scholarly journals Non-Volatile Kernel Root kit Detection and Prevention in Cloud Computing

2019 ◽  
Vol 8 (5S3) ◽  
pp. 139-144
Keyword(s):  
Cloud Computing ◽  
Everyday Life ◽  
General Framework ◽  
Significant Issue ◽  
Basic Part ◽  
Proposed Model ◽  
Rootkit Detection ◽  
The Web

The field of web has turned into a basic part in everyday life. Security in the web has dependably been a significant issue. Malware is utilized to rupture into the objective framework. There are various kinds of malwares, for example, infection, worms, rootkits, trojan pony, ransomware, etc. Each malware has its own way to deal with influence the objective framework in various ways, in this manner making hurt the framework. The rootkit may be in some arbitrary records, which when opened can change or erase the substance or information in the objective framework. Likewise, by opening the rootkit contaminated record may debase the framework execution. Hence, in this paper, a Kernel Rootkit Detection and Prevention (KRDP) framework is proposed an avert the records. The avoidance system in this paper utilizes a calculation to forestall the opening of the rootkit influenced record as portrayed. By and large, the framework comprises of a free antivirus programming which is restricted to certain functionalities. The proposed model beats the functionalities by utilizing a calculation, in this way identifying the rootkits first and afterward cautioning the client to react to the rootkit tainted record. In this way, keeping the client from opening the rootkit contaminated record. Inevitably, in the wake of expelling the tainted document from the framework will give an improvement in the general framework execution

A Study for VM Placement Schemes in Cloud

2017 ◽  
Vol 7 (8) ◽  
pp. 208
Author(s):  
Ramandeep Kaur ◽  
Navpreet Kaur
Keyword(s):  
Cloud Computing ◽  
Reaction Time ◽  
Task Scheduling ◽  
Specific Time ◽  
Due Date ◽  
Vm Placement ◽  
Time Task ◽  
Wide Range ◽  
The Web

The cloud computing can be essentially expressed as aconveyance of computing condition where distinctive assets are conveyed as a support of the client or different occupants over the web. The task scheduling basically concentrates on improving the productive use of assets and henceforth decrease in task fruition time. Task scheduling is utilized to allot certain tasks to specific assets at a specific time occurrence. A wide range of systems has been exhibited to take care of the issues of scheduling of various tasks. Task scheduling enhances the productive use of asset and yields less reaction time with the goal that the execution of submitted tasks happens inside a conceivable least time. This paper talks about the investigation of need, length and due date based task scheduling calculations utilized as a part of cloud computing.

A Circular Business Model for Cloud Computing Services Providers

10.31355/33 ◽  
2018 ◽  
Vol 2 ◽  
pp. 105-120
Author(s):  
Hamed Motaghi ◽  
Saeed Nosratabadi ◽  
Thabit Qasem Atobishi
Keyword(s):  
Cloud Computing ◽  
Business Model ◽  
Circular Economy ◽  
Service Providers ◽  
Sustainable Consumption ◽  
Future Research ◽  
Extensive Literature ◽  
Computing Services ◽  
Proposed Model ◽  
Cloud Computing Service

NOTE: THIS ARTICLE WAS PUBLISHED WITH THE INFORMING SCIENCE INSTITUTE. Aim/Purpose................................................................................................................................................................................................. The main objective of the current study is to develop a business model for service providers of cloud computing which is designed based on circular economy principles and can ensure the sustainable consumption. Background Even though the demand for cloud computing technology is increasing day by day in all over the world, the current the linear economy principles are incapable to ensure society development needs. To consider the benefit of the society and the vendors at the same time, the principles of circular economy can address this issue. Methodology................................................................................................................................................................................................. An extensive literature review on consumption, sustainable consumption, circular economic, business model, and cloud computing were conducted. the proposed model of Osterwalder, Pigneur and Tucci (2005) is admitted designing the circular business model. Contribution................................................................................................................................................................................................. The proposed model of the study is the contribution of this study where provides the guidelines for the cloud computing service providers to achieve both their economic profits and the society’ needs. Findings Finding reveals that if the cloud computing service providers design their business model based on the “access” principle of circular economy, they can meet their economic profits and the society’ needs at a same time. Recommendations for Practitioners.............................................................................................................................................................. It is recommended to the startup and the existing businesses to utilize the proposed model of this study to reach a sustainable development. Recommendation for Researchers................................................................................................................................................................ It proposes a new circular business model and its linkages with community building. Impact on Society............................................................................................................................................................................................ The proposed model of the study provides guidelines to the cloud computing service providers to design a business model which is able not only to meet their economic profit, but also to meet the society’s and customers’ benefits. Future Research............................................................................................................................................................................................... Future researches can build on this research model which proposed in this study to examine the limitations of this model by using empirical researches.

