An Ontology for Software Requirements Modelling

Ontology provides means to describe concepts effectively. It has become an increasingly useful tool in understanding concepts in various fields of Information Systems and Technology. The aim of this paper is to build and evaluate an ontology that standardizes concepts and semantics of requirements modelling notations, in order to provide a common understanding of those concepts among software engineers. This ontology will lead to easy learning of modelling diagram concepts for new system developers. It will also allow software engineers to move from one modelling notation to another easily

An Efficient Certificateless Forward-Secure Signature Scheme for Secure Deployments of the Internet of Things

As an extension of the wired network, the use of the wireless communication network has considerably boosted users’ productivity at work and in their daily lives. The most notable aspect of the wireless communication network is that it overcomes the constraints of the wired network, reduces the amount of cost spent on wire maintenance, and distributes itself in a manner that is both more extensive and flexible. Combining wireless communication with the Internet of Things (IoT) can be used in several applications, including smart cities, smart traffic, smart farming, smart drones, etc. However, when exchanging data, wireless communication networks use an open network, allowing unauthorized users to engage in communication that is seriously destructive. Therefore, authentication through a digital signature will be the best solution to tackle such problems. Several digital signatures are contributing to the authentication process in a wireless communication network; however, they are suffering from several problems, including forward security, key escrow, certificate management, revocations, and high computational and communication costs, respectively. Keeping in view the above problems, in this paper we proposed an efficient certificateless forward-secure signature scheme for secure deployments in wireless communication networks. The security analysis of the proposed scheme is carried out using the random oracle model (ROM), which shows that it is unforgeable against type 1 and type 2 adversaries. Moreover, the computational and communication cost analyses are carried out by using major operations, major operations cost in milliseconds, and extra communication bits. The comparative analysis with the existing scheme shows that the proposed scheme reduces the computational cost from 19.23% to 97.54% and the communication overhead from 11.90% to 83.48%, which means that the proposed scheme is efficient, faster, and more secure for communication in the wireless communication network

Detection of renal cell hydronephrosis in ultrasound kidney images: a study on the efficacy of deep convolutional neural networks

In the realm of medical imaging, the early detection of kidney issues, particularly renal cell hydronephrosis, holds immense importance. Traditionally, the identification of such conditions within ultrasound images has relied on manual analysis, a labor-intensive and error-prone process. However, in recent years, the emergence of deep learning-based algorithms has paved the way for automation in this domain. This study aims to harness the power of deep learning models to autonomously detect renal cell hydronephrosis in ultrasound images taken in close proximity to the kidneys. State-of-the-art architectures, including VGG16, ResNet50, InceptionV3, and the innovative Novel DCNN, were put to the test and subjected to rigorous comparisons. The performance of each model was meticulously evaluated, employing metrics such as F1 score, accuracy, precision, and recall. The results paint a compelling picture. The Novel DCNN model outshines its peers, boasting an impressive accuracy rate of 99.8%. In the same arena, InceptionV3 achieved a notable 90% accuracy, ResNet50 secured 89%, and VGG16 reached 85%. These outcomes underscore the Novel DCNN’s prowess in the realm of renal cell hydronephrosis detection within ultrasound images. Moreover, this study offers a detailed view of each model’s performance through confusion matrices, shedding light on their abilities to categorize true positives, true negatives, false positives, and false negatives. In this regard, the Novel DCNN model exhibits remarkable proficiency, minimizing both false positives and false negatives. In conclusion, this research underscores the Novel DCNN model’s supremacy in automating the detection of renal cell hydronephrosis in ultrasound images. With its exceptional accuracy and minimal error rates, this model stands as a promising tool for healthcare professionals, facilitating early-stage diagnosis and treatment. Furthermore, the model’s convergence rate and accuracy hold potential for enhancement through further exploration, including testing on larger and more diverse datasets and investigating diverse optimization strategies

Enabling Secure Communication in Wireless Body Area Networks with Heterogeneous Authentication Scheme

Thanks to the widespread availability of Fifth Generation (5G) wireless connectivity, it is now possible to provide preventative or proactive healthcare services from any location and at any time. As a result of this technological improvement, Wireless Body Area Networks (WBANs) have emerged as a new study of research in the field of healthcare in recent years. WBANs, on the one hand, intend to gather and monitor data from the human body and its surroundings; on the other hand, biomedical devices and sensors interact through an open wireless channel, making them exposed to a range of cyber threats. However, WBANs are a heterogeneous-based system; heterogeneous cryptography is necessary, in which the transmitter and receiver can employ different types of public key cryptography. This article proposes an improved and efficient heterogeneous authentication scheme with a conditional privacy-preserving strategy that provides secure communication in WBANs. In the proposed scheme, we employed certificateless cryptography on the client side and Identity-Based Cryptography on the receiver side. The proposed scheme employs Hyperelliptic Curve Cryptography (HECC), a more advanced variation of Elliptic Curve Cryptography (ECC). HECC achieves the same level of security with a smaller key size and a more efficient approach than its counterpart methods. The proposed scheme not only meets the security and privacy standards of WBANs but also enhances efficiency in terms of computation and communication costs, according to the findings of the security and performance analysis

A Conditional Privacy Preserving Generalized Ring Signcryption Scheme for Micro Aerial Vehicles

Micro Aerial Vehicles (MAVs) are a type of UAV that are both small and fully autonomous, making them ideal for both civilian and military applications. Modern MAVs can hover and navigate while carrying several sensors, operate over long distances, and send data to a portable base station. Despite their many benefits, MAVs often encounter obstacles due to limitations in the embedded system (such as memory, processing power, energy, etc.). Due to these obstacles and the use of open wireless communication channels, MAVs are vulnerable to a variety of cyber-physical attacks. Consequently, MAVs cannot execute complex cryptographic algorithms due to their limited computing power. In light of these considerations, this article proposes a conditional privacy-preserving generalized ring signcryption scheme for MAVs using an identity-based cryptosystem. Elliptic Curve Cryptography (ECC), with a key size of 160 bits, is used in the proposed scheme. The proposed scheme’s security robustness has been analyzed using the Random Oracle Model (ROM), a formal security evaluation method. The proposed scheme is also compared in terms of computation cost, communication cost and memory overhead against relevant existing schemes. The total computation cost of the proposed scheme is 7.76 ms, which is 8.14%, 5.20%, and 11.40% schemes. The results show that the proposed scheme is both efficient and secure, proving its viability