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One of the key challenges in computer networks is network security. For securing the network, various solutions have been proposed, including network security protocols and firewalls. In the case of so-called packet-filtering firewalls, policy rules are implemented to monitor changes to the network and preserve the required security level. Due to the dramatic increase of devices, however, and herewith the rapid increase of the size of the policy rules, firewall policy anomalies occur more frequently. This requires careful implementation of the policy rules to ensure cost-efficient solutions for anomaly detection to support network security. In this study, we present an anomaly detection framework for detecting intrafirewall policy anomaly rules. The framework supports the simulation of packets through the firewall ruleset for validating and enhancing the security level of the network. The framework is validated using four different types of firewall policy anomalies. Experimental results demonstrate that the framework is effective and efficient in detecting firewall policy anomalies. [ABSTRACT FROM AUTHOR]

Filtered Smith predictors are well established for controlling linear plants with constant time delays. Apart from this classical application scenario, they are also employed within networked control loops, where the measurements are sent in separate packets over transmission channels that are subject to time-varying delays. Consequently, classical tools for the stability analysis, e.g., for time delay systems, have to be extended to facilitate an explicit consideration of network-induced effects such as packet skipping and disordering of sent packets. The present paper illustrates that the time-varying delays and, particularly important, the packetized character of the transmissions have to be explicitly taken into account for the stability analysis. Three network protocols, which use different packet selection and hold mechanisms, are considered to state criteria for the robust stability of the networked feedback loops with filtered Smith predictors. They are based on the small gain theorem and allow a computationally inexpensive way to check stability for the case with uncertain plant models and bounded time-varying packet delays in the communication channels. • Filtered Smith predictor for packet-based networked systems. • Communication network with bounded and time-varying packet delays. • Three different network protocols (different packet skipping and hold mechanisms). • Easy-to-use stability analysis for uncertain plants and time-varying packet delays. [ABSTRACT FROM AUTHOR]

The 3rd generation partnership project (3GPP) has been enhancing the security of the 5G AKA (authentication and key agreement) protocol. However, there may still be some shortcomings in the latest version of the 5G AKA protocol. According to the analysis of the latest version of the 5G AKA protocol, this paper points out seven of its shortcomings. To overcome these shortcomings, an improved primary authentication and key agreement protocol for 5G networks is proposed, which is named 5G-IPAKA. Compared with the latest version of the 5G AKA protocol, the main improvements include that the pre-shared key between the user equipment (UE) and the home network (HN) is replaced with a derivation key as the pre-shared key, the challenge-–response mechanism for the serving network (SN) is added, the mutual authentication and key confirmation occurs between the UE and the SN, and the message authentication code (MAC) failure procedure is replaced with a timeout mechanism on the HN. Then, the 5G-IPAKA protocol is proven secure in the mixed strand space model for mixed protocols. Further discussion and comparative analysis show that the 5G-IPAKA protocol can overcome the above shortcomings of the latest version of the 5G AKA protocol, and is better than the recently improved 5G AKA protocols. Additionally, the 5G-IPAKA protocol is efficient and backward-compatible. [ABSTRACT FROM AUTHOR]

A mobile ad hoc network (MANET) is a wireless network created by a radio terminal built into a mesh topology. Each node is deflected with respect to the other nodes. The Temporary networks can self-heal and automatically redirect back around a lost node. There is an MANET networks require different network layout protocols, such as remote hierarchical remote vector navigation, associative-based navigation, ad-assigning remote vector navigation, and dynamic source navigation. An improved meta-heuristic optimization algorithm is proposed in this paper. It works in conjunction with an autonomous mobile network to increase its power and efficiency. It can transmit large amounts of data using less power and its bandwidth speed increases as its data transfer speed increases. This will improve the amount of service generated there and the users can satisfy the provided services. [ABSTRACT FROM AUTHOR]

Background. Indonesia is one of the Southeast Asian countries with high case numbers of COVID-19 with up to 4.2 million confirmed cases by 29 October 2021. Understanding the genome of SARS-CoV-2 is crucial for delivering public health intervention as certain variants may have different attributes that can potentially affect their transmissibility, as well as the performance of diagnostics, vaccines, and therapeutics. Objectives. We aimed to investigate the dynamics of circulating SARS-CoV-2 variants over a 15-month period in Bogor and its surrounding areas in correlation with the first and second wave of COVID-19 in Indonesia. Methods. Nasopharyngeal and oropharyngeal swab samples collected from suspected patients from Bogor, Jakarta and Tangerang were confirmed for SARS-CoV-2 infection with RT-PCR. RNA samples of those confirmed patients were subjected to whole genome sequencing using the ARTIC Network protocol and sequencer platform from Oxford Nanopore Technologies (ONT). Results. We successfully identified 16 lineages and six clades out of 202 samples (male nD116, female nD86). Genome analysis revealed that Indonesian lineage B.1.466.2 dominated during the first wave (nD48, 23.8%) while Delta variants (AY.23, AY.24, AY.39, AY.42, AY.43 dan AY.79) were dominant during the second wave (n D 53, 26.2%) following the highest number of confirmed cases in Indonesia. In the spike protein gene, S_D614G and S_P681R changes were dominant in both B.1.466.2 and Delta variants, while N439K was only observed in B.1.466.2 (nD44) and B.1.470 (nD 1). Additionally, the S_T19R, S_E156G, S_F157del, S_R158del, S_L452R, S_T478K, S_D950N and S_V1264L changes were only detected in Delta variants, consistent with those changes being characteristic of Delta variants in general. Conclusions. We demonstrated a shift in SARS-CoV-2 variants from the first wave of COVID-19 to Delta variants in the second wave, during which the number of confirmed cases surpassed those in the first wave of COVID-19 pandemic. Higher proportion of unique mutations detected in Delta variants compared to the first wave variants indicated potential mutational effects on viral transmissibility that correlated with a higher incidence of confirmed cases. Genomic surveillance of circulating variants, especially those with higher transmissibility, should be continuously conducted to rapidly inform decision making and support outbreak preparedness, prevention, and public health response. [ABSTRACT FROM AUTHOR]

