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A Digital Signature System Based on Real Time Face Recognition
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This study proposed a biometric-based digital signature scheme proposed for facial recognition. The scheme is designed and built to verify the person’s identity during a registration process and retrieve their public and private keys stored in the database. The RSA algorithm has been used as asymmetric encryption method to encrypt hashes generated for digital documents. It uses the hash function (SHA-256) to generate digital signatures. In this study, local binary patterns histograms (LBPH) were used for facial recognition. The facial recognition method was evaluated on ORL faces retrieved from the database of Cambridge University. From the analysis, the LBPH algorithm achieved 97.5% accuracy; the real-time testing was done on thirty subjects and it achieved 94% recognition accuracy. A crypto-tool software was used to perform the randomness test on the proposed RSA and SHA256.

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Publication Date
Fri Sep 01 2017
Journal Name
Journal Of Baghdad College Of Dentistry
Assessing the Radiopacity of Three Resin Composite Materials Using a Digital Radiography Technique
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Background: Radiopacity is one of the prerequisites for dental materials, especially for composite restorations. It's essential for easy detection of secondary dental caries as well as observation of the radiographic interface between the materials and tooth structure. The aim of this study to assess the difference in radiopacity of different resin composites using a digital x-ray system. Materials and methods: Ten specimens (6mm diameter and 1mm thickness) of three types of composite resins (Evetric, Estelite Sigma Quick,and G-aenial) were fabricated using Teflon mold. The radiopacity was assessed using dental radiography equipment in combination with a phosphor plate digital system and a grey scale value aluminum step wedge with thickness

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Publication Date
Fri Sep 15 2017
Journal Name
Journal Of Baghdad College Of Dentistry
Assessing The Radiopacity of Three Resin Composite Materials Using a Digital Radiography Technique
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Background: Radiopacity is one of the prerequisites for dental materials, especially for composite restorations. It's essential for easy detection of secondary dental caries as well as observation of the radiographic interface between the materials and tooth structure. The aim of this study to assess the difference in radiopacity of different resin composites using a digital x-ray system. Materials and methods: Ten specimens (6mm diameter and 1mm thickness) of three types of composite resins (Evetric, Estelite Sigma Quick,and G-aenial) were fabricated using Teflon mold. The radiopacity was assessed using dental radiography equipment in combination with a phosphor plate digital system and a grey scale value aluminum step wedge with thickness

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Publication Date
Fri Jan 01 2016
Journal Name
Engineering And Technology Journal
Face Retrieval Using Image Moments and Genetic Algorithm
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Publication Date
Sat Dec 01 2012
Journal Name
Journal Of Economics And Administrative Sciences
International Cooperation in the Face of Internet Crimes
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في بداية الستينيات ظهرت شبكة الإنترنت لاستعمالها في أغراض غير تجارية ، ثم تطورت بشكل مذهل خلال السنوات الأخيرة، فبعد أن كانت مجرد شبكة صغيرة أصبحت الآن تضم ملايين المستخدمين حول العالم ، وتحولت من مجرد شبكة بحث أكاديمي إلى بيئة متكاملة للاستثمار والعمل والإنتاج والإعلام والحصول على المعلومات .

 وفي بداية تأسيس الشبكة لم يكن ثمة اهتمام بمسائل الأمن بقدر ما كان الاهتمام ببنائها وتوسيع نش

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Publication Date
Tue Dec 30 2025
Journal Name
Journal Of Al-qadisiyah For Computer Science And Mathematics
Deep Spoof Face Detection Techniques in React Native
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The rapid rise in the use of artificially generated faces has significantly increased the risk of identity theft in biometric authentication systems. Modern facial recognition technologies are now vulnerable to sophisticated attacks using printed images, replayed videos, and highly realistic 3D masks. This creates an urgent need for advanced, reliable, and mobile-compatible fake face detection systems. Research indicates that while deep learning models have demonstrated strong performance in detecting artificially generated faces, deploying these models on consumer mobile devices remains challenging due to limitations in computing power, memory, privacy, and processing speed. This paper highlights several key challenges: (1) optimiz

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Publication Date
Tue Dec 30 2025
Journal Name
Journal Of Al-qadisiyah For Computer Science And Mathematics
Deep Spoof Face Detection Techniques in React Native
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The rapid rise in the use of artificially generated faces has significantly increased the risk of identity theft in biometric authentication systems. Modern facial recognition technologies are now vulnerable to sophisticated attacks using printed images, replayed videos, and highly realistic 3D masks. This creates an urgent need for advanced, reliable, and mobile-compatible fake face detection systems. Research indicates that while deep learning models have demonstrated strong performance in detecting artificially generated faces, deploying these models on consumer mobile devices remains challenging due to limitations in computing power, memory, privacy, and processing speed. This paper highlights several key challenges: (1) optimiz

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Publication Date
Wed Jun 28 2023
Journal Name
Mathematics
The Impact of Fear on a Harvested Prey–Predator System with Disease in a Prey
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A mathematical eco-epidemiological model consisting of harvested prey–predator system involving fear and disease in the prey population is formulated and studied. The prey population is supposed to be separated into two groups: susceptible and infected. The susceptible prey grows logistically, whereas the infected prey cannot reproduce and instead competes for the environment’s carrying capacity. Furthermore, the disease is transferred through contact from infected to susceptible individuals, and there is no inherited transmission. The existence, positivity, and boundedness of the model’s solution are discussed. The local stability analysis is carried out. The persistence requirements are established. The global behavior of th

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Publication Date
Mon Jun 19 2023
Journal Name
Journal Of Engineering
REVIEW THE ASSESSMENT OF EFFECTS OF LOST TIME INJURIES IN AN INDUSTRIAL SYSTEM BY USING AN EXPLANATORY PROGRAM
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Health and safety problem can be described by statistics it can only be understood by knowing and feeling the pain, suffering, and depression. Health and safety has a legal responsibility to protect it for everyone who can affect in the workplace. This includes manufacturers, suppliers, designers and controllers of work places and employees. Work injury is one of the major problems in manufacturing and production systems industries; it is reduced production efficiency and affects the cost. To gain flexibility from a traditional manufacturing system and production efficiency, this paper is about the application of estimating technology to preview and synthesis of Lost Time of Work Injuries in industry systems aims to provide a safe workin

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Publication Date
Fri Aug 31 2012
Journal Name
Al-khwarizmi Engineering Journal
Design a Security Network System against Internet Worms
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 Active worms have posed a major security threat to the Internet, and many research efforts have focused on them. This paper is interested in internet worm that spreads via TCP, which accounts for the majority of internet traffic. It presents an approach that use a hybrid solution between two detection algorithms: behavior base detection and signature base detection to have the features of each of them. The aim of this study is to have a good solution of detecting worm and stealthy worm with the feature of the speed. This proposal was designed in distributed collaborative scheme based on the small-world network model to effectively improve the system performance.

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Publication Date
Mon Dec 14 2020
Journal Name
2020 13th International Conference On Developments In Esystems Engineering (dese)
Anomaly Based Intrusion Detection System Using Hierarchical Classification and Clustering Techniques
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With the rapid development of computers and network technologies, the security of information in the internet becomes compromise and many threats may affect the integrity of such information. Many researches are focused theirs works on providing solution to this threat. Machine learning and data mining are widely used in anomaly-detection schemes to decide whether or not a malicious activity is taking place on a network. In this paper a hierarchical classification for anomaly based intrusion detection system is proposed. Two levels of features selection and classification are used. In the first level, the global feature vector for detection the basic attacks (DoS, U2R, R2L and Probe) is selected. In the second level, four local feature vect

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