Supervised Classifier Approach for Intrusion Detection on KDD with Optimal MapReduce Framework Model in Cloud Computing

2019 ◽  
Vol 12 ◽  
Author(s):  
M. Ilayaraja ◽  
S. Hemalatha ◽  
P. Manickam ◽  
K. Sathesh Kumar ◽  
K. Shankar
Keyword(s):  
Machine Learning ◽  
Cloud Computing ◽  
Intrusion Detection ◽  
Decision Tree ◽  
Learning Strategies ◽  
Nearest Neighbor ◽  
Detection System ◽  
K Nearest Neighbor ◽  
Mapreduce Model ◽  
The Web

Cloud computing is characterized as the arrangement of assets or administrations accessible through the web to the clients on their request by cloud providers. It communicates everything as administrations over the web in view of the client request, for example operating system, organize equipment, storage, assets, and software. Nowadays, Intrusion Detection System (IDS) plays a powerful system, which deals with the influence of experts to get actions when the system is hacked under some intrusions. Most intrusion detection frameworks are created in light of machine learning strategies. Since the datasets, this utilized as a part of intrusion detection is Knowledge Discovery in Database (KDD). In this paper detect or classify the intruded data utilizing Machine Learning (ML) with the MapReduce model. The primary face considers Hadoop MapReduce model to reduce the extent of database ideal weight decided for reducer model and second stage utilizing Decision Tree (DT) classifier to detect the data. This DT classifier comprises utilizing an appropriate classifier to decide the class labels for the non-homogeneous leaf nodes. The decision tree fragment gives a coarse section profile while the leaf level classifier can give data about the qualities that influence the label inside a portion. From the proposed result accuracy for detection is 96.21% contrasted with existing classifiers, for example, Neural Network (NN), Naive Bayes (NB) and K Nearest Neighbor (KNN).

Providing a Smart Industrial Environment with the Web of Things and Cloud Computing

2016 ◽  
Author(s):  
Marlon C. Domenech ◽  
Leonardo P. Rauta ◽  
Marcelo Dornbusch Lopes ◽  
Paulo H. Da Silva ◽  
Rodrigo C. Da Silva ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Industrial Environment ◽  
Web Of Things ◽  
The Web

Placebos and Movies: What Do They Have in Common?

2021 ◽  
pp. 096372142110038
Author(s):  
Fabrizio Benedetti
Keyword(s):  
Everyday Life ◽  
Common Sense ◽  
Placebo Effect ◽  
Psychological Factors ◽  
General Framework ◽  
Physiological Responses ◽  
Therapeutic Effects ◽  
Physiological Effects ◽  
Placebo Effects ◽  
What Matters

Placebos are fake therapies that can induce real therapeutic effects, called placebo effects. It goes without saying that what matters for inducing a placebo effect is not so much the fake treatment itself, but rather the therapeutic ritual that is carried out, which is capable of triggering psychobiological mechanisms in the patient’s brain. Both laypersons and scientists often accept the phenomenon of the placebo effect with reluctance, as fiction-induced clinical improvements are at odds with common sense. However, it should be emphasized that placebo effects are not surprising after all if one considers that fiction-induced physiological effects occur in everyday life. Movies provide one of the best examples of how fictitious reality can induce psychological and physiological responses, such as fear, love, and tears. In the same way that a horror movie induces fear-related physiological responses, even though the viewer knows everything is fake, so the sight of a syringe may trigger the release of pain-relieving chemicals in the patient’s brain, even if the patient knows there is a fake painkiller inside. From this perspective, placebos can be better conceptualized as rituals, actions, and fictions within a more general framework that emphasizes the power of psychological factors in everyday life, including the healing context.

scholarly journals Cloud-based intelligent self-diagnosis and department recommendation service using Chinese medical BERT