The Objective Function (OF) can be used by the Routing protocol for low power lossy networks (RPL) to construct a Destination Oriented Directed Acyclic Graph (DODAG) based on routing metrics. The standard OFs suffer from long hops when selecting the route, which may cause consume the node's energy faster. In this paper, we suggest an improvement of RPL OF that considers three metrics. The results show that the proposed protocol increases network lifetime by reducing energy consumption, increasing efficiency, increasing Packet Delivery Ratio (PDR), and decreasing packet loss ratio. In terms of PDR, packet loss ratio, and average power consumption, the best performance of the proposed protocol is shown in the network with 70 nodes and when the transmission range is 50m. Compared with the MRHOF, the proposed protocol increased the PDR by 58.425%, decreased the packet loss ratio by 0.21765, and decreased the total power consumption by 181.815mW. In terms of the average Expected Transmission Count (ETX) the best performance of the proposed protocol is shown in the network with 60 nodes and the transmission range is 40m. The proposed protocol reduced the average ETX by 49 compared to the MRHOF. [ABSTRACT FROM AUTHOR]

The global Signalling System No. 7 (SS7) network protocol standard has been developed and regulated based only on trusted partner networks. The SS7 network protocol by design neither secures the communication channel nor verifies the entire network peers. The SS7 network protocol used in telecommunications has deficiencies that include verification of actual subscribers, precise location, subscriber’s belonging to a network, absence of illegitimate message filtering mechanism, and configuration deficiencies in home routing networks. Attackers can take advantage of these deficiencies and exploit them to impose threats such as subscriber or network data disclosure, intercept mobile traffic, perform account frauds, track subscriber location, and deny services. Existing methods are unable to identify suspicious hosts as they use a minimal number of network parameters. So, there is a vital need to overcome these deficiencies to detect the abnormal behaviour of users and hence mitigate security attacks in a mobile network. This research proposes a model for anomaly detection in mobile networks based on Rule-based filtering with stateful correlation. The performance of the proposed method is evaluated using synthetic datasets. Results show that the proposed anomaly detection model performs 0.37% better in terms of security attack detection rate, 24.25% better in terms of false alarm rate, and 31.45% better in terms of true positive rate when compared with the existing pattern recognition Artificial Neural Network (ANN) algorithm. [ABSTRACT FROM AUTHOR]

This paper analyzes the typical abnormal behaviors such as hidden and invisible attacks of network protocols and proposes a new method to perceive and mine the abnormal behaviors of protocols so as to evaluate the operational security of protocols. Aiming at the problems of long latency and difficulty to expose the hidden behavior of network protocols, a scheme combining dynamic stain analysis and instruction clustering analysis is proposed. The proposed method cannot only quickly distinguish the hidden behavior but also accurately grasp the hidden behavior instruction sequence. Experimentation results show that the proposed method can mine unknown protocols for abnormal behavior with high accuracy. [ABSTRACT FROM AUTHOR]

Controller failures can result in unsafe physical plant operations and deteriorated performance in industrial cyber–physical systems. In this paper, we present a controller switching mechanism over wireless sensor–actuator networks to enhance the resiliency of control systems against problems and potential physical failures. The proposed mechanism detects controller failures and quickly switches to the backup controller to ensure the stability of the control system in case the primary controller fails. To show the efficacy of our proposed method, we conduct a performance evaluation using a hardware-in-the-loop testbed that considers both the actual wireless network protocol and the simulated physical system. Results demonstrate that the proposed scheme recovers quickly by switching to a backup controller in the case of controller failure. [ABSTRACT FROM AUTHOR]

Background: Lymphedema is a condition that affects up to 130 million subjects worldwide. Since it is related to several complications and a significant reduction in terms of quality of life, it is a heavy burden not only to the patients but also for the healthcare system worldwide. Despite the development of supermicrosurgery, such as vascularized lymph node transfer (VLNT) and lymphovenous anastomosis LVA, the indications and outcomes of these complex groups of interventions remain a controversial topic in the field of reconstructive plastic surgery. Methods: This systematic review and network meta-analysis aims to assess the evidence of outcomes of LVA and VLNT in patients with lymphedema. Secondary aims of the project are to determine if for any outcomes, LVA or VLNT is superior to conservative therapy alone, and whether the available evidence favors any kind of supermicrosurgical interventions for lymphedema patients. This study will include original studies of patients with lymphedema on the extremities indexed in PubMed, EMBASE, CENTRAL, PASCAL, FRANCIS, ISTEX, LILACS, CNKI, and IndMED that reported microsurgery (supermicrosurgery) of all techniques aiming the re-functionalization of the lymphatic system. As comparators, mere observation, conservative treatment of any kind, and the other subgroups of supermicrosurgery are planned. The primary outcome of this systematic review and network meta-analysis is the difference of the limb volume, while the secondary outcomes of interest will be erysipelas rates, major and minor complications, postoperative necessity of continuous compression garments, and patient satisfaction, measured by already published and validated scores for quality of life. Discussion: We will provide an overview and evidence grade analysis of the scientific literature available on the effectiveness of the subcategories of supermicrosurgical interventions for lymphedema. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the performance of non-orthogonal multiple access (NOMA)-based overlay cognitive integrated satellite-terrestrial relay network with secondary network selection, where the selected secondary network accesses the licensed spectrum by assisting the communication of primary network with amplify-and-forward protocol. Besides, NOMA techniques are used to improve the spectrum efficiency. Specifically, the closed-form expressions of outage probability (OP) for both primary network and secondary network are obtained. To get inherent insights, the asymptotic analysis of OP is further derived at high signal-to-noise ratios. Moreover, the diversity orders of the both networks are further provided. Finally, Monte Carlo simulations are given to valuate our analysis, and the effects of key parameters on system performance are revealed. Through the comparison between orthogonal multiple access (OMA) scheme and NOMA scheme, the superiority of our proposed scheme is proved. [ABSTRACT FROM AUTHOR]

Background: Gestational diabetes mellitus (GDM) in pregnancy leads to a range of perinatal complications. Although several randomized controlled trials (RCT) have tested the effect of non-pharmacological standard GDM care adjuncts on these outcomes, there is no agglomerated statistical evidence on how their occurrence risk varies across interventions and with placebo. Therefore, a systematic review and network meta-analysis (NMA) protocol is proposed here to address this evidence gap. Materials and methods: A search for above RCTs published in the English language will transpire in PubMed, Embase, and Scopus databases irrespective of date and geographic boundary. The RCTs must test nutritional supplementation, digital intervention, structured exercise program, educational program, counseling service, or a combination of these prenatally in GDM patients. These should report ≥1 of the following outcomes- cesarean section, pre-eclampsia, polyhydramnios, preterm birth, macrosomia, prolonged labor, gestational hypertension, premature rupture of membranes, congenital anomaly, Apgar scores, birth weight, birth length, gestational age at birth, neonatal hypoglycemia, neonatal hyperbilirubinemia, and neonatal Corpulence Index. The risk of bias assessment of the recruited trials will transpire using the Revised Cochrane risk-of-bias tool. Determination of the comparative effectiveness between interventions will occur by the frequentist method NMA for respective outcomes. The categorical and continuous outcomes effect size will get calculated in risk ratio and weighted or standardized mean difference, respectively. For each NMA model, network maps and league tables will show the connections between interventions and effect sizes with their 95% confidence intervals for each intervention pair compared, respectively. The publication bias assessment will occur using comparison-adjusted funnel plots. Best intervention prediction for NMA models with statistically significant intervention effect will happen by determining the surface under the cumulative ranking curve values. Statistical analysis will ensue using Stata software (v16). The statistical significance estimation will happen at p<0.05 and 95% confidence interval. Trial registration: PROSPERO registration no: CRD42021271199; https://clinicaltrials.gov/. [ABSTRACT FROM AUTHOR]

