... -
DistPrivacy: Privacy-Aware Distributed Deep Neural Networks in IoT surveillance systems
Baccour E.; Erbad A.; Mohamed A.; Hamdi M.; Guizani M. ( Institute of Electrical and Electronics Engineers Inc. , 2020 , Conference Paper)With the emergence of smart cities, Internet of Things (IoT) devices as well as deep learning technologies have witnessed an increasing adoption. To support the requirements of such paradigm in terms of memory and computation, ... -
Distributed CNN Inference on Resource-Constrained UAVs for Surveillance Systems: Design and Optimization
Jouhari M.; Al-Ali A.K.; Baccour E.; Mohamed A.; Erbad A.; Guizani M.; Hamdi M.... more authors ... less authors ( Institute of Electrical and Electronics Engineers Inc. , 2022 , Article)Unmanned aerial vehicles (UAVs) have attracted great interest in the last few years owing to their ability to cover large areas and access difficult and hazardous target zones, which is not the case of traditional systems ... -
FacebookVideoLive18: A Live Video Streaming Dataset for Streams Metadata and Online Viewers Locations
Baccour E.; Erbad A.; Bilal K.; Mohamed A.; Guizani M.; Hamdi M.... more authors ... less authors ( Institute of Electrical and Electronics Engineers Inc. , 2020 , Conference Paper)With the advancement in personal smart devices and pervasive network connectivity, users are no longer passive content consumers, but also contributors in producing new contents. This expansion in live services requires a ... -
Iterative per Group Feature Selection for Intrusion Detection
Chkirbene Z.; Erbad A.; Hamila R.; Gouissem A.; Mohamed A.; Guizani M.; Hamdi M.... more authors ... less authors ( Institute of Electrical and Electronics Engineers Inc. , 2020 , Conference Paper)Network security is an critical subject in any distributed network. Recently, machine learning has proven their efficiency for intrusion detection. By using a comprehensive dataset with multiple attack types, a well-trained ... -
Machine Learning Based Cloud Computing Anomalies Detection
Chkirbene Z.; Erbad A.; Hamila R.; Gouissem A.; Mohamed A.; Hamdi M.... more authors ... less authors ( Institute of Electrical and Electronics Engineers Inc. , 2020 , Article)Recently, machine learning algorithms have been proposed to design new security systems for anomalies detection as they exhibit fast processing with real-time predictions. However, one of the major challenges in machine ... -
RL-PDNN: Reinforcement Learning for Privacy-Aware Distributed Neural Networks in IoT Systems
Baccour E.; Erbad A.; Mohamed A.; Hamdi M.; Guizani M. ( Institute of Electrical and Electronics Engineers Inc. , 2021 , Article)Due to their high computational and memory demand, deep learning applications are mainly restricted to high-performance units, e.g., cloud and edge servers. Particularly, in Internet of Things (IoT) systems, the data ... -
Severe plastic deformation of tubular AA 6061 via equal channel angular pressing
Jafarlou, D.M.; Zalnezhad, E.; Hassan, M.A.; Ezazi, M.A.; Mardi, N.A.; Hamouda, A.M.S.; Hamdi, M.; Yoon, G.H.... more authors ... less authors ( Elsevier, Ltd , 2016 , Article)Various severe plastic deformation (SPD) processes have been developed to produce metal tubes with ultrafine grain (UFG) structures. However, most techniques are complex and limited to working with components that are short ... -
TIDCS: A Dynamic Intrusion Detection and Classification System Based Feature Selection
Chkirbene Z.; Erbad A.; Hamila R.; Mohamed A.; Guizani M.; Hamdi M.... more authors ... less authors ( Institute of Electrical and Electronics Engineers Inc. , 2020 , Article)Machine learning techniques are becoming mainstream in intrusion detection systems as they allow real-time response and have the ability to learn and adapt. By using a comprehensive dataset with multiple attack types, a ... -
Weighted Trustworthiness for ML Based Attacks Classification
Chkirbene Z.; Erbad A.; Hamila R.; Gouissem A.; Mohamed A.; Guizani M.; Hamdi M.... more authors ... less authors ( Institute of Electrical and Electronics Engineers Inc. , 2020 , Conference Paper)Recently, machine learning techniques are gaining a lot of interest in security applications as they exhibit fast processing with real-time predictions. One of the significant challenges in the implementation of these ...