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The development of an electronic voting system that would replace traditional election procedures is a research topic of great interest for many years. Blockchain technology could provide some guarantees and fulfill strong requirements for electronic voting platforms, such as transparency, immutability, and confidentiality. From time to time research is conducted to address problems in voting systems. Many research works attempt to implement secure and reliable voting systems, which address known security, anonymity, and fraud issues that might threaten such systems. This paper presents a proposal of a secure electronic voting system, the EtherVote, using the Ethereum Blockchain network that focuses deeply on the field of identification of eligible citizens. The proposed system will be entirely based on Blockchain without any central authority servers or databases, thus improving security, privacy, and election cost. Limitations, problems, and solutions are discussed, in order to make the proposed electronic voting system ideal and ready to use for national elections., 2 pages, Poster presented in ACM 5th summit on Gender Equality in Computing, GEC 2023, Athens University of Economics and Business, Athens, Greece, 27 June 2023

A previously unknown form of compromising emanations has been discovered. LED status indicators on data communication equipment, under certain conditions, are shown to carry a modulated optical signal that is significantly correlated with information being processed by the device. Physical access is not required; the attacker gains access to all data going through the device, including plaintext in the case of data encryption systems. Experiments show that it is possible to intercept data under realistic conditions at a considerable distance. Many different sorts of devices, including modems and Internet Protocol routers, were found to be vulnerable. A taxonomy of compromising optical emanations is developed, and design changes are described that will successfully block this kind of "Optical TEMPEST" attack., 26 pages, 11 figures

Modern heterogeneous supercomputing systems are comprised of CPUs, GPUs, and high-speed network interconnects. Communication libraries supporting efficient data transfers involving memory buffers from the GPU memory typically require the CPU to orchestrate the data transfer operations. A new offload-friendly communication strategy, stream-triggered (ST) communication, was explored to allow offloading the synchronization and data movement operations from the CPU to the GPU. A Message Passing Interface (MPI) one-sided active target synchronization based implementation was used as an exemplar to illustrate the proposed strategy. A latency-sensitive nearest neighbor microbenchmark was used to explore the various performance aspects of the implementation. The offloaded implementation shows significant on-node performance advantages over standard MPI active RMA (36%) and point-to-point (61%) communication. The current multi-node improvement is less (23% faster than standard active RMA but 11% slower than point-to-point), but plans are in progress to purse further improvements., 12 pages, 17 figures

We consider distributed algorithms in the realistic scenario where distributed message passing is operated via circuits. We show that within this setting, modal substitution calculus MSC captures the expressive power of circuits. The translations between circuits and MSC-programs are linear in both directions. Furthermore, we show that the colouring algorithm based on Cole-Vishkin can be specified via logarithmic size programs.

Recent advances in web technologies make it more difficult than ever to detect and block web tracking systems. In this work, we propose ASTrack, a novel approach to web tracking detection and removal. ASTrack uses an abstraction of the code structure based on Abstract Syntax Trees to selectively identify web tracking functionality shared across multiple web services. This new methodology allows us to: (i) effectively detect web tracking code even when using evasion techniques (e.g., obfuscation, minification, or webpackaging); and (ii) safely remove those portions of code related to tracking purposes without affecting the legitimate functionality of the website. Our evaluation with the top 10k most popular Internet domains shows that ASTrack can detect web tracking with high precision (98%), while discovering about 50k tracking code pieces and more than 3,400 new tracking URLs not previously recognized by most popular privacy-preserving tools (e.g., uBlock Origin). Moreover, ASTrack achieved a 36% reduction in functionality loss in comparison with the filter lists, one of the safest options available. Using a novel methodology that combines computer vision and manual inspection, we estimate that full functionality is preserved in more than 97% of the websites., This paper has been accepted for publication at IEEE INFOCOM 2023. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses

Accurate localization of a large number of objects over a wide area is one of the keys to the pervasive interaction with the Internet of Things. This paper presents Hawkeye, a new mmWave backscatter that, for the first time, offers over (i) hundred-scale simultaneous 3D localization at (ii) subcentimeter accuracy for over an (iii) hectometer distance. Hawkeye generally applies to indoors and outdoors as well as under mobility. Hawkeye tag's Van Atta Array design with retro-reflectivity in both elevation and azimuth planes offers 3D localization and effectively suppresses the multipath. Hawkeye localization algorithm is a lightweight signal processing compatible with the commodity FMCW radar. It uniquely leverages the interplay between the tag signal and clutter, and leverages the spetral leakage for fine-grained positioning. Prototype evaluations in corridor, lecture room, and soccer field reveal 6.7 mm median accuracy at 160 m range, and simultaneously localizes 100 tags in only 33.2 ms. Hawkeye is reliable under temperature change with significant oscillator frequency offset., Submitted to ACM MobiSys '23

This article shows a brief history of Techno-Economic Assessment (TEA) in Communications, a proposed redefinition of TEA as well as the new challenges derived from a dynamic context with cloud-native virtualized networks, the Helium Network & alike blockchain-based decentralized networks, the new network as a platform (NaaP) paradigm, carbon pricing, network sharing, and web3, metaverse and blockchain technologies. The authors formulate the research question and show the need to improve TEA models to integrate and manage all this increasing complexity. This paper also proposes the characteristics TEA models should have and their current degree of compliance for several use cases: 5G and beyond, software-defined wide area network (SD-WAN), secure access service edge (SASE), secure service edge (SSE), and cloud cybersecurity risk assessment. The authors also present TEA extensibility to request for proposals (RFP) processes and other industries, to conclude that there is an urgent need for agile and effective TEA in Comms that allows industrialization of agile decision-making for all market stakeholders to choose the optimal solution for any technology, scenario and use case., 18 pages, 1 figure, 2 tables

