Biblio

Currently, the pulse position modulation (PPM) schemes are suffering from bandwidth application where the line rate is double that of the initial data rate. Thus, the offset pulse position modulation (OPPM) has been suggested to rectify this concern. Several attempts to improve the OPPM can be found in the open literature. This study focuses on the utilization of Reed Solomon (RS) codes to enhance the forward error correction (FEC) bit error rate, which is not yet explored. The performance of errors of the uncoded OPPM was compared to the one used by RS coded OPPM using the number of photons per pulse, the transmission's efficacy, and bandwidth growth. The results demonstrate that employing FEC coding would increase the system's error performance especially when the RS is operating at its finest settings. Specifically, when operating with a capacity that is equivalent to or even more 0.7, the OPPM with RS code outperforms the uncoded OPPM where the OPPM with MLSD needs only 1.2×103 photons per pulse with an ideal coding rate of about 3/4.

The suggested IsoQuadratic Exponentiation Randomized isocryptosystem design is the unique approach for public key encipher algorithm using IsoPartial Discrete Logarithm Problem and preservation of the recommended IsoQuadratic Exponentiation Randomized isocryptosystem be established against hardness of IsoPartial Discrete Logarithm Problem. Therewith, we demonstrated the possibility of an additional secured algorithm. The offered unique IsoQuadratic Exponentiation Randomized isocryptosystem is suitable for low bandwidth transmission, low storage and low numeration in cyberspace.

Information leaks are a top concern to industry and government leaders. The Internet of Things (IoT) is a rapidly growing technology capable of sensing real-world events. IoT devices lack a common security standard and typically use lightweight security solutions, exposing the sensitive real-world data they gather. Covert channels are a practical method of exfiltrating data from these devices.This research presents a novel IoT covert timing channel (CTC) that encodes data within preexisting network information, namely ports or addresses. This method eliminates the need for inter-packet delays (IPD) to encode data. Seven different encoding methods are implemented between two IoT protocols, TCP/IP and ZigBee. The TCP/IP covert channel is created by mimicking a Ring smart doorbell and implemented using Amazon Web Services (AWS) servers to generate traffic. The ZigBee channel is built by copying a Philips Hue lighting system and executed on an isolated local area network (LAN). Variants of the CTC focus either on Stealth or Bandwidth. Stealth methods mimic legitimate traffic captures to make them difficult to detect while the Bandwidth methods forgo this approach for maximum throughput. Detection results are presented using shape-based and regularity-based detection tests.The Stealth results have a throughput of 4.61 bits per second (bps) for TCP/IP and 3.90 bps for ZigBee. They also evade shape and regularity-based detection tests. The Bandwidth methods average 81.7 Kbps for TCP/IP and 9.76 bps for ZigBee but are evident in detection tests. The results show that CTC using address or port encoding can have superior throughput or detectability compared to IPD-based CTCs.

A weather radar is expected to provide information about weather conditions in real time and valid. To obtain these results, weather radar takes a lot of data samples, so a large amount of data is obtained. Therefore, the weather radar equipment must provide bandwidth for a large capacity for transmission and storage media. To reduce the burden of data volume by performing compression techniques at the time of data acquisition. Compressive Sampling (CS) is a new data acquisition method that allows the sampling and compression processes to be carried out simultaneously to speed up computing time, reduce bandwidth when passed on transmission media, and save storage media. There are three stages in the CS method, namely: sparsity transformation using the Discrete Cosine Transform (DCT) algorithm, sampling using a measurement matrix, and reconstruction using the Orthogonal Matching Pursuit (OMP) algorithm. The sparsity transformation aims to convert the representation of the radar signal into a sparse form. Sampling is used to extract important information from the radar signal, and reconstruction is used to get the radar signal back. The data used in this study is the real data of the IDRA beat signal. Based on the CS simulation that has been done, the best PSNR and RMSE values are obtained when using a CR value of two times, while the shortest computation time is obtained when using a CR value of 32 times. CS simulation in a sector via DCT using the CR value two times produces a PSNR value of 20.838 dB and an RMSE value of 0.091. CS simulation in a sector via DCT using the CR value 32 times requires a computation time of 10.574 seconds.

