# Safety and Security Considerations for Online Laboratory Management Systems
## 1 Introduction  
Different technologies have developed continuously in recent decades for e-learning education, leading to considerable progress and innovation in several fields, including industry, business, finance, healthcare, management, education, and other educational services. Consequently, e-learning frameworks and tools have expanded and incorporated rapidly as new concepts of e-learning tools and remote laboratories [1]. The COVID-19 pandemic significantly advanced the transition to e-learning, establishing it as a worldwide central component of modern education. Educational institutions adopted Online Laboratory Management Systems (OLMSs) to allow students to interact with professional engineering tools and gain real-world experiences through web-based platforms. OLMSs include features that help manage laboratory experiments, schedule experiments, deliver assignments, control remote experiments, generate experiment reports, and automatically grade laboratory experiments [2]. The Latin American and Caribbean Consortium of Engineering Institutions (LAC-CEI) [3] is a non-profit organization that collaborates with the Organization of American States (OAS) [4], supporting initiatives by the Ministers of Science and Technology of OAS member countries. The LACCEI research team is currently developing Smart Adaptive Remote Laboratories (SARLs) [5], which are a type of OLMS. SARL is an e-learning system that incorporates an adaptive approach based on student academic profiles, allowing SARL to adapt the activities and challenges of laboratory experiments accordingly. Remote laboratory stations utilize Raspberry Pi microcontrollers, which are connected to laboratory equipment and receive and execute SARL commands transmitted by students through a browser interface. In addition, laboratory stations are equipped with webcams to capture and stream the current state of the laboratory to the user. SARL developers actively engage in multiple Institute of Electrical and Electronic Engineers (IEEE) standard development working groups to ensure the integration of best practices and standards within their e-learning platforms. They consistently incorporate emerging standards into their platforms [6], including the IEEE Standard 1876-2019 on Networked Smart Learning Objects for Online Laboratories [7], IEEE P2834 Standard for Secure and Trusted E-Learning Systems [8], and IEEE P7004.1 Standard for Safe and Secure Virtual Classroom [9]. In addition, ongoing efforts are underway to develop additional IEEE and International Organization for Standardization (ISO) standards, such as the IEEE P2881 Standard for Learning Metadata [10] and ISO 2700x Information Security Standard [11]. This paper comprehensively analyzes safety and security solutions for OLMS and remote laboratories, highlighting seven key focus areas, including general security concerns, security frameworks, access control and authentication, threats and vulnerabilities, integrity and monitoring, communication security, and safety. Several researchers presented safety and security solutions for remote laboratories. However, gaps are unresolved, including the technical complexity of developing secure systems, the absence of standardized architecture, and the need for specialized security patterns. Addressing these issues could enhance scalability, promote broader adoption, and strengthen the overall security of remote laboratories by implementing a \"security by design\" approach. This paper is structured as follows: Section 2 describes the research methodology, including the taxonomy and the systematic literature review process. Section 3 outlines the field's state of the art, focusing on the history of the remote laboratories, the progression of computer safety and security, relevant legal frameworks and regulations, specific safety and security challenges, and the solutions proposed for OLMS environments. Section 4 details the results of the literature analysis and the remaining gaps. Section 5 addresses the conclusion and future work.