Papers by Amjad Alsirhani
Cloud computing is a technology that facilitates numerous configurable resources in which the dat... more Cloud computing is a technology that facilitates numerous configurable resources in which the data is stored and managed in a decentralized manner. However, since the data is out of the owner's control, concerns have arisen regarding data confidentiality. Encryption techniques have previously been proposed to provide users with confidentiality in terms of outsource storage; however, many of these encryption algorithms are weak, enabling data security to be breached simply by compromising an algorithm. We propose a combination of encryption algorithms and a distribution system to improve database confidentiality. This scheme distributes the database across the clouds based on the level of security that is provided by the encryption algorithms utilized. We analyzed our scheme by designing and conducting experiments and by comparing our scheme with existing solutions. The results demonstrate that our scheme offers a highly secure approach that provides users with data confidentiality and provides acceptable overhead performance.
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Cloud computing is a technology that promotes numerous configurable resources in which the data i... more Cloud computing is a technology that promotes numerous configurable resources in which the data is stored and managed in a decentralized manner. However, as the data is out of the owner’s control, concerns have arisen regarding data confidentiality. Encryption schemes have been proposed to provide users with confidentiality for data stored in a cloud; however, many of these encryption algorithms are weak, enabling data security to be breached simply by compromising a weak encryption algorithm. We propose a combination of encryption algorithms and a distributed system to improve database confidentiality. This scheme distributes the database over the clouds based on the level of security that is provided by the utilized encryption algorithms. We analyzed our proposed system by designing and conducting experiments and by comparing our scheme with existing solutions. The results show that our scheme offers a highly secure approach providing users with data confidentiality and providing acceptable overhead performance.
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Electronics, Jan 28, 2023
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Traitement Du Signal, Jun 30, 2022
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IEEE Access
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Alexandria Engineering Journal
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Date fruit dataset has over 2000 images of 27 classes.
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Electronics
Date fruits are the most common fruit in the Middle East and North Africa. There are a wide varie... more Date fruits are the most common fruit in the Middle East and North Africa. There are a wide variety of dates with different types, colors, shapes, tastes, and nutritional values. Classifying, identifying, and recognizing dates would play a crucial role in the agriculture, commercial, food, and health sectors. Nevertheless, there is no or limited work to collect a reliable dataset for many classes. In this paper, we collected the dataset of date fruits by picturing dates from primary environments: farms and shops (e.g., online or local markets). The combined dataset is unique due to the multiplicity of items. To our knowledge, no dataset contains the same number of classes from natural environments. The collected dataset has 27 classes with 3228 images. The experimental results presented are based on five stages. The first stage applied traditional machine learning algorithms for measuring the accuracy of features based on pixel intensity and color distribution. The second stage appl...
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Journal of Healthcare Engineering
Most medical images are low in contrast because adequate details that may prove vital decisions a... more Most medical images are low in contrast because adequate details that may prove vital decisions are not visible to the naked eye. Also, due to the low-contrast nature of the image, it is not easily segmented because there is no significant change between the pixel values, which makes the gradient very small Hence, the contour cannot converge on the edges of the object. In this work, we have proposed an ensembled spatial method for image enhancement. In this ensembled approach, we first employed the Laplacian filter, which highlights the areas of fast intensity variation. This filter can determine the sufficient details of an image. The Laplacian filter will also improve those features having shrill disjointedness. Then, the gradient of the image has been determined, which utilizes the surrounding pixels for the weighted convolution operation for noise diminishing. However, in the gradient filter, there is one negative integer in the weighting. The intensity value of the middle pixel...
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Sensors
Android has become the leading mobile ecosystem because of its accessibility and adaptability. It... more Android has become the leading mobile ecosystem because of its accessibility and adaptability. It has also become the primary target of widespread malicious apps. This situation needs the immediate implementation of an effective malware detection system. In this study, an explainable malware detection system was proposed using transfer learning and malware visual features. For effective malware detection, our technique leverages both textual and visual features. First, a pre-trained model called the Bidirectional Encoder Representations from Transformers (BERT) model was designed to extract the trained textual features. Second, the malware-to-image conversion algorithm was proposed to transform the network byte streams into a visual representation. In addition, the FAST (Features from Accelerated Segment Test) extractor and BRIEF (Binary Robust Independent Elementary Features) descriptor were used to efficiently extract and mark important features. Third, the trained and texture fea...
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ACM Transactions on Internet Technology
Blockchain-enabled Internet of Things (IoT) envisions a world with rapid development and implemen... more Blockchain-enabled Internet of Things (IoT) envisions a world with rapid development and implementations to change our everyday lives based on smart devices. These devices are attached to the internet that can communicate with each other without human interference. A well-known wireless network in blockchain-enabled IoT frameworks is the Low Power and Lossy Network (LLN) that uses a novel protocol known as Routing protocol for low power and lossy networks (RPL) to provide effective and energy-efficient routing. LLNs that run on RPL are inherently prone to multiple Denial of Service (DoS) attacks due to the low cost, shared medium and resource-constrained nature of blockchain-enabled IoT devices. A Spam DODAG Information Solicitation (DIS) attack is one of the novel attacks that drain the energy source of legitimate nodes and ends up causing the legitimate nodes to suffer from DoS. To address this problem, a mitigation scheme named DIS Spam Attack Mitigation (DISAM) is proposed. The ...
