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The level of dependence on data communication in the modern era is increasing exponentially. The internet of things (IoT) plays a very important role in the advancement of the industrial revolution 4.0 that utilizes data communication systems. IoT deployments require data communication protocols, such as hypertext transfer protocol (HTTP), and message queuing telemetry transport (MQTT) as well as network communication protocols (wireless) to meet the network needs of devices with limited resources. Optimization of data communication in IoT is needed to maintain the quality of sending and receiving data in real time. This research proposes a hybrid NarrowBand-IoT (NB-IoT) protocol designed using NarrowBand communication network technology with optimization of data communication using MQTT and HTTP protocols. In this research, the hybrid NB-IoT protocol has the best packet loss value of 0.010% against the HTTP NB-IoT protocol which has a value of 0.017%, and the MQTT NB-IoT protocol of 0.024%. The hybrid NB-IoT protocol has a latency value of 8.7 seconds compared to the HTTP NB-IoT protocol which has a latency of 10.9 seconds. Meanwhile, the throughput value of the hybrid NB-IoT protocol is 158906.1 byte/s and is better than the MQTT NB-IoT protocol which is only 158898.6 bytes/s.

This paper was designed with the intention of analyzing the vulnerability of e-commerce web sites. We are going to describe the transmission of data in clear text without encryption by hypertext transfer protocol (HTTP), reason why we argue that by means of a sniffer technique this information can be captured and this way violating customer privacy information.

An open-source P2P energy trading platform facilitates energy trading amongst the peers. The proposed system provides real time data acquisition, monitoring and control of self-generated energy at a remote location. The trading activities are done on a web interface that uses a private Ethereum blockchain. A smart contract is deployed on the Ethereum blockchain and the trading activities performed on the web interface are recorded on a tamper-proof blockchain network. An internet of things platform is used to monitor and control the self-generated energy. Energy data is collected and processed by means of ESP32-S2 microcontrollers using field instrumentation devices which are connected to the voltage source and load. An open-source decentralized Peer-to-Peer (P2P) energy trading system, designed on the blockchain and internet of things (IoT) architecture is proposed. The hardware setup includes a relay, a current sensor, a voltage sensor, a Wi-Fi router and ESP32-S2 microcontroller. For data transfer the Message Queuing Telemetry Transport (MQTT) protocol is used over a local network. ESP32-S2 is set up as MQTT client and Node-Red IoT server is used as MQTT broker. Hypertext Transfer Protocol (http) request method is implemented to connect the Node-Red server with the web interface developed using React.JS library. The system design, implementation, testing, and results are presented in this paper.

La presente investigación muestra el desarrollo de un modelo web semántico cuyo objetivo es crear una base de conocimiento de grupos y géneros musicales tradicionales de la ciudad de Bogotá, la forma en la que se transmite la información hacia y desde la base de conocimiento creada, es mediante el uso de un API basado en arquitectura REST, que utiliza el protocolo HTTP, esta información se presenta en un portal Web. Los visitantes y usuarios que ingresen al portal pueden realizar búsquedas que son basadas en SPARQL, para contactar grupos musicales de acuerdo con una serie de filtros tales como: ubicación geográfica, género musical, trayectoria en el mercado, tarifas entre otros, este desarrollo se convierte en una alternativa digital para que los grupos musicales de la ciudad de Bogotá puedan promocionar sus servicios y generen un canal virtual de contacto rápido y seguro, con ello se busca mejorar la calidad de vida de los integrantes de agrupaciones musicales.

In case there is a communication contrary to the system security policies, a covert channel has been created. The attacker can easily disclosure information from the victim’s system with just one public access permission. Covert timing channels, unlike covert storage channels, do not have memory storage and they draw less attention. Different methods have been proposed for their identification, which generally benefit from the shape of traffic and the channel’s regularity. The application nature of HTTP protocol allows the creation of a covert timing channel based on different features of this protocol (or different levels) that has not been addressed in previous researches. This research tries to study the effect of using different features (or levels) of HTTP protocol on identifying the covert channel. The amount of channel’s entropy could be manipulated by changing the channel’s level or adding intentional noise on the channel to protect from the analyzer’s detection. The difference in the placement of the covert channel and the detector causes the amount of channel entropy to be far from the detection threshold. Therefore, we concluded that the analyzer must investigate traffic at all possible levels. Adding noise on the covert channel decrease its capacity, but as entropy increases, it would be harder to detect it.

The aim of the author of this article is analyze the performance of WebSocket and HTTP protocol and their comparison. For this purpose, was used equipment working in a local network consisting of server, two client computers, switch and self-created research web application. Using a test application was measured time of data transfer between clients and server as well server and clients. The tests included transmission 100-character texts in specified number of copies considering speed of hardware (laptops) and software (web browsers). Additionally, was investigated the impact of overhead and TLS encryption to performance. The obtained results have illustrated in the form of charts, discussed and appropriate conclusions drawn.

In particular, the method used in this research is a case study where previously the p3m.pnp.ac.id website still uses the http protocol. However http protocol does not have a method of securing data in its communication. The final result of this research is the design and implementation of the https protocol for data communication security that occurs between visitors and the p3m.pnp.ac.id website. The https protocol that has been implemented is tested to ensure the data traffic on the p3m.pnp.ac.id website is guaranteed to be safe and protected from possible piracy and data theft.