Bluetooth is a communication technology used to wirelessly exchange data between devices. In the last few years there have been found a great number of security vulnerabilities, and adversaries are taking advantage of them causing harm and significant loss. Numerous system security updates have been approved and installed in order to sort out security holes and bugs, and prevent attacks that could expose personal or other valuable information. But those updates are not sufficient and appropriate and new bugs keep showing up. In Bluetooth technology, pairing is identified as the step where most bugs are found and most attacks target this particular process part of Bluetooth. A new technology that has been proved bulletproof when it comes to security and the exchange of sensitive information is Blockchain. Blockchain technology is promising to be incorporated well in a network of smart devices, and secure an Internet of Things (IoT), where Bluetooth technology is being extensively used. This work presents a vulnerability discovered in Bluetooth pairing process, and proposes a Blockchain solution approach to secure pairing and mitigate this vulnerability. The paper first introduces the Bluetooth technology and delves into how Blockchain technology can be a solution to certain security problems. Then a solution approach shows how Blockchain can be integrated and implemented to ensure the required level of security. Certain attack incidents on Bluetooth vulnerable points are examined and discussion and conclusions give the extension of the security related problems., 7 pages, 6 figures

Event processing is the cornerstone of the dynamic and responsive Internet of Things (IoT). Recent approaches in this area are based on representational state transfer (REST) principles, which allow event processing tasks to be placed at any device that follows the same principles. However, the tasks should be properly distributed among edge devices to ensure fair resources utilization and guarantee seamless execution. This article investigates the use of deep learning to fairly distribute the tasks. An attention-based neural network model is proposed to generate efficient load balancing solutions under different scenarios. The proposed model is based on the Transformer and Pointer Network architectures, and is trained by an advantage actor-critic reinforcement learning algorithm. The model is designed to scale to the number of event processing tasks and the number of edge devices, with no need for hyperparameters re-tuning or even retraining. Extensive experimental results show that the proposed model outperforms conventional heuristics in many key performance indicators. The generic design and the obtained results show that the proposed model can potentially be applied to several other load balancing problem variations, which makes the proposal an attractive option to be used in real-world scenarios due to its scalability and efficiency., 19 pages, 6 figures

The progression of innovation and technology and ease of inter-connectivity among networks has allowed us to evolve towards one of the promising areas, the Internet of Vehicles. Nowadays, modern vehicles are connected to a range of networks, including intra-vehicle networks and external networks. However, a primary challenge in the automotive industry is to make the vehicle safe and reliable; particularly with the loopholes in the existing traditional protocols, cyber-attacks on the vehicle network are rising drastically. Practically every vehicle uses the universal Controller Area Network (CAN) bus protocol for the communication between electronic control units to transmit key vehicle functionality and messages related to driver safety. The CAN bus system, although its critical significance, lacks the key feature of any protocol authentication and authorization. Resulting in compromises of CAN bus security leads to serious issues to both car and driver safety. This paper discusses the security issues of the CAN bus protocol and proposes an Intrusion Detection System (IDS) that detects known attacks on in-vehicle networks. Multiple Artificial Intelligence (AI) algorithms are employed to provide recognition of known potential cyber-attacks based on messages, timestamps, and data packets traveling through the CAN. The main objective of this paper is to accurately detect cyberattacks by considering time-series features and attack frequency. The majority of the evaluated AI algorithms, when considering attack frequency, correctly identify known attacks with remarkable accuracy of more than 99%. However, these models achieve approximately 92% to 97% accuracy when timestamps are not taken into account. Long Short Term Memory (LSTM), Xgboost, and SVC have proved to the well-performing classifiers.

In recent years, 5G network systems start to offer communication infrastructure for Internet of Things (IoT) applications, especially for health care service pro-viders. In smart health care systems, edge computing enabled Internet of Medical Things (IoMT) is an innovative technology to provide online health care monitor-ing facility to patients. Here, energy consumption, along with extending the lifespan of biosensor network, is a key concern. In this contribution, a Chicken Swarm Optimization algorithm, based on Energy Efficient Multi-objective clus-tering scheme is applied in the context of IoMT system. An effective fitness func-tion is designed for cluster head selection., using multiple objectives, such as re-sidual energy, queuing delay, communication cost, link quality and node centrali-ty. Simulated outcomes of the proposed scheme are compared with the existing schemes in terms of parameters such as cluster formation time, energy consump-tion, network lifetime, throughput and propagation delay.

This paper is a summary of the findings from a series of workshops which were held by Thinknet 6G and MUENCHNER KREIS in 2021, with the goal to provide orientation and input for developing a strategic 6G research plan. The topics selected for the workshops are aspects of 6G that we expect will have a significant impact on other industries and on society: - 6G as both a communication infrastructure and a sensing infrastructure - The extensive use of artificial intelligence in 6G - The security and resilience of 6G This paper does not go into the technical details of how to develop and implement 6G. Rather, it provides input from experts from both the wireless industry as well as from other sectors about (mostly) non-technical topics that will need to be addressed in parallel with the technical developments, such as new use cases, regulation, communication with the public, and cross-industry cooperation. We have identified six areas that will have a significant impact on the development and use of 6G, and that organizations must consider as they begin their plans and designs for 6G. Based on these six impact areas and on the discussion in the workshops, we compiled a list of the top 10 recommendations for specific areas where organizations should place their focus when developing their strategic plan for 6G. In addition, for our readers who are involved in 6G research, be it at a university, at a research institute or in industrial research, we also included a summary of the top 10 areas that require additional research, again based on the input received in the workshops. A version of this paper is also available at www.thinknet-6g.de. If you had a copy of the preview version of this paper, the text is exactly the same. Only the layout and graphics have changed., 20 pages, 1 figure

