Sahar Badri¹, Sana Ullah Jan^2,*, Daniyal Alghazzawi¹, Sahar Aldhaheri¹, Nikolaos Pitropakis²

Computer Systems Science and Engineering, Vol.46, No.3, pp. 3667-3684, 2023, DOI:10.32604/csse.2023.037531

Abstract Rapid technological advancement has enabled modern healthcare systems to provide more sophisticated and real-time services on the Internet of Medical Things (IoMT). The existing cloud-based, centralized IoMT architectures are vulnerable to multiple security and privacy problems. The blockchain-enabled IoMT is an emerging paradigm that can ensure the security and trustworthiness of medical data sharing in the IoMT networks. This article presents a private and easily expandable blockchain-based framework for the IoMT. The proposed framework contains several participants, including private blockchain, hospital management systems, cloud service providers, doctors, and patients. Data security is ensured by incorporating an attribute-based encryption scheme. Furthermore,… More >

So-Eun Jeon¹, Sun-Jin Lee¹, Eun-Young Lee¹, Yeon-Ji Lee², Jung-Hwa Ryu², Jung-Hyun Moon², Sun-Min Yi², Il-Gu Lee^1,2,*

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 4231-4253, 2023, DOI:10.32604/cmc.2023.034287

Abstract Recently, with the normalization of non-face-to-face online environments in response to the COVID-19 pandemic, the possibility of cyberattacks through endpoints has increased. Numerous endpoint devices are managed meticulously to prevent cyberattacks and ensure timely responses to potential security threats. In particular, because telecommuting, telemedicine, and tele-education are implemented in uncontrolled environments, attackers typically target vulnerable endpoints to acquire administrator rights or steal authentication information, and reports of endpoint attacks have been increasing considerably. Advanced persistent threats (APTs) using various novel variant malicious codes are a form of a sophisticated attack. However, conventional commercial antivirus and anti-malware systems that use signature-based… More >

Abdelwahed Motwakel^1,*, Fadwa Alrowais², Khaled Tarmissi³, Radwa Marzouk⁴, Abdullah Mohamed⁵, Abu Sarwar Zamani¹, Ishfaq Yaseen¹, Mohamed I. Eldesouki⁶

Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 3157-3173, 2023, DOI:10.32604/iasc.2023.034908

Abstract The paradigm shift towards the Internet of Things (IoT) phenomenon and the rise of edge-computing models provide massive potential for several upcoming IoT applications like smart grid, smart energy, smart home, smart health and smart transportation services. However, it also provides a sequence of novel cyber-security issues. Although IoT networks provide several advantages, the heterogeneous nature of the network and the wide connectivity of the devices make the network easy for cyber-attackers. Cyberattacks result in financial loss and data breaches for organizations and individuals. So, it becomes crucial to secure the IoT environment from such cyberattacks. With this motivation, the… More >

Faisal S. Alsubaei¹, Haya Mesfer Alshahrani², Khaled Tarmissi³, Abdelwahed Motwakel^4,*

Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 2897-2914, 2023, DOI:10.32604/iasc.2023.034907

Abstract Cybersecurity has become the most significant research area in the domain of the Internet of Things (IoT) owing to the ever-increasing number of cyberattacks. The rapid penetration of Android platforms in mobile devices has made the detection of malware attacks a challenging process. Furthermore, Android malware is increasing on a daily basis. So, precise malware detection analytical techniques need a large number of hardware resources that are significantly resource-limited for mobile devices. In this research article, an optimal Graph Convolutional Neural Network-based Malware Detection and classification (OGCNN-MDC) model is introduced for an IoT-cloud environment. The proposed OGCNN-MDC model aims to… More >

Younghoon Ban, Jeong Hyun Yi, Haehyun Cho^*

Computer Systems Science and Engineering, Vol.46, No.2, pp. 2215-2230, 2023, DOI:10.32604/csse.2023.036555

Abstract Android malware has evolved in various forms such as adware that continuously exposes advertisements, banking malware designed to access users’ online banking accounts, and Short Message Service (SMS) malware that uses a Command & Control (C&C) server to send malicious SMS, intercept SMS, and steal data. By using many malicious strategies, the number of malware is steadily increasing. Increasing Android malware threats numerous users, and thus, it is necessary to detect malware quickly and accurately. Each malware has distinguishable characteristics based on its actions. Therefore, security researchers have tried to categorize malware based on their behaviors by conducting the familial… More >

