Sử dụng mạng máy tính phân tán trong xây dựng giải pháp thám mã khối

Tóm tắt—Bài báo trình bày một giải pháp sử dụng năng lực của mạng máy tính phân tán cho thám mã khối. Hệ thống có cấu trúc dựa trên 3 phần mềm. Phần mềm quản trị sử dụng cho nhập dữ liệu đầu vào, phân tích và chia khoảng không gian khóa và phân tích kết quả. Phần mềm thám mã trên CPU và GPU được cài đặt tương ứng cho các máy tính trong mạng phân tán có nhiệm vụ thám mã đối với dữ liệu phần mềm quản trị cung cấp. Kết quả được gửi về phần mềm quản trị để phân tích và giải mã. Quá trình thám mã được thực hiện cùng lúc trên toàn bộ máy tính trong mạng vào thời gian máy tính nhàn rỗi, không ảnh hưởng tới hoạt động hàng ngày của người dùng. Hệ thống bao gồm cả các máy tính có sử card GPU giúp tăng hiệu suất thám mã lên gấp 11 lần. Giải pháp đã được ứng dụng trong thám mật khẩu Windows qua mã băm LAN Manager. Abstract—This paper presents a method to use the capabilities of distributed computer networks in cryptanalysis of block ciphers. The system is structured based on 3 software. Management software for input data entry, analysis, and keyspace division. Cryptanalysis software on CPU and GPU is installed respectively for client computers in the distributed network is responsible for cryptanalysis of data provided by the management software. The results are sent to the administrative software for analysis and decoding. The encryption process is performed on all computers in the network at the same time in their spare time, without affecting the user's daily activities. The system includes GPU computers that increase the performance of the cryptanalysis by 11 times. This solution has been applied in Windows password detection via LAN Manager hash code.

Distributed Authentication Model for Secure Network Connectivity in Network Separation Technology

Considering the increasing scale and severity of damage from recent cybersecurity incidents, the need for fundamental solutions to external security threats has increased. Hence, network separation technology has been designed to stop the leakage of information by separating business computing networks from the Internet. However, security accidents have been continuously occurring, owing to the degradation of data transmission latency performance between the networks, decreasing the convenience and usability of the work environment. In a conventional centralized network connection concept, a problem occurs because if either usability or security is strengthened, the other is weakened. In this study, we proposed a distributed authentication mechanism for secure network connectivity (DAM4SNC) technology in a distributed network environment that requires security and latency performance simultaneously to overcome the trade-off limitations of existing technology. By communicating with separated networks based on the authentication between distributed nodes, the inefficiency of conventional centralized network connection solutions is overcome. Moreover, the security is enhanced through periodic authentication of the distributed nodes and differentiation of the certification levels. As a result of the experiment, the relative efficiency of the proposed scheme (REP) was about 420% or more in all cases.

A Connection Access Mechanism of Distributed Network based on Block Chain

Cross-border payment optimization technology based on block chain has become a hot spot in the industry. The traditional method mainly includes the block feature detection method, the fuzzy access method, the adaptive scheduling method, which perform related feature extraction and quantitative regression analysis on the collected distributed network connection access data, and combine the fuzzy clustering method to optimize the data access design, and realize the group detection and identification of data in the block chain. However, the traditional method has a large computational overhead for distributed network connection access, and the packet detection capability is not good. This paper constructs a statistical sequence model of adaptive connection access data to extract the descriptive statistical features of the distributed network block chain adaptive connection access data similarity. The performance of the strategy retrieval efficiency in the experiment is tested based on the strategy management method. The experiment performs matching query tests on the test sets of different query sizes. The different parameters for error rate and search delay test are set to evaluate the impact of different parameters on retrieval performance. The calculation method of single delay is the total delay or the total number of matches. The optimization effect is mainly measured by the retrieval delay of the strategy in the strategy management contract; the smaller the delay, the higher the execution efficiency, and the better the retrieval optimization effect.

Distributed Destination Search Routing for 5G and beyond Networks

Fifth-generation and beyond networks target multiple distributed network application such as Internet of Things (IoT), connected robotics, and massive Machine Type Communication (mMTC). In the absence of a central management unit, the device need to search and establish a route towards the destination before initializing data transmission. In this paper, we proposes a destination search and routing method for distributed 5G and beyond networks. In the proposed method, the source node makes multiple attempts to search for a route towards the destination by expanding disk-like patterns originating from the source node. The source node increases the search area in each attempt, accommodating more nodes in the search process. As a result, the probability of finding the destination increases, which reduces energy consumption and time delay of routing. We propose three variants of routing for high, medium, and low-density network scenarios and analyze their performance for various network configurations. The results demonstrate that the performance of the proposed solution is better than previously proposed techniques in terms of time latency and reduced energy consumption, making it applicable for 5G and beyond networks.

