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Analysis of Machine Learning Algorithms to Protect from Phishing in Web Data Mining

N. Swapna
2017 International Journal of Computer Applications  
We designed prototype of website phishing detection solution to address the requirements for both effective and efficient phishing detection machine learning big data allows us to dig into a tremendous  ...  The term Big data is a large data sets those outgrow the simple kind of database and data handling design.  ...  Due to scientific, ethical, and legal barriers to publicly disseminating security data, the data sets used for validating cyber security research are often mentioned in a single publication and then  ... 
doi:10.5120/ijca2017912743 fatcat:nt4vh7gdazdqxa4r7u5ddqafa4

Comparison of Software Defined Networking with Traditional Networking

Saad H. Haji, Subhi R. M. Zeebaree, Rezgar Hasan Saeed, Siddeeq Y. Ameen, Hanan M. Shukur, Naaman Omar, Mohammed A. M. Sadeeq, Zainab Salih Ageed, Ibrahim Mahmood Ibrahim, Hajar Maseeh Yasin
2021 Asian Journal of Research in Computer Science  
In this paper, the SDN is reviewed; it introduces SDN, explaining its core concepts, how it varies from traditional networking, and its architecture principles.  ...  Furthermore, we presented the crucial advantages and challenges of SDN, focusing on scalability, security, flexibility, and performance. Finally, a brief conclusion of SDN is revised.  ...  With big data, a promising approach for networking will be big data and SDN joint architecture. Survey Discussion and Analysis Traditional networks are complicated and difficult to control.  ... 
doi:10.9734/ajrcos/2021/v9i230216 fatcat:pgbcvv7z65hkbppake3g2hstfi

An Efficient Analysis Technique to Detect Suspicious Web Pages in Real-Time

Mr. Bhaskara L, Mrs. Ankitha K
2018 International Journal of Engineering Research and Advanced Technology  
Phishing is a type of web risk, phisher make the copy of unique site and wrongfully endeavor to get Victim's own data like client name, secret key, Mastercard points of interest, SSN number and utilize  ...  it for possess advantage.  ...  Some of the prominent application of web is Hybrid cloud, Big Data, E-shopping.  ... 
doi:10.31695/ijerat.2018.3285 fatcat:evp4r7mnzbdwtjjxbtp2rsizdi

A Systemic Security and Privacy Review: Attacks and Prevention Mechanisms over IOT Layers

Muhammad Shoaib Akhtar, Tao Feng
2022 EAI Endorsed Transactions on Security and Safety  
Therefore, security and privacy has emerged as a big challenge for the IoT.  ...  Moreover, this paper will provide some possible solution mechanisms for such attacks. The aim is to produce a radical survey associated with the privacy and security challenges of the IoT.  ...  Phishing Attack It is very parlous attack for application layer. E-mail and other communication applications are hit list in this manner.  ... 
doi:10.4108/eetss.v8i30.590 fatcat:o3wysf4ha5f4rawekaxl4hu3he

A short review on Applications of Deep learning for Cyber security [article]

Mohammed Harun Babu R, Vinayakumar R, Soman KP
2019 arXiv   pre-print
This paper outlines the survey of all the works related to deep learning based solutions for various cyber security use cases.  ...  This has been applied towards various use cases in cyber security such as intrusion detection, malware classification, android malware detection, spam and phishing detection and binary analysis.  ...  The collected data is processed for both static and dynamic analysis for feature extraction and it is characterized by DBN based approach.  ... 
arXiv:1812.06292v2 fatcat:o7pcaf7xyncrpdn64byjxh47im

ScaleNet: Scalable and Hybrid Frameworkfor Cyber Threat Situational AwarenessBased on DNS, URL,and Email Data Analysis

R. Vinayakumar, K. P. Soman, Prabaharan Poornachandran, Vysakh S. Mohan, Amara Dinesh Kumar
2018 Journal of Cyber Security and Mobility  
Deep learning is a machine learning technique largely used by researchers in recent days. It avoids feature engineering which served as a critical step for conventional machine learning algorithms.  ...  Still, additional domain level features can be defined for deep learning methods in NLP tasks to enhance the performance. The cyber security events considered in this study are surrounded by texts.  ...  Acknowledgments This research was supported in part by Paramount Computer Systems and Lakhshya Cyber Security Labs. We are grateful to NVIDIA India, for the GPU hardware support to research grant.  ... 
doi:10.13052/jcsm2245-1439.823 fatcat:dpsz7dfa2bhufg2fljdafxt2zi

Big Data Analytics Architecture for Cybersecurity Applications

Roberto Omar Andrade, Luis Tello-Oquendo, Susana Cadena-Vela, Patricia Jimbo-Santana, Juan Zaldumbide, Diana Yacchirema
2021 Zenodo  
Concretely, we present a massive data processing methodology and introduce a big data architecture devised for cybersecurity applications.  ...  In this paper, we examine the application of big data to support some security activities and conceptual models to generate knowledge that can be used for the decision making or automation of security  ...  Concretely, we present a massive data processing methodology and introduce a big data architecture devised for cybersecurity applications.  ... 
doi:10.5281/zenodo.5747660 fatcat:bx6tzbm6wvabtbrybmdqyt3aoq

