Data Messages Research Articles

Detailed Analysis of Chaotic Logistic Map Model and Applications

Chaotic logistic map can be used to generate private key with different dimensions, this can be easily used to secure the process of data cryptography, required to encrypt-decrypt messages, images or audio files. Some of the encrypted-decrypted data (messages images) requires inter values keys, other like audio files require fraction values keys. In this research paper we will perform a detailed study of chaotic logistic map model to give some valuable recommendation of many aspects such as: the suitable range of the growth rate parameter, the suitable range of the initial generation, the sensitivity feature, the required time to generate private keys. It will be show how to generate 1D and 2D private keys with integer values and with fractional values, these key will be generated taking in mined the process of optimizing the generation time and the selected length of key which can optimize the process of cryptography.

Implementation of an E-Procurement System in Volta River Authority

Governments in both developed and developing nations have embraced the idea of using information communication technology to enable them enhance the quality of services offered by public sector institutions, increase access to information and public participation. The result of this is the emergence of e-procurement which has changed the way purchasing is done in the digital age. This paper therefore assesses the implementation of an e-procurement policy and emergent training needs of procurement practitioners - the case in Volta River Authority. The study adopted the descriptive research design and qualitative research approach. The purposive sampling strategy was used to sample 56 respondents from the population of 150 at VRA-NEDCO for the survey. Primary source of data was collected using semi-structured. Finding of the study revealed critical human resource and technical requirements for the implementation of e-procurement at VRA-NEDCO. Technically, quality IT infrastructure, standard data harmonization, adequate data management and messaging strategies were required while professionalism, high internal regards for procurement, adequate and skilled procurement specialists were the opportunities for the implementation of e-procurement in Volta River Authority. Also, VRA-NEDCO provides advanced computer literacy programs (Microsoft office, excel and notepad), advanced effective communication programs to create staff awareness of e-procurement, workshop on the public procurement Act of Ghana, Basic hardware training and Data management and supplier integration skills before the implementation of the Oracle e-procurement system. In examining the major challenges associated with the implementation of e-procurement, the study found the following as challenges VRA faces in the implementation of e-procurement; technology challenges such as data system hacking and cracking, unreliable internet and technology incompatibility and integration of external systems. Some process challenges also include; unwillingness to re-engineer process, challenge of supplier adoption and initial high cost of introducing e-procurement solution. The human resource challenges to e-procurement implementation at VRA include, issues of professionalism and training requirement, availability of e-procurement experts and resistance to change management.

System of Message Exchange and Data Processing of Ecological and Natural Communities

With the development of technological tools, it is increasingly common to meet systems which are using online messaging applications for communication with users. This process occurs with the help of so-called chatbots. Chatbot is a programmable application in which the algorithm of interaction with the user, provided by developers, is implemented. The bot provides information in the form of text or audio messages. This concept of information sharing is very convenient and mobile since the vast majority of online messaging applications are available on different platforms: desktops, smartphones, tablets etc. Accordingly, the user can access the information provided by the chatbot using any device with the necessary system requirements which is available in a certain period of time.

Two-Phase Defect Detection Using Clustering and Classification Methods

Autonomous fault management of network and distributed systems is a challenging research problem and attracts many research activities. Solving this problem heavily depends on expertise knowledge and supporting tools for monitoring and detecting defects automatically. Recent research activities have focused on machine learning techniques that scrutinize system output data for mining abnormal events and detecting defects. This paper proposes a two-phase defect detection for network and distributed systems using log messages clustering and classification. The approach takes advantage of K-means clustering method to obtain abnormal messages and random forest method to detect the relationship of the abnormal messages and the existing defects. Several experiments have evaluated the performance of this approach using the log message data of Hadoop Distributed File System (HDFS) and the bug report data of Bug Tracking System (BTS). Evaluation results have disclosed some remarks with lessons learned.

