Unreliable Networks Research Articles

Event-Triggered Data-Driven Security Formation Control for Quadrotors Under Denial-of-Service Attacks and Communication Faults.

In this article, the security formation control problem is investigated for underactuated quadrotors involving nonlinear coupled dynamics, subject to denial-of-service (DoS) attacks and uncertain communication faults. A security formation control method is proposed, including a distributed resilient observer and a hierarchical data-driven controller. The observer with an adaptive event-triggered mechanism is developed to restrain the influence of DoS and communication faults on interaction information among quadrotors, and Zeno behavior of all observers can be avoided. The optimal control laws are learned iteratively based on observation data and system data by utilizing reinforcement learning without knowledge of system dynamics. The stability of the constructed closed-loop control system is proven, and sufficient conditions are established for the unreliable network. Simulation results demonstrate the advantages of the proposed security control method.

THE EFFECT OF INTELLECTUAL CAPITAL ON OPERATIONAL PERFORMANCE AMONG DEPOSIT MONEY BANKS: MEDIATED BY INNOVATION

The banking sector, like many other service industries, is frequently characterized by a high level of rivalry, driving enterprises to come up with innovative ideas and strategies to improve their chances for success. Over the years, Nigerian Deposit Money Banks' operational efficiency has been bad in terms of per customer service timing, time spent at the bank, and an unreliable network, among other things. This tendency might be linked to a lack of investment in the bank's intangible assets, often known as intellectual capital. This study examined the mediating effect of innovation in the relationship between intellectual capital (IC) and operational performance (OP) of deposit money banks (DMBs) in the Nigerian Banking sector. The study was built on the idea of Resource Base View Theory (RBV) and Human Capital Theory. Three dimensions of intellectual capital namely: Human Capital (HC), Structural Capital (SC) and Relational Capital (RC) were used. Cross-sectional survey design was adopted in this study and structured questionnaire was used to collect data from the operational employees of all the 13 DMBs operating in Jalingo, Taraba state, Nigeria. 399 questionnaires were distributed out of which 357 usable questionnaires were retrieved. The data was analyzed using PLS-SEM. Results of the analysis showed that all the components of IC (HC, SC and RC) have significant positive effect on operational performance of DMBs in Jalingo with human capital (HC) having the highest influence. In addition, results of the analysis also show that innovation mediates the relationship between intellectual capital and operational performance of DMBs. The study concludes that innovation (INV) plays a mediating role in the relationship between intellectual capital and operational performance of DMBs.

A novel chaotic map-based encryption scheme for surveillance videos

The widespread use of surveillance cameras has initiated privacy concerns among individuals being captured by these devices. Due to the limited internal storage capacity, these cameras often transmit recorded videos over unreliable networks. This situation creates opportunities for attackers to exploit vulnerabilities, such as launching Man-in-the-Middle attacks, replayed scene attacks, and tampering with the video content. Considering these risks, this paper introduces a new chaotic map-based encryption scheme for surveillance videos. The work proposes a novel chaotic map using cascading and coupling operations on functions and is referred to as a Cascaded Coupled Logistic-Sine-Cosine (CCLSC) map. The chaotic performance of the novel CCLSC map has been evaluated using the Lyapunov exponent and the Bifurcation diagram. The scheme to encrypt surveillance videos is designed using the novel CCLSC map and our earlier designed Sine-Tangent-Sine (STS) chaotic map. The process involves extracting individual frames from the video and subsequently encrypts each frame as a digital image. The encryption of each frame involves three steps. The first step generates a Dynamic Chaotic Matrix (DCM) using CCLSC and STS map. The second phase is pixel scrambling using DCM and the final step changes the pixel values using DCM. Our results validate the security, robustness, and effectiveness of the proposed method.

Fast and Reliable Sending of Generic Object Oriented Substation Event Frames between Remote Locations over Loss-Prone Networks.