Mesfer Al Duhayyim^1,*, Heba G. Mohamed², Fadwa Alrowais³, Fahd N. Al-Wesabi⁴, Anwer Mustafa Hilal⁵, Abdelwahed Motwakel⁵

Computer Systems Science and Engineering, Vol.46, No.2, pp. 1293-1310, 2023, DOI:10.32604/csse.2023.035589

Abstract The Internet of Things (IoT) has gained more popularity in research because of its large-scale challenges and implementation. But security was the main concern when witnessing the fast development in its applications and size. It was a dreary task to independently set security systems in every IoT gadget and upgrade them according to the newer threats. Additionally, machine learning (ML) techniques optimally use a colossal volume of data generated by IoT devices. Deep Learning (DL) related systems were modelled for attack detection in IoT. But the current security systems address restricted attacks and can be utilized outdated datasets for evaluations.… More >

A. S. Yusuf^1,*, A. Q. Ayinde²

Journal of Cyber Security, Vol.4, No.3, pp. 185-188, 2022, DOI:10.32604/jcs.2022.035446

Abstract Hospitals provide daily health services for thousands of patients. People, processes, and technologies drive the objectives and goals of the hospitals to ensure optimal and satisfactory health care services are rendered to their customers. Due to the sensitivity of the organization data and patient data, it is essential to ensure that the confidentiality, integrity, availability, and security of these data are considered. The leadership of the organization (managers and executives) must integrate a robust security plan when choosing the technologies that will be used to drive the organization’s processes. This paper will evaluate the existing technologies risk assessment, and the… More >

Faneela¹, Muazzam A. Khan¹, Suliman A. Alsuhibany^2,*, Walid El-Shafai^3,4, Mujeeb Ur Rehman⁵, Jawad Ahmad⁶

Computer Systems Science and Engineering, Vol.46, No.1, pp. 165-179, 2023, DOI:10.32604/csse.2023.035066

Abstract The advancements in sensing technologies, information processing, and communication schemes have revolutionized the healthcare sector. Electronic Healthcare Records (EHR) facilitate the patients, doctors, hospitals, and other stakeholders to maintain valuable data and medical records. The traditional EHRs are based on cloud-based architectures and are susceptible to multiple cyberattacks. A single attempt of a successful Denial of Service (DoS) attack can compromise the complete healthcare system. This article introduces a secure and immutable blockchain-based framework for the Internet of Medical Things (IoMT) to address the stated challenges. The proposed architecture is on the idea of a lightweight private blockchain-based network that… More >

Dong-Wook Kim¹, Gun-Yoon Shin¹, Myung-Mook Han^2,*

Computer Systems Science and Engineering, Vol.46, No.1, pp. 153-164, 2023, DOI:10.32604/csse.2023.034589

Abstract Unlike external attacks, insider threats arise from legitimate users who belong to the organization. These individuals may be a potential threat for hostile behavior depending on their motives. For insider detection, many intrusion detection systems learn and prevent known scenarios, but because malicious behavior has similar patterns to normal behavior, in reality, these systems can be evaded. Furthermore, because insider threats share a feature space similar to normal behavior, identifying them by detecting anomalies has limitations. This study proposes an improved anomaly detection methodology for insider threats that occur in cybersecurity in which a discrete wavelet transformation technique is applied… More >

Maha Sabir¹, Jawad Ahmad^2,*, Daniyal Alghazzawi¹

Computer Systems Science and Engineering, Vol.46, No.1, pp. 57-72, 2023, DOI:10.32604/csse.2023.034277

Abstract The Internet of things (IoT) is an emerging paradigm that integrates devices and services to collect real-time data from surroundings and process the information at a very high speed to make a decision. Despite several advantages, the resource-constrained and heterogeneous nature of IoT networks makes them a favorite target for cybercriminals. A single successful attempt of network intrusion can compromise the complete IoT network which can lead to unauthorized access to the valuable information of consumers and industries. To overcome the security challenges of IoT networks, this article proposes a lightweight deep autoencoder (DAE) based cyberattack detection framework. The proposed… More >