Mohamed Desouki | Higher Institute of Applied Sciences and Technology (HIAST) (original) (raw)

Uploads

Papers by Mohamed Desouki

Journal of Big Data, 2020

Anomaly-based Intrusion Detection System (IDS) has been a hot research topic because of its abili... more Anomaly-based Intrusion Detection System (IDS) has been a hot research topic because of its ability to detect new threats rather than only memorized signatures threats of signature-based IDS. Especially after the availability of advanced technologies that increase the number of hacking tools and increase the risk impact of an attack. The problem of any anomaly-based model is its high false-positive rate. The high false-positive rate is the reason why anomaly IDS is not commonly applied in practice. Because anomaly-based models classify an unseen pattern as a threat where it may be normal but not included in the training dataset. This type of problem is called overfitting where the model is not able to generalize. Optimizing Anomaly-based models by having a big training dataset that includes all possible normal cases may be an optimal solution but could not be applied in practice. Although we can increase the number of training samples to include much more normal cases, still we need...

Journal of Big Data, 2019

With the growing use of information technology in all life domains, hacking has become more negat... more With the growing use of information technology in all life domains, hacking has become more negatively effective than ever before. Also with developing technologies, attacks numbers are growing exponentially every few months and become more sophisticated so that traditional IDS becomes inefficient detecting them. This paper proposes a solution to detect not only new threats with higher detection rate and lower false positive than already used IDS, but also it could detect collective and contextual security attacks. We achieve those results by using Networking Chatbot, a deep recurrent neural network: Long Short Term Memory (LSTM) on top of Apache Spark Framework that has an input of flow traffic and traffic aggregation and the output is a language of two words, normal or abnormal. We propose merging the concepts of language processing, contextual analysis, distributed deep learning, big data, anomaly detection of flow analysis. We propose a model that describes the network abstract ...

2011 International Conference on Innovations in Information Technology, 2011

... Damascus, Syria, 2008. [7] Sonbol. R, Ghneim, N. and Desouki, MS An Arabic Mor-phological Ana... more ... Damascus, Syria, 2008. [7] Sonbol. R, Ghneim, N. and Desouki, MS An Arabic Mor-phological Analyzer for various applications. ... [9] I. Mustafa, AH Alzayat, h. Abdel-kader, MA Alnajar, Al-Wasseet dictionary, 3rd edition, Alnouri Press, Damascus, 1960. 86

2008 3rd International Conference on Information and Communication Technologies: From Theory to Applications, 2008

Abstract Morphological analysis is an important step in the process of Arabic language processing... more Abstract Morphological analysis is an important step in the process of Arabic language processing which became a must in today&#x27;s IT development. We present here a new approach for Arabic root extraction. Our algorithm outperforms most other morphological ...

Journal of Big Data, Apr 21, 2022

Since social network analysis has been receiving massive attention in recent years, researchers h... more Since social network analysis has been receiving massive attention in recent years, researchers have gone a step further and studied multiple social networks together to capture the impact between them. By studying social networks together, more features and information can be extracted and identified. The link prediction problem [1] is one of the most studied problems in this field. One can define the link prediction problem as estimating the probability of connecting two unconnected nodes in a network. There are many link prediction applications such as Recommendation Systems [2]. Methods of link prediction are divided into (1) similarity based [3-5], (2) artificial intelligent based

Journal of Big Data, 2021

An amendment to this paper has been published and can be accessed via the original article.

Morphological analysis is an important step in natural language processing and its various applic... more Morphological analysis is an important step in natural language processing and its various applications. Each kind of these applications needs a certain balance between: performance, accuracy, and generality of solutions (i.e. getting all possible roots); while we focus on performance with a good accuracy in Information retrieval applications, we try to achieve high accuracy in systems like pos-tagger and machine translation, and both high accuracy and high generality in systems like language learning systems and Arabic lexical dictionaries. In this paper, we describe our approach to build a flexible and application oriented Arabic morphological analyzer; this approach is designed to satisfy various requirements of most applications which need morphological processing. It also provides a separate stage (Original Letters Detection Algorithm) which can be plugged easily in any Other morphological analyzer to improve its performance, and with no negative effect on its reliability.

Morphological analysis is an important step in the process of Arabic language processing which be... more Morphological analysis is an important step in the process of Arabic language processing which became a must in today's IT development. We present here a new approach for Arabic root extraction. Our algorithm outperforms most other morphological analysis algorithms; we achieved more reliable results with better performance and minimal storage. Our Morphological analyzer provides different levels of reliability and performance to support the needs of different applications. It also provides a separate stage which can be plugged easily in any other Morphological analyzer to improve its performance, and with no negative effect on its reliability.

Arabic Language Processing is gaining increasing importance all around the world. This language i... more Arabic Language Processing is gaining increasing importance all around the world. This language is spoken by nearly 300 millions in the Arab World, and is an interesting language for the 1.3 billion Muslims. Arabic is becoming also a focal point of interest in many universities all around the world. The positive aspect of this interest in Arabic-which was relatively ignored when compared with other live languages-, is the intensive work on language technologies, and an increasing amount of digital contents on the Internet. Arabic Language is one of the most promoted research axis in HIAST since its foundation in 1983 (Ghneim & Al-DAkkak, 2006). In the introduction of this paper, we mention the most relevant works, in both speech and text aspects, which can be of interest in many applications, and can be a subject of resource sharing. In the second section we detail our acoustic database of semi-syllables and in the third one we develop our morphological analyzer.

This paper presents the Interactive Arabic Dictionary (IAD) developed at the Higher Institute for... more This paper presents the Interactive Arabic Dictionary (IAD) developed at the Higher Institute for Applied Sciences and Technology (HIAST). IAD is an interactive web application based on the "Al-Wasseet" dictionary. It provides the different meanings of words with examples and multimedia illustrations. IAD presents also other related information like associated words, semantic domains, expressions, linguistic tips, common mistakes, and linguistic information. Users interact online with this dictionary to search information about Arabic words. Moreover, expert users can also enrich the dictionary with new words, different meanings, or other related information.

damascusuniversity.edu.sy