In the age of Big Genomics Data, institutions such as the National Human Genome Research Institute (NHGRI) are challenged in their efforts to share volumes of data between researchers, a process that has been plagued by unreliable transfers and slow speeds. These occur due to throughput bottlenecks of traditional transfer technologies. Two factors that affect the efficiency of data transmission are the channel bandwidth and the amount of data. Increasing the bandwidth is one way to transmit data efficiently, but might not always be possible due to resource limitations. Another way to maximize channel utilization is by decreasing the bits needed for transmission of a dataset. Traditionally, transmission of big genomic data between two geographical locations is done using general-purpose protocols, such as hypertext transfer protocol (HTTP) and file transfer protocol (FTP) secure. In this paper, we present a novel deep learning-based data minimization algorithm that 1) minimizes the datasets during transfer over the carrier channels; 2) protects the data from the man-in-the-middle (MITM) and other attacks by changing the binary representation (content-encoding) several times for the same dataset: we assign different codewords to the same character in different parts of the dataset. Our data minimization strategy exploits the alphabet limitation of DNA sequences and modifies the binary representation (codeword) of dataset characters using deep learning-based convolutional neural network (CNN) to ensure a minimum of code word uses to the high frequency characters at different time slots during the transfer time. This algorithm ensures transmission of big genomic DNA datasets with minimal bits and latency and yields an efficient and expedient process. Our tested heuristic model, simulation, and real implementation results indicate that the proposed data minimization algorithm is up to 99 times faster and more secure than the currently used content-encoding scheme used in HTTP of the HTTP content-encoding scheme and 96 times faster than FTP on tested datasets. The developed protocol in C# will be available to the wider genomics community and domain scientists.

With the development of the times, the concept of "interconnection of all things" has been deeply rooted in the hearts of people. As an early and developing Internet technology, the Internet of things(IoT) has shown its infinite potential in many fields of social life. In agriculture, the agricultural IoT is coverring a growing number of fields: greenhouse planting, climate factor collection, climate prediction and so on. Based on this idea, the design idea of "patchouli growth environment monitoring system" is put forward. In this paper, the medicinal plant "patchouli" is studied, and its medicinal value and growth factors are discussed. Meanwhile, based on zigbee technology, we design a set of feasible monitoring scheme including hardware and software. The hardware part used ZigBee wireless network design, mainly relies on the cc2530 chip and the esp8266 wifi chip to carry on the wireless distance transmission to the sensor data. It interacts between OneNET cloud server and mysql database through MQTT protocol, TCP/IP protocol and HTTP protocol.

Purpose This study aims to provide a system capable of static searching on a large number of unstructured texts directly on the Web domain while keeping costs to a minimum. The proposed framework is applied to the unstructured texts of Migne’s Patrologia Graeca (PG) collection, setting PG as an implementation example of the method. Design/methodology/approach The unstructured texts of PG have automatically transformed to a read-only not only Structured Query Language (NoSQL) database with a structure identical to that of a representational state transfer access point interface. The transformation makes it possible to execute queries and retrieve ranked results based on a specialized application of the extended Boolean model. Findings Using a specifically built Web-browser-based search tool, the user can quickly locate ranked relevant fragments of texts with the ability to navigate back and forth. The user can search using the initial part of words and by ignoring the diacritics of the Greek language. The performance of the search system is comparatively examined when different versions of hypertext transfer protocol (Http) are used for various network latencies and different modes of network connections. Queries using Http-2 have by far the best performance, compared to any of Http-1.1 modes. Originality/value The system is not limited to the case study of PG and has a generic application in the field of humanities. The expandability of the system in terms of semantic enrichment is feasible by taking into account synonyms and topics if they are available. The system’s main advantage is that it is totally static which implies important features such as simplicity, efficiency, fast response, portability, security and scalability.

Nowadays, heterogeneous devices are widely utilizing Hypertext Transfer Protocol (HTTP) to transfer the data. Furthermore, HTTP adaptive video streaming (HAS) technology transmits the video data over wired and wireless networks. In adaptive technology services, a client’s application receives a streaming video through the adaptation of its quality to the network condition. However, such a technology has increased the demand for Quality of Experience (QoE) in terms of prediction and assessment. It can also cause a challenging behavior regarding subjective and objective QoE evaluations of HTTP adaptive video over time since each Quality of Service (QoS) parameter affects the QoE of end-users separately. This paper introduces a methodology design for the evaluation of subjective QoE in adaptive video streaming over wireless networks. Besides, some parameters are considered such as video characteristics, segment length, initial delay, switch strategy, stalls, as well as QoS parameters. The experiment’s evaluation demonstrated that objective metrics can be mapped to the most significant subjective parameters for user’s experience. The automated model could function to demonstrate the importance of correlation for network behaviors’ parameters. Consequently, it directly influences the satisfaction of the end-user’s perceptual quality. In comparison with other recent related works, the model provided a positive Pearson Correlation value. Simulated results give a better performance between objective Structural Similarity (SSIM) and subjective Mean Opinion Score (MOS) evaluation metrics for all video test samples.

