Digital forensics and its role in promoting criminal prosecution

Digital forensics is essentially synonymous with computer forensics, but the term "digital forensics" is generally used for the technical review of all devices that have the ability to store data. Today, digital criminology is challenged in cloud computing. The first problem is to understand why and how criminal and social actions are so unique and complex. The second problem is the lack of accurate scientific tools for forensic medicine in cyberspace. So far, no complete tools or explanations for criminology have been provided in the virtual infrastructure, and no training for security researchers has been provided in detail. Therefore, the author of the present descriptive-analytical research is based on library resources and using fish taking tools. To investigate suspicious cases related to cyberspace, criminologists must be well-equipped with technical and legal issues to deal with. In this article, we analyze digital criminology and its role in judicial law. The benefit of computer forensic knowledge is not only an indispensable necessity for security and judicial institutions, but also professional users and owners of computer systems, systems and networks must be fully aware of and properly comply with its legal and technical requirements.

Road to Strengthen of Virtual Infrastructure and Security of Remote Laboratories on Trnava University in Trnava

Many organizations, both large and small, are investigating the potential of storage architectures for their companies. Few years ago, we built our own virtualized cloud for REMLABNET and we still are taking benefits of this decision. This item handels with using Cloud computing platform for providing Remote laboratories. This work shows, how it is possible to save money if we use centralized system for more consumers. Every consumer can use access to centralized portal in the Cloud computing from Consortium REMLABNET. Every item is focused on enviroments of universities, where this cloud is existing and this is what we want to use for remote labs. This is item from practice knowledge and experiences about system function and managing virtual platform and next construction this proposal.

Optimization of System Framework for Secure Communication and Data Virtualization on Cloud Computing

The consequent deployment of vital infrastructure to provide the secure communication and virtualization not only rectifies the challenges and difficulties but also benefits with saving the process of digitization. With a bang in evolution of cloud computing the uniqueness of every organization affects the virtualization of its information communication technology and applications. The answer for such organizations is to stipulate the precise cloud computing model equivalent to the deliberated and operational goals. This research article emphasized at budding and optimizing a framework for virtual infrastructure and cloud computing model to support the organization stakeholders. Moreover it also improves the cloud security with a protected virtual infrastructure and communication model with better performance. On account of data storage security necessities and distinctiveness of cloud computing environment, a method for secured data & storage based on dynamic allocation and access control mechanism is presented. Dynamic resource allocation is applied for resource utilization that focused on data virtualization and memory virtualization, for protection and access control a modified KPABE algorithm is integrated. The combination of these methods resulting on the optimize resource use, centralizing of storage. The implementation and comparison of results revealed that the proposed modified KP-ABE has performed effectively than the other security standards and especially for resource utilization. The proposed method serves for efficient data storage, access control solutions and computation in cloud environment

A Comparative Analysis of NSGA-II and NSGA-III for Autoscaling Parameter Sweep Experiments in the Cloud

The Cloud Computing paradigm is focused on the provisioning of reliable and scalable virtual infrastructures that deliver execution and storage services. This paradigm is particularly suitable to solve resource-greedy scientific computing applications such as parameter sweep experiments (PSEs). Through the implementation of autoscalers, the virtual infrastructure can be scaled up and down by acquiring or terminating instances of virtual machines (VMs) at the time that application tasks are being scheduled. In this paper, we extend an existing study centered in a state-of-the-art autoscaler called multiobjective evolutionary autoscaler (MOEA). MOEA uses a multiobjective optimization algorithm to determine the set of possible virtual infrastructure settings. In this context, the performance of MOEA is greatly influenced by the underlying optimization algorithm used and its tuning. Therefore, we analyze two well-known multiobjective evolutionary algorithms (NSGA-II and NSGA-III) and how they impact on the performance of the MOEA autoscaler. Simulated experiments with three real-world PSEs show that MOEA gets significantly improved when using NSGA-III instead of NSGA-II due to the former provides a better exploitation versus exploration trade-off.

Annotated Dataset for Anomaly Detection in a Data Center with IoT Sensors

The relative simplicity of IoT networks extends service vulnerabilities and possibilities to different network failures exhibiting system weaknesses. Therefore, having a dataset with a sufficient number of samples, labeled and with a systematic analysis, is essential in order to understand how these networks behave and detect traffic anomalies. This work presents DAD: a complete and labeled IoT dataset containing a reproduction of certain real-world behaviors as seen from the network. To approximate the dataset to a real environment, the data were obtained from a physical data center, with temperature sensors based on NFC smart passive sensor technology. Having carried out different approaches, performing mathematical modeling using time series was finally chosen. The virtual infrastructure necessary for the creation of the dataset is formed by five virtual machines, a MQTT broker and four client nodes, each of them with four sensors of the refrigeration units connected to the internal IoT network. DAD presents a seven day network activity with three types of anomalies: duplication, interception and modification on the MQTT message, spread over 5 days. Finally, a feature description is performed, so it can be used for the application of the various techniques of prediction or automatic classification.

Virtualization of Network infrastructure in Educational Institutions

The article discusses current issues of virtualization of the network infrastructure of educational institutions. The analysis of the literature on this issue. A new approach to creating a cloud virtualization environment for the educational institution’s network infrastructure is proposed, which is based on the joint use of virtualization technologies and software-defined networks. This approach allows you to unify the process of creating a network infrastructure, scale the resources provided on demand with minimal organizational and technical costs. The data processing center of the Belarusian State University has implemented a model that includes virtual network segments. Using virtualization technologies and software-defined networks allows you to unify the process of creating network infrastructure, scale the resources provided on demand with minimal organizational and technical costs, adapt the virtual infrastructure to the requirements of a particular educational institution.