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Purpose Long total waiting times (TWT) experienced by patients during a clinic visit have a significant adverse effect on patient’s satisfaction. Our aim was to use big data simulations of a patient scheduling calendar and its effect on TWT in a general ophthalmology clinic. Based on the simulation, we implemented changes to the calendar and verified their effect on TWT in clinical practice. Design and methods For this retrospective simulation study, we generated a discrete event simulation (DES) model based on clinical timepoints of 4.401 visits to our clinic. All data points were exported from our clinical warehouse for further processing. If not available from the electronic health record, manual time measurements of the process were used. Various patient scheduling models were simulated and evaluated based on their reduction of TWT. The most promising model was implemented into clinical practice in 2017. Results During validation of our simulation model, we achieved a high agreement of mean TWT between the real data (229 ± 100 min) and the corresponding simulated data (225 ± 112 min). This indicates a high quality of the simulation model. Following the simulations, a patient scheduling calendar was introduced, which, compared with the old calendar, provided block intervals and extended time windows for patients. The simulated TWT of this model was 153 min. After implementation in clinical practice, TWT per patient in our general ophthalmology clinic has been reduced from 229 ± 100 to 183 ± 89 min. Conclusion By implementing a big data simulation model, we have achieved a cost-neutral reduction of the mean TWT by 21%. Big data simulation enables users to evaluate variations to an existing system before implementation into clinical practice. Various models for improving patient flow or reducing capacity loads can be evaluated cost-effectively.

Around the globe, the need for additional housing, due to the increase in world population, has led to the exploration of more cost effective and environmentally friendly forms of construction. Out of many technologies found, mortar-free interlocked masonry systems were developed to eliminate the deficiency of traditional masonry. For such systems against earthquakes, lateral resistance can be enhanced with plaster. But there is a need to further improve the performance of plaster in mortar-free interlocking walls for better ductility. The objective of this study is to develop nonlinear finite element (NLFE) models to explore the likely failure mechanism (e.g. bond failure) of such systems and to do parametric studies more cheaply than constructing many walls. Lateral failure load, load–displacement curves and crack patterns were compared with the experimental results. Parametric studies involving variation in block and plaster compressive strength and plaster thickness were undertaken using TNO DIANA NLFE models. A 150% increase in thickness of plaster only resulted in 28% increase in failure load, and column thickness can be reduced to theoretical 25 mm of blocks with 8 mm of plaster and yet exceed the lateral strength of a 150-mm-thick unplastered column. A cost analysis was also carried out, based on NLFE models, and showed that fibrous plastered column with 25-mm-thickness blocks gave equivalent performance to the 150-mm-thick unplastered column with 67% cost saving.

Payment channel networks provide a fast and scalable solution to relay funds, acting as a second layer to slower and less scalable blockchain protocols. In this paper, we present an accessible, low-cost attack in which the attacker paralyzes multiple payment network channels for several days. The attack is based on overloading channels with requests that are kept unresolved until their expiration time. Reaching the maximum allowed unresolved requests (\(\mathtt {HTLCs}\)) locks the channel for new payments. The attack is in fact inherent to the way off-chain networks are constructed, since limits on the number of unresolved payments are derived from limits on the blockchain. We consider three versions of the attack: one in which the attacker attempts to block as many high liquidity channels as possible, one in which it disconnects as many pairs of nodes as it can, and one in which it tries to isolate individual nodes from the network. We evaluate the costs of these attacks on Bitcoin’s Lightning Network and compare how changes in the network have affected the cost of attack. Specifically, we consider how recent changes to default parameters in each of the main Lightning implementations contribute to the attacks. Finally, we suggest mitigation techniques that make these attacks much harder to carry out.

Light clients, also known as Simple Payment Verification (SPV) clients, are nodes which only download a small portion of the data in a blockchain, and use indirect means to verify that a given chain is valid. Instead of validating blocks, they assume that the chain favoured by the blockchain’s consensus algorithm only contains valid blocks, and that the majority of block producers are honest. By allowing such clients to receive fraud proofs generated by fully validating nodes that show that a block violates the protocol rules, and combining this with probabilistic sampling techniques to verify that all of the data in a block actually is available to be downloaded so that fraud can be detected, we can eliminate the honest-majority assumption for block validity, and instead make much weaker assumptions about a minimum number of honest nodes that rebroadcast data. Fraud and data availability proofs are key to enabling on-chain scaling of blockchains while maintaining a strong assurance that on-chain data is available and valid. We present, implement, and evaluate a fraud and data availability proof system.