The article presents a method for computer simulation of a network device using its digital emulator, for which a virtual environment is created to generate network traffic. During emulation, the simulated objects are defined by a set of functional and interface threads, which interact through virtual communication lines, which are common areas of memory. The proposed approach minimizes the time cost of packet transmission between digital objects and focuses on the algorithmic component of the simulated device. The method is illustrated by a computer simulation of the operation of the HTTP protocol filtering device as a part of the information Web system.

Mobile web-based augmented reality (MWAR) provides users with quick richer information interaction forms due to its convenience and universality. However, the 3D model data service for MWAR is a type of centralized file-based data service, which cannot simultaneously meet diverse user and response delay requirements in large-scale and complex applications. This affects the application and promotion of large-scale and complex MWAR application. To this end, this paper proposes a collaborative model data computing service framework (CMCSF) for MWAR between Mobile Edge Servers (MES), Cloud Servers (CS), and mobile devices. The main contributions of this paper include: (1) The CMCSF converts the file-based 3D model data service in MWAR to a computing-based and interfaced data service to meet the diverse service requirements of users; (2) The CMCSF establishes a collaborative computing model data service between the MES and the CS, and it computes a control and deployment strategy for the collaborative computing model data service in order to reduce the response delay of 3D model data; and (3) The CMCSF optimizes the loading method of the WebGL engine (for example, three.js) and applies the asynchronous loading method of the JSON interface data on the http protocol for browsers to get persistent model data services. An experimental evaluation shows the CMCSF improves the response efficiency of the 3D model data file Significantly when compared with the original centralized file-based 3D model file service.

In recent years, with the rapid development of the Internet of Things (IoT), various applications based on IoT have become more and more popular in industrial and living sectors. However, the hypertext transfer protocol (HTTP) as a popular application protocol used in various IoT applications faces a variety of security vulnerabilities. This article proposes a novel HTTP anomaly detection framework based on edge intelligence (EI) for IoT. In this framework, both clustering and classification methods are used to quickly and accurately detect anomalies in the HTTP traffic for IoT. Unlike the existing works relying on a centralized server to perform anomaly detection, with the recent advances in EI, the proposed framework distributes the entire detection process to different nodes. Moreover, a data processing method is proposed to divide the detection fields of HTTP data, which can eliminate redundant data and extract features from the fields of an HTTP header. Simulation results show that the proposed framework can significantly improve the speed and accuracy of HTTP anomaly detection, especially for unknown anomalies.

Online information systems with the Single Sign-On (SSO) model are currently widely used by many companies. Single Sign-On (SSO) is an independent authentication model. This system runs on the Hypertext Transfer Protocol (HTTP) protocol. Sending data or information without security is at risk of eavesdropping on information by the authorities. This study aims to compare the combination of Message-Digest and Advanced Encryption Standard (AES) algorithms to improve data security by modifying dynamic keys. The test results show that in each execution the user name and password with the MD5 algorithm are always the same while in the AES algorithm the results are always different so it is safe from replay attacks. So that the Advanced Encryption Standard (AES) algorithm can secure data through the Single-Sign-On authentication process with high-security accuracy.

Recently, due to unexpected conditions introduced by the COVID-19 outbreak, collaborative tools are widely adopted in almost all sectors of our daily lifestyle. Almost all tools rely mainly on the World Wide Web technologies that, in turn, are built upon the HTTP protocol. The HTTP protocol is considered as the “bricks” of all kind of communications among people/devices that exchange messages with different purposes and meanings. Unfortunately, it is widely used to track and monitor people when using the Internet. This paper exploits the HTTP protocol and try to reverse this negative aspect by designing and implementing a way to help users (and devices) to not disclose too much information when collaborating each other even in an unfriendly environment. A novel steganographic protocol is proposed by using the HTTP “control” messages. The proposed protocol can be easily adopted by devices communicating in a MEC (Mobile Edge Computing) environment where it is important to guarantee the integrity and the confidentiality of all communications, especially messages that give “instructions” to devices or in device-to-device communications. The proposed protocol allows to avoid using complex and computationally demanding cryptographic protocols that are very difficult to be used in devices with limited resources.

PDAM merupakan perusahaan yang bergerak dalam distribusi air bersih bagi masyarakat. Sebagian masyarakat Indonesia telah menjadi pelanggan air PDAM guna memenuhi kebutuhan air untuk aktivitas sehari-hari. Kualitas air menjadi persoalan penting karena berhubungan erat dengan kesehatan. Pada makalah ini dilakukan perancangan sistem monitoring kualitas air PDAM Banyumas berbasis IoT dengan meninjau parameter konduktivitas (EC) dan padatan terlarut (TDS). Hasil data pengukuran dapat diakses melalui aplikasi Andorid pada smartphone. Aplikasi dirancang menggunakan protokol HTTP dan MQTT. Protokol HTTP digunakan pada user interface untuk mengambil data terakhir pengukuran, sedangkan protokol MQTT digunakan untuk update data pengukuran sehingga proses transmisi data lebih cepat. Sistem akan mengirim pemberitahuan melalui Telegram apabila kualitas air berada di bawah baku mutu. Pengujian akurasi pengukuran dilakukan dengan membandingkan perangkat monitoring yang dibuat dengan alat ukur bersertifikat pada sampel air minum kemasan dan air PDAM. Hasil penelitian menunjukkan kinerja perangkat monitoring kualitas air PDAM yang dirancang sebesar 97,31% serta kualitas air PDAM Banyumas yang didistribusikan sangat stabil dan aman dikonsumsi.

