A threat intelligence framework for protecting smart satellite-based healthcare networks

Abstract

Human-to-machine (H2M) communication is an important evolution in the industrial internet of health things (IIoHT), where many H2M interfaces are remotely interacting with industrial and medical assets. Lightweight protocols, such as constrained application protocol (CoAP), have been widely utilised in transferring sensing data of medical devices to end-users in smart satellite-based healthcare IIoT networks (SmartSat-IIoHT). However, such protocols are extensively deployed without appropriate security configurations, making attackers’ mission easier for abusing these protocols to launch advanced cyber threats. This paper, therefore, presents a new threat intelligence framework to examine and model CoAP protocol’s attacks in these systems. We present a ransom denial of service (RDoS) as a new threat that would exploit this protocol’s vulnerabilities. We propose many RDoS attack’s techniques to understand the attack indicators and analyse their behaviour on systems. Moreover, we present a real-time discovery of attacks’ network behaviours using deep learning. The experiment results demonstrate that this proposed discovery model obtains a better performance in revealing RDoS than other conventional machine learning algorithms and accomplishing high fidelity of protecting SmartSat-IIoHT networks.

Navigating the nexus of security and privacy in modern financial technologies

“…Stay informed about the latest threat intelligence to anticipate emerging risks and vulnerabilities. According to [198], these activities are integral components of the cyber-security strategy in the financial services sector, where the landscape of cyber threats is dynamic and sophisticated. Continuous monitoring involves real-time surveillance of networks, systems, and data to promptly detect and respond to potential security incidents.…”

Cybersecurity Analytics in Protecting Satellite Telecommunications Networks: A Conceptual Development of Current Trends, Challenges, and Strategic Responses

“…Challenges in cybersecurity analytics for satellite networks include the complexity of satellite systems, limited visibility into network traffic, regulatory and compliance challenges, and insider threats and human error. To address these challenges, satellite operators are implementing strategic responses such as using advanced analytics techniques for anomaly detection, implementing secure-by-design principles in satellite system design, developing incident response plans and cyber resilience strategies, and investing in employee training and awareness programs (Al-Hawawreh, Moustafa & Slay, 2024, Bonnart, et. al., 2023, Breda, et.…”

Cybersecurity for Sustainable Smart Healthcare: State of the Art, Taxonomy, Mechanisms, and Essential Roles

“…This allows them to better understand threat incidents and make informed decisions about security approaches by sharing potential and existing cyber threat information with other organizations, individuals, or entities. Threat intelligence in smart healthcare refers to the collection, transformation, observation, analysis, and interpretation of any information or knowledge about cyber threats or attacks that will assist healthcare providers in taking appropriate action to protect their healthcare systems and networks [183]. Zhang et al [184] and Ali et al [185] define threat intelligence sharing as a proactive approach in which security experts in healthcare organizations collaborate to share insights and information about suspicious activities, potential cyber threats, attack patterns, and threat incidents with only trusted partners to enhance the entire security of the SHS and network.…”

“…Security professionals must analyze the acquired data to uncover trends and practical intelligence to help healthcare providers understand the threat scene and make informed security decisions. Smart healthcare systems use intrusion detection systems, firewalls, security information and event management solutions, and anomaly detection algorithms to quickly identify potential security incidents, suspicious activity and unauthorized access attempts [183]. Threat intelligence employs the information gathered through the security techniques mentioned above to determine threat or attack patterns [183].…”

“…Smart healthcare systems use intrusion detection systems, firewalls, security information and event management solutions, and anomaly detection algorithms to quickly identify potential security incidents, suspicious activity and unauthorized access attempts [183]. Threat intelligence employs the information gathered through the security techniques mentioned above to determine threat or attack patterns [183]. Healthcare providers must work with industry peers, government agencies, and cybersecurity organizations to share threat intelligence information and stay current on new cyber threats, vulnerabilities, and best practices to collectively defend SHSs and networks [140].…”