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A Machine Learning based Empirical Evaluation of Cyber Threat Actors High Level Attack Patterns over Low level Attack Patterns in Attributing Attacks

arXiv

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arXiv 2023年

作者： Noor, Umara Shahid, Sawera Kanwal, Rimsha Rashid, Zahid Pakistan Technology Management Economics and Policy Program College of Engineering Seoul National University 1 Gwanak-Ro Gwanak-Gu Seoul08826 Korea Republic of

Cyber threat attribution is the process of identifying the actor of an attack incident in cyberspace. An accurate and timely threat attribution plays an important role in deterring future attacks by applying appropriate and timely defense mechanisms. Manual analysis of attack patterns gathered by honeypot deployments, intrusion detection systems, firewalls, and via trace-back procedures is still the preferred method of security analysts for cyber threat attribution. Such attack patterns are low-level Indicators of Compromise (IOC). They represent Tactics, Techniques, Procedures (TTP), and software tools used by the adversaries in their campaigns. The adversaries rarely re-use them. They can also be manipulated, resulting in false and unfair attribution. To empirically evaluate and compare the effectiveness of both kinds of IOC, there are two problems that need to be addressed. The first problem is that in recent research works, the ineffectiveness of low-level IOC for cyber threat attribution has been discussed intuitively. An empirical evaluation for the measure of the effectiveness of low-level IOC based on a real-world dataset is missing. The second problem is that the available dataset for high-level IOC has a single instance for each predictive class label that cannot be used directly for training machine learning models. To address these problems in this research work, we empirically evaluate the effectiveness of low-level IOC based on a real-world dataset that is specifically built for comparative analysis with high-level IOC. The experimental results show that the high-level IOC trained models effectively attribute cyberattacks with an accuracy of 95% as compared to the low-level IOC trained models where accuracy is 40%. © 2023, CC BY.

关键词： Intrusion detection

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An Integer Linear programming for Hospital Bed Scheduling and Capacity management 22

An Integer Linear Programming for Hospital Bed Scheduling an...

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4th International Conference on management Science and Industrial engineering, MSIE 2022

作者： Jewpanya, Parida Acla, Arni Ellorin-Igros, Clarinda Joanne Santos, Aira Ronalie P. Rachmandika, Pino Prasetyo, Dimas Redi, Anak Agung Ngurah Perwira Department of Industrial Engineering Rajamangala University of Technology Lanna Tak Tak Thailand School of Industrial Engineering and Engineering Management Mapúa University 658 Muralla St. Intramuros Manila1002 Philippines Industrial Engineering Department Binus Graduate Program - Master of Industrial Engineering Bina Nusantara University Jakarta11480 Indonesia Binus University Banten Tangerang15325 Indonesia

ISBN: (纸本)9781450395816

COVID-19 has struck the Philippines in December 2019 and has brought great panic to the country's healthcare system. In a short period of time, the number of infected increased exponentially. Hospitals are suddenly filled with patients infected by the virus to the extent that patients wait for hours to days to be admitted. Others die on the road even before finding hospitals that can accommodate them. The hospitals and the country's healthcare system must consider this increasing demand to serve patients fully. Patient planning is commonly used in other countries to maximize bed allocation. A recent study using Bernoulli Distributed Random Variable represents the binary integer program. The approach combines the queuing model and simulation to reduce the patient dismissal rate and increase hospital output. On the other hand, this paper deals with strategic hospital bed capacity optimization using linear integer programming by considering the diverse resources, such as doctors, nurses, beds, and hospital rooms. © 2022 ACM.

关键词： Hospitals

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Reentrant hybrid flow shop scheduling with stockers in automated material handling systems using deep reinforcement learning

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Computers and Industrial engineering 2024年 189卷

作者： Lin, Chun-Cheng Peng, Yi-Chun Chang, Yung-Sheng Chang, Chun-Hsiang Department of Industrial Engineering and Management National Yang Ming Chiao Tung University Hsinchu300 Taiwan International Master Program of Smart Manufacturing and Applied Information Science National Chin-Yi University of Technology Taichung411 Taiwan