WAMPAC (Wide Area Monitoring Protection and Control) applications are becoming crucial for granting a stable operation of the electricity transmission grid. These systems use a set of sensors distributed between different electrical substations to gather real-time measurements from the field. These sensors are called Phasor Measurement Units (PMUs). Using the gathered data, different monitoring, protection, and control algorithms are run in a Phasor Data Concentrator (PDC) located in a central location. These algorithms close the loop via the generation of remedial commands, which are sent back to the field level with stringent delay, security, and reliability requirements. GOOSE (Generic Object Oriented Substation Events) protocol, defined by IEC 61850 (IEC stands for International Electrotechnical Commission), is used for that aim and also considers the option of sending these commands over IP networks (this option is called Routed-GOOSE). The present article proposes two alternatives for the tunneling of GOOSE frames over IP. Both options allow the decoupling of the transmission and the security aspects, thus increasing flexibility and allowing for easier deployment. The first option, called VX-GOOSE, is a combination of standard protocols, allowing the sending of these frames over UDP/IP tunnels. The tests that have been carried out demonstrate that, under certain network conditions, the transmission of GOOSE frames over UDP may fail, and in some extreme cases, even a whole burst of GOOSEs could be lost. This may have very bad consequences for a distributed electrical system. It should be noted that this limitation affects both VX-GOOSE and Routed-GOOSE. To overcome these limitations, the second option, called Simplemux blast mode, includes a novel mechanism that provides delivery guarantees and a reduced delay, with the counterpart of a certain degree of redundancy. As shown in the experiments, the incurred delays can be significantly reduced when remote locations are connected via unreliable networks, whereas the bandwidth increase caused by redundancy can be kept at reasonable levels. Finally, it should be remarked that although GOOSE is a relevant example use case, this approach can be applied in other fields where flows require very low delay and delivery guarantees.

Predicting Drug-Protein Interactions by Self-Adaptively Adjusting the Topological Structure of the Heterogeneous Network.

Many powerful computational methods based on graph neural networks (GNNs) have been proposed to predict drug-protein interactions (DPIs). It can effectively reduce laboratory workload and the cost of drug discovery and drug repurposing. However, many clinical functions of drugs and proteins are unknown due to their unobserved indications. Therefore, it is difficult to establish a reliable drug-protein heterogeneous network that can describe the relationships between drugs and proteins based on the available information. To solve this problem, we propose a DPI prediction method that can self-adaptively adjust the topological structure of the heterogeneous networks, and name it SATS. SATS establishes a representation learning module based on graph attention network to carry out the drug-protein heterogeneous network. It can self-adaptively learn the relationships among the nodes based on their attributes and adjust the topological structure of the network according to the training loss of the model. Finally, SATS predicts the interaction propensity between drugs and proteins based on their embeddings. The experimental results show that SATS can effectively improve the topological structure of the network. The performance of SATS outperforms several state-of-the-art DPI prediction methods under various evaluation metrics. These prove that SATS is useful to deal with incomplete data and unreliable networks. The case studies on the top section of the prediction results further demonstrate that SATS is powerful for discovering novel DPIs.

A new method for multi-state flow networks reliability estimation based on a Monte Carlo simulation and intersections of sets

The problem of the assessment of a multi-state flow network reliability can be very time-consuming, especially for large networks. Simulation approaches alleviate this problem by generating random capacity vectors and comparing them with d-MPs or d-MCs, for estimation of network reliability. In this study, a new approach to compare randomly generated vectors with a given list of vectors is developed. The presented method is based on intersections of some sets of indices of a given list of vectors. The computational complexity of the presented approach is examined and compared with existing approaches. Two comprehensive examples are provided to estimate the network reliability and compare the effectiveness of the presented method with existing ones. Numerical experiments show that the presented method is usually more efficient than existing ones especially if the network unreliability is estimated using d-MCs.