Probability of Data Leakage and Its Impacts on Confidentiality

A multi-channel communication architecture featuring distributed fragments of data is presented as a method for improving security available in a communication architecture. However, measuring security remains challenging. The Quality of Secure Service (QoSS) model defines a manner by which the probability of data leakage and the probability of data corruption may be used to estimate security properties for a given communication network. These two probabilities reflect two of the three aspects of the IT security triad, specifically confidentiality and integrity. The probability of data leakage is directly related to the probability of confidentiality and may be estimated based on the probabilities of data interception, decryption, and decoding. The number of listeners who have access to the communication channels influences these probabilities, and unique to the QoSS model, the ability to fragment and distribute data messages across multiple channels between sender and receiver. To simulate the behaviors of various communication architectures and the possibility of malicious interference, the probability of data leakage and its constituent metrics require a thorough analysis. Even if a listener is aware that multiple channels exist, each intermediate node (if any) simply appears to have one input and one output. There may be one or more listeners, and they may or may not be working cooperatively. Even if the listener(s) gains access to more than one channel, there is still the challenge of decrypting, decoding, or reassembling the fragmented data. The analysis presented herein will explore the probability of confidentiality from both the authorized user’s and the adversary’s perspective.

A hybrid soft bit flipping decoder algorithm for effective signal transmission and reception

The Euclidean geometry (EG) based low-density parity check (LDPC) codes are enciphered and deciphered in various modes. These algorithms have the back-and-forth between decoding delay, and power usage, device unpredictability resources, and error rate efficacy are all available with these methods. As a result, the goal of this paper is to develop a comprehensive method to describe both soft and burst error bits for optimal data transfer. As a result, for EG-LDPC codes, a hybrid soft bit flipping (HSBF) decoder is suggested, which decreases decoding complications while improving message data transfer. A simulation model is formed using Xilinx synthesis report to study decoding latency, hardware usage, and power usage. A HSBF decoder is used in this paper, which accepts a 64-bit coding sequence and assigns 64 Adjustable nodes to it. It checks all customizable cluster connections and quantifies adjustable node values and actions. As a consequence of the data collected, our simulation model demonstrates that the HSBF technique outperforms soft bit flipping (SBF) algorithms. As a result, the techniques are ideal for usage in intermediate applications and as well as in cyber security processing technologies, medical applications.

ASMA: An Advanced Secure Messaging Application

Background: User generated digital content, typically from mobile devices, can be of a personal nature. There have been several instances in which this personal content, including but not limited to, photographs, videos, messages and personal information has been misused by the recipients. The misuse has ranged from violating privacy through unauthorized sharing to manipulating/modifying the original content and finally forgery and fraud. Objective: To create an Advanced Secure Messaging Application (ASMA) allowing personal digital content to be shared across mobile devices in a secure, controlled and privacy preserving manner. The application allows the user to explicitly specify a micro-policy to control the way digital content sent by the user is consumed, shared or modified by the recipient(s). The users should be able to check the veracity of a shared news item besides controlling group formation and enforcing content sharing guidelines within a group. Methods: A micro-policy based novel mechanism is introduced for exercising fine-grained control over the manner in which digital content generated by users is shared and distributed among their contacts. Fact-checking is supported by cross checking the message content against credible news sources. Results: Measurements of message throughput show a consistent and manageable overhead, due to a per message micropolicy travelling with the message data compared to traditional message sharing applications. The high user-ratings received from users in a pilot test establish acceptance of the app and the need for its advanced features. Moreover, the overheads in implementing additional security features are imperceptible at the user level. Conclusion: ASMA is a highly secure and privacy preserving messaging application as demonstrated by experimental results and the pilot usability study. It offers novel security and content control features which are not available in existing mobile messaging applications.

Secure cloud‐based data storage scheme using postquantum integer lattices‐based signcryption for IoT applications

AbstractThe primary objective of postquantum cryptography (also known as quantum‐resistant cryptography) is to develop the cryptographic systems that need to be robust against both quantum and classical computers, and can also interoperate with the existing communications protocols and networks. In an Internet of Things (IoT) environment, the communicated messages contain sensitive information that are transmitted over an open channel, where message integrity and data privacy become challenging tasks. Although several traditional cryptographic security protocols can be applied for IoT security and data privacy, such as authentication, access control, key agreement, and digital signature, but they are not resilient against quantum attacks. To overcome these issues, in this article, we first present an advanced and efficient construction of postquantum lattice‐based signcryption scheme, and then apply the constructed lattice‐based signcryption in IoT applications, where data sensed by the deployed IoT smart devices is securely stored at the cloud, via the gateway nodes (aggregators). The data stored at the cloud servers cannot be even modified by them due to the involved signatures generated by the aggregators. The formal security analysis shows the robustness of our designed lattice‐based signcryption scheme. Other detailed information security analysis and a performance analysis with the traditional number‐theoretical based public key cryptosystems show the efficacy, and significantly better security and functionality features of the proposed scheme under the lattice‐based postquantum context.