In smart factories, automated material handling system (AMHSs) replace manual material handling to increase production efficiency, in which stockers serve as the temporary storage for work-in-process inventories. Furthermore, costly machines and complex processes in advanced manufacturing lead to the need for multiple reentrant processes of the same workstation. However, previous works on scheduling problems rarely considered the function of stockers and reentrant processes, and their approaches were mostly based on metaheuristic algorithms. Recent advances in artificial intelligence enable the possibility of solving scheduling problems using deep reinforcement learning (DRL). Therefore, this work investigates the reentrant hybrid flow shop scheduling problem with stockers (RHFS2) inspired by AMHSs, and solves it by DRL. Firstly, the states, actions, and rewards of the Markov decision process for this problem are designed;and then, two deep Q network (DQN) approaches based on the actions for determining machines and jobs, respectively, are proposed. Simulation results demonstrate that our proposed DQN approaches outperform for finding better solutions of different-scale problems than classical metaheuristic algorithms. © 2024 Elsevier Ltd

关键词： Reinforcement learning

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The last decade epidemiologic concern of drinking water contaminants of emerging concern (CECs) in Asian Countries: A scoping review

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Heliyon 2024年第20期10卷 e39236页

作者： Nathanael, Rinaldy Jose Adyanis, Latonia Nur Oginawati, Katharina Environmental Engineering Program Faculty of Science and Technology Airlangga University Surabaya 60115 Indonesia Department of Environmental Engineering Chung Yuan Christian University Taoyuan 320314 Taiwan Environmental Management Technology Research Group Department of Environmental Engineering Faculty of Civil and Environmental Engineering Bandung Institute of Technology Bandung 40132 Indonesia

With the rapid industrialization and urbanization in Asian countries, the challenge of rising emerging contaminants in the environment, including the water cycle, has become more pronounced. Consequently, the presence of CECs in drinking water systems is inevitable due to their ubiquitous nature in aquatic environments. This scoping review aims to identify epidemiological concerns regarding drinking water CECs in Asian countries over the past decade by describing the types of assessed CECs, their associated health effects, and identifying gaps and future research prospects through a summary of relevant studies. Searches were conducted on PubMed and Scopus up to February 29, 2024. Included were epidemiological studies from the past 10 years (since January 2014) in Asian countries that assessed emerging contaminants in drinking water through direct measurement or analysis as factors. From an initial pool of 3198 results, 15 relevant studies were selected. These studies assessed various types of CECs, including disinfection byproducts (n = 10), endocrine disruptors (n = 2), pesticides (n = 2), and a protozoan pathogen (n = 1). The meticulous assessment of CECs and associated health outcomes in Asian epidemiological studies over the past decade has been deemed inadequate to address the wide range of ubiquitous CECs in drinking water and their potential health effects that have not yet been addressed. While not the sole objective, the primary aim of epidemiological studies is to inform policy decisions and increase awareness among the public and policymakers. Therefore, researchers in Asian countries, particularly in environmental and public health fields, should prioritize the development of research in this area by exploring more CECs type and associated health outcomes. © 2024 The Author(s)

关键词： Asia Drinking water Emerging contaminants Epidemiology Scoping review

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Joint green dynamic order batching and picker routing problem using PSO with global worst experience

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Applied Soft Computing 2024年 154卷

作者： Lin, Chun-Cheng Peng, Yi-Chun Kang, Jia-Rong Department of Industrial Engineering and Management National Yang Ming Chiao Tung University Hsinchu300 Taiwan International Master Program of Smart Manufacturing and Applied Information Science National Chin-Yi University of Technology Taichung411 Taiwan Department of Information Management Tatung University Taipei104 Taiwan

With the increasing importance of various countries’ initiatives on reducing carbon emissions (e.g., carbon border adjustment mechanism, CBAM), intelligent order picking systems have assisted electronic retailers in realizing a green supply chain. Previous studies on picker routing operations focused on adopting offline static customer order information to carry out operational decisions. However, in practice, the customer order information is updated dynamically;and high-efficiency warehouse layouts have been increasingly concerned. Therefore, this study creates a mixed-integer programming model for minimizing both the total carbon footprint and the total penalty cost for delayed orders in the joint order batching and picker routing problem with dynamic arriving orders and shipping time constraints in a high-efficiency fishbone warehouse layout. To solve this complex problem, a particle swarm optimization algorithm that integrates the swarm's previous global and local worst experiences and a migration mechanism is further proposed to increase solution quality and computing efficiency. In addition, a three-dimensional space for the warehouse floorplan and shipping time constraints is designed to divide orders into batches to address the constraints. Theoretical analysis of this algorithm is conducted, and experimental analysis shows that this algorithm finds superior solutions than current practical strategies, to offer a valuable reference for carbon emission reduction in greening warehousing. © 2024 Elsevier B.V.