Parallel Algorithm of Hierarchical Phrase Machine Translation Based on Distributed Network Memory

Machine translation has developed rapidly. But there are some problems in machine translation, such as good reading, unable to reflect the mood and context, and even some language machines can not recognize. In order to improve the quality of translation, this paper uses the SSCI method to improve the quality of translation. It is found that the translation quality of hierarchical phrases is significantly improved after using the parallel algorithm of machine translation, which is about 9% higher than before, and the problem of context free grammar is also solved. The research also found that the use of parallel algorithm can effectively reduce the network memory occupation, the original 10 character content, after using the parallel algorithm, only need to occupy 8 characters, the optimization reaches 20%. This means that the parallel algorithm of hierarchical phrase machine translation based on distributed network memory can play a very important role in machine translation.

Sustainability of cryptocurrency in blockchain technology for business development in African Countries

The aim of the paper is to analyze the sustainability of cryptocurrency in blockchain technology in African countries for securing financial business transactions. Following the subprime crisis that shook the world economy, a new perception of money has emerged. It is a fully digital currency whose transactions are made through a distributed network. This algorithm-encrypted currency, reputed to be tamper-proof, transparent and inclusive, relies on a distributed network called the Blockchain. By comparison with traditional registers in which operations are paginated and successively recorded, transactions in blockchain technology are aggregated within the chain of blocks. It is decentralized since it is replicated on several geographic sites around the world. It enables peer-to-peer transactions, automated in real-time, reliable, secure, without intermediaries and non-repudiable. To ensure maximum security during financial transactions, blockchain miners use cryptography. This distributed system is, therefore, a major technological innovation capable of securing the financial infrastructure and mitigating failures by reducing operational risks. According to our analysis based on the Merkle tree model and blockchain energy consumption, the sustainability of cryptocurrency is a major issue for developing countries. Especially in Africa, its practicality poses a number of constraints.

Handling Trust in a Cloud based Multi Agent System

Cloud computing is an opened and distributed network that guarantees access to a large amount of data and IT infrastructure at several levels (software, hardware...). With the increase demand, handling clients’ needs is getting increasingly challenging. Responding to all requesting clients could lead to security breaches, and since it is the provider’s responsibility to secure not only the offered cloud services but also the data, it is important to ensure clients reliability. Although filtering clients in the cloud is not so common, it is required to assure cloud safety. In this paper, by implementing multi agent systems in the cloud to handle interactions for the providers, trust is introduced at agent level to filtrate the clients asking for services by using Particle Swarm Optimization and acquaintance knowledge to determine malicious and untrustworthy clients. The selection depends on previous knowledge and overall rating of trusted peers. The conducted experiments show that the model outputs relevant results, and even with a small number of peers, the framework is able to converge to the best solution. The model presented in this paper is a part of ongoing work to adapt interactions in the cloud.

Remote sensing based on time variance control in configurable area partitioning

In this paper a sensor data fusion approach for characteristics field monitoring, based on time variance control model, is proposed. Distributed sensing and remote processing are the basic features of the employed architecture. In fact, in order to obtain meaningful information about the temporal and spatial variations, which characterize the field levels of some characteristics (electromagnetic, air pollution, seismic, etc), a distributed network of wireless and mobile smart-sensors has been designed.Starting from the partitioned configuration of a monitored geographic areas, this model allows to take into account the different levels of degradation over time in the sensors' performances associated with the different geographic partitions, progressively increasing the severity of the control. To this end, through the introduction of a reliability curve, a revised traditional control chart for variables is proposed.The proposed approach, further constituting an element of the scientific debate, aims to be a useful operational tool for professionals and managers employed in the environment control.

Social-vocal brain networks in a non-human primate

During social interactions, individuals influence each other to coordinate their actions. Vocal communication is an exceptionally efficient way to exert such influence. Where and how social interactions are dynamically modulated in the brain is unknown. We used functional ultrasound imaging in marmoset monkeys, a highly vocal species, to investigate the dynamics of medial social brain areas in vocal perception, production, and audio-vocal interaction. We found that the activity of a distributed network of subcortical and cortical regions distinguishes calls associated with different social contexts. This same brain network showed different dynamics during externally and internally driven vocalizations. These findings suggest the existence of a social-vocal brain network in medial cortical and subcortical areas that is fundamental in social communication.