Transport layer security (TLS) protocol is the most widely used security protocol in modern network communications. However, protocol vulnerabilities caused by the design of the network protocol or its implementation by programmers emerge one after another. Meanwhile, various versions of TLS protocol implementations exhibit different behavioral characteristics. Researchers are attempting to find the differences in protocol implementations based on differential testing, which is conducive to discovering the vulnerabilities. This paper provides a solution to find the differences more efficiently by targeting the TLS protocol handshake process. The differences of different implementations during the fuzzing process, such as code coverage and response data, are taken to guide the mutation of test cases, and the seeds are mutated based on the TLS protocol syntax. In addition, the definition of duplicate discrepancies is theoretically explored to investigate the root cause of the discrepancies and to reduce the number of duplicate cases that are caused by the same reason. Besides, the necessary conditions for excluding duplicate cases are further analyzed to develop the deduplication strategy. The proposed method is developed based on open-source tools, i.e., NEZHA and TLS-diff. Three types of widely used TLS protocol implementations, i.e., OpenSSL, BoringSSL, and LibreSSL, are taken for experimental testing. The experimental results show that the proposed method can effectively improve the ability to find differences between different implementations. Under the same test scale or the same time, the amount of discrepancies increases by about 20% compared to TLS-diff, indicating the effectiveness of the deduplication strategy. [ABSTRACT FROM AUTHOR]

A critical requirement in Mobile Ad Hoc Networks (MANETs) is its ability to automatically discover existing services as well as their locations. Several solutions have been proposed in various communication domains which could be classified into two categories: (1) directory based, and (2) directory-less. The former is efficient but suffers from the amount of control messages being exchanged to maintain all directories in an agile environment. However, the latter approach attempts to reduce the amount of control messages to update directories, by simply sending broadcast messages to discover services; which is also a non-desirable approach in MANETs. This research work builds on top of our prior work (Nazeeruddin et al. in IFIP/IEEE international conference on management of multimedia networks and services, Springer, Berlin, 2006)) where we introduced a new efficient protocol for service discovery in MANETs (MSLD); a lightweight, robust, scalable, and flexible protocol which supports node heterogeneity and dynamically adapts to network changes while not flooding the network with extra protocol messages—a major challenge in today's network environments, such as Internet of Things (IoT). Extensive simulations study was conducted on MSLD to: (1) initially evaluate its performance in terms of latency, service availability, and overhead messages, then (2) compare its performance to Dir-Based, Dir-less, and PDP protocols under various network conditions. For most performance metrics, simulation results show that MSLD outperforms Dir-Based, Dir-less, and PDP by either matching or achieving high service availability, low service discovery latency, and considerably less communication overhead. [ABSTRACT FROM AUTHOR]

Based on the principle of cluster wireless sensor network, this article introduces typical routing protocols in wireless sensors, and wireless sensor network protocol in detail analyzes their advantages and disadvantages and addresses their shortcomings. First, in the clustering network, a uniform clustering protocol with multiple hops in the circular network is proposed. The circular network is divided into rings of equal width, and clusters of equal size are set on different rings. Secondly, the ordinary nodes on each layer of the ring send the collected data to the auxiliary intelligent nodes in the cluster in a single-hop manner, and the auxiliary intelligent nodes located on the outer ring transfer the data to the auxiliary intelligent nodes located on the adjacent inner ring. Finally, on the basis of studying the clustering network protocol, this paper proposes a new clustering routing algorithm, a multihop adaptive clustering routing algorithm. The simulation results show that the algorithm can effectively extend the life of the network, save network energy consumption, and achieve network load balance. At the same time, the initial energy of the auxiliary intelligent node is set according to the energy consumption of the ordinary node and the relative distance between the auxiliary intelligent node and the base station on each layer of the ring. The theoretical and simulation results prove that, compared with the clustered network and auxiliary intelligent nodes, the clustered network can extend the life of the network. [ABSTRACT FROM AUTHOR]

Most existing network communication systems, such as the Internet, are built around the TCP/IP protocol stack. However, TCP/IP cannot effectively support the upcoming network communication systems with more wireless communication links and higher requirements in terms of throughput, latency, and reliability. In this article, we introduce a general network communication protocol design based on batched network coding (BNC), which includes the existing framework as a special case and whose design can be guided by channel coding theory. BNC-based protocols can have significant throughput gain for single-hop or multihop wireless communications and provide better trade-off among throughput, latency and reliability. [ABSTRACT FROM AUTHOR]

Correctness of networking protocols represents the principal requirement of cybersecurity. Correctness of protocols is established via the procedures of their verification. A classical communication system includes a pair of interacting systems. Recent developments of computing and communication grids for radio broadcasting, cellular networks, communication subsystems of supercomputers, specialized grids for numerical methods and networks on chips require verification of protocols for any number of devices. For analysis of computing and communication grid structures, a new class of infinite Petri nets has been introduced and studied for more than 10 years. Infinite Petri nets were also applied for simulating cellular automata. Rectangular, triangular and hexagonal grids on plane, hyper cube and hyper torus in multidimensional space have been considered. Composing and solving in parametric form infinite Diophantine systems of linear equations allowed us to prove the protocol properties for any grid size and any number of dimensions. Software generators of infinite Petri net models have been developed. Special classes of graphs, such as a graph of packet transmission directions and a graph of blockings, have been introduced and studied. Complex deadlocks have been revealed and classified. In the present paper, infinite Petri nets are divided into two following kinds: a single infinite construct and an infinite set of constructs of specified size (and number of dimensions). Finally, the paper discusses possible future work directions. [ABSTRACT FROM AUTHOR]