关键词： Carbon footprint

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Sensory Perception of Haptic Rendering in Surgical Simulation

Sensory Perception of Haptic Rendering in Surgical Simulatio...

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International Conference on Computing and Networking technology (ICCNT)

作者： Rohit Kaushik Rachit Sachdeva Chirag Vashisht Krishan Kant Choudhary CS and Mathematics Department Data Analytics Program University of Illinois Springfield USA Electronics and Communication Engineering Department Dr. Akhilesh Das Gupta Institute of Technology and Management New Delhi India Information Technology and Engineering Department Dr. Akhilesh Das Gupta Institute of Technology and Management New Delhi India

The essential ideas behind haptic technology, including haptic interface and haptic rendering methods, as well as its application to surgical simulation, medical education, and other diverse topics, are presented in this paper. In empirical psychology and physiology, this refers to the sense of contact. The process of analyzing and developing capabilities in response to user interactions with virtual entities is elaborated as haptic rendering. Haptic may indicate haptic transmission, haptic perception, and haptic technology. Humans and other animals can respond to one another by using their feelings through haptic technology. Haptic perception is the process of recognizing objects through *** implies tactile response, which means it delivers feedback in the state of sensation as we may sense the material properties and motions of virtual objects devised by a computer. The use of haptic technology in the medical profession has proven extremely beneficial, and it has a wide range of applications in many different industries. Providing effective exchange via virtual reality helps to ease the surgeon’s obligations. Amplify a person’s experience in the virtual environment. The haptics ability ranges from computer graphics to psychophysics, cognitive science, and neurosciences.

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Dermatological Diagnostics: A Unified Deep Learning Framework for Skin Lesion and Cancer Classification

Dermatological Diagnostics: A Unified Deep Learning Framewor...

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Advances in Computing, Communication and Networking (ICAC2N), International Conference on

作者： Vinod Kumar Isha Jain Durga Sritha Dongla Shivangi Rai Vani Rastogi Eva Kaushik Rohit Kaushik School of Engineering & Applied Science The George Washington University Washington D.C USA Computer Science & Engineering Department Dr. Akhilesh Das Gupta Institute of Technology and Management New Delhi India Computer Science & Engineering Department Gandhi Institute of Technology and Management Visakhapatnam Andhra Pradesh Data Scientist DXC Technology Noida India CS and Mathematics Department Data Analytics Program University of Illinois Springfield USA

ISBN: (数字)9798350356816

ISBN: (纸本)9798350356823

Skin pathologies encompass a spectrum of conditions, with malignancies such as melanoma representing a critical diagnostic urgency. This investigation delineates the deployment of Convolutional Neural Networks (CNNs) for the classification of dermatological anomalies, benchmarking CNN diagnostic fidelity against dermatological expert evaluations. The study underscores the efficacy of CNN classifiers in expediting the diagnostic workflow for various cutaneous disorders. Advocating for an automated diagnostic framework, the research introduces a CNN-based system aimed at reducing human diagnostic load, accelerating diagnostic timelines, and enhancing survival outcomes. Utilizing advanced image processing algorithms and deep learning architectures, the research presents an automated classification system for skin pathologies, addressing both benign and malignant presentations. The classification matrix includes nine dermatological conditions: actinic keratosis, basal cell carcinoma, benign keratosis, dermatofibroma, melanoma, nevus, seborrheic keratosis, squamous cell carcinoma, and vascular lesions. The objective is to engineer a CNN model with robust diagnostic performance across a diverse lesion dataset, ensuring accurate identification and categorization of dermatological conditions.

关键词： Deep learning Pathology Accuracy Melanoma Computer architecture Benchmark testing Skin Convolutional neural networks Lesions Medical diagnosis

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The Challenges and Opportunities of Transitioning to Modular Smartphones

The Challenges and Opportunities of Transitioning to Modular...