This paper describes the Swapped Dragonfly. It is a two-parameter family of diameter three interconnection networks, D3(K,M), which are linearly scalable in M. Although D3(K,M) is a Dragonfly, it differs from standard Dragonflies in many respects. It has a K by M by M coordinate system (c;d; p). The routers (c,d,p) and (c',p,d) are globally connected using a swap of p and d. If L < K and/or N < M, D3(K;M) contains D3(L,N). The coordinate system enables source vector routing on D3(K,M). A source-vector induces KM squared parallel paths on D3(K,M). Because of this, the Swapped Dragonfly can support conflict-free parallelism over local ports, global ports, routers and source-vectors. In particular, there is an all-to-all algorithm which is not a pairwise exchange algorithm. Keywords: interconnection network, Dragonfly network, swapped network, source-vector routing, all-to-all exchange, 20 pages 3 figures

International audience; This paper proposes a cascade blockage model for analyzing the vision that a user has of a wireless network. This model, inspired by the classical multiplicative cascade models, has a radial structure meant to analyze blockages seen by the receiver at the origin in different angular sectors. The main novelty is that it is based on the geometry of obstacles and takes the joint blockage phenomenon into account. We show on a couple of simple instances that the Laplace transforms of total interference satisfies a functional equation that can be solved efficiently by an iterative scheme. This is used to analyze the coverage probability of the receiver and the effect of blockage correlation and penetration loss in both dense and sparse blockage environments. Furthermore, this model is used to investigate the effect of blockage correlation on user beamforming techniques. Another functional equation and its associated iterative algorithm are proposed to derive the coverage performance of the best beam selection in this context. In addition, the conditional coverage probability is also derived to evaluate the effect of beam switching. The results not only show that beam selection is quite efficient for multi-beam terminals, but also show how the correlation brought by blockages can be leveraged to accelerate beam sweeping and pairing.

Similarity caching systems have recently attracted the attention of the scientific community, as they can be profitably used in many application contexts, like multimedia retrieval, advertising, object recognition, recommender systems and online content-match applications. In such systems, a user request for an object o , which is not in the cache, can be (partially) satisfied by a similar stored object o ’, at the cost of a loss of user utility. In this paper we make a first step into the novel area of similarity caching networks, where requests can be forwarded along a path of caches to get the best efficiency–accuracy tradeoff. The offline problem of content placement can be easily shown to be NP-hard, while different polynomial algorithms can be devised to approach the optimal solution in discrete cases. As the content space grows large, we propose a continuous problem formulation whose solution exhibits a simple structure in a class of tree topologies. We verify our findings using synthetic and realistic request traces.

The internet has become a critical communications infrastructure, and access is among the ``assets, systems, and networks, whether physical or virtual, [that] are considered so vital to the United States that their incapacitation or destruction would have a debilitating effect on security, national economic security, national public health or safety, or any combination thereof.'' [CISA] But the internet is more than an issue for the nation as a whole. Internet access affects the security, health, safety, and opportunities in life for individuals and communities, and the economic vitality of businesses everywhere. On the one hand, the COVID-19 pandemic has revealed the success of broadband access in allowing society to function, even during lockdowns. On the other hand, the pandemic has exposed weak, unreliable, or even nonexistent, broadband access and usability in many areas and for many individuals, including especially rural residents and children in many school districts, urban, and rural, as well as a compelling need for universal reach and affordability. It was thus timely that in November 2020, the National Science Foundation (NSF) sponsored a series of workshops to identify new research areas to drive the broadband NSF agenda for the next five years. This request followed similar initiatives during the past twenty years, the most recent in 2016. This Broadband Research Workshop Report of 2021 discusses the research questions and challenges that need to be addressed to provide robust, affordable, and meaningful broadband access to every resident of the United States.

We study age-agnostic scheduling in a non-preemptive status update system with two sources sending time-stamped information packets at random instances to a common monitor through a single server. The server is equipped with a waiting room holding the freshest packet from each source called "single-buffer per-source queueing". The server is assumed to be work-conserving and when the waiting room has two waiting packets (one from each source), a probabilistic scheduling policy is applied so as to provide Age of Information (AoI) differentiation for the two sources of interest. Assuming Poisson packet arrivals and exponentially distributed service times, the exact distributions of AoI and also Peak AoI (PAoI) for each source are first obtained. Subsequently, this analytical tool is used to numerically obtain the optimum probabilistic scheduling policy so as to minimize the weighted average AoI/PAoI by means of which differentiation can be achieved between the two sources. In addition, a pair of heuristic age-agnostic schedulers are proposed on the basis of heavy-traffic analysis and comparatively evaluated in a wide variety of scenarios, and guidelines are provided for scheduling and AoI differentiation in status update systems with two sources., 14 pages, 7 figures, 2 tables