Clustering is one of the most energy-efficient techniques for extending the lifetime of wireless sensor networks (WSNs). In a clustered WSN, each sensor node transmits the data acquired from the sensing field to the leader node (cluster head). The cluster head (CH) is in charge of aggregating and routing the collected data to the Base station (BS) of the deployed network. Thereby, the selection of the optimum CH is still a crucial issue to reduce the consumed energy in each node and extend the network lifetime. To determine the optimal number of CHs, this paper proposes an Enhanced Fuzzy-based LEACH (E-FLEACH) protocol based on the Fuzzy Logic Controller (FLC). The FLC system relies on three inputs: the residual energy of each node, the distance of each node from the base station (sink node), as well as the node's centrality. The proposed protocol is implemented using the Castalia simulator in conjunction with OMNET++, and simulation results indicate that the proposed protocol outperforms the traditional LEACH protocol in terms of network lifetime, energy consumption, and stability. [ABSTRACT FROM AUTHOR]

• A dynamic-distributed structure is designed as a satellite organizational structure. • An improved contract network protocol under the dynamic-distributed structure is proposed. • A blackboard model mechanism is proposed to coordinate the satellites under uncertainty. • An online single-satellite scheduling algorithm is designed. • The applicability of the proposed methods to different implementations of problems is studied. To meet the demand for real-time response to emergent events in the uncertain environment, the multi-autonomous-satellite system with real-time inter-satellite links and on-board scheduling capability has been proposed. This paper focuses on the multi-autonomous-satellite coordination and scheduling problem which is formulated by a novel mathematical model based on the multi-agent system (MAS). To solve the problem, we firstly analyze general organizational structures for the MAS and propose a new dynamic-distributed organizational structure. For these different structures, an improved contract network protocol (ICNP) and a blackboard model (BM) negotiation mechanism are proposed to coordinate the satellites. Then, an online single-satellite scheduling algorithm is proposed to schedule the tasks. In the experiments, we build up a multi-satellite system to analyze the performance of different autonomous coordination mechanisms. Experimental results indicate that the ICNP mechanism can increase the total revenue and reduce the inter-satellite communication cost. In scenarios where satellites could break down randomly, the BM can reduce the revenue losses and the number of task failures efficiently, which proves the good performance of the proposed methods in terms of robustness. The proposed methods have important practicality in the real application of the multi-autonomous-satellite system. [ABSTRACT FROM AUTHOR]

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Quality of Service (QoS) is the rate of complete performance of a service, such as computer networking or services in the area of cloud computing. Quality of Service is an important factor and point of consideration in the development of cross layered frameworks or cross layered architectures. With the increase in use of cross layered technology QoS is a highly critical parameter which has been subject to vast amounts of research. Data aggregation is one of the most important techniques to increase bandwidth utilization and energy efficiency in WSNs (wireless sensor networks). There are a lot of research activities being carried out in this field, but a majority of them have a disadvantage that they cannot meet practical requirements in an optimal manner, such as the requirements of latency and heterogeneity of application data. Providing Quality of Service (QoS) in an efficient manner is highly important for some networks (WSNs), since they are required to provide present-time services like audio, video, and VoIP which is nothing but Voice Over IP other than the conventional data service approach. Many solutions have been proposed to provide soft QoS over networks that are wireless and are multihop from other layers in the pack of network protocols. Somehow, the concepts of layers were primarily created for networks which are wired, and wireless networks that are multihop oppose stricter layer based design because of their varying nature, architecture which are infra structure less & time-varied unstable connection topology and links. The idea of cross-layered design is premised on the architecture where several layers can exchange content or information in order to enhance the complete performance of the network. Accurate results could be obtained by optimizations in cross-layered that brought about considerable research in this area. This paper aims to research the current works on the cross-layer approach for QoS support in the realm of wireless networks which are multihop. [ABSTRACT FROM AUTHOR]

The reliability of the modelling system mainly depends on the simulation of underwater acoustic channel characteristics. The reliability of simulator is improved because of the use of Bellhop in NS-Miracle. World Ocean Simulation System (WOSS) can retrieve the data of marine environment by accessing the database of seabed depth, sound speed profile and seabed sediment, and transmit them to Bellhop simulator automatically, so that the model is closer to the actual underwater acoustic transmission channel than not using WOSS. In order to verify the reliability of NS2/NS-Miracle simulation system with WOSS, a centralized underwater sensor network with five nodes is simulated on the integrated simulation system. The characteristic empirical model, Bellhop Ray-Tracing model, and WOSS combined with Bellhop model are, respectively, adopted to simulate underwater acoustic channel. The results of three types of simulation, such as average throughput, average delay, and packet error rate, and simulation time are very close under the same condition. It proves that the accuracy of integrated simulation system is as excellent as that of NS-Miracle. However, WOSS can automatically acquire the actual sea environment parameters and provide them to the simulator, which can improve the authenticity of the simulation system. Furthermore, three MAC protocols, Aloha-CS, CSMA/CA, and DACAP, are simulated on the integrated simulation system under the same condition including ocean environment, network topology, and parameters. The results show that the performance of CSMA/CA is greater than the other protocols in such networks. It also proves that the integrated simulation system can accurately simulate the relevant characteristics of the MAC protocol. [ABSTRACT FROM AUTHOR]

Network attacks show a trend of increased attack intensity, enhanced diversity, and more concealed attack methods, which put forward higher requirements for the performance of network security equipment. Unlike the SDN (software defined network) switch with a fixed-function data plane, switches with programmable data planes can help users realize more network protocols. Programming Protocol-independent Packet Processors (P4) is proposed to define the operations of the data plane and to implement user's applications, e.g., data center networks, security, or 5G. This paper provides a review of research papers on solving network security problems with P4-based programmable data plane. The work can be organized into two parts. In the first part, the programming language P4, P4 program, architectures, P4 compilers, P4 Runtime, and P4 target are introduced according to the workflow model. The advantages of P4-based programmable switching in solving network security are analyzed. In the second part, the existing network security research papers are divided into four parts according to the perspectives of passive defense, active defense, and combination of multiple technologies. The schemes in each category are compared, and the core ideas and limitations are clarified. In addition, a detailed comparison is made for the research on the performance of P4 targets. Finally, trends and challenges related to the P4-based programmable data plane are discussed. [ABSTRACT FROM AUTHOR]