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Junshu Wang ◽  
Guoming Zhang ◽  
Wei Wang ◽  
Ka Zhang ◽  
Yehua Sheng
Keyword(s):  
Cloud Computing ◽  
Large Scale ◽  
Medical Service ◽  
Rapid Development ◽  
Medical Knowledge ◽  
Language Models ◽  
Computing Environment ◽  
Computing Power ◽  
Cloud Computing Environment ◽  
Proposed Model

AbstractWith the rapid development of hospital informatization and Internet medical service in recent years, most hospitals have launched online hospital appointment registration systems to remove patient queues and improve the efficiency of medical services. However, most of the patients lack professional medical knowledge and have no idea of how to choose department when registering. To instruct the patients to seek medical care and register effectively, we proposed CIDRS, an intelligent self-diagnosis and department recommendation framework based on Chinese medical Bidirectional Encoder Representations from Transformers (BERT) in the cloud computing environment. We also established a Chinese BERT model (CHMBERT) trained on a large-scale Chinese medical text corpus. This model was used to optimize self-diagnosis and department recommendation tasks. To solve the limited computing power of terminals, we deployed the proposed framework in a cloud computing environment based on container and micro-service technologies. Real-world medical datasets from hospitals were used in the experiments, and results showed that the proposed model was superior to the traditional deep learning models and other pre-trained language models in terms of performance.

Proposed Back Propagation Deep Neural Network for Intrusion Detection in Internet of Things Fog Computing

2021 ◽  
Vol 9 (4) ◽  
pp. 464-469
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Intrusion Detection ◽  
Fog Computing ◽  
Denial Of Service ◽  
Back Propagation ◽  
Security And Privacy ◽  
Brute Force ◽  
Iot Platform ◽  
Proposed Model

Internet of things (IoT) is an emerging concept which aims to connect billions of devices with each other anytime regardless of their location. Sadly, these IoT devices do not have enough computing resources to process huge amount of data. Therefore, Cloud computing is relied on to provide these resources. However, cloud computing based architecture fails in applications that demand very low and predictable latency, therefore the need for fog computing which is a new paradigm that is regarded as an extension of cloud computing to provide services between end users and the cloud user. Unfortunately, Fog-IoT is confronted with various security and privacy risks and prone to several cyberattacks which is a serious challenge. The purpose of this work is to present security and privacy threats towards Fog-IoT platform and discuss the security and privacy requirements in fog computing. We then proceed to propose an Intrusion Detection System (IDS) model using Standard Deep Neural Network's Back Propagation algorithm (BPDNN) to mitigate intrusions that attack Fog-IoT platform. The experimental Dataset for the proposed model is obtained from the Canadian Institute for Cybersecurity 2017 Dataset. Each instance of the attack in the dataset is separated into separate files, which are DoS (Denial of Service), DDoS (Distributed Denial of Service), Web Attack, Brute Force FTP, Brute Force SSH, Heartbleed, Infiltration and Botnet (Bot Network) Attack. The proposed model is trained using a 3-layer BP-DNN

scholarly journals Cloud Computing Technique Applied to Detect Cyber-Attacks on Web Application

2020 ◽  
Vol 9 (4) ◽  
pp. 1498-1500
Keyword(s):  
Cloud Computing ◽  
Web Application ◽  
Current System ◽  
Cyber Attacks ◽  
Individual Data ◽  
Computing Technique ◽  
Correct Number ◽  
Proposed Model

The targeted malignant emails (TME) for PC arrange misuse have become progressively deceptive and all the more generally common as of late. Aside from spam or phishing which is intended to fool clients into uncovering individual data, TME can misuse PC systems and accumulate touchy data which can be a major issue for the association. They can comprise of facilitated and industrious battles that can be terrible. Another email-separating procedure which depends on bowl classifier and beneficiary arranged highlights with an arbitrary backwoods classifier which performs superior to two conventional recognition techniques, Spam Assassin and Clam AV, while keeping up sensible bogus positive rates. This proposed model deals with how to recognize a pernicious bundle (email) for ordinary system into current system. We build up an undermined protocol of network detection that powerfully concludes the correct number of congestive loss of packets that is going to happen. On the chance that one damages the steering convention itself, at that point aggressor may make enormous segments of the system become untreatable. We build up an option shifting technique by utilizing TME explicit element extraction. Our conventions naturally anticipate clog in a deliberate manner, as it is vital in making any such flaw in network recognition reasonable.

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