Over the past decade, the Internet has become the gigantic and richest source of data. The data is used for the extraction of knowledge by performing machine leaning analysis. In order to perform data mining of the web-information, the data should be extracted from the source and placed on analytical storage. This is the ETL-process. Different web-sources have different ways to access their data: either API over HTTP protocol or HTML source code parsing. The article is devoted to the approach of high-performance data extraction from sources that do not provide an API to access the data. Distinctive features of the proposed approach are: load balancing, two levels of data storage, and separating the process of downloading files from the process of scraping. The approach is implemented in the solution with the following technologies: Docker, Kubernetes, Scrapy, Python, MongoDB, Redis Cluster, and СephFS. The results of solution testing are described in this article as well.

Content regarding various illegal activities, such as weapon and drug trafficking, is shared on the dark web. Most of the illegal content is distributed on anonymous networks that cannot be directly accessed from the World Wide Web. A number of studies have been conducted on the network structure of the World Wide Web since its advent. Similar to the World Wide Web, the dark web is connected by hypertext transfer protocol (http); this makes it possible to use the methods developed for the web in the dark web. Many studies have investigated the dark web and its network structure. However, few studies have focused on the visualization of the dark web network structure, and there have been no studies investigating the temporal changes in the network structure. In this study, to understand the hypertext markup language (html) network structure of the dark web, we created and visualized a graph of the html hyperlink relations of the Tor network, which is popular on the dark web. We then compared the insights gained from graph centrality metrics with those gained from visualizations. The analyzed dataset comprised 25,270,157 pages of html text files crawled from the Tor network by breadth-first search from June 1, 2018, to January 30, 2021. Subsequently, we acquired half-yearly snapshots from the collected data and investigated the change in the dark web network over time using a time-series graph. Then, we derived the centrality metrics from the created graph data and confirmed the differences between the centrality metrics and visualizations. The results obtained in this study provided new insights into the dark web. First, we found that the dark web fluctuated significantly; the structure of the dark web network was more strongly interconnected. Second, most of the nodes that had increased in the past two years may have disappeared rapidly after May 2020. Third, analysis of each snapshot revealed that the proportion of highly volatile domains increased from 40% to 75% during the observation period. Fourth, after calculating the network centrality metrics from each snapshot and comparing the transition of hub nodes in chronological order, we observed that the importance of link-collection sites as the main information retrieval method used in the dark web decreased. Finally, we estimated the size of the dark web based on our observed dark web measurements using the mark-recapture method. To the best of our knowledge, this is the first study to use the mark-recapture method to estimate the size of the dark web network.

Software-defined networks (SDNs) offer robust network architectures for current and future Internet of Things (IoT) applications. At the same time, SDNs constitute an attractive target for cyber attackers due to their global network view and programmability. One of the major vulnerabilities of typical SDN architectures is their susceptibility to Distributed Denial of Service (DDoS) flooding attacks. DDoS flooding attacks can render SDN controllers unavailable to their underlying infrastructure, causing service disruption or a complete outage in many cases. In this paper, machine learning-based detection and classification of DDoS flooding attacks on SDNs is investigated using popular machine learning (ML) algorithms. The ML algorithms, classifiers and methods investigated are quadratic discriminant analysis (QDA), Gaussian Naïve Bayes (GNB), $k$ -nearest neighbor (k-NN), and classification and regression tree (CART). The general principle is illustrated through a case study, in which, experimental data (i.e. jitter, throughput, and response time metrics) from a representative SDN architecture suitable for typical mid-sized enterprise-wide networks is used to build classification models that accurately identify and classify DDoS flooding attacks. The SDN model used was emulated in Mininet and the DDoS flooding attacks (i.e. hypertext transfer protocol (HTTP), transmission control protocol (TCP), and user datagram protocol (UDP) attacks) have been launched on the SDN model using low orbit ion cannon (LOIC). Although all the ML methods investigated show very good efficacy in detecting and classifying DDoS flooding attacks, CART demonstrated the best performance on average in terms of prediction accuracy (98%), prediction speed ( $5.3\,\,{\times }\,\,10^{5}$ observations per second), training time (12.4 ms), and robustness.

The research aimed to make e-commerce web services using a microservices architecture. Web service was built using Representational State Transfer Protocol (REST) with Hypertext Transfer Protocol (HTTP) method and JavaScript Object Notation (JSON) response format. Meanwhile, the microservices architecture was developed using Domain-driven Design (DDD) approach. The research began by analyzing e-commerce business processes and was modeled using Unified Modeling Language (UML) based on business process analysis. Next, the bounded context was used to make a small responsible service for a function. The Programming language used to make the system was Go programming language with Go-kit tool and apply database-per-service pattern for data management. The system also applied the concept of containerization using Docker as the container platform and using API Gateway to manage each endpoint. Last, the evaluation process was carried out using the Postman application by testing each endpoint based on the white-box testing method. Based on the results of the evaluation process, the e-commerce web service can work as expected. The results also show that the system has a high level of resilience. It means that the system has a low level of dependencies between services and adapts to future changes.

