Decrypting live SSH traffic in virtual environments

It is very essential for companies in the retail industry to exchange sensitive information like Purchase Orders, Invoices, Payments Information, Contracts and other types of information for improving efficiency, reducing costs, and for strengthening business relationships. The sensitive information also gets exchanged between different teams within an organization for better collaboration, efficiency and to extract valuable insights. This paper introduces a cost effective and secure approach which is tailored for bulk ingestion into databricks data lake using SFTP and SMB protocols. The proposed file transfer framework makes use of python packages like paramiko (which implements the Secure Shell SSHv2 protocol for secure file transfer over unsecured network) and pysmb(which implements SMB protocol for secure file sharing across different operating systems within a network) to transfer the files into the databricks volume for further processing by transformation pipelines in databricks cluster. Using this methodology various types of file transfers like synchronous small file transfer, asynchronous large file transfer and continuous file transfer can be achieved. Deletion of files on the remote server after a configured number of successful transfers is also achieved using the proposed methodology. The key findings of this implementation are as following: simplified setup procedure, less development effort and decent performance. The findings suggest that the proposed framework with data integrity and remote file management capabilities is a secure, simplified, versatile and a reliable choice for transferring sensitive files.

In today’s digital era, secure and efficient file transfer mechanisms are crucial as digital communication becomes increasingly prevalent. This paper presents a File Transfer Application that enables collaborative file sharing among multiple users over a network. The application uses a client-server architecture, integrating UDP for fast communication and TCP for secure and reliable file transfers. The server manages client registrations, maintains a dynamic table of active users, and broadcasts file availability updates, fostering real-time collaboration. Clients register with the server by sending their details and receive a list of online peers. Users can share files or request them directly from others, promoting peer-to-peer interaction. A simple command-line interface allows easy navigation, making the application accessible to users with varying technical backgrounds. File transfers utilize TCP to ensure data integrity, while UDP handles lightweight communication, minimizing latency. The system allows clients to disconnect gracefully, updating the server and other users accordingly. Tested in various environments, including simulations on a single machine, the application demonstrates its robustness in handling concurrent users effectively. This paper not only highlights key networking and socket programming concepts but also lays the groundwork for future enhancements like encryption and authentication, ensuring secure, scalable digital file sharing.

The WSN technology is a highly efficient and effective way of gathering highly sensitive information and is often deployed in mission-critical applications, which makes the security of its data transmission of vital significance. However, the previous research paper failed to distinguish the role of centralized server for it being the main controller of the entire network. The decision of nodes communicating with each other in the previous research paper was based on the information received from the adjacent node. However, the proposed research paper will take into account the centralized server to develop a new technique to prevent the black node from joining the wireless sensor network. Key distribution technique along with the implementation of improved AES algorithm double key encryption will play an important role in transferring the data between authorized nodes securely and preventing unauthorized user from accessing it.

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<span lang="EN-US">This study aims to evaluate the level of digital security literacy among parents of elementary school students in Indonesia, focusing on personal data security, prevention of digital crime, devices, digital identity security, privacy security, and interaction security. The data was collected from 219 parents of elementary school students through a reliable online survey form. The study findings reveal that parents demonstrated a high level of digital security literacy in personal data security, digital crime prevention, and device and identity security. However, their privacy and interaction security knowledge fell within the medium range. While the mean score of parents' digital security literacy did not correlate strongly with gender, female parents scored higher in privacy security than male parents. Additionally, the study observed a trend indicating that younger, more educated parents who spent more time using digital devices exhibited higher digital safety literacy. On average, parents reported using digital devices for 5.6 hours daily, and their level of digital safety literacy influenced their efforts to limit their children's screen time. These findings underscore the importance of implementing programs to enhance parental digital safety literacy, addressing gaps, and empowering parents as guardians of their children's safety in virtual environments.</span>

Spatial crime simulations contribute to our understanding of the mechanisms that drive crime and can support decision-makers in developing effective crime reduction strategies. Agent-based models that integrate geographical environments to generate crime patterns have emerged in recent years, although data-driven crime simulations are scarce. This article (1) identifies numerous important drivers of crime patterns, (2) collects relevant, openly available data sources to build a GIS-layer with static and dynamic geographical, as well as temporal features relevant to crime, (3) builds a virtual urban environment with these layers, in which individual offender agents navigate, (4) proposes a data-driven decision-making process using machine-learning for the agents to decide whether to engage in criminal activity based on their perception of the environment and, finally, (5) generates fine-grained crime patterns in a simulated urban environment. The novelty of this work lies in the various large-scale data layers, the integration of machine learning at individual agent level to process the data layers, and the high resolution of the resulting predictions. The results show that the spatial, temporal, and interaction layers are all required to predict the top street segments with the highest number of crimes. In addition, the spatial layer is the most informative, which means that spatial data contributes most to predictive performance. Thus, these findings highlight the importance of the inclusion of various open data sources and the potential of theory-informed, data-driven simulations for the purpose of crime prediction. The resulting model is applicable as a predictive tool and as a test platform to support crime reduction.