Smart Security Solutions are in high demand with the ever-increasing vulnerabilities within the IT domain. Adjusting to a Work-From-Home (WFH) culture has become mandatory by maintaining required core security principles. Therefore, implementing and maintaining a secure Smart Home System has become even more challenging. ARGUS provides an overall network security coverage for both incoming and outgoing traffic, a firewall and an adaptive bandwidth management system and a sophisticated CCTV surveillance capability. ARGUS is such a system that is implemented into an existing router incorporating cloud and Machine Learning (ML) technology to ensure seamless connectivity across multiple devices, including IoT devices at a low migration cost for the customer. The aggregation of the above features makes ARGUS an ideal solution for existing Smart Home System service providers and users where hardware and infrastructure is also allocated. ARGUS was tested on a small-scale smart home environment with a Raspberry Pi 4 Model B controller. Its intrusion detection system identified an intrusion with 96% accuracy while the physical surveillance system predicts the user with 81% accuracy.

Wireless-fidelity (Wi-Fi) and Bluetooth are examples of modern wireless communication technologies that employ radio waves as the primary channel for data transmission. but it ought to find alternatives over the limitation and interference in the radio frequency (RF) band. For viable alternatives, visible light communication (VLC) technology comes to play as Light Fidelity (Li-Fi) which uses visible light as a channel for delivering very high-speed communication in a Wi-Fi way. In terms of availability, bandwidth, security and efficiency, Li-Fi is superior than Wi-Fi. In this paper, we present a Li-Fi-based indoor communication system. prototype model has been proposed for single user scenario using visible light portion of electromagnetic spectrum. This system has been designed for audio data communication in between the users in transmitter and receiver sections. LED and photoresistor have been used as optical source and receiver respectively. The electro-acoustic transducer provides the required conversion of electrical-optical signal in both ways. This system might overcome problems like radio-frequency bandwidth scarcity However, its major problem is that it only works when it is pointed directly at the target.

In Forward Error Correction (FEC), redundant bits are added for detecting and correcting bit error which increases the bandwidth. To solve this issue we combined FEC method with higher order M-ary modulation to provide a bandwidth efficient system. An input bit stream is mapped to a bi-orthogonal code on different levels based on the code rates (4/16, 3/16, and 2/16) used. The jamming attack on wireless networks are mitigated by Chaotic Frequency Hopping (CFH) spread spectrum technique. In this paper, to achieve better data rate and to transmit the data in a secured manner we combined FEC and CFH technique, represented as Code and Chaotic Frequency Modulation (CCFM). In addition, two rate adaptation algorithms namely Static retransmission rate ARF (SARF) and Fast rate reduction ARF (FARF) are employed in CFH technique to dynamically adapt the code rate based on channel condition to reduce a packet retransmission. Symbol Error Rate (SER) performance of the system is analyzed for different code rate with the conventional OFDM in the presence AWGN and Rayleigh channel and the reliability of CFH method is tested under different jammer.

Many applications are bandwidth consuming but may tolerate longer flow completion times. Multipath protocols, such as multipath TCP (MPTCP), can offer bandwidth aggregation and resilience to link failures for such applications, and low priority congestion control (LPCC) mechanisms can make these applications yield to other time-sensitive ones. Properly combining the above two can improve the overall user experience. However, the existing LPCC mechanisms are not adequate for MPTCP. They do not take into account the characteristics of multiple network paths, and cannot ensure fairness among the same priority flows. Therefore, we propose a multipath LPCC mechanism, i.e., Dynamic Coupled Low Extra Delay Background Transport, named DC-LEDBAT. Our scheme is designed based on a standardized LPCC mechanism LEDBAT. To avoid unfairness among the same priority flows, DC-LEDBAT trades little throughput for precisely measuring the minimum delay. Moreover, to be friendly to single-path LEDBAT, our scheme leverages the correlation of the queuing delay to detect whether multiple paths go through a shared bottleneck. Then, DC-LEDBAT couples the congestion window at shared bottlenecks to control the sending rate. We implement DC-LEDBAT in a Linux kernel and experimental results show that DC-LEDBAT can not only utilize the excess bandwidth of MPTCP but also ensure fairness among the same priority flows.

