Network File System Research Articles

Evidence Vault

Ensuring the integrity of evidence is paramount within the realm of digital forensics. The preservation of evidence gathered at a crime scene is essential for concluding investigations and delivering justice to those involved. Hence, it is imperative to safeguard this evidence from any form of tampering. The process that upholds the reliability of evidence is known as the "chain of custody." Failure to maintain the chain of custody can render the evidence inadmissible in court, potentially resulting in the dismissal of the case. To address these challenges and promote an eco-friendly approach, there is a need to modernize the forensic evidence protection system through digitalization. Blockchain technology offers a promising solution in this regard. Blockchains are decentralized digital ledgers that chronologically record transactions through cryptographic signatures. These transactions are organized into blocks and are accessible to all participants within the blockchain network. In conjunction with this, the Interplanetary File System (IPFS) serves as a network file system that complements the blockchain. The current research aims to develop a system that leverages blockchain technology to digitize the forensic evidence protection system while preserving the chain of custody. This approach is rooted in the principles of blockchain and the utilization of IPFS. Keywords: Evidence, Blockchain Technology, Digital Forensics, Chain of Custody, IPFS, Cryptography.

Development and Evaluation of Remote Learning Management System using Intranet Network for Hinterland Schools

The lack of internet access in underdeveloped nations, including the Philippines, has significant impact on the digital divide. One of the challenges faced by students in underdeveloped nations, particularly those in far-flung and hinterland schools, is the lack of access to up-to-date educational resources due to their geographic isolation. This can lead to a significant disadvantage in terms of academic performance and future opportunities. Thus, a Remote Learning Management System (RLMS) is proposed. The study includes the development and testing of the RLMS system, as well as an evaluation of its acceptance through the Technology Acceptance Model survey questionnaire. This system utilizes intranet networks and a Network File System to provide distant learning and teaching-based eLearning in far-flung and hinterland schools. The system intends to make sharing educational resources easier, such as to let students access their lessons, modules, and assignments, take exams and quizzes and even watch video lessons on their laptops, smartphones, and tablets, even without an internet connection. The results show that the RLMS system is fully functional and accessible, with positive acceptance and intention to use from teachers and students. Future studies can focus on enhancing the RLMS capabilities, improving user-friendliness, and providing in-depth training to teachers to maximize the system's potential. Overall, the RLMS system provides a viable alternative for blended learning in areas with slow and limited internet access.

Overarching Data Management Ecosystem at HZDR

When dealing with research data management, researchers at Helmholtz- Zentrum Dresden – Rossendorf (HZDR) face a variety of systems and tools. These range from the project planning phase (proposal management, data management plans and policies), over documentation during the experiment or simulation campaign, to the publication (collaborative authoring tools, metadata catalogs, publication systems, data repositories). In addition, modern research projects usually are required to interact with a variety of software stacks and workflow management systems to allow comprehensi- ble and FAIR science on the underlying IT infrastructure (HPC, data storage, network file systems, archival). This article first demonstrates the data management systems and services provided at HZDR, followed by an overview of a self-developed guidance system. It is concluded by a real-world example.

Overcoming Performance Bottlenecks With a Network File System in Solid State Drives

Overcoming Performance Bottlenecks With a Network File System in Solid State Drives

Network Security Analysis with SnortIDS Using ACID (Analysis Console for Intrusion Databases

The use of Wi-Fi and Ethernet is increasing in today's computer networks due to the advancement of technology. The development of networks today is characterized by the need for low-latency and high-bandwidth technology. The technology has also introduced 5G and Wi-Fi 6 which support high-speed internet surfing. The introduction of Network File System (NFS) in this era sparked the demand for Ethernet. NFS also increased the use of UNIX in education and professional computing in the 1980s. Then, in 1982, Token Ring Topology emerged as an alternative to the internet and was only standardized in 1985. Network security is an important factor in ensuring data is not stolen or damaged. With the increasing knowledge of hacking and cracking, and the availability of tools that can be easily used to launch attacks or intrusions, it is important to investigate when an attack occurs. One network forensic method for monitoring attacks on the network is using Snort IDS and Ntop to facilitate the logging process for monitoring the network system. Based on the results obtained from designing a network security with Snort Intrusion Detection System (IDS) using ACID (Analysis Console for Intrusion Databases) with the utilization of IPTables on Ubuntu Server can stop attackers. In this research, the researcher used IPTables on Ubuntu as a firewall to anticipate attacks. To prevent port scanning attacks conducted by the attacker, the author created a firewall using IPTables where the IPTables rules aim to block the IP address of the attacker.

