With the development of the Internet, network security has aroused people’s attention. It can be said that a secure network environment is a basis for the rapid and sound development of the Internet. Phishing is an essential class of cybercriminals which is a malicious act of tricking users into clicking on phishing links, stealing user information, and ultimately using user data to fake logging in with related accounts to steal funds. Network security is an iterative issue of attack and defense. The methods of phishing and the technology of phishing detection are constantly being updated. Traditional methods for identifying phishing links rely on blacklists and whitelists, but this cannot identify new phishing links. Therefore, we need to solve how to predict whether a newly emerging link is a phishing website and improve the accuracy of the prediction. With the maturity of machine learning technology, prediction has become a vital ability. This paper offers a state-of-the-art survey on methods for phishing website detection. It starts with the life cycle of phishing, introduces common anti-phishing methods, mainly focuses on the method of identifying phishing links, and has an in-depth understanding of machine learning-based solutions, including data collection, feature extraction, modeling, and evaluation performance. This paper provides a detailed comparison of various solutions for phishing website detection.

A Survey of Machine Learning-Based Solutions for Phishing Website Detection

This study intends to find the industries that have leveraged Robotic Process Automation (RPA) technology and elucidate the extent of the adoption of RPA in various industry domains with benefits. The identification of tasks eligible for RPA itself is a challenge. Therefore, the study further brings out the challenges faced in various industry verticals and postulates the future direction of research and applications in RPA.,The study focuses on articles from popular databases such as SCOPUS, Web of Science and Google scholar. PRISMA methodology is used for systematic literature review and 113 papers are shortlisted for study. Three questions are framed to carry out the review and set the research direction.,It is evident from this study that RPA has been widely used in banking and related areas with moderate use in healthcare and manufacturing leading to operational efficiency and productivity. However, there are a lot more opportunities in other domains that need to be taped by leveraging technology advancements and a research agenda has been devised by postulating future directions.,The study brings out a new comprehensive perspective as regards RPA implementation across domains. There is no promising study found that gathers three-dimensional aspects of the meta-themes applications, benefits and challenges. The study summarizes the research agenda and projects the industry domains that have not yet explored, the benefits of RPA. This will be a good reference article for those who develop RPA techniques and organizations that have plans to go for RPA.

Robotic process automation for industry: adoption status, benefits, challenges and research agenda

SI-BBA – A novel phishing website detection based on Swarm intelligence with deep learning

Cross channel scripting (XCS) is a common web application vulnerability, which is a variant of a cross-site scripting (XSS) attack. An XCS attack vector can be injected through network protocol and smart devices that have web interfaces such as routers, photo frames, and cameras. In this attack scenario, the network devices allow the web administrator to carry out various functions related to accessing the web content from the server. After the injection of malicious code into web interfaces, XCS attack vectors can be exploited in the client browser. In addition, scripted content can be injected into the networked devices through various protocols, such as network file system, file transfer protocol (FTP), and simple mail transfer protocol. In this paper, various computational techniques deployed at the client and server sides for XCS detection and mitigation are analyzed. Various web application scanners have been discussed along with specific features. Various computational tools and approaches with their respective characteristics are also discussed. Finally, shortcomings and future directions related to the existing computational techniques for XCS are presented.

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Cross Channel Scripting and Code Injection Attacks on Web and Cloud-Based Applications: A Comprehensive Review

Hyperparameter tuning of convolutional neural networks for building construction image classification

Phishing is the process of portraying malignant web pages in the place of genuine web pages to obtain important and delicate information from the end-user. Nowadays phishing is considered as one of the most serious threats to web security. Most of the existing techniques for phishing detection use Bayesian classification for differentiating malignant web pages from genuine web pages. These methods work well if a dataset contains less no of web pages and they provide accuracy up to 90 percent. In recent years the size of the web is increasing tremendously and the existing methods have not provideda good enough accuracy for large datasets. So this paper proffers an innovative approach to identify phishing websites using hyperlinks available in the source code of the HTML page in the corresponding website. The proposed method uses a feature vector with 30 parameters to detect malignant web pages. These features are used in training the supervised Deep Neural Network model with Adam optimizer for differentiating fraudulent websites from genuine websites. The proposed deep learning model with Adam Optimizer uses a Listwise approach to classify phishing websites and genuine websites. The performance of the proposed approach is decent when compared to other traditional machine learning approaches like SVM, Adaboost, AdaRank. The results show that the proposed approach provides more accurate results in detecting phishing websites.