Blockchain protocols’ primary security goal is consensus: one version of the global ledger that everyone in the network agrees on. Their proofs of security depend on assumptions on how well their peer-to-peer (P2P) overlay networks operate. Yet, surprisingly, little is understood about what factors influence the P2P network properties. In this work, we extensively study the Ethereum P2P network’s connectivity and its block propagation mechanism. We gather data on the Ethereum network by running the official Ethereum client, geth, modified to run as a “super peer” with many neighbors. We run this client in North America for over seven months, as well as shorter runs with multiple vantages around the world. Our results expose an incredible amount of churn, and a surprisingly small number of peers who are actually useful (that is, who propagate new blocks). We also find that a node’s location has a significant impact on when it hears about blocks, and that the precise behavior of this has changed over time (e.g., nodes in the US have become less likely to hear about new blocks first). Finally, we find prune blocks propagate faster than uncles.

Mining pools decrease the variance in the income of cryptocurrency miners (compared to solo mining) by distributing rewards to participating miners according to the shares submitted over a period of time. The most common definition of a “share” is a proof-of-work for a difficulty level lower than that required for block authorization—for example, a hash with at least 65 leading zeroes (in binary) rather than at least 75.

An important feature of Proof-of-Work (PoW) blockchains is full dynamic availability, allowing miners to go online and offline while requiring only 50% of the online miners to be honest. Existing Proof-of-stake (PoS), Proof-of-Space and related protocols are able to achieve this property only partially, either putting the additional assumption that adversary nodes to be online from the beginning and no new adversary nodes come online afterwards, or use additional trust assumptions for newly joining nodes.We propose a new PoS protocol PoSAT which can provably achieve dynamic availability fully without any additional assumptions. The protocol is based on the longest chain and uses a Verifiable Delay Function for the block proposal lottery to provide an arrow of time. The security analysis of the protocol draws on the recently proposed technique of Nakamoto blocks as well as the theory of branching random walks. An additional feature of PoSAT is the complete unpredictability of who will get to propose a block next, even by the winner itself. This unpredictability is at the same level of PoW protocols, and is stronger than that of existing PoS protocols using Verifiable Random Functions.

One of the biggest challenges currently facing the industry is to make systems more flexible. Technological advances are enabling new application scenarios such as safe and efficient human-robot collaboration, which is based on the real-time availability of required data at the location where it is needed at that point in time. The crucial building block for this modernization of factories is the communication network between the automation components as it is the one enabler for constant and reliable exchange of information. In the future, an essential and ever increasing part of such a communication network will be wireless communication. It plays a major role in expanding the mobility and agility of sensors and actuators and in the retrofitting of rigid legacy structures. For smart production in particular, wireless technologies that are reliable and support deterministic cycle times in the range of less than 1 ms are required, which is barely addressed by current wireless developments based on IEEE 802.11 and 5G URLLC. This paper presents a novel real-time radio technology – Ultra Reliable Wireless Industrial Network (UWIN), developed by Fraunhofer IIS, which is currently in a preliminary pre-product development stage. In addition to explaining the UWIN concept, this paper provides a short overview on state-of-the-art real-time radio technologies.

Several attacks have been proposed against Proof-of-Work blockchains, which may increase the attacker's share of mining rewards (e.g., selfish mining, block withholding). A further impact of such attacks, which has not been considered in prior work, is that decreasing the profitability of mining for honest nodes incentivizes them to stop mining or to leave the attacked chain for a more profitable one. The departure of honest nodes exacerbates the attack and may further decrease profitability and incentivize more honest nodes to leave. In this paper, we first present an empirical analysis showing that there is a statistically significant correlation between the profitability of mining and the total hash rate, confirming that miners indeed respond to changing profitability. Second, we present a theoretical analysis showing that selfish mining under such elastic hash supply leads either to the collapse of a chain, i.e., all honest nodes leaving, or to a stable equilibrium depending on the attacker's initial share.