The widespread application of wireless communication technology brings great convenience to people, but security and privacy problems also arise. To assess and guarantee the security of wireless networks and user devices, discovering and identifying wireless devices become a foremost task. Currently, effective device identification is still a challenging issue, as device fingerprinting requires huge training datasets and is difficult to expand, and rule-based identification is not accurate and reliable enough. In this paper, we propose WND-Identifier, a universal and extensible framework for the identification of wireless devices, which can generate high-precision device labels (vendor, type, and product model) efficiently without user interaction. We first introduce the concept of device-info-related network protocols. WND-Identifier makes full use of the natural language features in such protocol messages and combines with the device description in the welcome page, thereby utilizing extraction rules to generate concrete device labels. Considering that the device information in the protocol messages may be incomplete or forged, we further take advantage of the application logic independence and stability of the device-info-related protocol, so as to build a multiprotocol text classification model, which maps the device to a known label. We conduct experiments in homes and public networks and present three application scenarios to verify the effectiveness of WND-Identifier. [ABSTRACT FROM AUTHOR]

Low-power wireless communication is a central building block of cyber-physical systems and the Internet of Things. Conventional low-power wireless protocols make avoiding packet collisions a cornerstone design choice. The concept of synchronous transmissions challenges this view. As collisions are not necessarily destructive, under specific circumstances, commodity low-power wireless radios are often able to receive useful information even in the presence of superimposed signals from different transmitters. We survey the growing number of protocols that exploit synchronous transmissions for higher robustness and deficiency as well as unprecedented functionality and versatility compared to conventional designs. The illustration of protocols based on synchronous transmissions is cast in a conceptional framework we establish, with the goal of highlighting differences and similarities among the proposed solutions. We conclude this article with a discussion on open questions and challenges in this research field. [ABSTRACT FROM AUTHOR]

Satisfying the stringent 5G quality of service requirements necessitates efficient resource utilization by mobile networks. Consequently, we argue that multi-connectivity (MC) is an effective solution to leverage the limited radio resources from multiple base stations in order to enhance user throughput, provide seamless connectivity, and increase data reliability. For this, we study different MC architectures, where distinct network entities and protocol layers are used to split or aggregate the user traffic. The benefits and challenges of MC are analyzed as well as the open issues that network/device vendors and mobile network operators have to address for its use. Finally, through experimental evaluations, we illustrate the importance of MC design decisions for overall network performance. [ABSTRACT FROM AUTHOR]

This paper presents an in-depth study and analysis of X-ray inspection of basin insulators by wireless sensing technology. Aiming at the characteristics of low contrast and many kinds of noise in the basin insulator ray image, this paper proposes an X-ray basin insulator image denoising method based on improved 3D block matching. Using the RF microcontroller CC2530 chip as the core hardware and networked by ZigBee protocol, the sensor senses and collects various parameters and transmits this information to the monitoring end in real time through wireless. The method proposes an improved wavelet thresholding denoising method to overcome the pseudo-Gibbs phenomenon caused by the wavelet hard thresholding method in the 3D block matching algorithm cofiltering and retain more details of the image. Aiming at the ringing effect caused by the Wiener filtering method used in the three-dimensional block matching algorithm collaborative filtering, an improved Kalman filtering method based on anisotropic diffusion is proposed, which avoids the ringing effect, and has clear edges and complete details. An improved Kalman filtering method based on anisotropic diffusion is proposed to avoid the ringing effect, and the edges are clear, and the details are complete. The proposed method is a safe, efficient, accurate, and feasible method for detecting defects in basin insulators by combining X-ray and improved wireless image sensing technology to detect the internal equipment without disassembling or touching the GIS equipment. [ABSTRACT FROM AUTHOR]

Using the NS2 network simulation tool to teach the "wireless network" course can enhance students' understanding of wireless network protocols through visualization and can also improve students' ability to analyze problems hands on. We built a multimedia wireless network modularized English teaching platform based on NS2 simulation software; made full use of the rich components and network resources provided by NS2 to achieve a high degree of code reuse and reduce the time for developing simulation codes; designed the overall framework of this multimedia wireless network modular English teaching platform based on the B/S structure; and solved the weight coefficient and importance value of the learning input evaluation index, based on the feedback elite teaching optimization algorithm, the improved teaching formula, the increase in the number of exchanges, and the improvement in the learner's performance. The experimental results show that the LEACH and LEACH-C protocols of the clustered NS2 simulation software have more surviving nodes most of the time, which indicates that the clustering routing protocol has better performance. [ABSTRACT FROM AUTHOR]

Health big data has already been the most important big data for its serious privacy disclosure concerns and huge potential value of secondary use. Measurements must be taken to balance and compromise both the two serious challenges. One holistic solution or strategy is regarded as the preferred direction, by which the risk of reidentification from records should be kept as low as possible and data be shared with the principle of minimum necessary. In this article, we present a comprehensive review about privacy protection of health data from four aspects: health data, related regulations, three strategies for data sharing, and three types of methods with progressive levels. Finally, we summarize this review and identify future research directions. [ABSTRACT FROM AUTHOR]

With the increasing connectivity between the Electronic Control Units (ECUs) and the outside world, safety and security have become stringent problems. The Controller Area Network (CAN) bus is the most commonly used in-vehicle network protocol, which lacks security mechanisms by design, so it is vulnerable to various attacks. In this paper, we propose a novel intrusion detection model called CNN-LSTM with Attention model (CLAM) for the in-vehicle network, especially CAN. The CLAM model uses one-dimensional convolution (Conv1D) to extract the abstract features of the signal values at each time step and feeds it into the Bidirectional Long Short Term Memory (Bi-LSTM) to extract the time dependence. By combining the attention mechanisms, we calculate the weight of each hidden state output by Bi-LSTM and perform a weighted summation, so that the model focuses only on locally important time steps, which can improve the convergence speed of the model and prediction accuracy. The proposed model uses the bit flip rate to extract continuous signal boundaries in the 64-bit CAN data, so it does not need to parse the CAN communication matrix and is suitable for different vehicles. The extensive evaluation results demonstrate that our proposed CLAM model can effectively detect CAN attacks, with an average F1-score of 0.951 and an error rate of 2.16%. Compared with the work in related research fields, the accuracy of attack detection is improved by 2.5%. [ABSTRACT FROM AUTHOR]

This article connects mobile terminals through improved network protocols, and connects monitoring devices through improved network protocols in the local area network. At the same time, it can convert mobile terminal requests into requests that comply with improved network protocols and forward them to monitoring devices. Method of three-dimensional feature extraction based on dynamic data. First, normalize the coordinates and scales of the three-dimensional calculus model, and use two kinds of data (voxel representation and pixel representation) to deal with video object recognition. Then construct a convolutional neural network as an input to the network, extract visual information and geometric information, and use deep learning to improve the recognition ability of single-modal features. Based on the convolutional neural network, the geometric descriptor and the view descriptor of the three-dimensional calculus model are extracted separately, and the two feature descriptors are fused in a network to find the association between the patterns. After forming the fused feature descriptor, it is applied to micro Classification and retrieval of integral 3D features. The multi-feature fusion layer can not only learn more distinguishing features of the two descriptors, but also supplement relevant information between the two descriptors. Compared with using these two representations alone, this method produces a much better classifier and improves retrieval efficiency. [ABSTRACT FROM AUTHOR]

