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Neural Knowledge Extraction From Cloud Service Incidents [article]

Manish Shetty, Chetan Bansal, Sumit Kumar, Nikitha Rao, Nachiappan Nagappan, Thomas Zimmermann
2021 arXiv   pre-print
We have built SoftNER, a framework for unsupervised knowledge extraction from service incidents.  ...  In this work, we address the fundamental problem of structured knowledge extraction from service incidents.  ...  Different from existing work, we focus on the fundamental problem of knowledge extraction from the service incidents.  ... 
arXiv:2007.05505v4 fatcat:p5z5hmtedvayffljwb5gw4z2jq

DeepTriage: Automated Transfer Assistance for Incidents in Cloud Services [article]

Phuong Pham, Vivek Jain, Lukas Dauterman, Justin Ormont, Navendu Jain
2020 arXiv   pre-print
However, automated incident triage in large cloud services faces many challenges: (1) a highly imbalanced incident distribution from a large number of teams, (2) wide variety in formats of input data or  ...  neural networks - in an ensemble to recommend the responsible team to triage an incident.  ...  To the best of our knowledge, we are the first one to present a deployed incident triage service for cloud-scale online services.  ... 
arXiv:2012.03665v1 fatcat:z76hgim6nfbv5amfsondytjlki

SoftNER: Mining Knowledge Graphs From Cloud Incidents [article]

Manish Shetty, Chetan Bansal, Sumit Kumar, Nikitha Rao, Nachiappan Nagappan
2021 arXiv   pre-print
In this work, we address the fundamental problem of structured knowledge extraction from service incidents. We have built SoftNER, a framework for mining Knowledge Graphs from incident reports.  ...  We have deployed SoftNER at Microsoft, a major cloud service provider and have evaluated it on more than 2 months of cloud incidents.  ...  As shown in Figure 3 , the knowledge graph nodes represent cloud services, incidents, and entities extracted from incidents, and edges represent relatedness.  ... 
arXiv:2101.05961v2 fatcat:envypijvyvej3lieo3yqudf6ri

Role of artificial intelligence in cloud computing, IoT and SDN: Reliability and scalability issues

Mohammad Riyaz Belgaum, Zainab Alansari, Shahrulniza Musa, Muhammad Mansoor Alam, M. S. Mazliham
2021 International Journal of Power Electronics and Drive Systems (IJPEDS)  
Information technology fields are now more dominated by artificial intelligence, as it is playing a key role in terms of providing better services.  ...  The key technologies like cloud, internet of things (IoT), and software-defined networking (SDN) are emerging as future applications and rendering benefits to the society.  ...  Machine learning can be used for extracting knowledge from previous instances. Neural networks can be used for mapping the tasks.  ... 
doi:10.11591/ijece.v11i5.pp4458-4470 fatcat:n3qfb3y5bjfljfp5jcgbnnto6m

Securing Machine Learning in the Cloud: A Systematic Review of Cloud Machine Learning Security

Adnan Qayyum, Aneeqa Ijaz, Muhammad Usama, Waleed Iqbal, Junaid Qadir, Yehia Elkhatib, Ala Al-Fuqaha
2020 Frontiers in Big Data  
Our evaluation reveals that there is an increasing interest from the research community on the perspective of attacking and defending different attacks on Machine Learning as a Service platforms.  ...  With the advances in machine learning (ML) and deep learning (DL) techniques, and the potency of cloud computing in offering services efficiently and cost-effectively, Machine Learning as a Service (MLaaS  ...  oblivious NN Cloud-hosted DL models, neural network for cloud-based prediction services MNIST and CIFAR-10 Response latency and message sizes (Rouhani et al., 2018) Adversarial attacks ReDCrypt  ... 
doi:10.3389/fdata.2020.587139 pmid:33693420 pmcid:PMC7931962 fatcat:b36smykjcncqdadml6mufsi3ry

Fast Outage Analysis of Large-scale Production Clouds with Service Correlation Mining [article]

Yaohui Wang, Guozheng Li, Zijian Wang, Yu Kang, Yangfan Zhou, Hongyu Zhang, Feng Gao, Jeffrey Sun, Li Yang, Pochian Lee, Zhangwei Xu, Pu Zhao (+4 others)
2021 arXiv   pre-print
Cloud-based services are surging into popularity in recent years.  ...  ., severe incidents that always impact multiple services, can dramatically affect user experience and incur severe economic losses.  ...  ACKNOWLEDGEMENT We thank our colleagues in Microsoft Azure who developed the incident management system, for their kind help and support in this work.  ... 
arXiv:2103.03649v1 fatcat:tga2x2drajf4bjteuq67gs3owe

Taxonomy and Proposed Architecture of Intrusion Detection and Prevention Systems for Cloud Computing [chapter]

Ahmed Patel, Mona Taghavi, Kaveh Bakhtiyari, Joaquim Celestino Júnior
2012 Lecture Notes in Computer Science  
services.  ...  The distributed and open structure of cloud computing and services becomes an attractive target for potential cyber-attacks by intruders.  ...  Artificial Neural Network (ANN) is used as a feature extraction selector and classifier of machine learning for IDE.  ... 
doi:10.1007/978-3-642-35362-8_33 fatcat:tmq6ndhbojblfdym6g6lsln5ta