Packet replication and elimination functions are used by time-sensitive networks (as in the context of IEEE TSN and IETF DetNet) to increase the reliability of the network. Packets are replicated onto redundant paths by a replication function. Later the paths merge again and an elimination function removes the duplicates. This redundancy scheme has an effect on the timing behavior of time-sensitive networks and many challenges arise from conducting timing analyses. The replication can induce a burstiness increase along the paths of replicates, as well as packet mis-ordering that could increase the delays in the crossed bridges or routers. The induced packet mis-ordering could also negatively affect the interactions between the redundancy and scheduling mechanisms such as traffic regulators (as with per-flow regulators and interleaved regulators, implemented by TSN asynchronous traffic shaping). Using the network calculus framework, we provide a method of worst-case timing analysis for time-sensitive networks that implement redundancy mechanisms in the general use case, i.e., at end-devices and/or intermediate nodes. We first provide a network calculus toolbox for bounding the burstiness increase and the amount of reordering caused by the elimination function of duplicate packets. We then analyze the interactions with traffic regulators and show that their shaping-for-free property does not hold when placed after a packet elimination function. We provide a bound for the delay penalty when using per-flow regulators and prove that the penalty is not bounded with interleaved regulators. Finally, we use an industrial use-case to show the applicability and the benefits of our findings., published

We consider the problem of video caching across a set of 5G small-cell base stations (SBS) connected to each other over a high-capacity short-delay back-haul link, and linked to a remote server over a long-delay connection. Even though the problem of minimizing the overall video delivery delay is NP-hard, the Collaborative Caching Algorithm (CCA) that we present can efficiently compute a solution close to the optimal, where the degree of sub-optimality depends on the worst case video-to-cache size ratio. The algorithm is naturally amenable to distributed implementation that requires zero explicit coordination between the SBSs, and runs in $O(N + K \log K)$ time, where $N$ is the number of SBSs (caches) and $K$ the maximum number of videos. We extend CCA to an online setting where the video popularities are not known a priori but are estimated over time through a limited amount of periodic information sharing between SBSs. We demonstrate that our algorithm closely approaches the optimal integral caching solution as the cache size increases. Moreover, via simulations carried out on real video access traces, we show that our algorithm effectively uses the SBS caches to reduce the video delivery delay and conserve the remote server's bandwidth, and that it outperforms two other reference caching methods adapted to our system setting., 11 pages, 10 figures, WiOpt 2021

The rapidly increasing number of smart devices on the Internet necessitates an efficient inspection system for safeguarding our networks from suspicious activities such as Address Resolution Protocol (ARP) probes. In this research, we analyze sequence data of ARP traffic on LAN based on the numerical count and degree of its packets. Moreover, a dynamic threshold is employed to detect underlying suspicious activities, which are further converted into feature vectors to train an unsupervised autoencoder neural network. Then, we leverage K-means clustering to separate the extracted latent features of suspicious activities from the autoencoder into various patterns. Besides, to evaluate the performance, we collect and adopt a real-world network traffic dataset from five different LANs. At last, we successfully detect suspicious ARP patterns varying in scale, lifespan, and regularity on the LANs., 5 pages, 7 figures, submitted to 2022 IEEE Consumer Communications & Networking Conference

Several encryption proposals for DNS have been presented since 2016, but their adoption was not comprehensively studied yet. This research measured the current adoption of DoH (DNS over HTTPS), DoT (DNS over TLS), and DoQ (DNS over QUIC) for five months at the beginning of 2021 by three different organizations with global coverage. By comparing the total values, amount of requests per user, and the seasonality of the traffic, it was possible to obtain the current adoption trends. Moreover, we actively scanned the Internet for still-unknown working DoH servers and we compared them with a novel curated list of well-known DoH servers. We conclude that despite growing in 2020, during the first five months of 2021 there was statistically significant evidence that the average amount of Internet traffic for DoH, DoT and DoQ remained stationary. However, we found that the amount of, still unknown and ready to use, DoH servers grew 4 times. These measurements suggest that even though the amount of encrypted DNS is currently not growing, there may probably be more connections soon to those unknown DoH servers for benign and malicious purposes., 16 pages, 10 figures

The present paper shows a proposal of the characteristics Cloud Risk Assessment Models should have and presents the review of the literature considering those characteristics in order to identify current gaps. This work shows a ranking of Cloud RA models and their degree of compliance with the theoretical reference Cloud Risk Assessment model. The review of literature shows that RA approaches leveraging CSA (Cloud Security Alliance) STAR Registry that have into account organizations security requirements present higher degree of compliance, but they still lack risk economic quantification. The myriad of conceptual models, methodologies and frameworks although based on current NIST SP 800:30, ISO 27001, ISO 27005, ISO 30001, ENISA standards could be enhanced by the use of techno-economic models like UTEM, created by the author, in order to conceive more simplified models for effective Risk Assessment and Mitigation closer to the theoretical reference model for Cloud Risk Assessment, available for all cloud models (IaaS, PaaS, SaaS) and easy to use for all stakeholders., 12 pages, 5 figures, 2 tables

Secure Device-to-Device (D2D) communication is becoming increasingly important with the ever-growing number of Internet-of-Things (IoT) devices in our daily life. To achieve secure D2D communication, the key agreement between different IoT devices without any prior knowledge is becoming desirable. Although various approaches have been proposed in the literature, they suffer from a number of limitations, such as low key generation rate and short pairing distance. In this paper, we present InaudibleKey, an inaudible acoustic signal-based key generation protocol for mobile devices. Based on acoustic channel reciprocity, InaudibleKey exploits the acoustic channel frequency response of two legitimate devices as a common secret to generating keys. InaudibleKey employs several novel technologies to significantly improve its performance. We conduct extensive experiments to evaluate the proposed system in different real environments. Compared to state-of-the-art works, InaudibleKey improves key generation rate by 3-145 times, extends pairing distance by 3.2-44 times, and reduces information reconciliation counts by 2.5-16 times. Security analysis demonstrates that InaudibleKey is resilient to a number of malicious attacks. We also implement InaudibleKey on modern smartphones and resource-limited IoT devices. Results show that it is energy-efficient and can run on both powerful and resource-limited IoT devices without incurring excessive resource consumption., Comment: 13 pages, 11 figures, IPSN 2021