Safety Monitoring System of CAVs Considering the Trade-Off between Sampling Interval and Data Reliability.

The safety of urban transportation systems is considered a public health issue worldwide, and many researchers have contributed to improving it. Connected automated vehicles (CAVs) and cooperative intelligent transportation systems (C-ITSs) are considered solutions to ensure the safety of urban transportation systems using various sensors and communication devices. However, realizing a data flow framework, including data collection, data transmission, and data processing, in South Korea is challenging, as CAVs produce a massive amount of data every minute, which cannot be transmitted via existing communication networks. Thus, raw data must be sampled and transmitted to the server for further processing. The data acquired must be highly accurate to ensure the safety of the different agents in C-ITS. On the other hand, raw data must be reduced through sampling to ensure transmission using existing communication systems. Thus, in this study, C-ITS architecture and data flow are designed, including messages and protocols for the safety monitoring system of CAVs, and the optimal sampling interval determined for data transmission while considering the trade-off between communication efficiency and accuracy of the safety performance indicators. Three safety performance indicators were introduced: severe deceleration, lateral position variance, and inverse time to collision. A field test was conducted to collect data from various sensors installed in the CAV, determining the optimal sampling interval. In addition, the Kolmogorov–Smirnov test was conducted to ensure statistical consistency between the sampled and raw datasets. The effects of the sampling interval on message delay, data accuracy, and communication efficiency in terms of the data compression ratio were analyzed. Consequently, a sampling interval of 0.2 s is recommended for optimizing the system’s overall efficiency.

A novel intrusion detection model for the CAN bus packet of in-vehicle network based on attention mechanism and autoencoder

The attacks on in-vehicle Controller Area Network (CAN) bus messages severely disrupt normal communication between vehicles. Therefore, researches on intrusion detection models for CAN have positive business value for vehicle security, and the intrusion detection technology for CAN bus messages can effectively protect the in-vehicle network from unlawful attacks. Previous machine learning-based models are unable to effectively identify intrusive abnormal messages due to their inherent shortcomings. Hence, to address the shortcomings of the previous machine learning-based intrusion detection technique, we propose a novel method using Attention Mechanism and AutoEncoder for Intrusion Detection (AMAEID). The AMAEID model first converts the raw hexadecimal message data into binary format to obtain better input. Then the AMAEID model encodes and decodes the binary message data using a multi-layer denoising autoencoder model to obtain a hidden feature representation that can represent the potential features behind the message data at a deeper level. Finally, the AMAEID model uses the attention mechanism and the fully connected layer network to infer whether the message is an abnormal message or not. The experimental results with three evaluation metrics on a real in-vehicle CAN bus message dataset outperform some traditional machine learning algorithms, demonstrating the effectiveness of the AMAEID model.

CAN message unpack and pack based on simulink automatic code generation technology

Aiming at the problem of a large amount of CAN communication message data of automobile controllers and low efficiency of traditional software development, this paper proposes a method of CAN message unpack and pack based on Simulink automatic code generation technology. S-Function is used to design CAN message sending and receiving model that can import DBC files, and use RTW (real-time workshop) to realize Simulink model to automatically generate C code. This method effectively solves the unpack and pack of CAN messages, simplifies the code development process, and improves the efficiency of software development, especially when there are DBC files, which simplifies the work of sending and receiving and testing.

Development of main functional modules for MVB and its application in rail transit

Abstract In this work, multi-function vehicle bus (MVB) controller-based Field Programmable Gate Array (FPGA) and MVB manager based on the real-time multitasking operating system were explored and developed. The function of the MVB controller data link layer was realised by using FPGA. The embedded real-time multitasking operating system uCOS-II was applied to the development of MVB manager’s processing data, device state management, message data and bus management function. The network consistency test was performed to validate data communication of MVB link layer control protocol and the management function of MVB manager; the equipment was shown to be compatible with each other and met the requirements of IEC61375-1.