Analyzing execution path non-determinism of the Linux kernel in different scenarios

Safety-critical systems play a significant role in industrial domains, and their complexity is increasing with advanced technologies such as Artificial Intelligence (AI). To provide efficient services, safety-critical systems that integrate AI applications are always built based on Linux, where Linux offers massive amounts of features and an incredibly perfect software ecosystem for AI applications. Since Linux is a pre-existing complex software system, different research programmes aim to pave the way for developing Linux-based safety-critical systems. Still, only some focus on the system calls for file operations. However, the execution path of a system call is effectively non-deterministic in Linux kernel space, which challenges the test coverage-based verification recommended by the functional safety standards. This research analyzes the influence of system state on Linux kernel path variability from two perspectives: file system type and system load. Therefore, an online data collection system for system call execution paths was constructed based on Ftrace, network file system (NFS), and MD5 hash function, uniquely identifying the system call execution path. The collected data were processed and analysed in this study. Evaluations show that the number of function execution paths of the system calls relevant to file systems increased with the increase in system load but would eventually be stable. Additionally, the function execution paths of the system call varied in different file systems. Based on the evaluations, the results of this work can provide advice for analyzing Linux-based safety-critical systems. In addition, the method introduced in this research can also provide support for the verification of Linux-based safety-critical systems.

Artificial neural networks based predictions towards the auto-tuning and optimization of parallel IO bandwidth in HPC system

Super-computing or HPC clusters are built to provide services to execute computationally complex applications. Generally, these HPC applications involve large scale IO (input/output) processing over the networked parallel file system disks. They are commonly developed on top of the C/C++ based MPI standard library. The HPC clusters MPI–IO performance significantly depends on the particular parameter value configurations, not generally considered when writing the algorithms or programs. Therefore, this leads to poor IO and overall program performance degradation. The IO is mostly left to individual practitioners to be optimised at code level. This usually leads to unexpected consequences due to IO bandwidth degradation which becomes inevitable as the file data scales in size to petabytes. To overcome the poor IO performance, this research paper presents an approach for auto-tuning of the configuration parameters by forecasting the MPI–IO bandwidth via artificial neural networks (ANNs), a machine learning (ML) technique. These parameters are related to MPI–IO library and lustre (parallel) file system. In addition to this, we have identified a number of common configurations out of numerous possibilities, selected in the auto-tuning process of READ/WRITE operations. These configurations caused an overall READ bandwidth improvement of 65.7% with almost 83% test cases improved. In addition, the overall WRITE bandwidth improved by 83% with number of test cases improved by almost 93%. This paper demonstrates that by using auto-tuning parameters via ANNs predictions, this can significantly impact overall IO bandwidth performance.

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

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.