In the last decade or so, many collaborative technologies have been developed which aim to allow people in geographically distributed locations to work together as if sharing the same space. Such tools range from the simple asynchronous resources of email and file transfer, to fully-featured collaborative virtual environments allowing virtual groups of designers to interact with virtual designs in real time. Despite many reported practical experiments with such tools, it is far from clear which flavour of collaborative technology best suits collaborative design. This study takes the approach of studying one particular form of design collaboration — the small group design meeting — and briefly discusses how such interaction could be technologically supported in virtual space. In particular, we will focus on the use of shared design workspace.

The current information security threat landscape now includes advanced persistent attackers whose tactics, techniques, and procedures (TTPs) are designed to provide for a stealthy infiltration of systems, lateral movement, privilege escalation, and exfiltration of sensitive data (typically for purposes of corporate espionage). Once forensically detected, these same TTPs act as `fingerprints' (called indicators), locating where the attackers have been elsewhere with a network of host computers. A very commonly used technique to locate compromised systems is to calculate the MD5 hash values for each file within a filesystem and compare against a known `bad fingerprint' (hash value of known malware components). Our research demonstrates that of all of the indicators, the exhaustive computation of MD5 hash values across the full file contents of every file within the entire filesystem consumes the largest amount of time. Given the goal of reducing the time to determine if a system is compromised, we develop a novel approach to optimizing the creation of these indicators. Our experiments identify that computing a MD5 hash value of just the first four kilobytes (4KB) of each file provides a substantially faster method to search for specific MD5-based indicators with a very low false positive rate.

File recovery is one of the stages in computer forensic investigative process to identify an acquired file to be used as digital evident. The recovery is performed on files that have been deleted from a file system. However, in order to recover a deleted file, some considerations should be taken. A deleted file is potentially modified from its original condition because another file might either partly or entirely overriding the file content. A typical approach in recovering deleted file is to apply Boyer-Moore algorithm that has rather high time complexity in terms of string searching. Therefore, a better string matching approach for recovering deleted file is required. We propose Aho-Corasick parsing technique to read file attributes from the master file table (MFT) in order to examine the file condition. If the file was deleted, then the parser search the file content in order to reconstruct the file. Experiments were conducted using several file modifications, such as 0% (unmodified), 18.98%, 32.21% and 9.77%. From the experimental results we found that the file reconstruction process on the file system was performed successfully. The average successful rate for the file recovery from four experiments on each modification was 87.50% and for the string matching process average time on searching file names was 0.32 second.

To meet the rising demand for comprehensive bioinformatics tools in the life sciences, the German Network for Bioinformatics Infrastructure (de.NBI) was established in 2015 as a national bioinformatics consortium offering high quality bioinformatics services, comprehensive training and powerful computing capacities. The de.NBI Cloud is one of the flagship services for the de.NBI & ELIXIR Germany network with more than 4000 registered users, over 1350 projects, of which more than 620 are currently active, and over 1380 publications citing its use. Eight federated cloud centers adhere to a unified governance structure and utilize the centralized project application and management workflow available through the de.NBI Cloud Portal. Single sign-on and user management are provided via LifeScience Login and eduGAIN. PIs from German universities or research institutes may submit project applications, which are reviewed by the Cloud Access Committee and, upon approval, resources are allocated to one of the cloud centers. Regular staff training, mutual internal audits and external ISMS certification (ISO27001 or BSI C5) ensure secure operations of the data centers. The de.NBI Cloud offers various project types for your computing needs, covering different levels of expertise and experience in cloud computing: From the simple and fast start of pre-configured VMs with easy access (SimpleVM), to the use of bioinformatics tools and workflows (Galaxy), to the possibility of running your own infrastructures and services (OpenStack & Kubernetes). We offer pre-configured virtual research environments (VRE), which can be accessed easily when using our SimpleVM platform. They include integrated development environments, data science notebooks and virtual desktop environments. The VREs can be accessed in the web browser or by secure shell (ssh). VREs and images tailored for specific needs can also be used to provide uniform VMs for trainings and workshops. The cluster module makes it easy to set up a SLURM-based grid cluster for resource-intensive computations. Users can also provide recipes for custom VREs. The de.NBI Cloud provides computational resources for a diverse portfolio of projects within Europe (ELIXIR, EOSC, Horizon Europe) and Germany (NFDI projects), ranging from (web)service development and hosting, to execution of memory and CPU-intensive bioinformatics workflows, GPU resources for machine learning, resources for hackathons, workshops and trainings, as well as resources for proof-of-concept development, and secure environments for sensitive data processing. Regular trainings and workshops teach you how to use the cloud infrastructure effectively for your research. The annual Cloud User Meeting offers users the opportunity for networking and to get in touch with the administrators of the cloud locations and the cloud governance. Researchers present their work in the cloud and training courses expand the range of expertise for experienced cloud users, while also providing a comprehensive introduction for beginners. The de.NBI Cloud offers various project types for your computing needs, covering different levels of expertise and experience in cloud computing: From the simple and fast start of pre-configured VMs with easy access (SimpleVM), to the use of bioinformatics tools and workflows (Galaxy), to the possibility of running your own infrastructures and services (OpenStack & Kubernetes). Selection of training course topics: • VM basics: Linux & command line • SimpleVM & Research Environments • BioConda & BioContainers • CWL, Nextflow, Snakemake • Infrastructure as Code: Ansible, Terraform • Grid computing: BiBiGrid / SLURM

