Delay Impact on Stubborn Mining Attack Severity in Imperfect Bitcoin Network

Stubborn mining attack greatly downgrades Bitcoin throughput and also benefits malicious miners (attackers). This paper aims to quantify the impact of block receiving delay on stubborn mining attack severity in imperfect Bitcoin networks. We develop an analytic model and derive formulas of both relative revenue and system throughput, which are applied to study attack severity. Experiment results validate our analysis method and show that imperfect networks favor attackers. The quantitative analysis offers useful insight into stubborn mining attack and then helps the development of countermeasures.Comment: arXiv admin note: text overlap with arXiv:2302.0021

CRS-FL: Conditional Random Sampling for Communication-Efficient and Privacy-Preserving Federated Learning

Federated Learning (FL), a privacy-oriented distributed ML paradigm, is being gaining great interest in Internet of Things because of its capability to protect participants data privacy. Studies have been conducted to address challenges existing in standard FL, including communication efficiency and privacy-preserving. But they cannot achieve the goal of making a tradeoff between communication efficiency and model accuracy while guaranteeing privacy. This paper proposes a Conditional Random Sampling (CRS) method and implements it into the standard FL settings (CRS-FL) to tackle the above-mentioned challenges. CRS explores a stochastic coefficient based on Poisson sampling to achieve a higher probability of obtaining zero-gradient unbiasedly, and then decreases the communication overhead effectively without model accuracy degradation. Moreover, we dig out the relaxation Local Differential Privacy (LDP) guarantee conditions of CRS theoretically. Extensive experiment results indicate that (1) in communication efficiency, CRS-FL performs better than the existing methods in metric accuracy per transmission byte without model accuracy reduction in more than 7% sampling ratio (# sampling size / # model size); (2) in privacy-preserving, CRS-FL achieves no accuracy reduction compared with LDP baselines while holding the efficiency, even exceeding them in model accuracy under more sampling ratio conditions

PA-iMFL: Communication-Efficient Privacy Amplification Method against Data Reconstruction Attack in Improved Multi-Layer Federated Learning

Recently, big data has seen explosive growth in the Internet of Things (IoT). Multi-layer FL (MFL) based on cloud-edge-end architecture can promote model training efficiency and model accuracy while preserving IoT data privacy. This paper considers an improved MFL, where edge layer devices own private data and can join the training process. iMFL can improve edge resource utilization and also alleviate the strict requirement of end devices, but suffers from the issues of Data Reconstruction Attack (DRA) and unacceptable communication overhead. This paper aims to address these issues with iMFL. We propose a Privacy Amplification scheme on iMFL (PA-iMFL). Differing from standard MFL, we design privacy operations in end and edge devices after local training, including three sequential components, local differential privacy with Laplace mechanism, privacy amplification subsample, and gradient sign reset. Benefitting from privacy operations, PA-iMFL reduces communication overhead and achieves privacy-preserving. Extensive results demonstrate that against State-Of-The-Art (SOTA) DRAs, PA-iMFL can effectively mitigate private data leakage and reach the same level of protection capability as the SOTA defense model. Moreover, due to adopting privacy operations in edge devices, PA-iMFL promotes up to 2.8 times communication efficiency than the SOTA compression method without compromising model accuracy.Comment: 12 pages, 11 figure

Inheritance of quantitative qualities of tobacco in F1 and F2 generations

Истраживањима су обухваћена четри генотипа дувана у типу вирџиније, као и њихови хибриди у Ф1 и Ф2 генерацији. Проучаване су следеће особине и њихов начин наслеђивања: висина биљке, број листова, дужина листа, ширина листа, растојање од основе до максималне ширине листа, број дана од расађивања до бутонизације, број дана од расађивања до почетка цветања, број дана од расађивања до пуног цветања, садржај никотина, садржај беланчевина и садржај простих шећера и принос по биљци. Изведена су диалелна укрштања између родитеља. За већи број анализираних особина код наслеђивања утврђено је преовлађујуће деловање адитивних и доминантних гена. Добијен је и хетерозис за неке проучаване особине. На основу испитаних општих и посебних комбинационих способности, издвојена су два родитељска генотипа који показују добра комбинациона својства.The investigations included four genotypes of tobacco in Virginia type, and their hybrids in the F1 and F2 generation. The studied properties were: plant height, leaf number, yield per field, leaf length, leaf width, the distance from the base to the maximum leaf width, number of days from planting to bud, the number of days from planting to early flowering, number of days from planting to full bloom, nicotine content, protein content and the content of the base sugar. Diallel crossbreeding between these four genotypes was performed. After the crossbreeding, obtained plants belonged to F1 and F2 generations, as well as to B1 and B2 generations obtained by repeated crossbreeding. For most of the studied traits in inheritance has been determined prevailing influence of additive and dominant gene. Was obtained and studied heterosis for some traits. Based on the investigation of general and specific combining properties, separate the two parental genotypes, which show good combining properties