Network management schemes for IoT environment towards 6G: A comprehensive review

Usage of smart devices, expansion of Internet of Things (IoT) network, and its adoption in variety of applications grows exponentially day-by-day. It leads to various issues such as network privacy, security management, unreliable network management (NM) scheme, resource utilization, energy utilization, decentralization, transparency, and data interoperability. Development of the NM platform/framework for secure data dissemination in IoT networks is tedious due to heterogeneity and imbalanced IoT protocol stack. Recently, traditional network scheduling methods, Software Defined Networks (SDN), Network Function Virtualization (NFV), and hybrid approaches are widely used for managing the IoT network. But, most of these approaches are controlled by a centralized server, which may not be appropriate due to the heterogeneity of the IoT devices. Motivated from the aforementioned discussion, In this paper, we present a systematic survey on various NM schemes used to secure data dissemination for the IoT environment. We present a detailed taxonomy of all the existing NM schemes for IoT networks. Pros and cons of the traditional NM methods applicable for IoT environment are discussed in detail. The paper discusses a state-of-art survey on integrating blockchain (BC) technology in the existing IoT NM techniques. In this paper, our prime focus is to understand the potential of BC for enabling secured IoT management. Finally, a case study on BC implication for Unmanned Aerial Vehicle (UAV) network using 6G is also discussed along with future directions.

Security sliding mode control for networked control system under multi‐channel Markovian hybrid cyber‐attacks

AbstractThis work investigates the security sliding mode control problem of uncertain discrete‐time systems under an unreliable network, in which denial of service and deception attacks may randomly occur in each sensor‐to‐controller channel. Two 2‐valued variables are introduced to model the available state signals for the controller side under random attacks. Meanwhile, by means of mapping rule, independent Markov chains are reformulated into a new Markov chain. And then, a hybrid‐attack‐probability dependent sliding function is constructed, and a desirable sliding mode controller is designed by adopting compensation strategy and available state signals. Moreover, sufficient conditions are derived, under which the closed‐loop system achieve stochastic stability along a quasi sliding mode. Moreover, a cone complementarity linearization (CCL)‐based iterative solving algorithm is proposed. Finally, simulation results are provided to verify the proposed security control approach.

Event‐triggered control of power buffers in DC microgrids over an unreliable network

AbstractPower buffers can help improve the inertia in DC microgrids and supply the additional power demand during short load transients. This article investigates distributed event‐triggered control of power buffers over an unreliable network, subject to packet losses and transmission delays. For each power buffer, a distributed event‐triggered control law regulates the input impedance while altering its stored energy. Moreover, a dynamic event‐triggered communication mechanism determines the time sequence of control updates and data transmissions among power buffers. An appealing feature of this mechanism is a designable positive minimum inter‐event time despite packet losses and transmission delays. The closed‐loop system is shown to be exponentially stable. Controller/hardware‐in‐the‐loop studies validate the theoretical findings.

A Huffman code LSB based image steganography technique using multi-level encryption and achromatic component of an image

In the recent couple of years, due to the accelerated popularity of the internet, various organizations such as government offices, military, private companies, etc. use different transferring methods for exchanging their information. The Internet has various benefits and some demerits, but the primary bad mark is security of information transmission over an unreliable network, and widely uses of images. So, Steganography is the state of the art of implanting a message in the cover objects, that nobody can suspect or identify it. Therefore, in the field of cover steganography, it is very critical to track down a mechanism for concealing data by utilizing different blends of compression strategies. Amplifying the payload limit, and robustness, and working on the visual quality are the vital factors of this research to make a reliable mechanism. Different cover steganography research strategies have been recommended, and each adores its benefits and impediments but there is a need to foster some better cover steganography implements to accomplish dependability between the essential model of cover steganography. To handle these issues, in this paper we proposed a method in view of Huffman code, Least Significant Bits (LSB) based cover steganography utilizing Multi-Level Encryption (MLE) and colorless part (HC-LSBIS-MLE-AC) of the picture. It also used different substitution and flicking concepts, MLE, Magic matrix, and achromatic concepts for proving the proficiency, and significance of the method. The algorithm was also statistically investigated based on some Statistical Assessment Metrics (SAM) such as Mean Square Error (MSE), Peak Signal Noise Ratio (PSNR), Normalized Cross Correlation (NCC), Structural Similarity Index Metric (SSIM), etc. and different perspectives. The observational outcomes show the likelihood of the proposed algorithm and the capacity to give unwavering quality between security, payload, perception, computation, and temper protection.