Evaluating CephFS Performance vs. Cost on High-Density Commodity Disk Servers

CephFS is a network filesystem built upon the Reliable Autonomic Distributed Object Store (RADOS). At CERN we have demonstrated its reliability and elasticity while operating several 100-to-1000TB clusters which provide NFS-like storage to infrastructure applications and services. At the same time, our lab developed EOS to offer high performance 100PB-scale storage for the LHC at extremely low costs while also supporting the complete set of security and functional APIs required by the particle-physics user community. This work seeks to evaluate the performance of CephFS on this cost-optimized hardware when it is combined with EOS to support the missing functionalities. To this end, we have setup a proof-of-concept Ceph Octopus cluster on high-density JBOD servers (840 TB each) with 100Gig-E networking. The system uses EOS to provide an overlayed namespace and protocol gateways for HTTP(S) and XROOTD, and uses CephFS as an erasure-coded object storage backend. The solution also enables operators to aggregate several CephFS instances and adds features, such as third-party-copy, SciTokens, and high-level user and quota management. Using simple benchmarks we measure the cost/performance tradeoffs of different erasure-coding layouts, as well as the network overheads of these coding schemes. We demonstrate some relevant limitations of the CephFS metadata server and offer improved tunings which can be generally applicable. To conclude, we reflect on the advantages and drawbacks related to this architecture, such as RADOS-level free space requirements and double-network penalties, and offer ideas for improvements in the future.

Accelerator virtualization

Welcome to this special issue on accelerator virtualization in Concurrency and Computation: Practice and Experience. Virtualization is a key technique developed for sharing the underlying physical resources of a computer, such as the processor or memory and the network. This enables effective use of resources by improving their utilization and reduces costs. A well-known example of virtualization are virtual machines that have become prominent with the advent of cloud technologies. Virtual machines are an abstraction of the underlying physical computer that can be made available to different users. The underpinning technology ensures data security by isolating the environment in which each user works. Creating and executing virtual machines requires both software and hardware support. It is thought that one of the earliest forms of virtualization was time-multiplexing a single processor for different applications. Although this significantly varies from the current notion of virtualization, processor multiplexing laid the groundwork for modern operating systems to facilitate the concurrent sharing of an expensive hardware resource among several applications as if they each used the resource exclusively. A network file system is another example of virtualization in which the file system is physically available to several nodes of a computer cluster while it is simultaneously accessed by different client nodes. In this case, storage is the common resource shared via multiplexing mechanisms. Recently, virtualization has been adopted for hardware accelerators, specialized hardware such as graphics processing units (GPUs), field programmable gate arrays (FPGAs), and tensor processing units (TPUs). Accelerators reduce the execution time of certain applications by allowing programmers to offload compute intensive components of their applications to accelerators. They are also known to improve energy efficiency. We hope that the contents of this special issue are useful to you and that you enjoy them as much as we did.

A self-tuning client-side metadata prefetching scheme for wide area network file systems

A self-tuning client-side metadata prefetching scheme for wide area network file systems

Key Exchange Protocols for Parallel Network File Systems Using Optimized Cryptography

The utilization of parallel file system is expanding quickly nowadays; security moves toward becoming are significant worry about inside this work is to structure capable and secure affirmed key trade conventions that meet explicit necessities of pNFS. The current techniques neglected to achieve alluring properties, for instance, scalability, viability, escrow free and forward mystery. A large portion of existing techniques either has not been alluringly practiced or are not reachable by the current Kerberos-based arrangement. These issues overwhelmed by a late technique which is utilizing an assortment of authenticated key trade conventions that are intended to address the above issues. This technique utilized AES calculation for security. In this undertaking, It is giving that a new AES calculation objective of accomplishing speed and security. This new AES is called as IAES (improved AES). The proposed security technique will accomplish better execution as far as speed, security, and correspondence overhead when contrasted with existing strategies.

Curious Containers: A framework for computational reproducibility in life sciences with support for Deep Learning applications

In clinical scenarios, there is an increasing interest in complex computational experiments, as for example the training of Deep Learning models. Reproducibility is an essential property of such experiments, especially if the result contributes to a patient’s treatment. This paper introduces Curious Containers, a software framework for computational reproducibility that treats data, software and runtime environment as decentralized network resources. All experiment resources are described in a single file, using a new format that is compatible with a subset of the Common Workflow Language. Docker is used to deploy the experiment software in a container image, including arbitrary data transmission programs to connect with existing storage solutions. The framework supports Deep Learning applications, that have a high demand in storage and processing capabilities. Large datasets can be mounted inside containers via network filesystems like SSHFS based on the filesystem in user-space technology. The Nvidia-Container-Toolkit enables GPU usage. Curious Containers has been tested in two biomedical scenarios. The first use case is a Deep Learning application for tumor classification in images that requires a large dataset and a GPU. In this context, a prototypical integration of the framework with the existing Data Version Control system for exploratory Deep Learning modeling has been developed. The second use case extends an existing container image, including a scientific workflow for detection and comparison of human protein in mass spectrography data. The container image was originally developed for an archiving platform and could be extended to be compatible with both Curious Containers and cwltool, the Common Workflow Language reference implementation. The presented solution allows for consistent description and execution of computational experiments, while trying to be both flexible and interoperable with existing software and standards. Support for Deep Learning experiments is gaining importance as such systems are increasingly validated as medical decision support systems.