In the energy sector, distributed synchronism and a high degree of stability are necessary for all real-time monitoring and control systems. Instantaneous response to critical situations is essential for the integration of renewable energies. The most widely used standards for clock synchronisation, such as Network Time Protocol (NTP) and Precision Time Protocol (PTP), do not allow for achieving synchronised simultaneous sampling in distributed systems. In this work, a novel distributed synchronism system based on the Time-Sensitive Networking (TSN) standard has been validated for its integration in an architecture oriented towards the high-resolution digitisation of photovoltaic (PV) generation systems. This method guarantees a time stamping with an optimal resolution that allows for the analysis of the influence of fast-evolving atmospheric fluctuations in several plants located in the same geographical area. This paper proposes an enhanced micro-phasor measurement unit (µPMU) that acts as a phasor meter and TSN master controlling the monitoring system synchronism. With this technique, the synchronism would be extended to the remaining measurement systems that would be involved in the installation at distances greater than 100 m. Several analyses were carried out with an on-line topology of four acquisition systems capturing simultaneously. The influence of the Ethernet network and the transducers involved in the acquisition process were studied. Tests were performed with Ethernet cable lengths of 2, 10, 50, and 75 m. The results were validated with 24-bit Sigma-Delta converters and high-precision resistor networks specialised in high-voltage monitoring. It was observed that with an appropriate choice of sensors and TSN synchronism, phase errors of less than ±1 µs can be guaranteed by performing distributed captures up to 50 kS/s. Statistical analysis showed that uncertainties of less than ±100 ns were achieved with 16-bit Successive Approximation Register (SAR) converters at a moderate cost. Finally, the requirements of the IEEE C37.118.1-2011 standard for phasor measurement units (PMU) were also satisfied. This standard establishes an uncertainty of ±3.1 μs for 50 Hz systems. These results demonstrate the feasibility of implementing a simultaneous sampling system for distributed acquisition systems coordinated by a µPMU. [ABSTRACT FROM AUTHOR]

Featured Application: Position location information plays a crucial role in the automated and adaptable operation of Industry 4.0, allowing sensor fault detection as well as operators localization. The development of 3D positioning techniques is crucial for massive sensor network operability imposed by the Internet of Things. Several network protocols depend on position location information for security and routing purposes. Alternative positioning techniques are necessary for new paradigms imposed by new network applications. The proliferation of 3D applications in Industry 4.0 demands alternative 3D location algorithms. Industry 4.0, or smart factory, refers to the fourth industrial revolution, as a result of which it is expected that massive sensor deployment, high device connectivity, automation, and real-time data acquisition support improve industrial processes. Sensor fault detection and operator tracking allow adequate performance of the sensor network supporting Industry 4.0, and sensor localization has become crucial to enable sensor fault detection. Hence, the development of new localization methods is necessary for environments where GPS localization technology is unfeasible. Furthermore, position location information (PLI) is a crucial requirement for the deployment of multiple services and applications in wireless ad hoc and sensor networks supporting Industry 4.0. Three-dimensional (3D) scenarios are considered to extend the applicability of PLI-based services. However, PLI acquisition presents several challenges within any 3D ad hoc sensor network paradigm. For instance, conventional triangulation algorithms are often no longer applicable due to the lack of direct land-fixed references and the inclusion of a third-dimension coordinate. In this paper, a PL relational searching algorithm suitable for 2D and 3D ad hoc environments was formulated in terms of a discretized searching space and a vertex weight assignment process according to distance relationships from anchor nodes to the node to be located on a feasibility space. The applicability of the proposed algorithm was examined through analytic formulation and simulation processes. Results show small distance errors (less than 1 m) are achievable for some scenarios. [ABSTRACT FROM AUTHOR]

The purpose of this study was to look at the link between sleep quality and sports performance of athletes. Here physical fitness among athletes' also can be predicted using Internet-of-Things (IoT) environment. The IoT has the potential to make people's live style different and easy to work. Now-a-days people are connected with Internet, where the entire human beings and living communities are getting transformed because of different Network protocols. By investigating the causes for sleep quality, its goal was to make coaches and players aware of the necessity of sleeping in order to improve training and competition performance. This study is conducted for twelve female and male athletes of 22 to 27 age group. The associations between sleep quality and other variables were investigated using a one-way ANCOVA model, three main factors are Consuming caffeine or alcohol, sleeping environment and extreme moods such as shocks or being exited before sleep are important reason for poor sleep quality. Here Athletes who are suffering due to inadequate sleep owing to poor characteristics of sleep, which has resulted in negative physical and psychological effects, as well as negative consequences on training and competition performance. And it is proposed that hygiene of sleep be pushed to trainers or coaches and players in order to increase their understanding on how to have healthier sleeping habits. And also in this paper we create procedures for predicting athletes' physical fitness using an IoT context, laying a solid basis for associated athlete index improvement applications. The findings of this study demonstrate that the professional group's wellness prediction accuracy rate using the athletes' model of physical fitness prediction and indexing optimization in an Internet of Things environment is greater than the control groups', with a difference of p<001. [ABSTRACT FROM AUTHOR]

The blockchain technology introduced by bitcoin, with its decentralised peer-to-peer network and cryptographic protocols, provides a public and accessible database of bitcoin transactions that have attracted interest from both economics and network science as an example of a complex evolving monetary network. Despite the known cryptographic guarantees present in the blockchain, there exists significant evidence of inconsistencies and suspicious behavior in the chain. In this paper, we examine the prevalence and evolution of two types of anomalies occurring in coinbase transactions in blockchain mining, which we reported on in earlier research. We further develop our techniques for investigating the impact of these anomalies on the blockchain transaction network, by building networks induced by anomalous coinbase transactions at regular intervals and calculating a range of network measures, including degree correlation and assortativity, as well as inequality in terms of wealth and anomaly ratio using the Gini coefficient. We obtain time series of network measures calculated over the full transaction network and three sub-networks. Inspecting trends in these time series allows us to identify a period in time with particularly strange transaction behavior. We then perform a frequency analysis of this time period to reveal several blocks of highly anomalous transactions. Our technique represents a novel way of using network science to detect and investigate cryptographic anomalies. [ABSTRACT FROM AUTHOR]