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Conference on Technologies for Sustainability (Sustech)

作者： Kevin Lomax Jaap Donker Jonah Milnor Charles Pringle Susan Rivera Information Technology and Administrative Management Department Central Washington University Finance Accounting and Economics Departments Central Washington University Engineering Technologies Safety and Construction Department Central Washington University Professor MET Program Coordinator Engineering Technologies Safety and Construction Department Central Washington University Professor Information Technology and Administrative Management Department Central Washington University

ISBN: (数字)9798350394344

ISBN: (纸本)9798350394351

This paper proposes a perspective analysis of the barriers that inhibit the uptake of modular phones as well as feasible design and market opportunities. Electronic waste (e-waste) increases yearly, and precious materials are often improperly recycled. A few thought leaders have proposed modular electronics as a solution to reduce waste and harmful GHG emissions at all stages of the smartphone lifecycle. However, obstacles exist, such as planned obsolescence business strategies that tend to dominate the current market and technical challenges associated with sealing modular devices. To compete with existing smartphone products, such as iPhone and Samsung devices, the ingress protection ratings of the more repairable modular devices should be comparable. The paper will propose potential solutions to each of the identified obstacles.

关键词： Resistance Supply chains Electronic waste Sustainable development Protection Consumer electronics Commercialization

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Quantifying Construction and Demolition Waste Using SLAM-Based Mobile Mapping System: A Case Study from Kafr El Sheikh, Egypt

Quantifying Construction and Demolition Waste Using SLAM-Bas...

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2021 International Conference on Data Analytics for Business and Industry, ICDABI 2021

作者： Attia, Tarek Elshaboury, Nehal Hesham, Amr Elhadary, Mohamed Construction and Project Management Research Institute Housing and Building National Research Centre Giza Egypt Construction Engineering Management Program Arab Academy for Science Technology Maritime Transport Giza Egypt

ISBN: (纸本)9781665416566

The quantities of construction and demolition waste (CDW) have significantly augmented due to rapid urbanization in Egyptian cities. This waste stream threatens public health and the environment. Quantifying waste is considered aCDW in Kafr El Sheikh Governorate, Egypt. The results show that the quantity of CDW in the study areas is estimated to be 19,174.071 cubic meters. The proposed methodology could be further extended in other Egyptian governorates facing the same challenges of data unavailability. This research provides the government bodies, policymakers, investors, demolition engineers, and researchers with reliable estimates of CDW quantities. © 2021 IEEE.

关键词： Demolition

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Conceptual Model of Graph-based Individual Tree and Its Utilization in Digital Twin and Metaverse of Urban Forest

Conceptual Model of Graph-based Individual Tree and Its Util...

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2024 Symposium on Spatial Information to Empower the Metaverse

作者： Ambarwari, Agus Suwardhi, Deni Rani, Medria Shekar Husni, Emir Junaidy, Deny Willy Agirachman, Fauzan Alfi Murtiyoso, Arnadi Griess, Verena Christiane Doctoral Program of Electrical Engineering and Informatics School of Electrical Engineering and Informatics Institut Teknologi Bandung Jl. Ganesha No.10 Bandung40132 Indonesia Faculty of Earth Sciences and Technology Institut Teknologi Bandung Indonesia School of Architecture Planning and Policy Development Institut Teknologi Bandung Indonesia School of Electrical Engineering and Informatics Institut Teknologi Bandung Indonesia Faculty of Art and Design Institut Teknologi Bandung Indonesia Department of Environmental Systems Science Forest Resources Management Institute of Terrestrial Ecosystems Zurich8092 Switzerland

3D city models are an important cornerstone in the development of digital twin cities, allowing for various analyses and simulations. CityGML, as an open standard for 3D city models, emphasizes five main aspects: scale or level of detail (LoD), semantics, geometry, topology, and appearance. One of the important elements in CityGML 3D city models is representation of vegetation. Vegetation in CityGML, especially individual trees, is still limited in terms of detail and resolution, reducing its effectiveness for specific applications. This paper proposes a graph-based conceptual model for individual trees that conforms to the CityGML v2.0 specification. The model refers to the morphological structure of a tree consisting of roots, trunk, and crown (including branches, twigs, and leaves), and considers the five main aspects of CityGML. By enhancing semantic information and geometric details, the model aims to provide an information-rich and realistic representation of individual trees in a 3D city environment. The 3D tree model created based on this conceptual model may be applicable in the development of digital twin urban forests and virtual forest simulations that utilize immersive technologies such as the metaverse. This research opens up new opportunities in the development of solitary vegetation objects through CityGML ADE by including more detailed semantic and topological information. © Author(s) 2024.

关键词： Digital elevation model

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