In cryptocurrencies, the block reward is meant to serve as the incentive mechanism for miners to commit resources to create blocks and in effect secure the system. Existing systems primarily divide the reward in proportion to expended resources and follow one of two static models for total block reward: (i) a fixed reward for each block (e.g., Ethereum), or (ii) one where the block reward halves every set number of blocks (e.g., the Bitcoin model of halving roughly every 4 years) but otherwise remains fixed between halvings. In recent work, a game-theoretic analysis of the static model under asymmetric miner costs showed that an equilibrium always exists and is unique [4]. Their analysis also reveals how asymmetric costs can lead to large-scale centralization in blockchain mining, a phenomenon that has been observed in Bitcoin and Ethereum and highlighted by other studies including [11, 16].

Blockchain protocols suffer from an interesting conundrum: owning stake in the Blockchain doesn’t necessarily mean that the party is willing to participate in day to day operations. This leads to large quantities of stake being owned by parties who do not actually participate in the growth of the blockchain, reducing its security. Pass and Shi [23] captured this concern in the sleepy model, and subsequent work by Pass et al. [5] extended their results into a full Proof of Stake blockchain protocol which can continue to securely progress even when the majority of parties may be offline. However, their protocol requires 10 or more blocks to be added after a transaction first appears in the ledger for it to be confirmed. On the other hand, existing Byzantine Agreement based blockchain protocols such as Algorand [6, 7, 14] confirm transactions as soon as they appear in the ledger, but are unable to progress when users are not online when mandated.

A popular method in practice offloads computation and storage in blockchains by relying on committing only hashes of off-chain data into the blockchain. This mechanism is acknowledged to be vulnerable to a stalling attack: the blocks corresponding to the committed hashes may be unavailable at any honest node. The straightforward solution of broadcasting all blocks to the entire network sidesteps this data availability attack, but it is not scalable. In this paper, we propose ACeD, a scalable solution to this data availability problem with O(1) communication efficiency, the first to the best of our knowledge. The key innovation is a new protocol that requires each of the N nodes to receive only O(1/N) of the block, such that the data is guaranteed to be available in a distributed manner in the network. Our solution creatively integrates coding-theoretic designs inside of Merkle tree commitments to guarantee efficient and tamper-proof reconstruction; this solution is distinct from Asynchronous Verifiable Information Dispersal [7] (in guaranteeing efficient proofs of malformed coding) and Coded Merkle Tree [25] (which only provides guarantees for random corruption as opposed to our guarantees for worst-case corruption). We implement ACeD with full functionality in 6000 lines of Rust code, integrate the functionality as a smart contract into Ethereum via a high-performance implementation demonstrating up to 10,000 transactions per second in throughput and 6000x reduction in gas cost on the Ethereum testnet Kovan. Our code is available in [1].

Adaptor signatures (AS) are an extension of digital signatures that enable the encoding of a cryptographic hard problem (e.g., discrete logarithm) within the signature itself. An AS scheme ensures that (i) the signature can be created only by the user knowing the solution to the cryptographic problem; (ii) the signature reveals the solution itself; (iii) the signature can be verified with the standard verification algorithm. These properties have made AS a salient building block for many blockchain applications, in particular, off-chain payment systems such as payment-channel networks, payment-channel hubs, atomic swaps or discrete log contracts. Current AS constructions, however, are not secure against adversaries with access to a quantum computer.

Information processing systems with some form of machine-learned component are making their way into the industrial application and offer high potentials for increasing productivity and machine utilization. However, the systematic engineering approach to integrate and manage these machine-learned components is still not standardized and no reference architecture exist. In this paper we will present the building block of such an architecture which is developed with the ML4P project by Fraunhofer IFF.

Contact interaction of two bodies can be modeled using the penalty function approach while its accuracy and robustness are directly associated with the geometry of contact bodies. Particularly, in the research fields of rock mechanics, we need to treat polygonal shapes such as mineral grains/particles at a mesoscale and rock blocks at a macroscale. The irregular shapes (e.g., polygons with small angles or small edges) pose challenges to traditional contact solution approach in terms of algorithmic robustness and complexity. This paper proposed a robust potential-based penalty function approach to solve contact of polygonal particles/block. An improved potential function is proposed considering irregular polygonal shapes. A contact detection procedure based on the entrance block concept is presented, followed by a numerical integral algorithm to compute the contact force. The proposed contact detection approach is implemented into discontinuous deformation analysis with an explicit formulation. The accuracy and robustness of the proposed contact detection approach are verified by benchmarking examples. The potential of the proposed approach in analysis of kinetic behavior of complex polygonal block systems is shown by two application examples. It can be applied in any discontinuous computation models using stepwise contact force-based solution procedures., Alexander von Humboldt Foundation, National Natural Science Foundation of China http://dx.doi.org/10.13039/501100001809

Regarding the design of single screw extruders, the prediction of the throughput needs to be of high accuracy. The calculation of the solids conveying throughput is particularly important for extruders with a grooved feed section. In contrast to smooth barrel extruders the throughput of the entire plant is determined at the feed section. Various simplifications are necessary for an analytical modelling of the solids conveying, e.g. the classification into conveying cases, the assumption of solid block flow and the assumption of pressure anisotropy coefficients.

