Biblio

The report examines approaches to assessing the information security of data transmission networks (DTN). The analysis of methods for quantitative assessment of information security risks is carried out. A methodological approach to the assessment of IS DTN based on the risk-oriented method is presented. A method for assessing risks based on the mathematical apparatus of the queening systems (QS) is considered and the problem of mathematical modeling is solved.

Natural language processing (NLP) is a division of artificial intelligence. The constructed model's quality is entirely reliant on the training dataset's quality. A data streaming pipeline is an adhesive application, completing a managed connection from data sources to machine learning methods. The recommended NLP pipeline composition has well-defined procedures. The implemented message broker design is a usual apparatus for delivering events. It makes it achievable to construct a robust training dataset for machine learning use-case and serve the model's input. The reconstructed dataset is a valid input for the machine learning processes. Based on the data pipeline's product, the model recreation and redeployment can be scheduled automatically.

In order to improve the status monitoring and management ability of wireless sensor networks, a dynamic data compression method based on grid deduplication is proposed. Grid-based sensor node spatial positioning and big data fusion method are adopted to realize dynamic feature mining of wireless sensor network data, extract feature sequence points of wireless sensor network data, reconstruct wireless sensor network data feature space by adopting spatial grid node recombination, build a statistical detection model of dynamic feature mining of wireless sensor network data by combining grid area grouping compression method, and realize embedded fuzzy control and joint feature distributed adaptive learning. The association matching degree of wireless sensor network data is analyzed. Combining fuzzy subspace compression and big data fusion clustering, the quantitative regression analysis model of wireless sensor network data is established. The time series reorganization of wireless sensor network database is realized by index table name, index column and other information. Compressed sensing method is used in linear fusion subspace to realize data compression and adaptive detection of wireless sensor network. Constraint feature points of wireless sensor network data compression are constructed, and dynamic compression and clustering processing of wireless sensor network data are realized at constraint points. Simulation results show that the feature clustering of data compression in wireless sensor networks is better and the storage space of data is reduced.

In this article we have developed a simulation model in the Mininet environment for analyzing the operation of a software-defined network (SDN) in cloud data centers. The results of the simulation model of the operation of the SDN network on the Mininet emulator and the results of the simulation of the traditional network in the Graphical Network Simulator 3 emulator are presented.

IoT devices introduce unprecedented threats into home and professional networks. As they fail to adhere to security best practices, they are broadly exploited by malicious actors to build botnets or steal sensitive information. Their adoption challenges established security standard as classic security measures are often inappropriate to secure them. This is even more problematic in sensitive environments where the presence of insecure IoTs can be exploited to bypass strict security policies. In this paper, we demonstrate an attack against a highly secured network using a Bluetooth smart bulb. This attack allows a malicious actor to take advantage of a smart bulb to exfiltrate data from an air gapped network.

In today's world, software is ubiquitous and relied upon to perform many important and critical functions. Unfortunately, software is riddled with security vulnerabilities that invite exploitation. Attackers are particularly attracted to software systems that hold sensitive data with the goal of compromising the data. For such systems, this paper proposes a modeling method applied at design time to identify and reduce the attack surface, which arises due to the locations containing sensitive data within the software system and the accessibility of those locations to attackers. The method reduces the attack surface by changing the design so that the number of such locations is reduced. The method performs these changes on a graphical model of the software system. The changes are then considered for application to the design of the actual system to improve its security.

Now-a-days vehicular information network technology is receiving a lot of attention due to its practical as well as safety related applications. By using this technology, participating vehicles can communicate among themselves on the road in order to obtain any interested data or emergency information. In Vehicular Ad-Hoc Network (VANET), due to the fast speed of the vehicles, the traditional host centric approach (i.e. TCP/IP) fails to provide efficient and robust communication between large number of vehicles. Therefore, Named Data Network (NDN) newly proposed Internet architecture is applied in VANET, named as VNDN. In which, the vehicles can communicate with the help of content name rather than vehicle address. In this paper, we explored the concepts and identify the main packet forwarding issues in VNDN. Furthermore, we proposed a protocol, named Control of Useless Interests Flooding (CUIF) in Vehicular Named Data Network. In which, it provides the best and efficient communication environment to users while driving on the highway. CUIF scheme reduces the Interest forwarding storm over the network and control the flooding of useless packets against the direction of a Producer vehicle. Our simulation results show that CUIF scheme decreases the number of outgoing Interest packets as well as data download time in the network.

This article is devoted to the development of a platform for reliable storage of information on supplies based on blockchain technology. The article discusses the main approaches to the work of decentralized applications, as well as the main problems.

