ORCID Profile
0000-0001-6852-1206
Current Organisation
Prince Sultan University
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Publisher: IGI Global
Date: 2020
DOI: 10.4018/978-1-7998-2701-6.CH003
Abstract: Cloud computing technology provides cost-saving and flexibility of services for users. With the explosion of multimedia data, more and more data owners would outsource their personal multimedia data on the cloud. In the meantime, some computationally expensive tasks are also undertaken by cloud servers. However, the outsourced multimedia data and its applications may reveal the data owner's private information because the data owners lose control of their data. Recently, this thought has aroused new research interest on privacy-preserving reversible data hiding over outsourced multimedia data. Anonymous Authentication Scheme will be proposed in this chapter as the most relatable, applicable, and appropriate techniques to be adopted by the cloud computing professionals for the eradication of risks that have been associated with the risks and challenges of privacy.
Publisher: IGI Global
Date: 2021
DOI: 10.4018/978-1-7998-8954-0.CH020
Abstract: Cloud computing technology provides cost-saving and flexibility of services for users. With the explosion of multimedia data, more and more data owners would outsource their personal multimedia data on the cloud. In the meantime, some computationally expensive tasks are also undertaken by cloud servers. However, the outsourced multimedia data and its applications may reveal the data owner's private information because the data owners lose control of their data. Recently, this thought has aroused new research interest on privacy-preserving reversible data hiding over outsourced multimedia data. Anonymous Authentication Scheme will be proposed in this chapter as the most relatable, applicable, and appropriate techniques to be adopted by the cloud computing professionals for the eradication of risks that have been associated with the risks and challenges of privacy.
Publisher: Mark Allen Group
Date: 2020
DOI: 10.1016/S1361-3723(20)30109-3
Abstract: The development, deployment and management of software applications have shifted dramatically in the past 10 years. This fundamental shift is what we now know as development operations (DevOps). Infrastructure as Code (IaC) is one of the main tenets of DevOps. Previously, manual configuration via cloud providers’ UI consoles and physical hardware used to take place. But now, with the concept of IaC, the IT infrastructure can be automated by using blueprints that are easily readable by machines.
Publisher: Blue Eyes Intelligence Engineering and Sciences Engineering and Sciences Publication - BEIESP
Date: 30-09-2019
DOI: 10.35940/IJRTE.C5374.098319
Abstract: Security is a significant concern in software development. Risks and errors should be reduced and as much as possible eliminated. Especially with how the computer and internet provide numerous technological benefits and are being optimally utilized in the present times, users have high expectations when it comes to secure software products. The development cycle in software design is comprised of a systematic process wherein security risk assessment should be integrated into each phase. In order to ensure quality software with a high level of security, the best practices in risk management should be implemented from the beginning and should be performed throughout the process. While developing highly secure software is a complex task, therefore, it must involve more dedicated security activities that are usually ignored in traditional SDLC. In this paper, the nature and phases of secure software development will be discussed as well as the security risk assessment models and practices involved in it. This will provide software developers, programmers, or engineers the awareness on secure software development cycle which will allow them to plan efficient strategies and enhance their performance, thus, resulting in quality and reliable output. In addition, we present a qualitative study looking at real-life practice employed towards software security risk. We reflect on how well current risk practices follow best practice, identify pitfalls, and explore why these occur & mitigate.
Publisher: MDPI AG
Date: 30-04-2020
DOI: 10.3390/S20092559
Abstract: The pursuit to spot abnormal behaviors in and out of a network system is what led to a system known as intrusion detection systems for soft computing besides many researchers have applied machine learning around this area. Obviously, a single classifier alone in the classifications seems impossible to control network intruders. This limitation is what led us to perform dimensionality reduction by means of correlation-based feature selection approach (CFS approach) in addition to a refined ensemble model. The paper aims to improve the Intrusion Detection System (IDS) by proposing a CFS + Ensemble Classifiers (Bagging and Adaboost) which has high accuracy, high packet detection rate, and low false alarm rate. Machine Learning Ensemble Models with base classifiers (J48, Random Forest, and Reptree) were built. Binary classification, as well as Multiclass classification for KDD99 and NSLKDD datasets, was done while all the attacks were named as an anomaly and normal traffic. Class labels consisted of five major attacks, namely Denial of Service (DoS), Probe, User-to-Root (U2R), Root to Local attacks (R2L), and Normal class attacks. Results from the experiment showed that our proposed model produces 0 false alarm rate (FAR) and 99.90% detection rate (DR) for the KDD99 dataset, and 0.5% FAR and 98.60% DR for NSLKDD dataset when working with 6 and 13 selected features.
No related grants have been discovered for Mamdouh Alenezi.