The results of research in the field of organizational behavior and team management in cyber-physical systems of technical service have shown that self-organizing teams are the most effective in the group behavior of resources. The paper presents a multi-level self-organization of resources of a cyber-physical system of technical service based on a situational-oriented approach. The approach is based on the concept of the organizational behavior of the upper-level resources and ensuring their accounting in the self-organization of the lower-level resources. A schematic representation of the principles of construction and functioning of the cyber-physical system of technical service is given. It has been found that access to information about the resources of the cyber-physical system of the technical service is provided by using the technology of intelligent spaces. The implementation of the situational-oriented approach is carried out on the example of a scenario for the provision of services in the maintenance of motor transport and mobile agricultural machinery with the participation of physical devices controlled by resource managers and planning resources responsible for generating the direction of the behavior of control resources. The concept of a structure-oriented approach is depicted in the form of levels of self-organization of resources in accordance with situations in the cyber-physical system of technical service. Self-organization at all levels of generation of situations of behavior of groups of resources, as well as internal-level self-organization are considered. It is noted that the technology of intelligent space is built on the open platform Smart-M3 and its structure is presented. The general structure of the platform contains three groups of devices with information agents, a semantic information broker and physical storage of information. The platform itself is based on the concept of the Semantic Web. It is shown that the exchange of information between space participants is based on the Hyper Text Transfer Protocol standard using the resource identifier. The standard is based on client-server technology.

Nowadays, much research attention is focused on human–computer interaction (HCI), specifically in terms of biosignal, which has been recently used for the remote controlling to offer benefits especially for disabled people or protecting against contagions, such as coronavirus. In this paper, a biosignal type, namely, facial emotional signal, is proposed to control electronic devices remotely via emotional vision recognition. The objective is converting only two facial emotions: a smiling or nonsmiling vision signal captured by the camera into a remote control signal. The methodology is achieved by combining machine learning (for smiling recognition) and embedded systems (for remote control IoT) fields. In terms of the smiling recognition, GENKl-4K database is exploited to train a model, which is built in the following sequenced steps: real-time video, snapshot image, preprocessing, face detection, feature extraction using HOG, and then finally SVM for the classification. The achieved recognition rate is up to 89% for the training and testing with 10-fold validation of SVM. In terms of IoT, the Arduino and MCU (Tx and Rx) nodes are exploited for transferring the resulting biosignal remotely as a server and client via the HTTP protocol. Promising experimental results are achieved by conducting experiments on 40 individuals who participated in controlling their emotional biosignals on several devices such as closing and opening a door and also turning the alarm on or off through Wi-Fi. The system implementing this research is developed in Matlab. It connects a webcam to Arduino and a MCU node as an embedded system.

La tendencia actual es interconectar cualquier dispositivo para ser monitoreado y controlado de manera remota por medio de tecnologías propias del concepto de IoT. Uno de los problemas es conectar los dispositivos a una red mediante tecnologías con suficiente cobertura y capacidad, por lo que en el presente artículo se muestra el desarrollo de un gateway móvil para aplicaciones IoT bajo la plataforma Android, evaluado en redes móviles de 4G. El gateway móvil IoT envía los datos recolectados de sensores mediante la selección de los protocolos MQTT y HTTP, hacia plataformas IoT en Internet. La arquitectura se compone de sensores de temperatura, luminosidad y presión que se integran en un nodo sensor, cuya función es la obtención de los datos, procesamiento y luego, mediante Bluetooth, se envía a un smartphone Android, donde se ejecuta una aplicación que hace la función gateway móvil. Aquí se realiza el entramado de datos que son enviados mediante la red 4G LTE hacia las plataformas IoT de Ubidots y Watson IoT. Posteriormente se realizaron pruebas con varias métricas como latencia, demanda de corriente y costos de conexión. Se concluye que el gateway móvil IoT tiene un mejor rendimiento bajo el protocolo MQTT, en comparación con HTTP.

With more and more people accessing the internet to get information and the absence of settings on data traffic it will cause the network to be slow. The network traffic settings in Linux Ubuntu still use scripts that are relatively more difficult to use and understand for some people, so tools are needed to configure them. Capture network traffic application is Software designed to capture communications connected to servers. Capture network traffic application can only log data and read TCP/IP and HTTP protocols. The Capture network traffic application has various features, including checking whether the server is on or off, capturing traffic packets on a LAN network, and displaying a map of the URL location. So the results of this study explain the creation of a Traffic Management Configurator to facilitate traffic monitoring settings in gateways that connect different networks. Furthermore, this traffic monitoring application is used to view the actual packets of traffic on the network and network statistics. Both applications use the web as an interface to the user.