Necessity of data science for enhanced Cybersecurity

Shiv Hari Tewari
2021 International Journal of Data Science and Big Data Analytics  
Extracting security incident patterns or insights from cybersecurity data and building corresponding data-driven model, is the key to make a security system automated and intelligent.  ...  In this paper, I have briefly described the data science its evolution its applications in cloud security and how cybersecurity data science came in existence what kind of advantages are given by Cybersecurity  ...  content on a cloud service.  ... 
doi:10.51483/ijdsbda.1.1.2021.63-79 fatcat:ycciwntsd5aodjp4tjzmhn4odu

Enabling Cognitive Smart Cities Using Big Data and Machine Learning: Approaches and Challenges

Mehdi Mohammadi, Ala Al-Fuqaha
2018 IEEE Communications Magazine  
Unfortunately, most of the generated data is wasted without extracting potentially useful information and knowledge because of the lack of established mechanisms and standards that benefit from the availability  ...  The proposed framework is scalable to meet the needs of smart city services.  ...  Data analytic methods and machine learning algorithms should be able to extract knowledge and useful information from data to reduce the amount of digital waste.  ... 
doi:10.1109/mcom.2018.1700298 fatcat:b2tijduyjfcrrgabnkitkccboy

Proactive Maintenance Strategy Based on Resilience Empowerment for Complex Buildings [chapter]

Francesco Rota, Maria Cinzia Luisa Talamo, Giancarlo Paganin
2020 Smart Innovation, Systems and Technologies  
Current IoT and machine learnings tools, which exploit data extracted directly from the systems, can help to build a proactive strategy, which pursues anticipation (knowledge, decision, actions), that  ...  Bhat et al. (2017) DbaaS Cloud storage and database Cloud and IoT-based emerging services systems.  ... 
doi:10.1007/978-3-030-52869-0_21 fatcat:4dgcbwsennbgxekozpdjzs4d3q

Crime Mapping Model based on Cloud and Spatial Data: A Case Study of Zambia Police Service

Jonathan Phiri, Jackson Phiri, Charles S.
2020 International Journal of Advanced Computer Science and Applications  
Crime mapping is a strategy used to detect and prevent crime in the police service.  ...  A baseline study was conducted to identify the challenges in the current crime mapping system used by the Zambia Police Service.  ...  ACKNOWLEDGMENT We would like to thank the Zambia Police Service for the support and also for providing us with all relevant information towards this project.  ... 
doi:10.14569/ijacsa.2020.0110132 fatcat:ey7jd6rrlzfnbc6vgn5lgcom4e

Predicting Breakdowns in Cloud Services (with SPIKE) [article]

Jianfeng Chen, Joymallya Chakraborty, Philip Clark, Kevin Haverlock, Snehit Cherian, Tim Menzies
2019 arXiv   pre-print
Also, SPIKE performed relatively better than other widely-used learning methods (neural nets, random forests, logistic regression).  ...  Maintaining web-services is a mission-critical task. Any downtime of web-based services means loss of revenue.  ...  ACKNOWLEDGEMENTS This work was partially funded by (a) a gift from LexisNexis managed by Phillpe Poignant; and (b) an NSF CCF grant #1703487.  ... 
arXiv:1905.06390v1 fatcat:7zjhwdde4zfy7ddzar5nmlf3za

Deep-Net: Deep Neural Network for Cyber Security Use Cases [article]

Vinayakumar R and Barathi Ganesh HB and Prabaharan Poornachandran and Anand Kumar M and Soman KP
2018 arXiv   pre-print
This is due to the fact that DNNs implicitly extract and build better features, identifies the characteristics of the data that lead to better accuracy.  ...  Deep neural networks (DNNs) have witnessed as a powerful approach in this year by solving long-standing Artificial intelligence (AI) supervised and unsupervised tasks exists in natural language processing  ...  Each sample is labeled based on the knowledge related to the incident status of the log samples.  ... 
arXiv:1812.03519v1 fatcat:ujvoi2xxdrdmpfbdprfnkkzqzq

Block Chain and Big Data-Enabled Intelligent Vehicular Communication

Shahid Mumtaz, Anwer Al-Dulaimi, Haris Gacanin, Ai Bo
2021 IEEE transactions on intelligent transportation systems (Print)  
In other applications, using big data to identify driver's driving habits and develop usage-based insurance as well as personalized recommend vehicle maintenance services.  ...  Thus, the congestions, incidents, and environmental pollution which are caused by the increasing number of road vehicles and traffics have resulted in hundreds of millions of losses and become a major  ...  Channel characteristics extracted from channel measurements 1558-0016 © 2021 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission.  ... 
doi:10.1109/tits.2021.3090720 fatcat:nblknyxbzjfslna3h7zrrtozky

A Dynamic Malware Detection in Cloud Platform

Nani Lee Yer Fui, Aziah Asmawi, Masnida Hussin
2020 International journal of difference equations  
Cloud computing not only provides high availability on elastic resources, scalable, and cost-efficient.  ...  The platform is also widely used in information technology (IT) to support technology infrastructure and services.  ...  The moving toward Cloud computing resources as a service that is provided remotely to the users, makes computer hackers actively tried to steal online data without needed to rent for the services.  ... 
doi:10.37622/ijde/15.2.2020.243-258 fatcat:3suhiwp36zh6bdi5idrm3vvzaa
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