Assessing Risks and Cloud Readiness in PaaS Environments

2019 International journal of recent technology and engineering  
This research has implemented the risk assessment and cloud readiness for PaaS environment by scanning its code with a software vendor.  ...  The complex architecture, multitenant and virtual environment in cloud infrastructure asks for risks identification and mitigation.  ...  not participate in audits then it is considered a big risk as the service provider is responsible for security and integrity of data. • Shared Resource Environment: As cloud nature is to share all computing  ... 
doi:10.35940/ijrte.c1057.1083s19 fatcat:b4mcnwvptjgklhbl4zqw4szrzu

Enabling trustworthy spaces via orchestrated analytical security

Joshua Howes, James Solderitsch, Ignatius Chen, Jonté Craighead
2013 Proceedings of the Eighth Annual Cyber Security and Information Intelligence Research Workshop on - CSIIRW '13  
To help them do so, we introduce a conceptual blueprint for the analytics solution.  ...  We propose security operations teams extend their existing security infrastructure with emerging Big Data analytics and Complex Event Processing platforms.  ...  ACKNOWLEDGEMENTS Some of the work discussed in this paper was done by co-authors Ignatius Chen and Jonté Craighead while they were interns with the Accenture Product and Offering Development Security team  ... 
doi:10.1145/2459976.2459991 dblp:conf/csiirw/HowesSCC13 fatcat:7hl3mtawpng7lidpmb7jutxmi4

A Review on Cloud Computing Security and Privacy in Service Oriented Architecture (SOA)

Surbhi Sharma
2017 International Journal of Machine Learning and Networked Collaborative Engineering  
In this paper we review some securities issues and give a survey solution that have been done to minimize the security risk and describe future research work about all these risk that occur when data is  ...  Many organizations like Google, Microsoft, and Amazon accelerate in developing this computing and provide the services for lots of users and storing the data through cloud now become a norm.  ...  IaaS is providing the infrastructure for enterprises and it totally changed the way developer deploy the application, instead of spending big investment with their own data centre or manage hosting companies  ... 
doi:10.30991/ijmlnce.2017v01i02.004 fatcat:77lltw5rnbgtdh5lbgucqtxgwa

Cyber Threats to Industrial IoT: A Survey on Attacks and Countermeasures

Konstantinos Tsiknas, Dimitrios Taketzis, Konstantinos Demertzis, Charalabos Skianis
2021 IoT  
In this framework, given that the protection of industrial equipment is a requirement inextricably linked to technological developments and the use of the IoT, it is important to identify the major vulnerabilities  ...  as to how to secure these systems.  ...  is proposed in the work blockchain security architecture for IIoT [94] , which is based on deep learning smart contracts for the security and functionality of industrial applications, providing a decentralized  ... 
doi:10.3390/iot2010009 fatcat:qf2won2u5zes3gag264k3l7pjq

Advanced Network Security Analysis (ANSA) in Big Data Technology

In the big data environment, securing a large amount of data has become a challenging issue in both security and research industry.  ...  Using this framework provides users' a benefit of being able to investigate Big Data and helps them to detect attacks.  ...  A system architecture and framework is proposed for the stimulation of security systems in the Big Data and internet-based security.  ... 
doi:10.35940/ijitee.j9369.0881019 fatcat:4wd3d4ok4jfnljlhoz4bdhv3gu

A novel approach to big data analysis using deep belief network for the detection of android malware

Uma Narayanan, Varghese Paul, Shelbi Joseph
2019 Indonesian Journal of Electrical Engineering and Computer Science  
What's more, besides distinguishing sensitive customer data sources is fundamental for security protection in portable applications.  ...  So we propose a Novel way to deal with overseeing tremendous information examination utilizing Deep learning for the affirmation of Android malware.  ...  I am extremely thankful for providing such friendly support and guidance, although he had a busy schedule.  ... 
doi:10.11591/ijeecs.v16.i3.pp1447-1454 fatcat:ggg5lg7inbappe45cdl4fzft44

Artificial Immune System Based Classification Approach for Detecting Phishing Mails

Dr.A.Vijaya kathir avan, B.Vasumathi
2015 International Journal of Innovative Research in Computer and Communication Engineering  
Phishing/Spam is an attack that deals with social engineering methodology to illegally acquire and use someone else's data on behalf of legitimate website for own benefits.  ...  It has been investigated that the statistical filtering of phishing emails, where a classifier is trained on characteristic features of existing emails and subsequently is able to identify new phishing  ...  The Data Mining RIPPER algorithm is used to characterize the Phishing emails and classify them based on both content-based and non-content based characteristics of Phishing emails.  ... 
doi:10.15680/ijircce.2015.0305044 fatcat:u3t3vuddjfcytgjwlyvrn3da7q

PhishStorm: Detecting Phishing With Streaming Analytics

Samuel Marchal, Jerome Francois, Radu State, Thomas Engel
2014 IEEE Transactions on Network and Service Management  
For this purpose, we define the new concept of intra-URL relatedness and evaluate it using features extracted from words that compose a URL based on query data from Google and Yahoo search engines.  ...  We discuss in the paper efficient implementation patterns that allow real time analytics using Big Data architectures like STORM and advanced data structures based on Bloom filter.  ...  We leverage search engine query data in order to extract 12 features from a URL characterizing its intra relatedness and its popularity.  ... 
doi:10.1109/tnsm.2014.2377295 fatcat:wer2f6njkzbbpgef64ricbcmiy
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