Constraint Application Protocol (CoAP), an application layer based protocol, is a compressed version of HTTP protocol that is used for communication between lightweight resource constraint devices in Internet of Things (IoT) network. The CoAP protocol is generally associated with connectionless User Datagram Protocol (UDP) and works based on Representational State Transfer architecture. The CoAP is associated with Datagram Transport Layer Security (DTLS) protocol for establishing a secure session using the existing algorithms like Lightweight Establishment of Secure Session for communication between various IoT devices and remote server. However, several limitations regarding the key management, session establishment and multi-cast message communication within the DTLS layer are present in CoAP. Hence, development of an efficient protocol for secure session establishment of CoAP is required for IoT communication. Thus, to overcome the existing limitations related to key management and multicast security in CoAP, we have proposed an efficient and secure communication scheme to establish secure session key between IoT devices and remote server using lightweight elliptic curve cryptography (ECC). The proposed ECC-based CoAP is referred to as ECC-CoAP that provides a CoAP implementation for authentication in IoT network. A number of well-known cryptographic attacks are analyzed for validating the security strength of the ECC-CoAP and found that all these attacks are well defended. The performance analysis of the ECC-CoAP shows that our scheme is lightweight and secure.

This paper discusses the comparison of service quality between HTTP protocol and MQTT protocol implemented using internet of things to research on soil moisture around plants, quality of service compared to delay, jitter, throughput and packet loss. In this study the results showed that the HTTP and MQTT protocols have an average delay value below 150 or 63 ms. HTTP has an average jitter value between 0 - 62 ms, while MQTT has a jitter range value of between 0 - 16 ms. Whereas the HTTP throughput value is 88 ms and the MQTT protocol is 68 ms. Then for packet loss parameters both have the same quality as it generates a packet loss value of 0%. In this study it can be concluded that the use of http protocols is the superior protocol of MQTT in terms of quality of service.

In the era of information technology, the use of computer technology for both work and personal use is growing rapidly with time. Unfortunately, with the increasing number and size of computer networks and systems, their vulnerability also increases. Protecting web applications of organizations is becoming increasingly relevant as most of the transactions are carried out over the Internet. Traditional security devices control attacks at the network level, but modern web attacks occur through the HTTP protocol at the application level. On the other hand, the attacks often come together. For example, a denial of service attack is used to hide code injection attacks. The system administrator spends a lot of time to keep the system running, but they may forget the code injection attacks. Therefore, the main task for system administrators is to detect network attacks at the application level using a web application firewall and apply effective algorithms in this firewall to train web application firewalls automatically for increasing his efficiency. The article introduces parameterization of the task for increasing the accuracy of query classification by the random forest method, thereby creating the basis for detecting attacks at the application level.

The massive amounts of spatio-temporal information often present in LiDAR data sets make their storage, processing, and visualisation computationally demanding. There is an increasing need for systems and tools that support all the spatial and temporal components and the three-dimensional nature of these datasets for effortless retrieval and visualisation. In response to these needs, this paper presents a scalable, distributed database system that is designed explicitly for retrieving and viewing large LiDAR datasets on the web. The ultimate goal of the system is to provide rapid and convenient access to a large repository of LiDAR data hosted in a distributed computing platform. The system is composed of multiple, share-nothing nodes operating in parallel. Namely, each node is autonomous and has a dedicated set of processors and memory. The nodes communicate with each other via an interconnected network. The data management system presented in this paper is implemented based on Apache HBase, a distributed key-value datastore within the Hadoop eco-system. HBase is extended with new data encoding and indexing mechanisms to accommodate both the point cloud and the full waveform components of LiDAR data. The data can be consumed by any desktop or web application that communicates with the data repository using the HTTP protocol. The communication is enabled by a web servlet. In addition to the command line tool used for administration tasks, two web applications are presented to illustrate the types of user-facing applications that can be coupled with the data system.

Web server is software that provides data services in the form of HTTP (Hypertext Transfer Protocol) requests and responses in the form of HTML documents (Hypertext Markup Language) with the aim of managing data in the form of text files, images, videos and files. But in managing large amounts of data, good security monitoring is needed so that the data stored on the web server is not easily hacked. To protect the web server from hackers need an application to detect activities that are considered suspicious or possible hacking activities. By utilizing logs from a web server that is processed using the Jaro Winkler algorithm to see hacking attempts that produce a matrix and hacking activity reports to the admin. Thus the web server admin can see suspicious activity on the web server directly.Keywords: Web Server, Jaro Winkler Algorithm.

The existing 3rd Generation Partnership Project (3GPP) packet- switched streaming (PSS) architecture that was developed for 3G and 4G and evolved to carry streaming content with DASH [Dynamic and Adaptive Streaming over Hypertext Transfer Protocol (HTTP)], is now seen as too limited for 5G. 3GPP has, therefore, started developing a new media streaming architecture, considering the latest advances in the media industry and the features offered by the 5G system. Recognizing that, most media and video content delivered to the user is provided by several online service providers, the new 3GPP 5G media streaming architecture focuses on different collaboration and deployment models between mobile network operators and media data service providers. These collaboration and deployment models also cater to traditional broadcasters, which increasingly see the need for high-quality contributions via a mobile network, for example, to cover unplanned or transient events. The new architecture supports unicast downlink media data distribution and uplink streaming .