Payment channel hubs (PCHs) constitute a promising solution to the inherent scalability problem of blockchain technologies, allowing for off-chain payments between sender and receiver through an intermediary, called the tumbler. While state-of-the-art PCHs provide security and privacy guarantees against a malicious tumbler, they do so by relying on the scripting-based functionality available only at few cryptocurrencies, and they thus fall short of fundamental properties such as backwards compatibility and efficiency.In this work, we present the first PCH protocol to achieve all aforementioned properties. Our PCH builds upon A2L, a novel cryptographic primitive that realizes a three-party protocol for conditional transactions, where the tumbler pays the receiver only if the latter solves a cryptographic challenge with the help of the sender, which implies the sender has paid the tumbler. We prove the security and privacy guarantees of A2L (which carry over to our PCH construction) in the Universal Composability framework and present a provably secure instantiation based on adaptor signatures and randomizable puzzles. We implemented A2L and compared it to TumbleBit, the state-of-the-art Bitcoin-compatible PCH. Asymptotically, A2L has a communication complexity that is constant, as opposed to linear in the security parameter like in TumbleBit. In practice, A2L requires 33x less bandwidth than TumleBit, while retaining the computational cost (or providing 2x speedup with a preprocessing technique). This demonstrates that A2L (and thus our PCH construction) is ready to be deployed today.In theory, we demonstrate for the first time that it is possible to design a secure and privacy-preserving PCH while requiring only digital signatures and timelock functionality from the underlying scripting language. In practice, this result makes our PCH backwards compatible with virtually all cryptocurrencies available today, even those offering a highly restricted form of scripting language such as Ripple or Stellar. The practical appealing of our construction has resulted in a proof-of-concept implementation in the COMIT Network, a blockchain technology focused on cross-currency payments.

We propose and experimentally demonstrate a compressive sensing scheme based on optical coherent receiver that recovers sparse optical arbitrary signals with an analog bandwidth up to 25GHz. The proposed scheme uses 16x lower sampling rate than the Nyquist theorem and spectral resolution of 24.4MHz.

Satellite networks are booming to provide high-speed and low latency Internet access, but the transport layer becomes one of the main obstacles. Legacy end-to-end TCP is designed for terrestrial networks, not suitable for error-prone, propagation delay varying, and intermittent satellite links. It is necessary to make a clean-slate design for the satellite transport layer. This paper introduces a novel Information-centric Hop-by-Hop transport layer design, INTCP. It carries out hop-by-hop packets retransmission and hop-by-hop congestion control with the help of cache and request-response model. Hop-by-hop retransmission recovers lost packets on hop, reduces retransmission delay. INTCP controls traffic and congestion also by hop. Each hop tries its best to maximize its bandwidth utilization and improves end-to-end throughput. The capability of caching enables asynchronous multicast in transport layer. This would save precious spectrum resources in the satellite network. The performance of INTCP is evaluated with the simulated Starlink constellation. Long-distance communication with more than 1000km is carried out. The results demonstrate that, for the unicast scenario INTCP could reduce 42% one-way delay, 53% delay jitters, and improve 60% throughput compared with the legacy TCP. In multicast scenario, INTCP could achieve more than 6X throughput.

Recently, several Internet of Things Tools have been created, contributing to growing network loads. To refrain from IoT should use the idea of cognitive radio networks because of the lack of bandwidth. This article presents much of the research discusses the distribution of channels and preparation of packets when combining cognitive radio networks with IoT technology and we are further discussing the spectrum-based Features and heterogeneity in cognitive IoT Security. Surveying the research performed in this field reveals that the work performed is still developing. A variety of inventions and experiments are part of its initial phases.

Research has been conducted on wireless network single link failures. However, cascaded link failures due to fraudulent attacks have not received enough attention, whereas this requires solutions. This research developed an enhanced genetic algorithm (EGA) focused on capacity efficiency and fast restoration to rapidly resolve link-link failures. On complex nodes network, this fault-tolerant model was tested for such failures. Optimal alternative routes and the bandwidth required for quick rerouting of video traffic were generated by the proposed model. Increasing cascaded link failures increases bandwidth usage and causes transmission delay, which slows down video traffic routing. The proposed model outperformed popular Dijkstra models, in terms of time complexity. The survived solution paths demonstrate that the proposed model works well in maintaining connectivity despite cascaded link failures and would therefore be extremely useful in pandemic periods on emergency matters. The proposed technology is feasible for current business applications that require high-speed broadband networks.

In the course of the research, the research of discriminatory methods of handling video information resource based on the JPEG platform was carried out. This research showed a high interest of the scientific world in identifying important data at different phases of handling. However, the discriminatory handling of the video information resource after the quantization phase is not well understood. Based on the research data, the goal is to find possible ways to operation a video information resource based on a JPEG platform in order to identify important data in a telecommunications system. At the same time, the proposed strategies must provide the required pace of dynamic picture grade and hiding in the context of limited bandwidth. The fulfillment of the condition with limited bandwidth is achieved through the use of a lossless compression algorism based on arithmetic coding. The purpose of the study is considered to be achieved if the following requirements are met:1.Reduction of the volume of dynamic pictures by 30% compared to the initial amount;2.The quality pace is confirmed by an estimate of the peak signal-to-noise ratio for an authorized user, which is Ψauthor ≥ 20 dB;3.The pace of hiding is confirmed by an estimate of the peak signal-to-noise ratio for unauthorized access, which is Ψunauthor ≤ 9 dBThe first strategy is to use encryption tables. The advantage of this strategy is its high hiding strength.The second strategy is the important matrix method. The advantage of this strategy is higher performance.Thus, the goal of the study on the development of possible ways of handling a video information resource based on a JPEG platform in order to identify important data in a telecommunication system with the given requirements is achieved.