This paper presents novel service-based grid data management middleware that leverages standards defined by WSRF specifications to create and manage dynamic grid file system sessions. A unique aspect of the service is that the sessions it creates can be customized to address application data transfer needs. Application-tailored configurations enable selection of both performance-related features (block-based partial file transfers and/or whole-file transfers, cache parameters and consistency models) and reliability features (file system copy-on-write checkpointing to aid recovery of client-side failures; replication, autonomous failure detection and data access redirection for server-side failures). These enhancements, in addition to cross-domain user identity mapping and encrypted communication, are implemented via user level proxies managed by the service, requiring no changes to existing kernels. Sessions established using the service is mounted as distributed file systems and can be used transparently by unmodified binary applications. The paper analyzes the use of the service to support virtual machine based grid systems and workflow execution, and also reports on the performance and reliability of service managed wide-area file system sessions with experiments based on scientific applications (NanoMOS/Matlab, CHID, GAUSS and SPECseis).

The authors have proposed Network Traversal with Mobility (NTMobile) that achieves both IP mobility and End-to-End connectivity in IPv4/IPv6 networks. In order to achieve end-to-end encrypted communication between IPv4 and IPv6 networks, it is necessary to relay a server in the cloud. This system model includes problems such as increased transmission delays and redundant communication paths. This paper proposes a new NTMobile system model that applies the concept of mobile edge computing. The proposed system model solves problems of the conventional model by deploying NTMobile servers on Virtual Customer Premises Equipment. The results of the verification of the proposed model in a virtual environment show that the communication performance is expected to be improved.

Norton Commander provides DOS services such as edit, copy, rename, move and delete. Users can quickly and easily view contents of directories and files and can also search for file names using DOS wildcards. Users can set up their own custom access menus.

The development of information society and the corresponding technologies raises to a new level the tasks of counteracting crimes committed using such technologies, and of minimizing damage from them. The growth in the scale of new types of crime is a cause of worry for the society and the authorities, and especially for criminologists, as the penetration of criminals into the virtual environment and their mastery of new technologies acquire dangerous forms, change criminal motivation and, at the same time, to some extent stimulate the development of information and telecommunication technologies. The growing sophistication of the tasks of preventing and counteracting hi tech crimes makes it necessary to critically assess the current criminological methods and to make an attempt to go beyond the known «common» methods of neo-classical criminology. The development of the digital criminology concept cannot be reduced to an aggregate of pioneer technological methods developed on the basis of mathematical modeling, i.e. computer processing of quantitative and qualitative parameters of crimes, mathematical detection of different dependencies (on time, place and other variables), it could and should be understood in a wider sense: on the one hand, it should influence the new criminological paradigm, and on the other - it should develop within its boundaries. The modern information-analytical sphere in the work of law enforcement bodes includes the use of digital criminological instruments within the programs of crime prevention, mathematical methods of analyzing crimes, profiling, etc. Their aggregate is generally applicable to criminological analysis and prediction, however, it does not have the most cutting edge theoretical basis that corresponds to the tasks of counteracting crimes of the digital world; it is now being formed on the basis of criminological neo-classics, the advances of the social sciences and the humanities, digital criminology. The predictions of new industrial revolutions include a rapid acceleration of the pace of technological development, a systemic transformation of production and management, which will not only stimulate a global rise in the living standards, but will also increase inequality and, consequently, will provide an impetus to crime. These aspects should be taken into consideration when predicting future development of digital criminology, whose theories should be based on the conceptual models of social development of the near future. Social consequences of the predicted new industrial revolutions will inevitably become new common determiners of the crimes of the future, as it always happened in the past.

Limited main memory size is considered as one of the major bottlenecks in virtualization environments. Content-Based Page Sharing (CBPS) is an efficient memory deduplication technique to reduce server memory requirements, in which pages with same content are detected and shared into a single copy. As the widely used implementation of CBPS, Kernel Samepage Merging (KSM) maintains the whole memory pages into two global comparison trees (a stable tree and an unstable tree). To detect page sharing opportunities, each tracked page needs to be compared with pages already in these two large global trees. However since the vast majority of compared pages have different content with it, that will induce massive futility comparisons and thus heavy overhead.