Predictive maintenance (PdM) is a successful strategy used to reduce cost by minimizing the breakdown stoppages and production loss. Such a contribution is helpful as it allows researchers to compare existing approaches and to exploit the proposed future work opportunities. This SLR is intended to improve research work in the domain of DL-based web attacks detection, as it covers a significant number of research papers and identifies the key points that need to be addressed in this research field. (v) It is essential to define a common framework for developing and comparing DL-based web attacks detection models.
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(iv) It is important to create a corpus for web attacks detection in order to take full advantage of text mining in DL-based web attacks detection models construction. (iii) It is fundamental to bridge expertise in web applications security and expertise in Machine Learning to build theoretical Machine Learning models tailored for web attacks detection. (ii) It is interesting to explore some advanced DL models, such as Generative Adversarial Networks and variants of Encoders–Decoders, in the context of web attacks detection as they have been successful in similar domains such as networks intrusion detection. (i) It is fundamental to generate standard real-world web attacks datasets to encourage effective contribution in this field and to reduce the gap between research and industry. The key findings of our study include the following.
To the best of our knowledge, this study is the first of its kind on SLR in this field.
We investigated the PS from different perspectives and synthesized the results of the analyses. We performed a Systematic Literature Review (SLR) and quality analysis of 63 Primary Studies (PS) on DL-based web applications security published between 2010 and September 2021. To this end, more research work has recently been devoted to employing Deep Learning (DL) approaches for web attacks detection.
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Traditional Web Application Firewalls based on manual rules and traditional Machine Learning need a lot of domain expertise and human intervention and have limited detection results faced with the increasing number of unknown web attacks. Thus, enhancing web applications security against hacking attempts is of paramount importance. Web applications are the best Internet-based solution to provide online web services, but they also bring serious security challenges. Several scenarios are adopted to assess the proposed approach and achieve security and privacy for the user information.
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The proposed approach involves two theoretical solutions: Short message service (SMS) authentication code and the physical hardware number to prevent illegal access to user data. In this article, we proposed a security approach for Viber to safeguard user confidential data and sensitive information.
Hence, a loophole in an application's design may allow illegal access to the app and gain confidential and sensitive data. Viber users reached 800 million, and they increased dramatically due to the efficient services that this app provides. Consequently, many instant messaging applications, like Viber, have various security and privacy issues that need to be understood and resolved. Therefore, the security and privacy of user data over these apps have been concerned in recent years because of sensitive and confidential information considerations. These applications, such as instant messaging, can be run via the web, mobile, or computer-based devices.
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A variety of internet-based applications are widely used in our animation activities because they provide free and useful services.
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