The increased demand of multimedia leads to shortage of network bandwidth and memory capacity. As a result, image compression is more significant for decreasing data redundancy, saving storage space and bandwidth. Along with the compression the next major challenge in this field is to safeguard the compressed data further from the spy which are commonly known as hackers. It is evident that the major increments in the fields like communication, wireless sensor network, data science, cloud computing and machine learning not only eases the operations of the related field but also increases the challenges as well. This paper proposes a worthy composition for image compression encryption based on unsupervised learning i.e. k-means clustering for compression with logistic chaotic map for encryption. The main advantage of the above combination is to address the problem of data storage and the security of the visual data as well. The algorithm reduces the size of the input image and also gives the larger key space for encryption. The validity of the algorithm is testified with the PSNR, MSE, SSIM and Correlation coefficient.

In this paper, we focus on Information-Centric Delay-Tolerant Network (ICDTN), which incorporates the communication paradigm of Information-Centric Networking (ICN) into Delay-Tolerant Networking (DTN). Conventional ICNs adopt a naming scheme that names the content with the content identifier. However, a past study proposed an alternative naming scheme that describes the name of content with the content descriptor. We believe that, in ICDTN, it is more suitable to utilize the approach using the content descriptor. In this paper, we therefore propose keyword-based ICDTN that resolves content requests and deliveries contents based on keywords, i.e., content descriptor, in the request and response messages.

The availability of FPGAs in cloud data centers offers rapid, on-demand access to hardware compute resources that users can configure to their own needs. However, the low-level access to the hardware FPGA and associated resources such as PCIe, SSD, or DRAM also opens up threats of malicious attackers uploading designs that are able to infer information about other users or about the cloud infrastructure itself. In particular, this work presents a new, fast PCIe-contention-based channel that is able to transmit data between different FPGA-accelerated virtual machines with bandwidths reaching 2 kbps with 97% accuracy. This paper further demonstrates that the PCIe receiver circuits are able to not just receive covert transmissions, but can also perform fine-grained monitoring of the PCIe bus or detect different types of activities from other users' FPGA-accelerated virtual machines based on their PCIe traffic signatures. Beyond leaking information across different virtual machines, the ability to monitor the PCIe bandwidth over hours or days can be used to estimate the data center utilization and map the behavior of the other users. The paper also introduces further novel threats in FPGA-accelerated instances, including contention due to shared NVMe SSDs as well as thermal monitoring to identify FPGA co-location using the DRAM modules attached to the FPGA boards. This is the first work to demonstrate that it is possible to break the separation of privilege in FPGA-accelerated cloud environments, and highlights that defenses for public clouds using FPGAs need to consider PCIe, SSD, and DRAM resources as part of the attack surface that should be protected.

Aiming at the working mechanism of optical backbone network, based on the theory of complex network, the invulnerability evaluation index of optical backbone network is extracted from the physical topology of optical backbone network and the degree of bandwidth satisfaction, finally, the invulnerability evaluation model of optical backbone network is established. At the same time, the evaluation model is verified and analyzed with specific cases, through the comparison of 4 types of attack, the results show that the number of deliberate point attacks ( DP) is 16.7% lower than that of random point attacks ( RP) when the critical collapse state of the network is reached, and the number of deliberate edge attacks ( DE) is at least 10.4% lower than that of random edge attacks ( RE). Therefore, evaluating the importance of nodes and edges and strengthening the protection of key nodes and edges can help optical network effectively resist external attacks and significantly improve the anti-damage ability of optical network, which provides theoretical support for the anti-damage evaluation of optical network and has certain practical significance for the upgrade and reconstruction of optical network.

Currently, the technology of wireless mesh networks is actively developing. In 2021, Gartner included mesh network technologies and the tasks to ensure their security in the TOP global trends. A large number of scientific works focus on the research and modeling the traffic transmission in such networks. At the same time, they often bring up the “bottle neck” problem, characteristic of individual mesh network nodes. To address the issue, the authors of the article propose using the data caching mechanism and placing the cache data straight on the routers. The mathematical model presented in the article allows building a route with the highest access speed to the requested content by the modified Dijkstra algorithm. Besides, if the mesh network cache lacks the required content, the routers with the Internet access are applied. Practically, the considered method of creating routes to the content, which has already been requested by the users in the mesh network, allows for the optimal efficient use of the router bandwidth capacity distribution and reduces the latency period.