Schedule-based transit assignment with online bus arrival information

Most public transportation services deviate from their published schedule. To cope with the delay caused by the unreliable service, passengers use online information about the bus arrival time which affects their route choice behavior. Current schedule-based transit assignment models fail to capture the passengers’ adaptive response to unreliable service, resulting in an inaccurate estimation of passenger wait time and passenger loads on various transit routes. The current study proposes schedule-based transit assignment models that incorporate online bus arrival information when modeling the passenger route choice in a stochastic and time-dependent transit network. The authors propose that passengers employ strategies when traveling between different origin–destination pairs not only due to the limited capacity of vehicles but also to cope with the transit delay. The passenger routing problem is modeled as a Markov Decision Process, and efficient algorithms are developed to solve this problem. Depending on the vehicle capacity, two types of assignment models are presented, namely, uncapacitated and capacitated assignments. When penalties for arriving at the destination outside the desired arrival time window are not applied, the uncapacitated assignment problem is formulated as a linear program. On the other hand, the capacitated assignment is formulated as a variational inequality problem for which an efficient Method of Successive Averages-based heuristic solution algorithm is proposed. Computational experiments are presented for a small and a large schedule-based transit network. The results show that denied boarding in an unreliable network leads to higher expected costs to passengers compared to the reliable and uncongested network. Furthermore, the analysis shows that the strategies evaluated with reliable schedule assumption lead to unreliable paths in the network and produces more transferring flow than should happen in practice. The application of our method to a subnetwork of the Twin Cities transit network with artificial demand reveals that passengers traveling from a residential area to the University of Minnesota campus may prefer taking a path with transfer in the event of highly unreliable transit service on the direct routes.

Accessibility and utilization of information resources in the post COVID-19 era

University libraries play a pivotal role in fostering teaching, research, and innovation by offering essential information resources. However, patrons often encounter challenges in using these resources. The research aimed to examine the factors influencing the utilization of information resources in university libraries at Kenyatta University Meru University of Science and Technology and post-COVID-19. The objectives were to: determine the skills needed by librarians in supporting utilization of information, analyse the innovative methodologies used to facilitate access to library resources/services, examine the challenges faced by librarians and patrons and determine the importance of Information Communication Technology (ICT) in improving information resources usability and consumption. The study adopted a descriptive survey research design with quantitative research methods. The study was conducted at Kenyatta University and Meru University of Science and Technology libraries. Simple random and purposeful sampling techniques were used to distribute questionnaires to patrons and librarians, respectively. Data was collected from 20 librarians and 309 patrons, out of whom, 26 librarians and 357 patrons were sampled. The questionnaires underwent expert review to ensure their validity and reliability. The study found that 81% of librarians prefer online search resources, while 41% prefer physical textbooks. 16.5% of patrons preferred e-books and e-journals, with inadequate computers (32%) and unreliable networks (25.7%) as challenges affecting access and utilization of resources. The librarians identified lack of cooperation, inadequate digital library skills, understaffing, and poor network as major obstacles to facilitating access and utilization of library resources. The study recommends that university management should enhance librarian capacity building, training, and reengineer ICT infrastructure to enhance access and utilization of resources in the post-COVID-19 era. The study's findings will aid librarians in redesigning library functions to enhance the efficacy of library services in meeting user information needs.

Ghana’s blockchain scene on WhatsApp

Social media sites with global reach like Twitter and WhatsApp are playing a paramount role in the communication, socializing, and business practices of Ghana’s blockchain community. Specifically, WhatsApp has become the platform powering the principal instantiation of blockchain in Ghana, which is trading and investing in cryptocurrencies. Considering the country’s high internet fees and sometimes unreliable network access, WhatsApp is a particularly endearing platform to facilitate the blockchain scene due to the low internet data usage that it requires. Drawing on empirical research data from 33 semi-structured interviews with blockchain enthusiasts in Ghana, this paper analyzes the particularities of blockchain’s adoption and spread in its primarily virtual scene. Key to this examination is the consideration of the affordances and constraints of WhatsApp as the primary spatial frame driving and shaping blockchain’s adoption and use in Ghana. As coagents with the digital sphere they transact and interact on, members of the blockchain community are collectively and individually perpetuating processes of knowledge creation and communal exchanges interspersed with values of competitive innovating. Keywords: Ghana, blockchain scene, WhatsApp, cryptocurrency trading and investment