Zoro: A robotic middleware combining high performance and high reliability

With the significant advances of AI technology, robotic systems have achieved remarkable development and profound effects. The robotic middleware plays a critical role in robotic systems to provide message definition, data transmission, and service discovery functions. As the modern robotic systems are usually operated in safety critical environments, such as various autonomous driving scenarios, it requires the design of robotic middleware to combine both high performance and high reliability in order to achieve system reliability and product safety. However, conventional robotic middleware used in the majority of robotic systems is based on an inefficient socket communication mechanism and relies on a hasty service discovery design, which leads to system instability and high resource usage. In this work, we propose a sophisticated robotic middleware, Zoro, to fulfill both high performance and high reliability. For communication, we employ shared memory for performance improvement and propose a socket-based communication control algorithm to improve reliability during data transmission. Also, a hierarchical memory protection mechanism is proposed to address safety problems caused by shared memory. Furthermore, we design a light-weight service discovery, to achieve high performance and a weak centralized mechanism for high reliability. Experiments show the communication latency of Zoro significantly outperforms state-of-the-art robotic middleware such as ROS2 and CyberRT by up to 41%. In terms of service discovery, Zoro reduces CPU usage by up to 44% compared to ROS. Zoro achieves reliability with respect to communication and service discovery.

Ethical Views on Sharing Digital Data for Public Health Surveillance: Analysis of Survey Data Among Patients.

Digital data, including social media, wearable device data, electronic health records, and internet search data, are increasingly being integrated into public health research and policy. Because of the current issues around public distrust of science and other ethical issues in public health research, it is essential that researchers conduct ongoing studies assessing people's perceptions around and willingness to share digital data. This study aims to examine participants' social media use and comfort sharing their data with health researchers. One hundred and sixty-one participants with medical conditions were recruited through social media paid advertisements and referral from a website, and invited to complete surveys on social media use and ethical perspectives on data sharing. Eligibility criteria were adults 18 years old or older, living in the US, self-reported having been diagnosed by a physician with a medical condition, belonging to at least one social media platform, using social media at least twice a week, and owning a smartphone. Study participants were mostly female, White, and with a mean age of 36.31 years. More than one third of participants reported being very comfortable sharing electronic health data and social media data for personalized healthcare and to help others. Findings suggest that participants are very uncomfortable sharing their location and text message data with researchers, with primary concerns centered around loss of privacy, disclosing private information, and that friends, family, and others may find out that they shared text messages with researchers. We discuss the implications of this research before and after the COVID-19 pandemic, along with its potential implications for future collection of digital data for public health.

Impact of Artificial Intelligence News Source Credibility Identification System on Effectiveness of Media Literacy Education

During presidential elections and showbusiness or social news events, society has begun to address the risk of fake news. The Sustainable Development Goals 4 for Global Education Agenda aims to “ensure inclusive and equitable quality education and promote lifelong learning opportunities for all” by 2030. As a result, various nations have deemed media literacy education a required competence in order for audiences to maintain a discerning attitude and to verify messages rather than automatically believing them. This study developed a highly efficient message discrimination method using new technology using artificial intelligence and big data information processing containing general news and content farm message data on approximately 938,000 articles. Deep neural network technology was used to create a news source credibility identification system. Media literacy was the core of the experimental course design. Two groups of participants used different methods to perform message discrimination. The results revealed that the system significantly expanded the participants’ knowledge of media literacy. The system positively affected the participants’ attitude, confidence, and motivation towards media literacy learning. This research provides a method of identifying fake news in order to ensure that audiences are not affected by fake messages, thereby helping to maintain a democratic society.

MDICA: Maintenance of data integrity in column-oriented database applications

Current information technologies generate large amounts of data for management or further analysis, storing it in NoSQL databases which provide horizontal scaling and high performance, supporting many read/write operations per second. NoSQL column-oriented databases, such as Cassandra and HBase, are usually modelled following a query-driven approach, resulting in denormalized databases where the same data can be repeated in several tables. Therefore, maintaining data integrity relies on client applications to ensure that, for data changes that occur, the affected tables will be appropriately updated. We devise a method called MDICA that, given a data insertion at a conceptual level, determines the required actions to maintain database integrity in column-oriented databases. This method is implemented for Cassandra database applications. MDICA is based on the definition of (1) rules to determine the tables that will be impacted by the insertion, (2) procedures to generate the statements to ensure data integrity and (3) messages to warn the user about errors or potential problems. This method helps developers in two ways: generating the statements needed to maintain data integrity and producing messages to avoid problems such as loss of information, redundant repeated data or gaps of information in tables.