High-performance computing (HPC) researchers have long envisioned scenarios where application workflows could be improved through the use of programmable processing elements embedded in the network fabric. Recently, vendors have introduced programmable Smart Network Interface Cards (SmartNICs) that enable computations to be offloaded to the edge of the network. There is great interest in both the HPC and high-performance data analytics communities in understanding the roles these devices may play in the data paths of upcoming systems. This paper focuses on characterizing both the networking and computing aspects of NVIDIA's new BlueField-2 SmartNIC when used in an Ethernet environment. For the networking evaluation we conducted multiple transfer experiments between processors located at the host, the SmartNIC, and a remote host. These tests illuminate how much processing headroom is available on the SmartNIC during transfers. For the computing evaluation we used the stress-ng benchmark to compare the BlueField-2 to other servers and place realistic bounds on the types of offload operations that are appropriate for the hardware. Our findings from this work indicate that while the BlueField-2 provides a flexible means of processing data at the network's edge, great care must be taken to not overwhelm the hardware. While the host can easily saturate the network link, the SmartNIC's embedded processors may not have enough computing resources to sustain more than half the expected bandwidth when using kernel-space packet processing. From a computational perspective, encryption operations, memory operations under contention, and on-card IPC operations on the SmartNIC perform significantly better than the general-purpose servers used for comparisons in our experiments. Therefore, applications that mainly focus on these operations may be good candidates for offloading to the SmartNIC., 13 pages, 8 figures, 4 tables

Advances in computing have resulted in an emerging need for multi-factor authentication using an amalgamation of cryptographic and physical keys. This letter presents a novel authentication approach using a combination of signal and antenna activation sequences, and most importantly, perturbed antenna array geometries. Possible degrees of freedom in perturbing antenna array geometries affected physical properties and their detection are presented. Channel estimation for the plurality of validly authorized arrays is discussed. Accuracy is investigated as a function of signal-to-noise ratio (SNR) and number of authorized arrays. It is observed that the proposed authentication scheme can provide 1% false authentication rate at 10 dB SNR, while it is achieving less than 1% missed authentication rates., in IEEE Communications Letters

Trigger-action programming (TAP) is a popular end-user programming framework that can simplify the Internet of Things (IoT) automation with simple trigger-action rules. However, it also introduces new security and safety threats. A lot of advanced techniques have been proposed to address this problem. Rigorously reasoning about the security of a TAP-based IoT system requires a well-defined model and verification method both against rule semantics and physical-world features, e.g., concurrency, rule latency, extended action, tardy attributes, and connection-based rule interactions, which has been missing until now. By analyzing these features, we find 9 new types of rule interaction vulnerabilities and validate them on two commercial IoT platforms. We then present TAPInspector, a novel system to detect these interaction vulnerabilities in concurrent TAP-based IoT systems. It automatically extracts TAP rules from IoT apps, translates them into a hybrid model by model slicing and state compression, and performs semantic analysis and model checking with various safety and liveness properties. Our experiments corroborate that TAPInspector is practical: it identifies 533 violations related to rule interaction from 1108 real-world market IoT apps and is at least 60000 times faster than the baseline without optimization.

Machine learning algorithms have been used widely in various applications and areas. To fit a machine learning model into different problems, its hyper-parameters must be tuned. Selecting the best hyper-parameter configuration for machine learning models has a direct impact on the model's performance. It often requires deep knowledge of machine learning algorithms and appropriate hyper-parameter optimization techniques. Although several automatic optimization techniques exist, they have different strengths and drawbacks when applied to different types of problems. In this paper, optimizing the hyper-parameters of common machine learning models is studied. We introduce several state-of-the-art optimization techniques and discuss how to apply them to machine learning algorithms. Many available libraries and frameworks developed for hyper-parameter optimization problems are provided, and some open challenges of hyper-parameter optimization research are also discussed in this paper. Moreover, experiments are conducted on benchmark datasets to compare the performance of different optimization methods and provide practical examples of hyper-parameter optimization. This survey paper will help industrial users, data analysts, and researchers to better develop machine learning models by identifying the proper hyper-parameter configurations effectively., Published in Neurocomputing (Elsevier's journal, Q1, IF: 5.779). Tutorial code has got 1000+ stars. Github link: https://github.com/LiYangHart/Hyperparameter-Optimization-of-Machine-Learning-Algorithms

The problem of MPI programs execution time prediction on a certain set of computer installations is considered. This problem emerges with orchestration and provisioning a virtual infrastructure in a cloud computing environment over a heterogeneous network of computer installations: supercomputers or clusters of servers (e.g. mini data centers). One of the key criteria for the effectiveness of the cloud computing environment is the time staying by the program inside the environment. This time consists of the waiting time in the queue and the execution time on the selected physical computer installation, to which the computational resource of the virtual infrastructure is dynamically mapped. One of the components of this problem is the estimation of the MPI programs execution time on a certain set of computer installations. This is necessary to determine a proper choice of order and place for program execution. The article proposes two new approaches to the program execution time prediction problem. The first one is based on computer installations grouping based on the Pearson correlation coefficient. The second one is based on vector representations of computer installations and MPI programs, so-called embeddings. The embedding technique is actively used in recommendation systems, such as for goods (Amazon), for articles (Arxiv.org), for videos (YouTube, Netflix). The article shows how the embeddings technique helps to predict the execution time of a MPI program on a certain set of computer installations.