Fuzzy-Resilient Distributed Optimal Coordination for Nonlinear Multiagent Systems Under Command Attacks

In this paper, we consider the problem of resilient distributed optimal coordination for uncertain nonlinear multi-agent systems, where each agent is remotely dominated by an associated instruction generator via an unreliable network channel which may be distorted by false data injection (FDI) attacks. To avoid evaluating the quality of decision variable or computing its high-order derivatives when applying the backstepping method, which is difficult in a distributed way, a new two-layer integrated design protocol with fuzzy-approximation-based adaptive dynamics compensation mechanism is designed. Through the local online estimation of the optimal solution and design of adaptive feedback gain, the fuzzy adaptive mechanism realizes the mutual compensation of cyber dynamics and physical dynamics. Resultantly, all the agents are shown to achieve the optimal consensus regardless of the FDI attacks and nonlinear uncertainties.

Sequential Fusion Filter for State Estimation of Nonlinear Multi-Sensor Systems with Cross-Correlated Noise and Packet Dropout Compensation

This paper is concerned with the problem of state estimation for nonlinear multi-sensor systems with cross-correlated noise and packet loss compensation. In this case, the cross-correlated noise is modeled by the synchronous correlation of the observation noise of each sensor, and the observation noise of each sensor is correlated with the process noise at the previous moment. Meanwhile, in the process of state estimation, since the measurement data may be transmitted in an unreliable network, data packet dropout will inevitably occur, leading to a reduction in estimation accuracy. To address this undesirable situation, this paper proposes a state estimation method for nonlinear multi-sensor systems with cross-correlated noise and packet dropout compensation based on a sequential fusion framework. Firstly, a prediction compensation mechanism and a strategy based on observation noise estimation are used to update the measurement data while avoiding the noise decorrelation step. Secondly, a design step for a sequential fusion state estimation filter is derived based on an innovation analysis method. Then, a numerical implementation of the sequential fusion state estimator is given based on the third-degree spherical-radial cubature rule. Finally, the univariate nonstationary growth model (UNGM) is combined with simulation to verify the effectiveness and feasibility of the proposed algorithm.

Improved End-to-end service assurance and mathematical modeling of message queuing telemetry transport protocol based massively deployed fully functional devices in smart cities

QoS is an arguable feature of Message Queuing Telemetry Transport Protocol (MQTT) that is employed under constrained environment for communication over an unreliable network in smart cities. It gives extra control to the client for matching its needs according to the application but with confiscated network performance. For a reliable end-to-end service assurance, guaranteed QoS and controlled scalability, MQTT based IoT must be examined for various network parameters. In this work, an improved TCP based transparent MQTT network is proposed for massively deployed connected devices in smart cities. The mathematical modeling is carried out by analyzing end-to-end quality assurance. Network latency, content delivery rate, number of subscribe/publish requests and services offered by the MQTT broker for various topic IDs are then verified on physical network. These parameters are examined over a transparent gateway-based network for verifying the agreement of devised probability based mathematical model with the actual content delivery, service rate and request hold time at virtual machine based MQTT broker, local network broker and remote server respectively. The Improved MQTT model surpasses Apollo, RabbitMQ and Mosquitto server by evidencing the message queueing delay of 3.5 ms for QoS-0 and 3.6 ms for QoS-1 service IoT.