— Recently, the number of incidents related to Web applications, due to the increase in the number of users of mobile devices, the development of the Internet of things, the expansion of many services and, as a consequence, the expansion of possible computer attacks. Malicious programs can be used to collect information about users, personal data and gaining access to Web resources or blocking them. The purpose of the study is to enhance the detection accuracy of computer attacks on Web applications. In the work, a model for presenting requests to Web resources, based on a vector space model and attributes of requests via the HTTP protocol is proposed. Previously carried out research allowed us to obtain an estimate of the detection accuracy as well as 96% for Web applications for the dataset KDD 99, vector-based query representation and a classifier based on model decision treesTóm tắt – Trong những năm gần đây, số lượng sự cố liên quan đến các ứng dụng Web có xu hướng tăng lên do sự gia tăng số lượng người dùng thiết bị di động, sự phát triển của Internet cũng như sự mở rộng của nhiều dịch vụ của nó. Do đó càng làm tăng khả năng bị tấn công vào thiết bị di động của người dùng cũng như hệ thống máy tính. Mã độc thường được sử dụng để thu thập thông tin về người dùng, dữ liệu cá nhân nhạy cảm, truy cập vào tài nguyên Web hoặc phá hoại các tài nguyên này. Mục đích của nghiên cứu nhằm tăng cường độ chính xác phát hiện các cuộc tấn công máy tính vào các ứng dụng Web. Bài báo trình bày một mô hình biểu diễn các yêu cầu Web, dựa trên mô hình không gian vectơ và các thuộc tính của các yêu cầu đó sử dụng giao thức HTTP. So sánh với các nghiên cứu được thực hiện trước đây cho phép chúng tôi ước tính độ chính xác phát hiện xấp xỉ 96% cho các ứng dụng Web khi sử dụng bộ dữ liệu KDD 99 trong đào tạo cũng như phát hiện tấn công đi kèm với việc biểu diễn truy vấn dựa trên không gian vectơ và phân loại dựa trên mô hình cây quyết định

Today’s Internet knows no bounds. New applications are marketed every single day. Many of them incorporate video sequences. These must be transported over the Internet quickly (often in real time). However, the Internet has not been designed for live communications and, regrettably, this may become apparent all too quickly. Countermeasures are required in the form of new, efficient transport techniques facilitating online video services. MPEG-DASH is one of such modern techniques. But how good is this new technique really? This paper delves into the matter. The paper contains an analysis of the impact that the new technology exerts on the quality of video streaming over IP networks. It also describes a new numerical tool – QoSCalc (DASH-HTTP) which has been used to analyze MPEG-DASH under different use scenarios. The results are presented graphically and their interpretation is provided

The use of Internet of Things (IoT) plays an important role in supporting wireless communication for middleware in collecting data sensors. An actor-based middleware is designed to bridge protocol differences between cloud and sensor nodes. This middleware also acts as an initiator in accessing data from several sensor nodes, and then sending data that has been collected to the cloud. Incorporating the differences of communication protocols and data formats between sensor nodes and cloud is the responsibility of middleware. This Middleware acts as an actor by acting proactively accessing data from each sensor node, so that it can facilitate the completion of sending data from the sensor node to the middleware by avoiding from "signal collisions” among sensor nodes. After the data is collected in the middleware, the data is sent to the cloud using the Websocket or HTTP protocol above the TCP / IP protocol. The performance of the system is evaluated based on the success of the middleware bridging communication between sensor nodes and the cloud, as well as the readability of IoT data sensors that have been adjusted by cloud. The test results show that built-in middleware can bridge protocols between cloud and sensor nodes. In addition, the Websocket usage protocol produces a lower delay value than the MQTT and CoAP protocols.

The current network traffic is large, and the network attacks have multiple types. Therefore, anomaly detection model combined with machine learning is developing rapidly. Frequent occurrences of Web Application Firewall (WAF) bypass attacks and the redundancy of the data characteristics in Hypertext Transfer Protocol (HTTP) protocol make it difficult to extract data characteristics. In this paper, an integrated web intrusion detection system combined with feature analysis and support vector machine (SVM) optimization is proposed. By using expert’s knowledge, the characteristics of the common Web attacks are analyzed. The related data characteristics are selected by the analysis of the HTTP protocol. In the classification learning, the mature and robust support vector machine algorithm is utilized and the grid search method is used for the parameter optimization. Consequently, a better detection capability on Web attacks can be obtained. By using the HTTP DATASET CSIC 2010 data set, experiments have been carried out to compare the detection capability of different kernel functions. The results show that the proposed system performs good in the detection capability and can detect the WAF bypass attacks effectively.

High quality multimedia streaming over the Internet has proliferated in modern society due to the ever-increasing ties amongst people and businesses, thereby occupying the majority of all exchanged data traffic. The Internet is the primary multimedia exchange medium that is being used beyond its intended design. Using Hypertext Transfer Protocol/Transmission Control Protocol (HTTP/TCP), multimedia can be delivered to virtually all devices connected to the Internet. HTTP-based streaming suffers from the increasing overhead generated as the stream length, quality, and non-deterministic path conditions vary. In this paper, a novel cross-layer signalling reduction scheme is proposed to alleviate resource consumption in networks exchanging multimedia. The proposed scheme is a steganographic-based protocol translator that encodes information within multimedia payloads prior to packet flight to reduce the size of exchanged data. The encoded data is used by node pairs to replace bulky protocols, such as TCP, with lightweight protocols, such as User Datagram Protocol (UDP). In addition to the protocol translator, a routing scheme is given to be used in place of the inflated networking protocols to further reduce the header footprint. A utility function is developed to find the optimal overhead savings where simulations are conducted to verify the designs. Using virtual machines, the proposed translator is implemented where a multimedia file is exchanged and subject to encoding. The simulations and implementation show that the proposed methodologies will decrease the amount of signalling needed while increasing the overall network capacity. Furthermore, the proposed methods are capable of successfully extending existing signalling reduction methods.