When mobile network enters 5G era, 5G networks have a series of unparalleled advantages. Therefore, the application of 5G network technology in the Internet of Vehicles (IoV) can promote more intelligently vehicular networks and more efficiently vehicular information transmission. However, with the combination of 5G networks and vehicular networks technology, it requires safe and reliable authentication and low computation overhead. Therefore, it is a challenge to achieve such low latency, security, and high mobility. In this paper, we propose a secure and efficient lightweight authentication protocol for vehicle group. The scheme is based on the extended chaotic map to achieve authentication, and the Chinese remainder theorem distributes group keys. Scyther is used to verify the security of the scheme, and the verification results show that the security of the scheme can be guaranteed. In addition, through security analysis, the scheme can not only effectively resist various attacks but also guarantee security requirements such as anonymity and unlinkability. Finally, by performance analysis and comparison, our scheme has less computation and communication overhead. [ABSTRACT FROM AUTHOR]

Based on the improved adaptive filtering method, this paper conducts in-depth discussion and research on embedded graphics and video coding and chooses to improve the adaptive filtering algorithm from three aspects: starting point prediction, search template, and window partitioning. The algorithm is imported into the encoder for video capture and encoding. By capturing videos of different formats, resolutions, and times, the memory size of the video files collected before and after the algorithm optimization is compared, and the optimized algorithm occupies the memory space of the video file in the actual system. The conclusion of less and higher coding rates. The collected video information is stored on a personal computer equipped with a freeness, and external electronic devices only need to download and install the browser, and the collected video information can be accessed in the local area network through the protocol. The improved coding algorithm has higher coding efficiency and can reduce the storage space occupied by the video. [ABSTRACT FROM AUTHOR]

The low-rate denial of service (LDoS) attack mainly exploits security vulnerabilities of adaptive mechanisms in network protocols and application services. The high-rate attack pulses within a short time interval are sent periodically, which will result in the degradation of service quality. The attack traffic is similar to normal traffic from legitimate users in the network, consequently, it is easy to escape the traditional detection methods because of its intermittence. Research works have demonstrated that there are fractal characteristics (self-similarity) of the network traffic over the large scale of time. Although the fractal characteristics of the network traffic will be changed under the LDoS attack, the variations of the fractal characteristics in some network states are not apparent in real-time detection. Based on the fractal characteristics, the fractal residual of the network traffic is analyzed through the Hurst parameters calculating process by R/S algorithm in this article. It can be found that the fractal residual of the network traffic can better reflect the different states of the LDoS attack. Combining the idea behind the sliding window, a novel fractal residual based real-time detection (FR-RED) method of the LDoS attack is proposed. The effectiveness of the method in this article is verified by performing some experiments on two platforms, the NS2 and test-bed. The results manifest the beginning and end of the LDoS attack can be estimated in real-time with high detection accuracy. [ABSTRACT FROM AUTHOR]

Wireless blockchain network is proposed to enable a decentralized and safe wireless networks for various blockchain applications. To achieve blockchain consensus in wireless network, one of the important steps is to broadcast new block using wireless channel. Under wireless network protocols, the block transmitting will be affected significantly. In this work, we focus on the consensus process in blockchain-based wireless local area network (B-WLAN) by investigating the impact of the media access control (MAC) protocol, CSMA/CA. With the randomness of the backoff counter in CSMA/CA, it is possible for latter blocks to catch up or outpace the earlier one, which complicates blockchain forking problem. In view of this, we propose mining strategies to pause mining for reducing the forking probability, and a discard strategy to remove the forking blocks that already exist in CSMA/CA backoff procedure. Based on the proposed strategies, we design Block Access Control (BAC) approaches to effectively schedule block mining and transmitting for improving the performance of B-WLAN. Then, Markov chain models are presented to conduct performance analysis in B-WLAN. The results show that BAC approaches can help the network to achieve a high transaction throughput while improving block utilization and saving computational power. Meanwhile, the trade-off between transaction throughput and block utilization is demonstrated, which can act as a guidance for practical deployment of blockchain. [ABSTRACT FROM AUTHOR]

The Internet of Things tends to attract deep interest in areas such as electronic, environmental management and enhance the effectiveness from researchers, the industry, citizens and government. IoT provides internet connectivity between connected phones in any context, anytime or anywhere. Wireless sensor networks (WSNs) consequently play an important role in developing a robust, affordable and convenient network of smart devices. Even then, sensor networks are restricted in scope of power, processing, and memory. In this framework, authors proposed a routing protocol of hybrid meta-heuristic moth search algorithm based differential evolution (HMSA-DE). By choosing routes based on the quality of the link, residual energy and recommended measuring mechanisms, the HMSA enhances reliability and energy efficiency. In addition, HMSA offers an event-based load balancing system that further prevents premature node / network power consumption. The findings suggest that HMSA improves the life cycle and availability of the network as well as the performance of IoT application services. It distributes limited network resources evenly and reduces the packet loss rate compared with the results of network protocols. [ABSTRACT FROM AUTHOR]

Different schemes have been proposed for increasing network lifetime in mobile ad hoc networks (MANETs) where nodes move uncertainly in any direction. Mobility awareness and energy efficiency are two inescapable optimization problems in such networks. Clustering is an important technique to improve scalability and network lifetime, as it relies on grouping mobile nodes into logical subgroups, called clusters, to facilitate network management. One of the challenging issues in this domain is to design a real-time routing protocol that efficiently prolongs the network lifetime in MANET. In this paper, a novel fuzzy-based Q-learning approach for mobility-aware energy-efficient clustering (FQMEC) is proposed that relies on deciding the behavioral pattern of the nodes based on their stability and residual energy. Also, Chebyshev's inequality principle is applied to get node connectivity for load balancing by taking history from the monitoring phase to increase the learning accuracy. Extensive simulations are performed using the NS-2 network simulator, and the proposed scheme is compared with reinforcement learning (RL). The obtained results show the effectiveness of the proposed protocol regarding network lifetime, packet delivery ratio, average end-to-end delay, and energy consumption. [ABSTRACT FROM AUTHOR]

