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Advanced Persistent Threats (APT): evolution, anatomy, attribution and countermeasures

Journal of Ambient Intelligence and Humanized Computing 2023年第7期14卷 9355-9381页

作者： Sharma, Amit Gupta, Brij B. Singh, Awadhesh Kumar Saraswat, V.K. Department of Computer Engineering National Institute of Technology Kurukshetra Kurukshetra136119 India International Center for AI and Cyber Security Research and Innovations Department of Computer Science and Information Engineering Asia University Taichung Taiwan NITI Aayog New Delhi110001 India Lebanese American University Beirut Lebanon School of Computing Skyline University College Sharjah United Arab Emirates Department of Computer Engineering National Institute of Technology Kurukshetra Kurukshetra India Birkbeck University of London London United Kingdom

In today’s cyber warfare realm, every stakeholder in cyberspace is becoming more potent by developing advanced cyber weapons. They have equipped with the most advanced malware and maintain a hidden attribution. The precocious cyber weapons, targeted and motivated with some specific intention are called as Advanced Persistent Threats (APT). Developing defense mechanisms and performing attribution analysis of such advanced attacks are extremely difficult due to the intricate design of attack vector and sophisticated malware employed with high stealth and evasive techniques. These attacks also include advanced zero-day and negative-day exploits and payloads. This paper provides a comprehensive survey on the evolution of advanced malware design paradigms, APT attack vector and its anatomy, APT attack Tactics, Techniques, and Procedures (TTP) and specific case studies on open-ended APT attacks. The survey covers a detailed discussion on APT attack phases and comparative study on threat life-cycle specification by various organizations. This work also addresses the APT attack attribution and countermeasures against these attacks from classical signature and heuristic based detection to modern machine learning and genetics based detection mechanisms along with sophisticated zero-day and negative day malware countermeasure by various techniques like monitoring of network traffic and DNS logs, moving target based defense, and attack graph based defenses. Furthermore, the survey addresses various research scopes in the domain of APT cyber-attacks. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Life cycle

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Novel intelligent predictive networks for analysis of chaos in stochastic differential SIS epidemic model with vaccination impact

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Mathematics and computers in Simulation 2024年 219卷 251-283页

作者： Anwar, Nabeela Ahmad, Iftikhar Kiani, Adiqa Kausar Shoaib, Muhammad Raja, Muhammad Asif Zahoor Department of Mathematics University of Narowal 51600 Pakistan Department of Mathematics University of Gujrat 50700 Pakistan Future Technology Research Center National Yunlin University of Science and Technology 123 University Road Section 3 Yunlin Douliou64002 Taiwan Yuan Ze University AI Center Taoyuan320 Taiwan Department of Electrical and Computer Engineering COMSATS University Islamabad Attock Campus Attock43600 Pakistan

In this paper, stochastic predictive computing networks are exploited to investigate the dynamics of the SIS with vaccination impact based epidemic model (SISV-EM) represented by nonlinear systems of stochastic differential equations (SDEs) by exploitation of artificial neural networks (ANNs) with the backpropagated Levenberg-Marquardt technique (BLMT) i.e., (ANNs-BLMT) to approximate the solution behavior. The stochastic nonlinear SISV-EM is governed with three classes: susceptible, infectious, and vaccinated populations. The referenced or target datasets for ANNs-BLMT are constructed by employing Euler-Maruyama (EM) scheme for solving stochastic differential systems in case of sufficiently various nonlinear SISV-EM scenarios by varying the percentage of vaccination for newly born, the coefficient of transmission, the natural mortality rates, the infectious rates of recovery, the rate at which vaccinated people lose their immunity, the rate of death caused by disease, the proportion of vaccinated against susceptible and the white noise in the environment. Based on arbitrary training, testing, and validation samples from the referenced dataset, the ANNs-BLMT provides an approximate solution for the stochastic nonlinear SISV-EM, with significant correlations to the referenced results. Exhaustive simulation-based results using error histograms, mean square errors, and regression analyses further demonstrate that the proposed ANNs-BLMT is efficient, consistent, and accurate for solving SISV-EM. © 2023 International Association for Mathematics and computers in Simulation (IMACS)

关键词： Mean square error

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A Zero-Watermark Scheme Based on Quaternion Generalized Fourier Descriptor for Multiple Images

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computers, Materials & Continua 2022年第5期71卷 2633-2652页

作者： Baowei Wang Weishen Wang Peng Zhao Naixue Xiong School of Computer Science Nanjing University of Information Science and TechnologyNanjing210044China Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology(CICAEET) Nanjing210044China Engineering Research Center of Digital Forensics Ministry of EducationNanjing210044China Department of Mathematics and Computer Science Northeastern State UniversityTahlequahOK74464USA

