highlighting their impact. Various cyber security applications, including intrusion detection systems (IDS), biometric systems, cyber-physical systems, and spam filtering, are studied in detail from an adversarial threat perspective on how ML systems...
Machine data monitoring allows you to collect and visualize IIoT data, enabling better understanding of machines, increased productivity and proactive services.
(2022). Machine Learning Based Network Intrusion Detection System for Internet of Things Cybersecurity. In: Kovács, T.A., Nyikes, Z., Fürstner, I. (eds) Security-Related Advanced Technologies in Critical Infrastructure Protection. NATO Science for Peace and Security Series C: Environmental ...
Cybersecurity is evolving from attempting to build increasingly secure programs and systems that try to prevent external attacks, to a more rounded solution including ongoing monitoring and prediction of threats. As cloud computing starts to replace traditional on-site server farms and software, it is...
robust monitoring for medical cyber-physical systems [Paper] detection of nasopharyngeal carcinoma using routine medical tests via machine learning [Paper] a machine learning approach for medical device classification [Paper] machine learning for the developing world [Paper] prediction of adverse ...
security analysts and the broader security community: the matrix and the case studies are meant to help in strategizing protection and detection; the framework seeds attacks on ML systems, so that they can carefully carry out similar exercises in their organizations and validate ...
tg12/gpt_jailbreak_status - A tool for monitoring jailbreak status of GPT models. Cyberlion-Technologies/ChatGPT_DAN - Another implementation of ChatGPT DAN mode prompts. yes133/ChatGPT-Prompts-Jailbreaks-And-More - Collection of various jailbreak prompts. THUDM/ChatGLM-6B - Collection of vario...
M2M applications span across various fields such as health, monitoring, security, home, and city automation. To facilitate such autonomous communication, several challenges must be addressed in different areas. Among other reasons, these challenges emerge from the unique characteristics of M2M communicatio...
security system automated and intelligent. To understand and analyze the actual phenomena with data, various scientific methods, machine learning techniques, processes, and systems are used, which is commonly known as data science. In this paper, we focus and briefly discuss oncybersecurity data ...
system performance across distributed IoT devices, indicating a direction for future research and development [171]. This is further supported by the work of Ferrag et al., who highlight the effectiveness of federated deep learning approaches in enhancing IoT cybersecurity and provide a comparative ...