Booting of Diskless Workstation

This paper focuses on proposing a system for centralization of the IT infrastructure by building upon the concept of Diskless Booting. The client stations are configured to boot over an existing network using the Network Boot. The Client Station lacks an actual Hard Drive, which is responsible for storing the boot files and other necessary files. It consists of other hardware excluding the Hard Drive such as, RAM, Processor, etc. The network consists of DHCP (Dynamic Host Configuration Protocol) server which assigns IP addresses to several client stations connected. The NIS (Network Information Service) server stores the login credentials of all the users, enabling the users to login from any client station without any restrictions. The NFS (Network File System) server makes the files available for the user, even on the absence of local secondary storage. Security is ensured by SHA (Security Hash Algorithm), which encrypts the sensitive data by creating the hash values. Individual ports and services can be kept secured by using the Firewall service. The open source Cockpit Tool provides a GUI with which the administrator can conveniently carry out several admin-oriented tasks, such as memory management, user management.

An intelligent memory caching architecture for data-intensive multimedia applications

With the rapid developments in cloud computing and mobile networks, multimedia content can be accessed conveniently. Recently, some novel intelligent caching-based approaches have been proposed to improve the memory architectures for multimedia applications. These applications often face bottleneck related challenges which result in performance degradation and service delay issues. Intelligent multimedia network applications access the shared data by using a specific network file system. This results in answering the processing related constraints on hard-drive storage and might result in bringing bottleneck issues. Therefore, to improve the performance of these multimedia network applications, we present an intelligent distributed memory caching system. We integrate the multimedia application message passing interface in a multi-threaded environment and propose an algorithm which can handle concurrent response behavior for different multimedia applications. Results demonstrate that our proposed scheme outperforms traditional approaches in terms of throughput and file read access features.

Design and Implementation of an Overlay File System for Cloud-Assisted Mobile Apps

With cloud assistance, mobile apps can offload their resource-demanding computation tasks to the cloud. This leads to a scenario where computation tasks in the same program run concurrently on both the mobile device and the cloud. An important challenge is to ensure that the tasks are able to access and share the files on both the mobile and the cloud in a manner that is efficient, consistent, and transparent to locations. Existing distributed file systems and network file systems do not satisfy these requirements. Current systems for offloading tasks either do not support file access for offloaded tasks or do not offload tasks with file access. The paper addresses this issue by designing and implementing an application-level file system called Overlay File System (OFS). To improve efficiency, OFS maintains and buffers local copies of data sets on both the cloud and the mobile device. OFS ensures consistency and guarantees that all the reads get the latest data. It combines write-invalidate and write-update policies to effectively reduce the network traffic incurred by invalidating/updating stale data copies and to reduce the execution delay when the latest data cannot be accessed locally. To guarantee location transparency, OFS creates a unified view of the data that is location independent and is accessible as local storage. We overcome the challenges caused by the special features of mobile systems on an application-level file system, like the lack of root privilege and state loss when application is killed due to the shortage of resource and implement an easy to deploy prototype of OFS. The paper tests the OFS prototype on Android OS with a real mobile app and real mobile user traces. Extensive experiments show that OFS can effectively support consistent file accesses from computation tasks, no matter whether they are on a mobile device or offloaded to the cloud. In addition, OFS reduce both file access latency and network traffic incurred by file accesses.