A geometric network model of intrinsic grey-matter connectivity of the human brain

Network science provides a general framework for analysing the large-scale brain networks that naturally arise from modern neuroimaging studies, and a key goal in theoretical neuro- science is to understand the extent to which these neural architectures influence the dynamical processes they sustain. To date, brain network modelling has largely been conducted at the macroscale level (i.e. white-matter tracts), despite growing evidence of the role that local grey matter architecture plays in a variety of brain disorders. Here, we present a new model of intrinsic grey matter connectivity of the human connectome. Importantly, the new model incorporates detailed information on cortical geometry to construct ‘shortcuts’ through the thickness of the cortex, thus enabling spatially distant brain regions, as measured along the cortical surface, to communicate. Our study indicates that structures based on human brain surface information differ significantly, both in terms of their topological network characteristics and activity propagation properties, when compared against a variety of alternative geometries and generative algorithms. In particular, this might help explain histological patterns of grey matter connectivity, highlighting that observed connection distances may have arisen to maximise information processing ability, and that such gains are consistent with (and enhanced by) the presence of short-cut connections

Distinct and dissociable EEG networks are associated with recovery of cognitive function following anesthesia-induced unconsciousness

The temporal trajectories and neural mechanisms of recovery of cognitive function after a major perturbation of consciousness is of both clinical and neuroscientific interest. The purpose of the present study was to investigate network-level changes in functional brain connectivity associated with the recovery and return of six cognitive functions after general anesthesia. High-density electroencephalograms (EEG) were recorded from healthy volunteers undergoing a clinically relevant anesthesia protocol (propofol induction and isoflurane maintenance), and age-matched healthy controls. A battery of cognitive tests (motor praxis, visual object learning test, fractal-2-back, abstract matching, psychomotor vigilance test, digital symbol substitution test) was administered at baseline, upon recovery of consciousness (ROC), and at half-hour intervals up to 3 h following ROC. EEG networks were derived using the strength of functional connectivity measured through the weighted phase lag index (wPLI). A partial least squares (PLS) analysis was conducted to assess changes in these networks: (1) between anesthesia and control groups; (2) during the 3-h recovery from anesthesia; and (3) for each cognitive test during recovery from anesthesia. Networks were maximally perturbed upon ROC but returned to baseline 30-60 min following ROC, despite deficits in cognitive performance that persisted up to 3 h following ROC. Additionally, during recovery from anesthesia, cognitive tests conducted at the same time-point activated distinct and dissociable functional connectivity networks across all frequency bands. The results highlight that the return of cognitive function after anesthetic-induced unconsciousness is task-specific, with unique behavioral and brain network trajectories of recovery

An insight into seasonal changes of carbohydrates and phenolic compounds within the moss Polytrichum formosum (Polytrichaceae)

The same population of the polytrichaceous moss Polytrichum formosum was studied over four different periods of the year, analysing its carbohydrate and polyphenolic content and dynamics related to environmental seasonal changes. A total of 18 different types of sugars (including mono-, di-, tri- and tetra-saccharides) and four sugar alcohols were determined. Chlorogenic acid was the most represented among the 10 detected phenolic compounds. As inferred by the sugar content, sucrose, fructose and glucose were the most dominant sugars, but it is worth mentioning the abundance of trehalose and turanose at least during one of the observed seasons. The presence of four trisaccharides and one tetrasaccharide within P. formosum should be highlighted, as well as the first reports of turanose, isomaltotriose, panose and rhamnose within this species. The quantitative changes over the year clearly demonstrate carbohydrate dynamics in relation to seasonal climatic variation. Sugars are shown to be significant constitutive molecules within P. formosum, but also physiologically active compounds, i.e. signalling and energy storage and supplier molecules. We assume that phenolics have moss-supportive effects during oxidative stress and biotic interaction