In cyber world Botnets becoming more popular and great challenge to security. Attacker by using bot net taking legacy attacks towards new dimension. Existing Intrusion Prevention / Intrusion Detection (IPS/IDS) systems can detect botnets attacks by using anomaly detection methods (or) signature. To fly the radar of IDS/IPS systems Bot master creates an attack either anomaly (or) any known signature. One possible thing is mimicking attack. Attacker hack the popular website browsing history. By using, browsing history they will simulate thousands of users through bots and will try to degrade the performance of the website. Mimicking kind of attacks can be made as distributed by using Botnet. In this paper, we are discussing about the possibility of mimicking attack by using Botnet. The first phase attacker will inject bots into the targeted systems. In second phase Bot master will inject respective mimicking profile in to targeted systems similar to their browsing behavior. We are proposing possible algorithm to identify the mimicking attack at gate way level, which will be tied up with NIDS. We worked on example of mimicking attack by using HTTP protocol. The attacker will collect the profile of users and using that mimicking profile was extracted. With that heterogeneous mimicking attack was executed. NIDS will be installed at gateway which will collect the connection statistics. The statistics will be given to the detection algorithm which will identify the similar flows based on Layer 3, Layer 4, Layer 7. The suspicious flows will be sent for challenges to prove the identity of the user. If it is in attack mimicking applications can’t respond to the challenges, the source ip address does not respond to challenges were added to the block list.

HyperText Transfer Protocol (HTTP) cookies are widely used on the web to enhance communication efficiency between a client and a server by storing stateful information. However, cookies may contain private and sensitive information about users. Thus, in order to guarantee the security of cookies, most web browsers and servers support not only Transport Layer Security (TLS) but also other mechanisms such as HTTP Strict Transport Security and cookie flags. However, a recent study has shown that it is possible to circumvent cookie flags in HTTPS by exploiting a vulnerability in HTTP software that allows message truncation. In this paper, we propose a novel cookie hijacking attack called $rotten~cookie$ which deactivates cookie flags even if they are protected by TLS by exploiting a weakness in HTTP in terms of integrity checks. According to our investigation, all major browsers ignore uninterpretable sections of the header of HTTP response messages and accept incorrect formats without any rejection. We demonstrate that, when combined with TLS or application vulnerabilities, this form of attack can obtain private cookies by removing cookie flags. Thus, the attacker can impersonate a legitimate user in the eyes of the server when cookies are used as an authentication token. We prove the practicality of our attack by demonstrating that our attack can lead five major web browsers to accept a cookie without any cookie flags. We thus present a mitigation strategy for the transport layer to preserve cookie security against our attack.

As the number of Internet of Things (IoT) devices proliferates, the magnitude and velocity of data continues to increase rapidly. IoT systems rely primarily on using messaging protocols for exchanging IoT data and there exists several protocols or frameworks that support distinct types of messaging patterns. Given that IoT devices typically have limited computational resources and processing power, choosing a lightweight, reliable, scalable, interoperable, extensible and secure messaging protocol becomes a very challenging task. As a result, it is not uncommon that IoT systems may employ multiple messaging protocols for supporting device heterogeneity and different message exchange patterns. In addition, basic similarities among existing several messaging protocols or frameworks that exist today for exchanging IoT data within IoT systems suggest the potential of interoperability. Given that IoT systems help facilitate the interconnectivity among distributed, heterogeneous entities, interoperability among existing messaging protocols will play an increasingly important role in simplifying the development and deployment of IoT systems. In this paper, we present a comprehensive review of the existing messaging protocols that can be used in deploying IoT systems. Throughout this paper, we highlight the protocols' distinctive approaches and applicability of using them across various IoT environments. In addition, we highlight challenges, strengths and weaknesses of these messaging protocols in the context of IoT.

Multipath-based hypertext transfer protocol (HTTP) adaptive streaming (MPHAS) has been studied due to the increasing use of mobile devices equipped with multiple network interfaces and the prevalence of high-quality video streaming services. However, the existing MPHAS schemes undergo a degraded quality of experience (QoE) in multiple wireless networks. The segment request-based MPHAS (SR-MPHAS) encounters frequent quality switching, and the block request-based MPHAS (BR-MPHAS) causes results in playback stalling and inefficient bandwidth utilization, according to slow responsiveness. In this paper, we propose a dynamic block-based MPHAS (DBAS) to improve the QoE by overcoming the limitations of the existing schemes in multiple wireless networks. We propose buffer-based block length adaptation and QoE-based block quality adaptation to reduce the frequency of quality switching and to improve the responsiveness to network changes. Moreover, we propose a partial request-based block scheduler to mitigate segment reordering. The experimental results show that the DBAS improves the QoE by reducing the quality switching frequency and rapidly adapting to abrupt changes in the bandwidth.