Distributed Personal Cloud Storage without Third Parties

We present the “It's My Data file system” (IMDfs), a personal, version-tracking, distributed file system that allows users to take custody of their cross-device data management needs, without depending on cloud storage providers. Such a system may be desirable to privacy-conscious users, who worry about the increasing number of cloud storage incidents involving data leakage and corruption, or simply want to synchronize their devices without depending on third parties. IMDfs provides a global, unified view of a user's distributed data collection from any device, user-controlled replication of data across devices, transparent remote access, and support for non-restrictive conflict management. IMDfs achieves all this without sacrificing fault-tolerance or performance and with modest storage overhead. We present the design, implementation, and detailed performance evaluation of IMDfs using benchmarks and traces from real workloads, and we demonstrate that: 1) IMDfs, as a local file system, has reasonable overhead compared with a FUSE loopback file system and Wayback, a local versioning file system, and 2) IMDfs, as a network file system, outperforms NFS and Ori, a state-of-the-art file system for cross-device data management.

FGACFS: A fine-grained access control for *nix userspace file system

In this paper we present FGACFS — a fine-grained access control file system designed for creating and administering directories with shared access in the *nix operating system family. The proposed access control model extends POSIX ACLs. Its essential features are: 1) an extensive list of enforceable permissions, 2) separating file and directory permissions, 3) two different mechanisms of permission inheritance — one for classic inheritance and one for copying permissions for newly-created objects. In overall, there are 19 file and 29 directory permission types. These permissions are designed to be implemented in a single tool and to allow control of both system users and programs simultaneously.To evaluate our approach, we have developed a software implementation based on this model. FGACFS is a userspace file system that was created by implementing the FUSE interface. Our file system is independent of underlying network and on-disk file systems. In our experiments we have evaluated two different approaches for storing permissions and a single permission caching scheme that we have developed to speed up operations.The conducted performance tests show the efficiency of our approach and demonstrate that our solution is ready to be deployed and used at least in small workgroups.

Prediction of Energy Consumption by Checkpoint/Restart in HPC

The fault tolerance method most used today in high-performance computing (HPC) is coordinated checkpointing. This, like any other fault tolerance method, adds additional energy consumption to that of the execution of the application. Currently, knowing and minimizing this energy consumption is a challenge. The objective of this paper is to propose a model to estimate the energy consumption of checkpoint and restart operations and a method for its construction. These estimates allow the evaluation of different scenarios in order to minimize energy consumption. We focus on coordinated checkpoint/restart at the system level, in single-program multiple-data (SPMD) applications, on homogeneous clusters. We study the behavior of the power dissipated by the compute node during a checkpoint/restart operation, as well as its execution time, considering different parameters of the system and the application. The experimentation carried out on two platforms shows the validity of the proposal. We also evaluate the impact on power and energy consumption of the processor’s C states, the configuration of the network file system (NFS), where the checkpoint files are stored, and the compression of the checkpoint files. This paper contributes to the objective of predicting energy consumption in the execution of applications that use checkpoint/restart. Not counting the outliers, we can estimate the energy consumed by checkpoint/restart operations with errors lower than 7.5%.

Implementation And Analysis High Availability Network File System Based Server Cluster

Server is a computer system that provides the kind of service in a computer network. One of the functions of the server is as data storage. Computers servers with high availability values are generally referred to as High Availability (HA) Server. HA enables a server can be operational in a sustainable manner for long periods of time. Now, HA has been combined with a cluster technique known as High Availability Clusters or failover cluster. In this research the author intends to apply, analyze, and implement a network file server that has a high availability of service. Researchers used a pacemaker as cluster resource management, Corosync as cluster messaging service and DRBD for the synchronization of data if a failover occurs and measured network performer cluster file system that does have a high availability service. The result is a network file system or the availability of the cluster has a value of 99.998% availability, which means it has a High Availability. The server network file system failover cluster meets the conditions, which, if the primary server (master) dies it will be replaced by a slave server.