Foliage morphological features are important for plant recognition. However, the foliage shape generally presents big intra-class variations and small inter-class differences. This brings a great challenge to accurate plant foliage recognition. In this paper, we propose a deep residual squeeze-excitation network (R-SENet) for foliage recognition. Firstly, R-SENet learns and obtains the significance levels of each channel of the various convolutional layers in a residual block to recognition tasks via squeeze-excitation strategy. Then, the weights of each channel are rescaled by means of the significances to promote the relevant channels and inhibit non-important channels. Finally, we evaluate the proposed approach on the well-known Flavia dataset for foliage recognition. The experimental results indicate that our approach achieves more accurate average recognition rate (up to 97.86%) and more robustness to noise than other outstanding approaches.

Road scene segmentation has always been regarded as a pixel-wise task in computer vision studies. In this paper, we introduce a practical and new features fusion structure named “Dual Path Network” for road semantic segmentation. This form aims to reduce the gap between low-level and high-level information, thereby improving features fusion. The Dual Path consists of two subpaths: Context Path and Spatial Path. In the Context Path, we select a pre-trained ResNet-101 model as the backbone and use multi-scale convolution blocks comprise the Spatial Path. Then, we create a fusion residual block and channel attention model to further optimize the network. The results of the experiment confirm a state-of-the-art mean intersection-over-union of 68.5% using the CamVid dataset.

In sandwich construction, the structural element level coincides with the bonded sandwich panel, which represents the combination of the two main constituents, face sheet and core. It is generally assumed that the material properties and modelling approaches, which are derived on constituent level, enable to predict the material behavior on structural element level. The investigations within this second building block were firstly intended to validate this assumption. In addition, the objective was to consider additional relevant aspects that can only be investigated on structural element level.

The application of GPS technology in Qinghai–Tibet railway mainly focuses on the navigation, monitoring, command, and dispatching system of the train positioning. GPS is used as the auxiliary train positioning device in the railway train control system of Qinghai–Tibet railway and is taken as a backup of the query balise (redundant system) in the moving block control system. The vehicle-mounted GPS shown in Fig. 3.1 is used as the auxiliary correction of the reference position of the ground track. GPS-aided dispatching system uses GPS to compute the actual positioning, the operational direction and speed of the operational train, and then transmits the positioning results to the dispatch center through wireless communication channel to realize the real-time whole-process monitoring and ensure the safety of the train. The continuous operational location information of train provided by GPS covers the whole operational line of the train (station and zone), which can be used to adjust the operation plan, train dispatching and controlling, and accurate real-time monitoring

Bitcoin relies on the Unspent Transaction Outputs (UTXO) set to efficiently verify new generated transactions. Every unspent output, no matter its type, age, value or length is stored in every full node. In this paper we introduce a tool to study and analyze the UTXO set, along with a detailed description of the set format and functionality. Our analysis includes a general view of the set and quantifies the difference between the two existing formats up to the date. We also provide an accurate analysis of the volume of dust and unprofitable outputs included in the set, the distribution of the block height in which the outputs where included, and the use of non-standard outputs.

In this work, we propose a first version of an e-voting scheme that achieves end-to-end verifiability, everlasting privacy and efficient coercion resistance in the JCJ setting. Everlasting privacy is achieved assuming an anonymous channel, without resorting to dedicated channels between the election authorities to exchange private data. In addition, the proposed scheme achieves coercion resistance under standard JCJ assumptions. As a core building block of our scheme, we also propose a new primitive called publicly auditable conditional blind signature (PACBS), where a client receives a token from the signing server after interaction; the token is a valid signature only if a certain condition holds and the validity of the signature can only be checked by a designated verifier. We utilize this primitive to blindly mark votes under coercion in an auditable manner.