Fuzzy logic based nodes distributed clustering for energy efficient fault tolerance in IoT-enabled WSN

The Internet of Things (IoT) enabled wireless sensor network (WSN) is now widely employed in various sectors like smart city and vehicle transportation for their expanded capabilities such as data storage, access, and monitoring. The use of smart sensors that continuously collect data from the smart environment makes these possible. Furthermore, these facilitate the easy access of stored data over a secure IoT-gateway for mobile users. This device mobility that allows shifting to multiple locations, makes it challenging to route data across many access points. In this regard, it induces packet loss and improper node selection, which could result in connection failure and network unreliability. This study proposes a new data routing protocol called as Fuzzy Logic Nodes Distributed Clustering for Energy-Efficient Fault Tolerance (F-NDC-EEFT). It can be deployed on any network platform, including mobile and non-mobile nodes. It considers performance metrics such as delivery rate, withstand node aliveness, communication delay, and energy efficiency to find an optimized path for the better performance of IoT enabled WSNs. The clustering approach is applied to the instant data load, which divides it into the distinct node groups. When proposed algorithm is tested alongside existing routing protocols for performance, it is found to save energy, minimize the number of connection failures, boost the throughput, and increase the network’s lifetime.

New results on [formula omitted] control for interval type-2 fuzzy singularly perturbed systems with fading channel: The weighted try-once-discard protocol case

This article deals with the interval type-2 (IT2) fuzzy model-based H∞ control problem for networked singularly perturbed systems (SPSs) under fading channel. To prevent data collision, a weighted try-once-discard (WTOD) communication scheme is adopted to adjust the communication sequence of sensor nodes. Based on this transmission strategy, only one sensor with more considerable difference is allowed to be transmitted at each time instant. On the other hand, a time-varying stochastic process model is introduced to describe the behavior of the fading channels in unreliable networks. Based on fading state signal and known bounds, the imperfectly matched membership functions (MFs) are reconstructed in the controller. Accordingly, under the effect of fading channels and WTOD protocol, a new IT2 fuzzy controller is constructed for the networked IT2 fuzzy SPSs. Meanwhile, by constructing a singular perturbation parameter (SPP) dependent Lyapunov function, sufficient conditions are established to guarantee the mean square stability of networked IT2 fuzzy SPSs, and the numerical stiffness issue is avoided. Finally, the practicability of the proposed methods is proved through a tunnel diode circuit simulation.

Multi-AUG three-dimensional path planning and secure cooperative path following under DoS attacks

This article is concerned with the design of a three-dimensional path planning and secure event-triggered cooperative path following for multiple disk-type autonomous underwater gliders (AUGs) in the presence of underwater obstacles and denial-of service (DoS) attacks. A three-dimensional collision-free path planning method is firstly proposed by using a quantum-behaved adaptive particle swarm optimization method in the global path planning layer and an artificial potential field method in the local path planning layer. Secondly, a path variable update law is devised based on a three-dimensional line-of-sight guidance mechanism, which can achieve the cooperative control for networked AUGs, in addition, AUGs can stop at the target points automatically. Finally, an event-triggered mechanism is presented to achieve secure cooperative control for AUGs under the unreliable network environment in the presence of DoS attacks. The stability is validated based on the input-to-state stability theory. Simulation results and numerical analysis demonstrate the effectiveness of the proposed integrated three-dimensional collision-free path planning and secure event-triggered cooperative path following method.

Realizing credible remote agricultural auditing with trusted video technology

Abstract The conventional approaches of auditing agricultural commodities from the production and transportation level to the retailers and consumers often get obstructed by the lack of human resources, delayed response, and high frequency of location updates—resulting in poor quality and safety compliance. Its digital transformation, known as remote auditing, could address these limitations to a greater extent; however, it is still subject to diverse cyberattacks, including tampering with the video streams provided for verification. Since a detailed and concurrent forensic examination of videos during remote auditing significantly increases the computational burden on the network and infrastructure, alternative or complementary solutions should be developed. This paper outlines the technical feasibility of applying digital signatures over live video streams as a way to authenticate the source during remote auditing and thus contributes to limiting the scope of potential cyber threats. It proposes design options for realizing the authentication process with trusted computing technologies at different phases, from signing the videos to transmitting them through unreliable networks. A reference prototype is also developed based on the proposed end-to-end design to quantify the performance of trusted remote agricultural auditing in terms of the frame signing time, attack resistance, and resource overhead.