Most of the existing zero-watermark schemes for medical images are only appropriate for a single grayscale *** they protect a large number of medical images,repeating operations will cause a significant amount of time and storage ***,this paper proposes an efficient zero-watermark scheme for multiple color medical images based on quaternion generalized Fourier descriptor(QGFD).Firstly,QGFD is utilized to compute the feature invariants of each color image,then the representative features of each image are selected,stacked,and reshaped to generate a feature matrix,which is then binarized to get a binary feature *** information can be converted into the copyright image by using QR code technology,which contains more ***,the zero-watermark image is constructed by executing the XOR operation on the copyright image and the feature image scrambled by the Cat *** the experiment,different parameters are selected to determine the maximum number of images that the proposed scheme can protect simultaneously while achieving good *** experimental results demonstrate that the proposed scheme can effectively resist common attacks,geometric attacks and joint attacks,and effectively improve the operation efficiency of the algorithm,thus effectively decreasing the time and storage cost of copyright protection for lots of medical images.

关键词： Copyright protection color medical image zero-watermark QGFD

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A leap by the rise of solid-state electrolytes for Li-air batteries

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Green Energy & Environment 2023年第4期8卷 939-944页

作者： Kecheng Pan Minghui Li Weicheng Wang Shuochao Xing Yaying Dou Shasha Gao Zhang Zhang Zhen Zhou Interdisciplinary Research Center for Sustainable Energy Science and Engineering(IRC4SE2) School of Chemical EngineeringZhengzhou UniversityZhengzhou450001China Key Laboratory of Microelectronics and Energy of Henan Province Department of Physics and Electronic EngineeringXinyang Normal UniversityXinyang464000China Key Laboratory of Advanced Energy Materials Chemistry(Ministry of Education) College of ChemistryNankai UniversityTianjin300071China

Li-air batteries have attracted extensive attention because of their ultrahigh theoretical energy density. However, the potential safety hazard of flammable organic liquid electrolytes hinders their practical applications. Replacing liquid electrolytes with solidstate electrolytes(SSEs) is expected to fundamentally overcome the safety issues. In this work, we focus on the development and challenge of solid-state Li-air batteries(SSLABs). The rise of different types of SSEs, interfacial compatibility and verifiability in SSLABs are presented. The corresponding strategies and prospects of SSLABs are also proposed. In particular, combining machine learning method with experiment and in situ(or operando)techniques is imperative to accelerate the development of SSLABs.

关键词： Solid-state Li-air batteries Solid-state electrolytes Interfacial compatibility and verifiability

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Climate-Based AI-Powered Precision Irrigation: Sustainably Smart Agriculture Frameworks for Maximum Crop Yields

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Remote Sensing in Earth Systems sciences 2024年第1期8卷 161-172页

作者： Dhanke, Jyoti A. Srivastava, Diksha Menaga, D. Raj, Roop Kumar, Kambala Vijaya Jangir, Pradeep Mani, P. Department of Engineering Science (Mathematics) Bharati Vidyapeeth’s College of Engineering Lavale Pune India Department of Biotechnology and Chemical Engineering Manipal University Jaipur Jaipur India Department of Computer Science and Engineering St. Joseph’s Institute of Technology Chennai India Department of Economics HNBG Central University Uttarakhand Srinagar India Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation AP Vaddeswaram India Department of Biosciences Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India Hourani Center for Applied Scientific Research Al-Ahliyya Amman University Amman 19328 Jordan K.Ramakrishnan College of Technology Trichy India

A digital transformation is necessary for agriculture to achieve sustainability and increase productivity. With the use of IoT, high-tech detectors and helicopters can monitor crop health and environmental factors in real time, transmitting crucial data to cloud-based systems. Due to their robust computational and storage capabilities, these systems are capable of handling large datasets and carrying out intricate data analytics. Even before the COVID-19 pandemic, the world’s food supply was precariously balanced and insufficient. The present agricultural system prioritizes short-term gains above the preservation of the earth and its ecosystems. To construct agricultural systems that can meet the needs of ten billion individuals in the next 30 years, significant structural and automated changes are required. However, with the support of intelligent technology and the progress of artificial intelligence in agriculture, these obstacles might be overcome. Integration of data, processing images, and neural networks are examples of artificial intelligence technologies that have allowed producers to make better choices using up-to-date information and prediction models. The study emphasizes the need to address the ethical and practical concerns associated with climate-based AI in agriculture to promote its equitable deployment. The results of this research contribute to the ongoing debate about artificial intelligence’s possible applications in farming. New agricultural technologies provide optimism for a future that is environmentally friendly and will be able to feed the growing global population. The integration of renewable energy sources is one of the areas where artificial intelligence is seen to be able to assist in reaching global sustainability goals. Artificial intelligence (AI) has the potential to revitalize both newly developed and existing agricultural land by modifying, deploying, and implementing automated systems and tools. We take stock of where AI is at