Blockchain is a mainstream technology in which many untrustworthy nodes work together to maintain a distributed ledger with advantages such as decentralization, traceability, and tamper-proof. The network layer communication mechanism in its architecture is the core of the networking method, message propagation, and data verification among blockchain nodes, which is the basis to ensure blockchain's performance and key features. When blocks are propagated in peer-to-peer (P2P) networks with gossip protocol, the high propagation delay of the protocol itself reduces the propagation speed of the blocks, which is prone to the chain forking phenomenon and causes double payment attacks. To accelerate the propagation speed and reduce the fork probability, this paper proposes a blockchain network propagation mechanism based on proactive network provider participation for P2P (P4P) architecture. This mechanism first obtains the information of network topology and link status in a region based on the internet service provider (ISP), then it calculates the shortest path and link overhead of peer nodes using P4P technology, prioritizes the nodes with good local bandwidth conditions for transmission, realizes the optimization of node connections, improves the quality of service (QoS) and quality of experience (QoE) of blockchain networks, and enables blockchain nodes to exchange blocks and transactions through the secure propagation path. Simulation experiments show that the proposed propagation mechanism outperforms the original propagation mechanism of the blockchain network in terms of system overhead, rate of data success transmission, routing hops, and propagation delay. [ABSTRACT FROM AUTHOR]

The fuzzing test is able to discover various vulnerabilities and has more chances to hit the zero-day targets. And ICS(Industrial control system) is currently facing huge security threats and requires security standards, like ISO 62443, to ensure the quality of the device. However, some industrial proprietary communication protocols can be customized and have complicated structures, the fuzzing system cannot quickly generate test data that adapt to various protocols. It also struggles to define the mutation field without having prior knowledge of the protocols. Therefore, we propose a fuzzing system named ICPFuzzer that uses LSTM(Long short-term memory) to learn the features of a protocol and generates mutated test data automatically. We also use the responses of testing and adjust the weight strategies to further test the device under testing (DUT) to find more data that cause unusual connection status. We verified the effectiveness of the approach by comparing with the open-source and commercial fuzzers. Furthermore, in a real case, we experimented with the DLMS/COSEM for a smart meter and found that the test data can cause a unusual response. In summary, ICPFuzzer is a black-box fuzzing system that can automatically execute the testing process and reveal vulnerabilities that interrupt and crash industrial control communication. Not only improves the quality of ICS but also improves safety. [ABSTRACT FROM AUTHOR]

Peer-to-peer systems rely on a scalable overlay network that enables efficient routing between its members. Hypercubic topologies facilitate such operations while each node only needs to connect to a small number of other nodes. In contrast to static communication networks, peer-to-peer networks allow nodes to adapt their neighbor set over time in order to react to join and leave events and failures. This article shows how to maintain such networks in a robust manner. Concretely, we present a distributed and self-stabilizing algorithm that constructs a (slightly extended) skip graph, SKIP+, in polylogarithmic time from any given initial state in which the overlay network is still weakly connected. This is an exponential improvement compared to previously known self-stabilizing algorithms for overlay networks. In addition, our algorithm handles individual joins and leaves locally and efficiently. [ABSTRACT FROM AUTHOR]

With the rapid development of network technology, computer viruses have developed at a fast pace. The threat of computer viruses persists because of the constant demand for computers and networks. When a computer virus infects a facility, the virus seeks to invade other facilities in the network by exploiting the convenience of the network protocol and the high connectivity of the network. Hence, there is an increasing need for accurate calculation of the probability of computer-virus-infected areas for developing corresponding strategies, for example, based on the possible virus-infected areas, to interrupt the relevant connections between the uninfected and infected computers in time. The spread of the computer virus forms a scale-free network whose node degree follows the power rule. A novel algorithm based on the binary-addition tree algorithm (BAT) is proposed to effectively predict the spread of computer viruses. The proposed BAT utilizes the probability derived from PageRank from the scale-free network together with the consideration of state vectors with both the temporal and learning effects. The performance of the proposed algorithm was verified via numerous experiments. [ABSTRACT FROM AUTHOR]

Spontaneous networks lack an a priori communication infrastructure, the neighbors are unknown right after the deployment, and they are used during a period of time and in a certain location. In this paper, we present a new randomized creation model of a spontaneous wireless ad hoc network based on trusted neighbors. The idea is to manage the neighbor discovery with the exchange of identity cards, and the checking of a signature establishes a relationship based on trust of the neighbors. To asses the performance of our randomized trusted network proposal and compare it against an existing deterministic protocol used as reference, we relied on Castalia 3.2 simulator, regarding 4 metrics: time, energy consumption, throughput, and number of discoveries vs packet sent ratio. We found that our proposal outperforms the reference protocol in terms of time, energy, and discoveries vs packet sent ratio in a one-hop setting, while it outperforms the reference protocol regarding all 4 metrics in multihop environments. We also evaluated our proposal through simulations varying the transmission probability and proved that it does not require to know the number of nodes if a fixed transmission probability is set, providing reasonable results. Moreover, our proposal is based on collision detection, it knows when to terminate the process, it does not require a transmission schedule, and it follows more realistic assumptions. In addition, a qualitative comparison is carried out, comparing our proposal against existing protocols from the literature. [ABSTRACT FROM AUTHOR]

In today's security landscape, advanced threats are becoming increasingly difficult to detect as the pattern of attacks expands. Classical approaches that rely heavily on static matching, such as blacklisting or regular expression patterns, may be limited in flexibility or uncertainty in detecting malicious data in system data. This is where machine learning techniques can show their value and provide new insights and higher detection rates. The behavior of botnets that use domain-flux techniques to hide command and control channels was investigated in this research. The machine learning algorithm and text mining used to analyze the network DNS protocol and identify botnets were also described. For this purpose, extracted and labeled domain name datasets containing healthy and infected DGA botnet data were used. Data preprocessing techniques based on a text-mining approach were applied to explore domain name strings with n-gram analysis and PCA. Its performance is improved by extracting statistical features by principal component analysis. The performance of the proposed model has been evaluated using different classifiers of machine learning algorithms such as decision tree, support vector machine, random forest, and logistic regression. Experimental results show that the random forest algorithm can be used effectively in botnet detection and has the best botnet detection accuracy. [ABSTRACT FROM AUTHOR]

To model the power measurement conditions of an energy system, an initial reference should be made within the specification of a generic energy consumption (EC) model. This EC model is based on the energy state of a system comprising goods, networks, and services, which supports energy management capabilities. Therefore, a prototype tool to record power consumption (PC) at the device level is designed and implemented, thereby enabling devise use optimization. The core is to collect energy-related information in internet protocol networks that support the simple network management protocol, in addition to the standard proposed in RFC-7460, and the green information technology. The information obtained is related to the energy consumed by devices that support those technologies. Then, the information is processed to evaluate different PC characteristics of the network. This research impacts the knowledge gap of information system management, where the objective sought is to establish metrics and methodological schemes for obtaining data regarding measurable behaviors in the EC field. [ABSTRACT FROM AUTHOR]