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IEEE Access
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Mathematics
Internet of Things (IoT) allows the integration of the physical world with network devices for pr... more Internet of Things (IoT) allows the integration of the physical world with network devices for proper privacy and security in a healthcare system. IoT in a healthcare system is vulnerable to spoofing attacks that can easily represent themselves as a legal entity of the network. It is a passive attack and can access the Medium Access Control address of some valid users in the network to continue malicious activities. In this paper, an algorithm is proposed for detecting spoofing attacks in IoT using Received Signal Strength (RSS) and Number of Connected Neighbors (NCN). Firstly, the spoofing attack is detected, located and eliminated through Received Signal Strength (RSS) in an inter-cluster network. However, the RSS is not useful against intra-cluster spoofing attacks and therefore the NCN is introduced to detect, identify and eliminate the intra-cluster spoofing attack. The proposed model is implemented in Network Simulator 2 (NS-2) to compare the performance of the proposed algori...
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Electronics
Organizations of every size and industry are facing a new normal. Adversaries have become more so... more Organizations of every size and industry are facing a new normal. Adversaries have become more sophisticated and persistent than ever before. Every network is facing never-ending onslaughts. Yet many organizations continue to rely on signature-based reactive threat detection and mitigation solutions as the primary line of defense against new-age, cutting-edge attacks. Even conventional attacks can bypass such security solutions. This means legacy protection solutions leave the organization’s data vulnerable to damage, destruction, and theft. Adversarial attacks are like ocean waves: they are very persistent and keep coming like attack campaigns. Sometimes the waves, in our case, attacks, look the same, where indicators of compromise (IoCs) effectively detect the attacks, while sometimes, the waves or attacks change and continue to look different, especially over a while. If somehow the defenders can recognize what is making those attacks or waves and the conditions, then detecting t...
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Electronics
Human face image analysis using machine learning is an important element in computer vision. The ... more Human face image analysis using machine learning is an important element in computer vision. The human face image conveys information such as age, gender, identity, emotion, race, and attractiveness to both human and computer systems. Over the last ten years, face analysis methods using machine learning have received immense attention due to their diverse applications in various tasks. Although several methods have been reported in the last ten years, face image analysis still represents a complicated challenge, particularly for images obtained from ’in the wild’ conditions. This survey paper presents a comprehensive review focusing on methods in both controlled and uncontrolled conditions. Our work illustrates both merits and demerits of each method previously proposed, starting from seminal works on face image analysis and ending with the latest ideas exploiting deep learning frameworks. We show a comparison of the performance of the previous methods on standard datasets and also ...
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Computers
The increase in internet connectivity has led to an increased usage of the Internet of Things (Io... more The increase in internet connectivity has led to an increased usage of the Internet of Things (IoT) and devices on the internet. These IoT devices are becoming the backbone of Industry 4.0. The dependence on IoT devices has made them vulnerable to cyber-attacks. IoT devices are often deployed in harsh conditions, challenged with less computational costs, and starved with energy. All these limitations make it tough to deploy accurate intrusion detection systems (IDSs) in IoT devices and make the critical IoT ecosystem more susceptible to cyber-attacks. A new lightweight IDS and a novel feature selection algorithm are introduced in this paper to overcome the challenges of computational cost and accuracy. The proposed algorithm is based on the Information Theory models to select the feature with high statistical dependence and entropy reduction in the dataset. This feature selection algorithm also showed an increase in performance parameters and a reduction in training time of 27–63% w...
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Drones
The Internet of Drones (IoD) has recently gained popularity in several military, commercial, and ... more The Internet of Drones (IoD) has recently gained popularity in several military, commercial, and civilian applications due to its unique characteristics, such as high mobility, three-dimensional (3D) movement, and ease of deployment. Drones, on the other hand, communicate over an unencrypted wireless link and have little computational capability in a typical IoD environment, making them exposed to a wide range of cyber-attacks. Security vulnerabilities in IoD systems include man-in-the-middle attacks, impersonation, credential leaking, GPS spoofing, and drone hijacking. To avoid the occurrence of such attacks in IoD networks, we need an extremely powerful security protocol. To address these concerns, we propose a blockchain-based authentication scheme employing Hyperelliptic Curve Cryptography (HECC). The concepts of a blockchain as a Certificate Authority (CA) and a transaction as a certificate discussed in this article are meant to facilitate the use of a blockchain without CAs or...
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Traitement du Signal
The incidence of malicious threats to computer systems has increased with the increasing use of A... more The incidence of malicious threats to computer systems has increased with the increasing use of Android devices and high-speed Internet. Malware visualization mechanism can analyze a computer whenever a software or system crash occurs because of malicious activity. This paper presents a new malware classification approach to recognize such Android device malware families by capturing suspicious processes in the form of different size color images. Important local and global characteristics of color images are extracted through a combined local and global feature descriptor (structure based local and statistical based global combined texture analysis) to reduce the training complexity of neural networks. A multihead ensemble of neural networks is proposed to increase network classification performance by merging prediction results from weak learners (convolutional neural network + gated recurrent unit) and using them as learning input to a multi-layer perceptron meta learner. Two pub...
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Mathematical Problems in Engineering
Human activity recognition (HAR) is the examination of gestures and actions of humans from variou... more Human activity recognition (HAR) is the examination of gestures and actions of humans from various resources such as depth or RGB cameras. In this work, we have designed a dynamic and robust feature selection algorithm for a HAR system, through which the system accurately recognizes various kinds of activities. In the proposed approach, we employed mutual information algorithm, which selects the prominent features from the extracted features. The proposed algorithm is the expansion of two methods like max-relevance and min-redundancy, respectively. This method has the capability to gather the assets of various extraction algorithms. But the procedure of selection may be unfair due to the dissimilarity between the classification power and redundancy of the features. To resolve this type of unfair selection, we stabilize both parts through the proposed algorithm that has autonomous upper limit of the mutual information function. Likewise, for the feature extraction and recognition, we...
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Computer Systems Science and Engineering
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Papers by Amjad Alsirhani