关键词： Artificial intelligence Climatic conditions Cloud computing Deep learning Energy Sustainable precision irrigation

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Optimizing Quality of Service Parameters for Optical Networks 15

Optimizing Quality of Service Parameters for Optical Network...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Khurana, Jatin Jayasree, S. Gupta, Shivangi Gowrishankar, J. Birare, Komal M. Balaji, N.V. Chitkara University Institute of Engineering and Technology Chitkara University Centre for Interdisciplinary Research for Business and Technology Punjab India Prince Shri Venkateshwara Padmavathy Engineering College Department of Science and Humanities Chennai127 India Quantum University Research Center Quantum University India Jain [Deemed to be University School of Engineering and Technology Computer Science Engineering Karnataka Bangalore India Vishwakarma Institute of Information Technology Department of Information Technology Pune India Karpagam Academy of Higher Education Department of Computer Science Coimbatore641021 India

ISBN: (纸本)9798350370249

Optical networks are generally designed to offer best of provider (QoS) guarantees to users, which will deliver provider of the appropriate satisfactory. However, because of availability, capacity, and infrastructure constraints, those QoS parameters might not be without problems optimized. This paper explores exclusive strategies for optimizing the QoS parameters in optical networks. It examines numerous techniques inclusive of community slicing and clever manipulate for improving carrier availability, quit-to-end latency, and quit-to-end throughput. It also investigates a couple of routing strategies, together with redundant packet routing, multipath routing, and dynamic routing, to improve hyperlink and node reliabilities, and common hop-matter. Sooner or later, it discusses the potential of the use of disbursed manipulate algorithms for adjusting various QoS parameters in real-time. The paper draws on a spread of simulation situations to demonstrate the effectiveness of these optimization strategies and algorithms. Common, this paper gives an in-depth examination of the various optimization strategies to be had for boosting satisfactory of provider in optical networks. © 2024 IEEE.

关键词： Examination Manipulate Parameters Provider Reliabilities Throughput

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Self-Learning Based Dependable Offloading Optimization in Semi-Trusted Vehicular Edge Computing and Networks

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IEEE Transactions on Vehicular Technology 2025年第5期74卷 8141-8157页

作者： Li, Xuehan Jing, Tao Li, Ruinian Wang, Xiaoxuan Yan, Yu Fan, Xin Huo, Yan Yu, Fei Richard Beijing Jiaotong University School of Electronic and Information Engineering National Engineering Research Center of Advanced Network Technologies Beijing100044 China Bowling Green State University Department of CS Bowling GreenOH43403 United States Beijing Forestry University School of Information Science and Technology Beijing100083 China Carleton University Department of Systems and Computer Engineering OttawaONK1S 5B6 Canada

As vehicular edge computing and networks (VECONs) emerge, Internet of vehicles (IoVs) is gaining significant advantages. To provide users with dependable services, VECONs need to offer efficient and secure task offloading services. Unfortunately, little effort has been put into addressing security issues such as the risk of privacy exposure when offloading data. Modeling and optimizing offloading dependability are affected by these issues. To address these concerns, a dependable three-layer offloading framework involving blockchain technology is presented in this paper, with fully homomorphic encryption (FHE) algorithm incorporated in order to mitigate privacy exposure risks. The framework divides tasks reasonably and introduces a novel measure of offloading dependability called cost from energy consumption, delay, and privacy exposure risk (cEDP) for constructing dependable offloading optimization. Additionally, a self-learning based dependable privacy preservation offloading (SDPPO) algorithm is presented that is capable of solving the optimal offloading problem in a decentralized manner. Simulation results show that the SDPPO algorithm outperforms its counterparts in terms of faster convergence speed, better cEDP convergence results, and improved scalability and tunability characteristics. © 1967-2012 IEEE.

关键词： Differential privacy

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Continuous Integration and Continuous Deployment (CI/CD) Pipeline for the SaaS Documentation Delivery 1

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3rd International Conference on Information Technology, InCITe 2023

作者： Satapathy, Bishnu Shankar Satapathy, Siddhartha Sankar Singh, S. Ibotombi Chakraborty, Joya Center for Multidisciplinary Research Tezpur University Napaam India Department of Computer Science and Engineering Tezpur University Napaam India Department of MCJ Tezpur University Assam Napaam784028 India

ISBN: (数字)9789819959945

ISBN: (纸本)9789819959938

User documentation is crucial in any product development lifecycle, Software or hardware. Without it, stakeholders struggle to comprehend the more complex functionalities—usually the most valuable critical components of any software. Providing comprehensive and easily accessible product documentation always helps avoid this worst‑case scenario. It enhances the user experience and takes full advantage of the Software. Many organizations prefer the unstructured local authoring license that is easy to use for the stakeholders involved in developing the product documentation. However, setting up an automated pipeline for this is a complex approach. Based on our several years of industry experience, we have presented an automated documentation deployment workflow in this article. This workflow helps stakeholders involved in decision-making to lay out a plan for documentation scope for the SaaS delivery. Following a doc-as-a-code approach, our proposed method will help the organization to save time and focus more on managing the end-user technical documentation related to SaaS customization and the application release delivery. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2023.