Collective communications, namely the patterns allgatherv, reduce_scatter, and allreduce in message-passing systems are optimised based on measurements at the installation time of the library. The algorithms used are set up in an initialisation phase of the communication, similar to the method used in so-called persistent collective communication introduced in the literature. For allgatherv and reduce_scatter the existing algorithms, recursive multiply/divide and cyclic shift (Bruck's algorithm) are applied with a flexible number of communication ports per node. The algorithms for equal message sizes are used with non-equal message sizes together with a heuristic for rank reordering. The two communication patterns are applied in a plasma physics application that uses a specialised matrix-vector multiplication. For the allreduce pattern the cyclic shift algorithm is applied with a prefix operation. The data is gathered and scattered by the cores within the node and the communication algorithms are applied across the nodes. In general our routines outperform the non-persistent counterparts in established MPI libraries by up to one order of magnitude or show equal performance, with a few exceptions of number of nodes and message sizes., accepted at PASC 2020/2021 conference as a poster

Programmable switches have emerged as powerful and flexible alternatives to fixed-function forwarding devices. But because of the unique hardware constraints of network switches, the design and implementation of compilers targeting these devices is tedious and error prone. Despite the important role that compilers play in software development, there is a dearth of tools for testing compilers for programmable network devices. We present Druzhba, a programmable switch simulator used for testing compilers targeting programmable packet-processing substrates. We show that we can model the low-level behavior of a switch's programmable hardware. We further show how our machine model can be used by compiler developers to target Druzhba as a compiler backend. Generated machine code programs are fed into Druzhba and tested using a fuzzing-based approach that allows compiler developers to test the correctness of their compilers. Using a program-synthesis-based compiler as a case study, we demonstrate how Druzhba has been successful in testing compiler-generated machine code for our simulated switch pipeline instruction set., 7 pages, 4 figures

Federated learning (FL) is a distributed machine learning paradigm where data are distributed among clients who collaboratively train a model in a computation process coordinated by a central server. By assigning a weight to each client based on the proportion of data instances it possesses, the rate of convergence to an accurate joint model can be greatly accelerated. Some previous works studied FL in a Byzantine setting, in which a fraction of the clients may send arbitrary or even malicious information regarding their model. However, these works either ignore the issue of data unbalancedness altogether or assume that client weights are a priori known to the server, whereas, in practice, it is likely that weights will be reported to the server by the clients themselves and therefore cannot be relied upon. We address this issue for the first time by proposing a practical weight-truncation-based preprocessing method and demonstrating empirically that it is able to strike a good balance between model quality and Byzantine robustness. We also establish analytically that our method can be applied to a randomly selected sample of client weights.

The Internet of Things (IoT) is emerging as a multi-purpose technology with enormous potential for improving the quality of life in several areas. In particular, IoT has been applied in agriculture to make it more sustainable ecologically. For instance, electronic traps have the potential to perform pest control without any pesticide. In this paper, a smart trap with IoT capabilities that uses computer vision to identify the insect of interest is proposed. The solution includes 1) an embedded system with camera, GPS sensor and motor actuators; 2) an IoT middleware as database service provider, and 3) a Web application to present data by a configurable heat map. The demonstration of proposed solution is exposed and the main conclusions are the perception about pest concentration at the plantation and the viability as alternative pest control over traditional control based on pesticides., 10 pages, 7 figures

Flow reshaping is used in time-sensitive networks (as in the context of IEEE TSN and IETF Detnet) in order to reduce burstiness inside the network and to support the computation of guaranteed latency bounds. This is performed using per-flow regulators (such as the Token Bucket Filter) or interleaved regulators (as with IEEE TSN Asynchronous Traffic Shaping). Both types of regulators are beneficial as they cancel the increase of burstiness due to multiplexing inside the network. It was demonstrated, by using network calculus, that they do not increase the worst-case latency. However, the properties of regulators were established assuming that time is perfect in all network nodes. In reality, nodes use local, imperfect clocks. Time-sensitive networks exist in two flavours: (1) in non-synchronized networks, local clocks run independently at every node and their deviations are not controlled and (2) in synchronized networks, the deviations of local clocks are kept within very small bounds using for example a synchronization protocol (such as PTP) or a satellite based geo-positioning system (such as GPS). We revisit the properties of regulators in both cases. In non-synchronized networks, we show that ignoring the timing inaccuracies can lead to network instability due to unbounded delay in per-flow or interleaved regulators. We propose and analyze two methods (rate and burst cascade, and asynchronous dual arrival-curve method) for avoiding this problem. In synchronized networks, we show that there is no instability with per-flow regulators but, surprisingly, interleaved regulators can lead to instability. To establish these results, we develop a new framework that captures industrial requirements on clocks in both non-synchronized and synchronized networks, and we develop a toolbox that extends network calculus to account for clock imperfections., ACM SIGMETRICS 2020 Boston, Massachusetts, USA June 8-12, 2020

This paper introduces a novel non-orthogonal multiple access (NOMA) concept named waveform-domain NOMA, which proposes the coexistence of different waveforms in the same resource element (RE). Regarding the demands of each user equipments (UEs), appropriate waveforms are assigned intelligently and decoded at the receiver side properly. Since the performance gain of power-domain NOMA compared to multi-user multiple-input-multiple-output (MU-MIMO) degrades in the case of successive interference cancellation (SIC) and channel estimation errors, NOMA is not considered as a work-item in 3GPP anymore. The novel waveform-domain NOMA concept provides a remedy for the problems of the power-domain NOMA scheme as well as flexibility in terms of reliability, latency, and energy efficiency. To mitigate SIC errors, low-density parity-check (LDPC) codes aided soft interference cancellation technique is used. As numerically evaluated, the proposed waveform-domain NOMA scheme outperforms the conventional power-domain NOMA in the power-balanced scenario., 6 pages,6 figures. Accepted for presentation in ICC Workshop 2020, Dublin, Ireland

