A New Collaborative Risk Assessment Model for Cloud Computing

Cloud computing has recently emerged a new paradigm by introducing potential benefits to Cloud users. Although the advantage of cloud computing are tremendous, number of security risk are emerging in association with cloud usage that need to be assessed. Assessing risk in Cloud computing environment remains an open research issue. This paper presents a collaborative risk assessment model for cloud computing, which is in compliance with all the specific characteristics of the Cloud Computing

An innovative medical waste management system in a smart city using XAI and vehicle routing optimization [version 1; peer review: 2 approved]

Background: The management of medical waste is a complex task that necessitates effective strategies to mitigate health risks, comply with regulations, and minimize environmental impact. In this study, a novel approach based on collaboration and technological advancements is proposed. Methods: By utilizing colored bags with identification tags, smart containers with sensors, object recognition sensors, air and soil control sensors, vehicles with Global Positioning System (GPS) and temperature humidity sensors, and outsourced waste treatment, the system optimizes waste sorting, storage, and treatment operations. Additionally, the incorporation of explainable artificial intelligence (XAI) technology, leveraging scikit-learn, xgboost, catboost, lightgbm, and skorch, provides real-time insights and data analytics, facilitating informed decision-making and process optimization. Results: The integration of these cutting-edge technologies forms the foundation of an efficient and intelligent medical waste management system. Furthermore, the article highlights the use of genetic algorithms (GA) to solve vehicle routing models, optimizing waste collection routes and minimizing transportation time to treatment centers. Conclusions: Overall, the combination of advanced technologies, optimization algorithms, and XAI contributes to improved waste management practices, ultimately benefiting both public health and the environment

LnaCBR:Case Based Reasoning Architecture for Intrusion Detection to Learning New Attacks

The agents used in the intrusion detection architectures have multiple characteristics namely delegation, cooperation and communication. However, an important property of agents: learning is not used. The concept of learning in existing IDSs used in general to learn the normal behavior of the system to secure. For this,normal profiles are built in a dedicated training phase, these profiles are then compared with the current activity. Thus, the IDS does not have the ability to detect new attacks. We propose in this paper, a new architecture based intrusion MAS adding a learning feature abnormal behaviors that correspond to new attack patterns detection. Thanks to this feature to update the knowledge base of attacks take place when a new plan of attack is discovered. To learn a new attack, the architecture must detect at first and then update the basic attack patterns. For the detection step, the detection approach adopted is based on the technique of Case-Based Reasoning (CBR). Thus, the proposed architecture is based on a hierarchical and distributed strategy where features are structured and separated into layers

Multi-Rotors Unmanned Aerial Vehicles Power Supply and Energy Management

Interest in electric unmanned aerial vehicles (UAVs) has grown rapidly in recent years, and their applications have expanded and diversified considerably since they first appeared, for both commercial and private purposes. Thanks to their ability to perform challenging and hazardous tasks with high mobility, safety, and low cost. As academic researchers, we are concerned with commercial multi-rotor UAVs, which are revolutionizing many public services, including search and rescue operations, wireless coverage, delivery services, precision agriculture, wildlife surveys, and real-time surveillance. One of the UAVs main issues when it comes to mobility is the limited energy autonomy/endurance. Many types of power supplies can be implemented in UAVs, each with its specific strengths and shortfalls in terms of size, charging/discharging time, energy density and power density. This paper focuses on UAVs energy aspect, with a comprehensive review of the main power sources available for multi-rotors UAVs, and energy management systems to uncover gaps and provide further insights and guidelines for future research