K-nearest neighbor algorithm that searches the K closest samples in a high dimensional feature space is one of the most fundamental tasks in machine learning and image retrieval applications. Computational storage device that combines computing unit and storage module on a single board becomes popular to address the data bandwidth bottleneck of the conventional computing system. In this paper, we propose a nearest neighbor search acceleration platform based on computational storage device, which can process a large-scale image dataset efficiently in terms of speed, energy, and cost. We believe that the proposed acceleration platform is promising to be deployed in cloud datacenters for data-intensive applications.

In this article we have developed a simulation model in the Mininet environment for analyzing the operation of a software-defined network (SDN) in cloud data centers. The results of the simulation model of the operation of the SDN network on the Mininet emulator and the results of the simulation of the traditional network in the Graphical Network Simulator 3 emulator are presented.

Cloud computing adoption is on the rise. Many organizations have decided to shift their workload to the cloud to benefit from the scalability, resilience, and cost reduction characteristics. Mobile Cloud Computing (MCC) is an emerging computing paradigm that also provides many advantages to mobile users. Mobile devices function on wireless internet connectivity, which entails issues of limited bandwidth and network congestion. Hence, the primary focus of Web applications in MCC is on improving performance by quickly fulfilling customer's requests to improve service satisfaction. This paper investigates a new approach to caching data in these applications using Redis, an in-memory data store, to enhance Quality of Service. We highlight the two implementation approaches of fetching the data of an application either directly from the database or from the cache. Our experimental analysis shows that, based on performance metrics such as response time, throughput, latency, and number of hits, the caching approach achieves better performance by speeding up the data retrieval by up to four times. This improvement is of significant importance in mobile devices considering their limitation of network bandwidth and wireless connectivity.

Anonymous Zether, proposed by Bünz, Agrawal, Zamani, and Boneh (FC'20), is a private payment design whose wallets demand little bandwidth and need not remain online; this unique property makes it a compelling choice for resource-constrained devices. In this work, we describe an efficient construction of Anonymous Zether. Our protocol features proofs which grow only logarithmically in the size of the "anonymity sets" used, improving upon the linear growth attained by prior efforts. It also features competitive transaction sizes in practice (on the order of 3 kilobytes).Our central tool is a new family of extensions to Groth and Kohlweiss's one-out-of-many proofs (Eurocrypt 2015), which efficiently prove statements about many messages among a list of commitments. These extensions prove knowledge of a secret subset of a public list, and assert that the commitments in the subset satisfy certain properties (expressed as linear equations). Remarkably, our communication remains logarithmic; our computation increases only by a logarithmic multiplicative factor. This technique is likely to be of independent interest.We present an open-source, Ethereum-based implementation of our Anonymous Zether construction.

With fast growing research in the area of application partitioning for offloading, determining which devices to prioritize over the other for mobile code offloading is fundamental. Multiple methods can be adopted using both single-criterion and multiple-criteria strategies. Due to the characteristics of pervasive environments, whereby devices having different computing capability, different level of privacy and security and the mobility nature in such environment makes the decision-making process complex. To this end, this paper proposes a method using a combination of the method Analytic Hierarchy Process (AHP) to calculate weights criteria of participating devices. Next the fuzzy technique for order preference by similarity to ideal solution (TOPSIS) is considered to sort in order of priority the participating devices, hence facilitating the decision to opt for which participating device first. An evaluation of the method is also presented.

VANET plays a vital role to optimize the journey between source and destination in the growth of smart cities worldwide. The crucial information shared between vehicles is concerned primarily with safety. VANET is a MANET sub-class network that provides a free movement and communication between the RSU and vehicles. The self organized with high mobility in VANET makes any vehicle can transmit malicious messages to some other vehicle in the network. In the defense horizon of VANETs this is a matter of concern. It is the duty of RSU to ensure the safe transmission of sensitive information across the Network to each node. For this, network access exists as the key safety prerequisite, and several risks or attacks can be experienced. The VANETs is vulnerable to a range of security attacks including masquerading, selfish node attack, Sybil attack etc. One of the main threats to network access is this Denial of Service attack. The most important research in the literature on the prevention of Denial of Service Attack in VANETs was explored in this paper. The limitations of each reviewed paper are also presented and Game theory based security model is defined in this paper.