Smart Phishing Detection in Web Pages using Supervised Deep Learning Classification and Optimization Technique ADAM

The amount and variety of data in natural sciences increases rapidly. Data abstraction, data manipulation and pattern discovery techniques are of great need in order to deal with such large quantities. Integration between different sources of data is also of major interest, as complex relations may arise. Biology is a good example of a field that provides extensive, highly variable and multi-sources data. The scope of these investigations has now expanded greatly owing to the development of high throughout sequencing techniques and novel statistical and computational methods. These methods require easy-to-use computer programs. We have developed a new software package, molecular genetics analysis to integrate their diverse data and tools under Common Graphical User Interfaces (GUIs) by using BLAST, FASTA data searches. One of the most exciting things about being involved in computer programming and biology is that both fields are rich in new techniques and results. The illumina is sequence analyzer in Next Generation Sequence Technology.

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Role of Computers in Bioinformatics by Using Different Biological Datasets

In recent times, we have abundant sources for information out of which not every detail is significant. So the point of concern is identifying the most relevant and important information out of vast data. The focus should be given to the relevant information present in the entire data in such a way that we can understand the entire gist of the text. Considering the above concern as our problem statement, in this paper we discuss “Text Summarization”—it is the process of generating pertinent and significant text from the entire information. Text resources include websites, text documents, and direct text feed from users. Text Summarization can be performed using 2 methods—Extractive Summarization and Abstractive summarization. Here we are going to generate a summary from various types of text sources using extractive techniques. In extractive techniques, we have used a frequency driven approach where the relevance of a particular sentence is measured through sentence weightage and term frequency. We measured the accuracy of the model using a sequence matcher which provides us the relevance between generated summary and human perceived summary.

Extractive Summarization Using Frequency Driven Approach

In the 21st century everyone knows that technology has improved a lot from the past. Home Automation (HA) is a concept that has improved a lot and is an important one in daily life. HA controls the working of several home appliances like Air conditioner, home lighting, geysers, fans and all electrically controlled appliances. It also provides security and saves power being consumed by those electrical appliances. By using HA human efforts can be reduced and it also improves time utilization. Actual use of HA is to offer help for old aged and handicapped people by allowing them to monitor and to use appliances safely. The work done by the authors and presented in this paper suggests a prototype for designing of Home Automation using Global System for Mobile communication (GSM). As from the previous design, major problem faced by designers is cost of the HA. So, the proposed design in this paper uses a small scale processor viz., 8051 μc. The model is dependent on the independent embedded system development board and GSM Module. Home Appliances have to be connected to the development board & these appliances are controlled by using our phones. Choosing the device with less cost is very important.

An Efficient Robotic Process Automation Platform Designed for the Modern Enterprise Home Using GSM and CDMA

Phylogenetic trees represent headway relationship among characteristic collection, residing topics. The tree finds the likeliness or divergence of received skills. I construct phylogenetic tree for developments coming across comparison among wonderful species developments using institution exam, as an example, Hierarchical Bunching, KMEANS and SOM with PCA. As in line with author species, tendencies can be comparative at the off threat that they have got comparative examples or conduct contrast can be removed in conduct, examples. For actualizing the understanding, I applied COX dataset from NCBI website online for manufacturing the phylogenetic tree.

Chukka Santhaiah

Papers

Smart Phishing Detection in Web Pages using Supervised Deep Learning Classification and Optimization Technique ADAM

Role of Computers in Bioinformatics by Using Different Biological Datasets

Extractive Summarization Using Frequency Driven Approach

An Efficient Robotic Process Automation Platform Designed for the Modern Enterprise Home Using GSM and CDMA

Construction of Phylogenetic Tree for Cyclooxygenase Dataset by Clustering