This article discusses the vulnerabilities and complexity of designing secure IoT-solutions, and then presents proven approaches to protecting devices and gateways. Specifically, security mechanisms such as device authentication (including certificate-based authentication), device authentication, and application a verification of identification are described. The authors consider a protocol of message queue telemetry transport for speech and sensor networks on the Internet, its features, application variants, and characteristic procedures. The principle of "publishersubscriber" is considered. An analysis of information elements and messages is carried out. The urgency of the theme is due to the rapid development of "publisher-subscriber" architecture, for which the protocol is most characteristic.

Wireless Sensor Networks (WSNs) are important and becoming more important as we integrate wireless sensor networks and the internet with different things, which has changed our life, and it is affected everywhere in our life like shopping, storage, live monitoring, smart home etc., called Internet of Things (IoT), as any use of the network physical devices that included in electronics, software, sensors, actuators, and connectivity which makes available these things to connect, collect and exchange data, and the most importantly thing is the accuracy of the data that has been collected in the Internet of Things, detecting sensor data with faulty readings is an important issue of secure communication and power consumption. So, requirement of energy-efficiency and integrity of information is mandatory.

This paper describes an early design research exploration into the potential of folds and pockets to serve as places for safekeeping and secrecy in wearables. We explore what such secrecy may mean through woven data codes. We report on early material exploration, a pilot study with ten participants, and the personalization of a data object. We then outline, how we will make use of these early indications to build future stages of the project.

The Business Intelligence (BI) paradigm is challenged by emerging use cases such as news and social media analytics in which the source data are unstructured, the analysis metrics are unspecified, and the appropriate visual representations are unsupported by mainstream tools. This case study documents the work undertaken in Microsoft Research to enable these use cases in the Microsoft Power BI product. Our approach comprises: (a) back-end pipelines that use AI to infer navigable data structures from streams of unstructured text, media and metadata; and (b) front-end representations of these structures grounded in the Visual Analytics literature. Through our creation of multiple end-to-end data applications, we learned that representing the varying quality of inferred data structures was crucial for making the use and limitations of AI transparent to users. We conclude with reflections on BI in the age of AI, big data, and democratized access to data analytics.

There are many risks in moving data into public storage environments, along with an increasing threat around large-scale data leakage. Secret sharing scheme has been proposed as a keyless and resilient mechanism to mitigate this, but scaling through large scale data infrastructure has remained the bane of using secret sharing scheme in big data storage and retrievals. This work applies secret sharing methods as used in cryptography to create robust and secure data storage and retrievals in conjunction with data fragmentation. It outlines two different methods of distributing data equally to storage locations as well as recovering them in such a manner that ensures consistent data availability irrespective of file size and type. Our experiments consist of two different methods - data and key shares. Using our experimental results, we were able to validate previous works on the effects of threshold on file recovery. Results obtained also revealed the varying effects of share writing to and retrieval from storage locations other than computer memory. The implication is that increase in fragment size at varying file and threshold sizes rather than add overheads to file recovery, do so on creation instead, underscoring the importance of choosing a varying fragment size as file size increases.

An increasing number of everyday objects are now connected to the internet, collecting and sharing information about us: the "Internet of Things" (IoT). However, as the number of "social" objects increases, human concerns arising from this connected world are starting to become apparent. This paper presents the results of a preliminary qualitative study in which five participants lived with an ambiguous IoT device that collected and shared data about their activities at home for a week. In analyzing this data, we identify the nature of human and socio-technical concerns that arise when living with IoT technologies. Trust is identified as a critical factor - as trust in the entity/ies that are able to use their collected information decreases, users are likely to demand greater control over information collection. Addressing these concerns may support greater engagement of users with IoT technology. The paper concludes with a discussion of how IoT systems might be designed to better foster trust with their owners.

NSTX used MDSplus extensively to record data, relay information and control data acquisition hardware. For NSTX-U the same functionality is expected as well as an expansion into the realm of securely maintaining parameters for machine protection. Specifically, we designed the Digital Coil Protection System (DCPS) to use MDSplus to manage our physical and electrical limit values and relay information about the state of our acquisition system to DCPS. Additionally, test and development systems need to use many of the same resources concurrently without causing interference with other critical systems. Further complications include providing access to critical, protected data without risking changes being made to it by unauthorized users or through unsupported or uncontrolled methods either maliciously or unintentionally. To achieve a level of confidence with an existing software system designed with minimal security controls, a number of changes to how MDSplus is used were designed and implemented. Trees would need to be verified and checked for changes before use. Concurrent creation of trees from vastly different use-cases and varying requirements would need to be supported. This paper will further discuss the impetus for developing such designs and the methods used to implement them.