关键词： Pipelines

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A Comprehensive Image Processing Framework for Early Diagnosis of Diabetic Retinopathy

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computers, Materials & Continua 2024年第11期81卷 2665-2683页

作者： Kusum Yadav Yasser Alharbi Eissa Jaber Alreshidi Abdulrahman Alreshidi Anuj Kumar Jain Anurag Jain Kamal Kumar Sachin Sharma Brij BGupta College of Computer Science and Engineering University of Ha’ilHa’il81481Saudi Arabia Department of CSE Chandigarh UniversityMohaliPunjab140413India Department of Electronics and Communication Engineering Amity UniversityNoida201301India Department of Information Technology Indira Gandhi Delhi Technical University for WomenNew Delhi110006India Chief Manager State Bank of IndiaPanchkulaHaryana134109India Department of Computer Science and Information Engineering Asia UniversityTaichung City413Taiwan Symbiosis Centre for Information Technology(SCIT) Symbiosis International UniversityPune411057India Center for Interdisciplinary Research University of Petroleum and Energy Studies(UPES)Dehradun248007India

In today’s world,image processing techniques play a crucial role in the prognosis and diagnosis of various diseases due to the development of several precise and accurate methods for medical *** analysis of medical images is essential for doctors,as manual investigation often leads to inter-observer *** research aims to enhance healthcare by enabling the early detection of diabetic retinopathy through an efficient image processing *** proposed hybridized method combines Modified Inertia Weight Particle Swarm Optimization(MIWPSO)and Fuzzy C-Means clustering(FCM)*** FCM does not incorporate spatial neighborhood features,making it highly sensitive to noise,which significantly affects segmentation *** method incorporates a modified FCM that includes spatial functions in the fuzzy membership matrix to eliminate *** results demonstrate that the proposed FCM-MIWPSO method achieves highly precise and accurate medical image ***,segmented images are classified as benign or malignant using the Decision Tree-Based Temporal Association Rule(DT-TAR)*** analysis with existing state-of-the-art models indicates that the proposed FCM-MIWPSO segmentation technique achieves a remarkable accuracy of 98.42%on the dataset,highlighting its significant impact on improving diagnostic capabilities in medical imaging.

关键词： Image processing biological data PSO Fuzzy C-Means(FCM)

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Light Fidelity and Internet of Things for Medical Applications 4

Light Fidelity and Internet of Things for Medical Applicatio...

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4th International Conference of science and Information Technology in Smart Administration, ICSINTESA 2024

作者： Adi, Puput Dani Prasetyo Sariningrum, Ros Rahmatullah, Rizky Novita, Hessy Situngkir, Tiar Lina Adji, Priyo Hartono Lusiastuti, Angela Mariana Wibowo, Antonia Rahayu Rosaria Prastiyono, Yudi Adiprabowo, Tjahjo Yassir, Muhammad Maulana, Fairuz Iqbal Department of Telecommunication Bandung Indonesia Veterinary Research Center Bandung Indonesia Singaperbangsa University Faculty of Economics Department of Management Karawang Indonesia Bandung Indonesia Langlangbuana University Faculty of Engineering Department of Electrical Engineering Bandung Indonesia Institut Teknologi Dan Bisnis Nobel Department of System and Information System Makassar Indonesia Bina Nusantara University School of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350376111

This study focuses on transmitting data utilizing medical sensors that are vital for patients in hospitals and other settings. In this situation, Light Fidelity refers to transmitting medical sensor data or other data comprising the Transmitter (Tx) and the Receiver (Rx). If the Light Fidelity Principle is used, the Transmitter transmits LEDs or light to the Receiver. At the same time, the Receiver contains a receiver or light detection component known as the Light Dependent Resistor (LDR);using programming and this basic working principle, data can be sent from the LED Transmitter to the LDR Receiver using C++ Programming and its Library to send Medical sensor data. Sensors can include pulse sensors, like in prior research, and additional sensors such as SPO2 or blood pressure sensors. For medical data, a modest bit rate is sufficient, but LiFi applications can be created in such a way that they can be hybridized with WiFi and other RF devices such as LoRa and the Internet of Things. © 2024 IEEE.

关键词： C++ (programming language)

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