Reversible data hiding in encrypted images without additional information transmission

Reversible data hiding in encrypted images (RDHEI) is an essential branch of image reversible data hiding. Over the past decade, many significant achievements have been made. However, for most RDHEI researches, the cloud service user (CSU) demands either an encryption method specified by the cloud service provider (CSP) or prior knowledge about the original image to indicate the preprocessing operation. This characteristic may lead to some security issues like information leakage that may limit the use of this type of technology. To solve this problem, we propose a simple but effective RDHEI method that separates the CSU and CSP. The owner CSU exclusively sends the standard stream cipher image to the CSP, while the CSP can embed message data into the encrypted image through a simple MSB replacement without knowing the encrypted method or prior knowledge about the original image. The embedded message data can be extracted; meanwhile, the image can be approximately recovered by another authentic CSU. Since the proposed fundamental method is not error-free in most circumstances, we provide an alternative option to achieve reversibility by transmitting a perfect recovery key from the owner CSU to any authentic CSU. The experimental results demonstrate the efficacy of the proposed method.

Communication MWSN Data Transmission Mechanism Based on a Wireless Sensor Network

A wireless sensor network (WSN) is considered to have a wide application prospect in a smart distribution network due to its unique low power consumption, fast self-organization, and superior coordination. In order to study the communication MWSN data transmission mechanism based on a wireless sensor network, the difficulty of applying a wireless sensor network to an intelligent distribution network communication is to meet the real-time and reliability requirements of power industry distribution network data communication specifications under the limited network resources. Firstly, the transmission probability is calculated by considering the path loss, the speed of the node, the direction of the node, and the residual energy of the node. In addition, the transmission and replacement order of the message is determined according to the survival time of the data message. Simulation experiments are carried out on MATLAB. The result shows the proposed routing algorithm, compared with the DT algorithm, flooding algorithm, and FAD algorithm, the delivery rate of data messages is increased by at least 6%, and the number of copies is reduced by at least 10% compared with the flooding algorithm and the FAD algorithm. On the basis of satisfying the mobility of sink nodes, the algorithm proposed in this paper can effectively save network energy consumption and prolong the network lifetime.

THE ANALYSIS OF THE USES OF CODE SWITCHING AND CODE MIXING IN SOCIAL MEDIA AMONG FACEBOOKERS

The present study was aimed at identifying the types and function of code-mixing and switching used by Facebookers. This study was designed as a qualitative study. There were 50 Facebook accounts were observed in this study. The results showed that alternation code mixing was mostly used by Facebookers. A mix language between English and Indonesian was identified in their caption of Facebook wall. The functions of code-switching and code-mixing are 50 data, some of the data, namely 26 data, have code-switching with from 26 data code-switching there are 18 personalization and objectivization and 7 facilities of expression and 1 message qualification. And 50 data code-mixing with details of 31 data personalization objectivization and 12 data facility of expression and 5 data message qualification and 2 data repetition.

Secure data communication for wireless mobile nodes in intelligent transportation systems

Intelligent Transportation Systems (ITS) is one of the demanding area of research based on fast communication services. However, these networks are suffered with some congestion, routing and security issues especially in urban areas and cause of delay and computational complexities issues and lead to late messages delivery or data congestion. The Unmanned Ariel Vehicles (UAV) or drones and Internet of Vehicles (IoV) are facilitating ITS networks by collecting the data from road nodes and forward to the Road Side Units (RSU) or to the backbone architecture for decision making. This strategy will open new threats and challenges in the form of security, user privacy and other malicious activities. The traditional security and authentication mechanisms have not been feasible due to their complex and heavy computational processing. This study presents a novel Secure Data Communication in Drone Enables Internet of Vehicle (SDCD-IoV), solution for authentication among vehicle nodes, RSU and trust authority database in ITS networks. The proposed system is based on three main phases including initialization, registration, and authentication. The proposed solution provides the authentication mechanism to fulfill the security requirements to intelligent mobile nodes and provides node anonymity where vehicle nodes and drones are protected the identity during data transmission. The second important contribution of proposed solution is unlinkability where the network prevents them from adversary. Traceability and mutual authentication are also considered where nodes check malicious action and real identity of nodes recovery and verifying the messages from other entities. The proposed solution is tested in terms of time cost, computational cost, overhead in the presence of different number of nodes and velocities. The proposed solution achieved the high performance as compared to existing solutions.