Reducing Software Testing Time with Combinatorial Testing and Test Automation

The development of large software systems is a complex and error prone process. Errors may occur at any stage of software development. These errors, sometimes referred to as bugs, can cause great losses in terms of both time and money if not identified and removed as early as possible. Testing a software product is costly, since it takes much time and need to test many combinations of its functions, integrity, performance etc., which can be called as test cases. The company\u27s goal is to reduce the testing time, so that they can save money and deliver the product much faster to the customer. Testing time can be reduced in two main ways, first by reducing number of test cases and second by automating repeatedly testing areas. This paper will discuss fundamentals of testing such as importance and difference of verification and validation, testing throughout the software development life cycle and testing methods, levels and types. Then it will discuss the possibility of reducing the time spent on testing by reducing number of test cases with combinatorial testing and automating repeatedly tested areas with test automation using Selenium tool. Finally it will also shed some light on a real world test automation project with selenium and two integrated develop environments

A Novel Method for Moving Laterally and Discovering Malicious Lateral Movements in Windows Operating Systems: A Case Study

Lateral movement is a pervasive threat because modern networked systems that provide access to multiple users are far more efficient than their non-networked counterparts. It is a well-known attack methodology with extensive research conducted investigating the prevention of lateral movement in enterprise systems. However, attackers use increasingly sophisticated methods to move laterally that bypass typical detection systems. This research comprehensively reviews the problems in lateral movement detection and outlines common defenses to protect modern systems from lateral movement attacks. A literature review outlines techniques for automatic detection of malicious lateral movement, explaining common attack methods utilized by advanced persistent threats and components built into the Windows operating system that can assist with discovering malicious lateral movement. Finally, a novel approach for moving laterally designed by other security researchers is reviewed and studied, an original process for detecting this method of lateral movement is proposed, and the application of the detection methodology is also expanded

Robust Efficiency Evaluation of NextCloud and GoogleCloud

Cloud storage services such as GoogleCloud and NextCloud have become increasingly popular among Internet users and businesses. Despite the many encrypted file cloud systems being implemented worldwide today for different purposes, we are still faced with the problem of their usage, security, and performance. Although some cloud storage solutions are very efficient in communication across different clients, others are better in file encryption, such as images, videos, and text files. Therefore, it is evident that the efficiency of these algorithms varies based on the purpose and type of encryption and compression. This paper focuses on the comparative analysis of NextCloud with composed end-to-end solutions that use both an unencrypted cloud storage and an encrypted solution. In this paper, we measured the network use, file output size, and computation time of given workloads for two different services to thoroughly evaluate the efficiency of NextCloud and GoogleCloud. Our findings concluded that there is similar network usage and synchronization time. However, GoogleCloud had more CPU utilization than NextCloud. On the other hand, NextCloud had a longer delay when uploading files to their cloud service. Our experimental results show that the evaluation model is considered robust if its output and forecasts are consistently accurate, even if one or more of the input variables or assumptions are drastically changed due to unforeseen circumstances

Analyzing Data Encryption Efficiencies for Secure Cloud Storages: A Case Study of Pcloud vs OneDrive vs Dropbox

Now more than ever has it become important to keep the information confidential in an age that is losing its value of individual privacy. In this cloud computing era, regardless of the power of the cloud computing concept, many people do not know that their information can be used and sent to third parties from their cloud storage provider. Today the use of cloud storage is well established however the security of protecting the data on the cloud is a limited thought for most users. Therefore, this study aims to experimentally research which encryption program works best when storing data onto three of the main cloud storage providers currently available on the market. This study will go over the hardware and network impact as well as the time to encrypt and decrypt the data. This study will determine if “7zip” or “rclone” encryption programs work best with these three cloud storage. The data will be collected using NetData tool and accordingly determine which encryption application works best with which cloud storage provider. Thereafter, based on the data analysis, it is recommended that experimental outcomes to all users to keep their sensitive data secured and safe from snooping or prevent private information from being collected and sold to third parties with the help of black market