Newer cellular communication generations are planned to allow asynchronous transmission of multiple numerologies (waveforms with different parameters) in adjacent bands, creating unavoidable adjacent channel interference. Most prior work on windowing assume additional extensions reserved for windowing, which does not comply with standards. Whether windowing should be applied at the transmitter or the receiver was not questioned. In this work, we propose two independent algorithms that are implemented at the transmitter and receiver, respectively. These algorithms estimate the transmitter and receiver windowing duration of each resource element (RE) with an aim to improve fair proportional network throughput. While doing so, we solely utilize the available extension that was defined in the standard and present standard-compliant algorithms that also do not require any modifications on the counterparts or control signaling. Furthermore, computationally efficient techniques to apply per-RE transmitter and receiver windowing to signals synthesized and analyzed using conventional cyclic prefix orthogonal frequency division multiplexing are derived and their computational complexities are analyzed. The spectrotemporal relations between optimum window durations at either side, as well as functions of the excess signal to noise ratios, the subcarrier spacings and the throughput gains provided over previous similar techniques are numerically verified., 15 pages, 2 algorithms, 3 tables, 11 figures (1 of which includes 3 subfigures) and 3 author biographies. Final version accepted for publication in IEEE Transactions on Vehicular Technology

The article presents the research and comparative analysis of the bandwidth of low-power wireless IoT devices as wireless switches. The following IoT devices were investigated: Raspberry Pi 3 Model B and Raspberry Pi Zero W. The DS18B20 and INA219 sensors investigated and analyzed the dependence of FTP multimedia data transmission speed on wireless Wi-Fi network on the temperature of the switch processor, temperature. The environment and the current and voltage consumed by the switch. Advantages of sensors with GPIO interface over analog meters for this experiment are revealed. Much of the work is devoted to the development of automation of results from GPIO interfaces, which helped eliminate human error and get more accurate metrics. Measurement automation was developed using Python 3.7 programming language. Using the INA219 library we were able to obtain current and voltage indicators from the ina219 board. To get temperature indicators sufficiently built into Python libraries to read temperature files in Raspbian. The article focuses on the synchronicity of measurement results records for more accurate analysis. Therefore, an FTP client was developed that measures the download speed of the file from the FTP server and records the results simultaneously with temperature, current and voltage measurements. To this end, attention is drawn to the multithreading in Python programming language and the transmission of commands using TCP sockets in that language. As a result, the dependence of the measured factors was calculated using the Pearson correlation formula. These measurement factors affect the autonomy and energy consumption, which is very important for IoT devices, and therefore, among the devices tested, recommendations were made regarding their choice when used depending on the conditions., in Ukrainian

The use of autonomous vehicles (AVs) is a promising technology in Intelligent Transportation Systems (ITSs) to improve safety and driving efficiency. Vehicle-to-everything (V2X) technology enables communication among vehicles and other infrastructures. However, AVs and Internet of Vehicles (IoV) are vulnerable to different types of cyber-attacks such as denial of service, spoofing, and sniffing attacks. In this paper, an intelligent intrusion detection system (IDS) is proposed based on tree-structure machine learning models. The results from the implementation of the proposed intrusion detection system on standard data sets indicate that the system has the ability to identify various cyber-attacks in the AV networks. Furthermore, the proposed ensemble learning and feature selection approaches enable the proposed system to achieve high detection rate and low computational cost simultaneously., Published in IEEE Global Communications Conference (GLOBECOM) 2019; Code is available at Github link: https://github.com/Western-OC2-Lab/Intrusion-Detection-System-Using-Machine-Learning

In this contribution we propose a novel steganographic method based on several orthogonal polynomials and their combinations. The steganographic algorithm embeds a secrete message at the first eight coefficients of high frequency image. Moreover, this embedding method uses the Beta chaotic map to determine the order of the blocks where the secret bits will be inserted. In addition, from a 128-bit private key and the steps of a cryptography algorithm according to the Advanced Encryption Standard (AES) to generate the key expansion, the proposed method generates a key expansion of 2560 bits, with the purpose to permute the first eight coefficients of high frequency before the insertion. The insertion takes eventually place at the first eight high frequency coefficients in the transformed orthogonal moments domain. Before the insertion of the message the image undergoes a series of transformations. After the insertion the inverse transformations are applied to the original transformations in reverse order. The experimental work on the validation of the algorithm consists of the calculation of the Peak Signal-to-Noise Ratio (PSNR), the Universal Image Quality Index (UIQI), the Image Fidelity (IF), and the Relative Entropy (RE), comparing the same characteristics for the cover and stego image. The proposed algorithm improves the level of imperceptibility and security analyzed through the PSNR and RE values, respectively., 30 pages, 23 figures

