Mohammad Alamgeer¹, Fahd N. Al-Wesabi^2,3,*, Huda G. Iskandar^3,4, Imran Khan⁵, Nadhem Nemri⁶, Mohammad Medani⁶, Mohammed Abdullah Al-Hagery⁷, Ali Mohammed Al-Sharafi^3,8

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2497-2513, 2022, DOI:10.32604/cmc.2022.018591

Abstract Content authentication, integrity verification, and tampering detection of digital content exchanged via the internet have been used to address a major concern in information and communication technology. In this paper, a text zero-watermarking approach known as Smart-Fragile Approach based on Soft Computing and Digital Watermarking (SFASCDW) is proposed for content authentication and tampering detection of English text. A first-level order of alphanumeric mechanism, based on hidden Markov model, is integrated with digital zero-watermarking techniques to improve the watermark robustness of the proposed approach. The researcher uses the first-level order and alphanumeric mechanism of Markov model as a soft computing technique… More >

Kazim Ali^*, Adnan N. Quershi

Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 271-284, 2022, DOI:10.32604/iasc.2022.021296

Abstract The current development of artificial intelligence is largely based on deep Neural Networks (DNNs). Especially in the computer vision field, DNNs now occur in everything from autonomous vehicles to safety control systems. Convolutional Neural Network (CNN) is based on DNNs mostly used in different computer vision applications, especially for image classification and object detection. The CNN model takes the photos as input and, after training, assigns it a suitable class after setting traceable parameters like weights and biases. CNN is derived from Human Brain's Part Visual Cortex and sometimes performs even better than Haman visual system. However, recent research shows… More >

Mohamed Ali¹, Ibrahim A. Abd El-Moghith², Mohamed N. El-Derini³, Saad M. Darwish^2,*

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 6127-6140, 2022, DOI:10.32604/cmc.2022.021305

Abstract Routing is a key function in Wireless Sensor Networks (WSNs) since it facilitates data transfer to base stations. Routing attacks have the potential to destroy and degrade the functionality of WSNs. A trustworthy routing system is essential for routing security and WSN efficiency. Numerous methods have been implemented to build trust between routing nodes, including the use of cryptographic methods and centralized routing. Nonetheless, the majority of routing techniques are unworkable in reality due to the difficulty of properly identifying untrusted routing node activities. At the moment, there is no effective way to avoid malicious node attacks. As a consequence… More >

Abrar M. Alajlan^*

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4241-4259, 2022, DOI:10.32604/cmc.2022.020585

Abstract Detection of the wormhole attacks is a cumbersome process, particularly simplex and duplex over the wireless sensor networks (WSNs). Wormhole attacks are characterized as distributed passive attacks that can destabilize or disable WSNs. The distributed passive nature of these attacks makes them enormously challenging to detect. The main objective is to find all the possible ways in which how the wireless sensor network’s broadcasting character and transmission medium allows the attacker to interrupt network within the distributed environment. And further to detect the serious routing-disruption attack “Wormhole Attack” step by step through the different network mechanisms. In this paper, a… More >

Sana Ben Hamida^1,2, Hichem Mrabet^3,4, Sana Belguith^5,*, Adeeb Alhomoud⁶, Abderrazak Jemai⁷

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4897-4919, 2022, DOI:10.32604/cmc.2022.019709

Abstract From fraud detection to speech recognition, including price prediction, Machine Learning (ML) applications are manifold and can significantly improve different areas. Nevertheless, machine learning models are vulnerable and are exposed to different security and privacy attacks. Hence, these issues should be addressed while using ML models to preserve the security and privacy of the data used. There is a need to secure ML models, especially in the training phase to preserve the privacy of the training datasets and to minimise the information leakage. In this paper, we present an overview of ML threats and vulnerabilities, and we highlight current progress… More >

Anwer Mustafa Hilal^1,*, Fahd N. Al-Wesabi^2,3, Mohammed Alamgeer⁴, Manar Ahmed Hamza¹, Mohammad Mahzari⁵, Murad A. Almekhlafi⁶

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5583-5600, 2022, DOI:10.32604/cmc.2022.019686

Abstract Due to the rapid increase in the exchange of text information via internet networks, the security and authenticity of digital content have become a major research issue. The main challenges faced by researchers are how to hide the information within the text to use it later for authentication and attacks tampering detection without effects on the meaning and size of the given digital text. In this paper, an efficient text-based watermarking method has been proposed for detecting the illegal tampering attacks on the Arabic text transmitted online via an Internet network. Towards this purpose, the accuracy of tampering detection and… More >

Hassen Mestiri^1,2,3,*, Imen Barraj^4,5, Abdullah Alsir Mohamed¹, Mohsen Machhout³

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3667-3683, 2022, DOI:10.32604/cmc.2022.020716

Abstract The Advanced Encryption Standard cryptographic algorithm, named AES, is implemented in cryptographic circuits to ensure high security level to any system which required confidentiality and secure information exchange. One of the most effective physical attacks against the hardware implementation of AES is fault attacks which can extract secret data. Until now, a several AES fault detection schemes against fault injection attacks have been proposed. In this paper, so as to ensure a high level of security against fault injection attacks, a new efficient fault detection scheme based on the AES architecture modification has been proposed. For this reason, the AES… More >

Wided Ben Daoud¹, Sami Mahfoudhi^2,*

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2727-2742, 2022, DOI:10.32604/cmc.2022.020141

Abstract The Internet of Thing IoT paradigm has emerged in numerous domains and it has achieved an exponential progress. Nevertheless, alongside this advancement, IoT networks are facing an ever-increasing rate of security risks because of the continuous and rapid changes in network environments. In order to overcome these security challenges, the fog system has delivered a powerful environment that provides additional resources for a more improved data security. However, because of the emerging of various breaches, several attacks are ceaselessly emerging in IoT and Fog environment. Consequently, the new emerging applications in IoT-Fog environment still require novel, distributed, and intelligent security… More >

Rahmat Budiarto^1,*, Ahmad A. Alqarni¹, Mohammed Y. Alzahrani¹, Muhammad Fermi Pasha², Mohamed Fazil Mohamed Firdhous³, Deris Stiawan⁴

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2679-2698, 2022, DOI:10.32604/cmc.2022.019847

Abstract As nearly half of the incidents in enterprise security have been triggered by insiders, it is important to deploy a more intelligent defense system to assist enterprises in pinpointing and resolving the incidents caused by insiders or malicious software (malware) in real-time. Failing to do so may cause a serious loss of reputation as well as business. At the same time, modern network traffic has dynamic patterns, high complexity, and large volumes that make it more difficult to detect malware early. The ability to learn tasks sequentially is crucial to the development of artificial intelligence. Existing neurogenetic computation models with… More >

Mesfer Al Duhayyim¹, Manal Abdullah Alohali², Fahd N. Al-Wesabi^3,4, Anwer Mustafa Hilal^5,*, Mohammad Medani³, Manar Ahmed Hamza⁵

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2879-2894, 2022, DOI:10.32604/cmc.2022.019594

Abstract The most common digital media exchanged via the Internet is in text form. The Arabic language is considered one of the most sensitive languages of content modification due to the presence of diacritics that can cause a change in the meaning. In this paper, an intelligent scheme is proposed for improving the reliability and security of the text exchanged via the Internet. The core mechanism of the proposed scheme depends on integrating the hidden Markov model and zero text watermarking techniques. The watermark key will be generated by utilizing the extracted features of the text analysis process using the third… More >