Visible to the public Biblio

Filters: Author is Jararweh, Yaser  [Clear All Filters]
2021-08-31
Zarzour, Hafed, Al shboul, Bashar, Al-Ayyoub, Mahmoud, Jararweh, Yaser.  2020.  A convolutional neural network-based reviews classification method for explainable recommendations. 2020 Seventh International Conference on Social Networks Analysis, Management and Security (SNAMS). :1–5.
Recent advances in information filtering have resulted in effective recommender systems that are able to provide online personalized recommendations to millions of users from all over the world. However, most of these systems ignore the explanation purpose while producing recommendations with high-quality results. Moreover, the classification of reviews given to users as explanations is not fully exploited in previous studies. In this paper, we develop a convolutional neural network-based reviews classification method for explainable recommendation systems. The convolutional neural network is used to extract the reviews features for predicting whether the reviews provided as explanations are positive or negative. Based on such additional information, users can understand not only why certain items are recommended for them but also get support to know the nature of such explanations. We conduct experiments on a dataset from Amazon. The experimental results show that our method outperforms state-of-the-art methods.
2021-07-07
Al-hamouri, Rahaf, Al-Jarrah, Heba, Al-Sharif, Ziad A., Jararweh, Yaser.  2020.  Measuring the Impacts of Virtualization on the Performance of Thread-Based Applications. 2020 Seventh International Conference on Software Defined Systems (SDS). :131–138.
The following topics are dealt with: cloud computing; software defined networking; cryptography; telecommunication traffic; Internet of Things; authorisation; software radio; cryptocurrencies; data privacy; learning (artificial intelligence).
2021-06-01
Alfandi, Omar, Otoum, Safa, Jararweh, Yaser.  2020.  Blockchain Solution for IoT-based Critical Infrastructures: Byzantine Fault Tolerance. NOMS 2020 - 2020 IEEE/IFIP Network Operations and Management Symposium. :1—4.
Providing an acceptable level of security for Internet of Things (IoT)-based critical infrastructures, such as the connected vehicles, considers as an open research issue. Nowadays, blockchain overcomes a wide range of network limitations. In the context of IoT and blockchain, Byzantine Fault Tolerance (BFT)-based consensus protocol, that elects a set of authenticated devices/nodes within the network, considers as a solution for achieving the desired energy efficiency over the other consensus protocols. In BFT, the elected devices are responsible for ensuring the data blocks' integrity and preventing the concurrently appended blocks that might contain some malicious data. In this paper, we evaluate the fault-tolerance with different network settings, i.e., the number of connected vehicles. We verify and validate the proposed model with MATLAB/Simulink package simulations. The results show that our proposed hybrid scenario performed over the non-hybrid scenario taking throughput and latency in the consideration as the evaluated metrics.
2020-10-26
Gul, M. junaid, Rabia, Riaz, Jararweh, Yaser, Rathore, M. Mazhar, Paul, Anand.  2019.  Security Flaws of Operating System Against Live Device Attacks: A case study on live Linux distribution device. 2019 Sixth International Conference on Software Defined Systems (SDS). :154–159.
Live Linux distribution devices can hold Linux operating system for portability. Using such devices and distributions, one can access system or critical files, which otherwise cannot be accessed by guest or any unauthorized user. Events like file leakage before the official announcement. These announcements can vary from mobile companies to software industries. Damages caused by such vulnerabilities can be data theft, data tampering, or permanent deletion of certain records. This study uncovers the security flaws of operating system against live device attacks. For this study, we used live devices with different Linux distributions. Target operating systems are exposed to live device attacks and their behavior is recorded against different Linux distribution. This study also compares the robustness level of different operating system against such attacks.