The benefits of the ubiquitous caching in ICN are profound, such features make ICN promising for content distribution, but it also introduces a challenge to content protection against the unauthorized access. The protection of a content against unauthorized access requires consumer authentication and involves the conventional end-to-end encryption. However, in information-centric networking (ICN), such end-to-end encryption makes the content caching ineffective since encrypted contents stored in a cache are useless for any consumers except those who know the encryption key. For effective caching of encrypted contents in ICN, we propose a secure distribution of protected content (SDPC) scheme, which ensures that only authenticated consumers can access the content. SDPC is lightweight and allows consumers to verify the originality of the published content by using a symmetric key encryption. Moreover, SDPC naming scheme provides protection against privacy leakage. The security of SDPC was proved with the BAN logic and Scyther tool verification, and simulation results show that SDPC can reduce the content download delay., 15 pages, 8 figures, This article is an enhancement version of journal article published in IEEE Systems Journal, DOI: 10.1109/JSYST.2019.2931813. arXiv admin note: text overlap with arXiv:1808.03289

The widespread use of wireless technologies leads to an ever-increasing number of users and permanently functioning devices. However, the growth of the number of wireless users in a limited space and a limited frequency range leads to an increase in their mutual influence, which ultimately affects the throughput of wireless channels and even the performance of the system as a whole. The article presents the statistics and tendencies of the distribution of wireless networks of the IEEE 802.11 standard systems, as well as analyzes the main problems that arise during the expansion of their use. Substantiation and choice of ways to overcome these difficulties largely depends on the objective control of radiation parameters of access points and subscriber funds in a particular environment. The review of the state control facilities provided by the developers of the equipment is presented, and author's variants of experimental measuring complexes are offered, allowing to control signal and information parameters of Wi-Fi systems. The experimental results obtained with the use of the indicated means, obtained using the accelerating metal-plate lens as an additional autonomous element for focusing the field, including for MIMO systems, the effect of the accelerating metal-plate lens on the spatial distribution of the field, on the spectral structure of the signal are presented. In addition, polarization effects were investigated. Possible ways to further increase the availability, integrity of information and energy efficiency of wireless access systems are discussed. The authors propose simpler and less costly options for increasing the direction of radiation on the basis of an accelerating metal-plate lens, experimentally tested, as well as the use of zone zoning on the path of the computer., in Ukrainian

The article presents a method which organizes men-in-the-middle attack and penetration test on Bluetooth Low Energy devices and ZigBee packets by using software define radio with sniffing and spoofing packets, capture and analysis techniques on wireless waves with the focus on BLE. The paper contains the analysis of the latest scientific works in this area, provides a comparative analysis of SDRs with the rationale for the choice of hardware, gives the sequence order of actions for collecting wireless data packets and data collection from ZigBee and BLE devices, and analyzes ways which can improve captured wireless packet analysis techniques. The results of the experimental setup, collected for the study, were analyzed in real time and the collected wireless data packets were compared with the one, which have sent the origin. The result of the experiment shows the weaknesses of local wireless networks.

The article introduces a new scheme of dynamic interference free channelallocation. The scheme is based on additional spectral analyzers in wireless networks IEEE 802.11.Design and implementation is presented.

The rapid development of “smart” devices leads to explosive growth of unprotected or partially protected homenetworks. These networks are easy prey for unauthorized access, the collection of personal information (including fromsurveillance cameras), interference in the operation of individual devices and the entire system as a whole. In addition,existing solutions for managing a smart house offer work in the cloud, which in turn reduces the availability of thesystem and simultaneously increases the risk of the unscrupulous use of personal information by the service provider(up to the sale of data to a third party). This article examines the existing access technologies, their weaknesses, andoffers solutions to improve the overall security of the system with a local IoT gateway and virtual subnets. &nbsp

The problem of Wi-Fi and LTE coexistence has been significantly debated in the last years, with the emergence of LTE extensions enabling the utilization of unlicensed spectrum for carrier aggregation. Rather than focusing on the problem of resource sharing between the two technologies, in this paper, we study the effects of LTE's structured transmissions on the Wi-Fi random access protocol. We show how the scheduling of periodic LTE transmissions modifies the behavior of 802.11's distributed coordination function (DCF), leading to a degradation of Wi-Fi performance, both in terms of channel utilization efficiency and in terms of channel access fairness. We also discuss the applicability and limitations of a persistent DCF model in analyzing Wi-Fi performance under periodic LTE interference., 4 pages, 2 figures, 2 tables, 13 references, accepted for publication in IEEE Communications Letters

In the last decade, the use of fast flux technique has become established as a common practice to organise botnets in Fast Flux Service Networks (FFSNs), which are platforms able to sustain illegal online services with very high availability. In this paper, we report on an effective fast flux detection algorithm based on the passive analysis of the Domain Name System (DNS) traffic of a corporate network. The proposed method is based on the near-real-time identification of different metrics that measure a wide range of fast flux key features; the metrics are combined via a simple but effective mathematical and data mining approach. The proposed solution has been evaluated in a one-month experiment over an enterprise network, with the injection of pcaps associated with different malware campaigns, that leverage FFSNs and cover a wide variety of attack scenarios. An in-depth analysis of a list of fast flux domains confirmed the reliability of the metrics used in the proposed algorithm and allowed for the identification of many IPs that turned out to be part of two notorious FFSNs, namely Dark Cloud and SandiFlux, to the description of which we therefore contribute. All the fast flux domains were detected with a very low false positive rate; a comparison of performance indicators with previous works show a remarkable improvement., This is a pre-print of an article published in the proceedings of 21st International Conference, ISC 2018, Guildford, UK, September 9-12, 2018. The final authenticated version is available online at: https://doi.org/10.1007/978-3-319-99136-8_25

In the ICS, WUT a platform for simulation of cooperation of physical and virtual mobile agents is under development. The paper describes the motivation of the research, an organization of the platform, a model of agent, and the principles of design of the platform. Several experimental simulations are briefly described., 7 pages, 6 figures