In this paper we present three attacks against the predictable solo mining (PSM) scheme. In PSM, miners receive shares for submitting partially valid solutions to the current Proof of Work, adding those shares to their account. When the pool successfully mines a block, the block is awarded to the miner with the most shares, and the rewarded miner “pays” an amount of shares equal to the next highest miner’s to claim the block. Our attacks take advantage of the fact that the amount of shares expended winning two different blocks, which have the same monetary value, can vary by up to a factor of four. We show that by strategically spreading its shares across multiple accounts, a malicious miner can generate more revenue than a naive miner of the same computational power by only claiming blocks with a low share cost. By doing so, a miner can reduce computational power it must expend to win a block by more than 30%. Our other two attacks reduce the profitability of victim miners in the pool by minimizing the gap between first and second place when the victim wins a block. This drives up the average amount of computational power the victim must contribute to receive a reward. An adversary not concerned with cost can reduce the number of shares a victim retains after winning a block by up to 26%. We also find that an adversary with more computational power than their victim can reduce the number of shares the victim retains after winning a block by more than 8% with only limited impact on the adversary’s profitability.

Modern websites include various types of third-party content such as JavaScript, images, stylesheets, and Flash objects in order to create interactive user interfaces. In addition to explicit inclusion of third-party content by website publishers, ISPs and browser extensions are hijacking web browsing sessions with increasing frequency to inject third-party content (e.g., ads). However, third-party content can also introduce security risks to users of these websites, unbeknownst to both website operators and users. Because of the often highly dynamic nature of these inclusions as well as the use of advanced cloaking techniques in contemporary malware, it is exceedingly difficult to preemptively recognize and block inclusions of malicious third-party content before it has the chance to attack the user's system. In this paper, we propose a novel approach to achieving the goal of preemptive blocking of malicious third-party content inclusion through an analysis of inclusion sequences on the Web. We implemented our approach, called Excision, as a set of modifications to the Chromium browser that protects users from malicious inclusions while web pages load. Our analysis suggests that by adopting our in-browser approach, users can avoid a significant portion of malicious third-party content on the Web. Our evaluation shows that Excision effectively identifies malicious content while introducing a low false positive rate. Our experiments also demonstrate that our approach does not negatively impact a user's browsing experience when browsing popular websites drawn from the Alexa Top 500.

The multiscale block compressed sensing algorithm gives an unreasonable resource distribution. This is because it deploys the same subrate within each decomposition level of a wavelet transform of an image. A novel adaptive sampling method applying the prior information is proposed to ameliorate the algorithm performance. Taking the importance differences of the wavelet coefficients of each decomposition level into account, texture information and directionality obtained by low frequency coefficients are combined. They are used to deploy the subrate adaptively into each image block of each subband of each level, realizing adaptive multiscale block compressed sensing. Experimental results reveal that, at each total subrate, the proposed algorithm significantly improves both the reconstruction quality and the visual effect with the maximum PSNR gain up to 1.38 dB.

The software verification framework CPAchecker is built on basic approaches like CPA and CEGAR. The configuration for the SV-COMP'16 uses the concept of block-abstraction memoization and combines it with the parallel execution of value analysis and predicate analysis. The CEGAR loop uses a refinement strategy that prefers to refine the precision of the lightweight value analysis, such that the precision of the predicate analysis remains abstract and concise as long as possible. The usage of mature analyses like value analysis and predicate analysis allows us to bring together the potential of lazy abstraction and interpolation and the benefits of block-abstraction memoization.

Logic locking is a technique that has been proposed to protect outsourced IC designs from piracy and counterfeiting by untrusted foundries. A locked IC preserves the correct functionality only when a correct key is provided. Recently, the security of logic locking is threatened by a new attack called SAT attack, which can decipher the correct key of most logic locking techniques within a few hours [12] even for a reasonably large number of keys. This attack iteratively solves SAT formulas which progressively eliminate the incorrect keys till the circuit unlocked. In this paper, we present a circuit block (referred to as Anti-SAT block) to thwart the SAT attack. We show that the number of SAT attack iterations to reveal the correct key in a circuit comprising an Anti-SAT block is an exponential function of the key-size thereby making the SAT attack computationally infeasible. Through our experiments, we illustrate the effectiveness of our approach to securing modern chips fabricated in untrusted foundries.

We propose the Synthetic Counter-in-Tweak $$\mathsf {SCT}$$ mode, which turns a tweakable block cipher into a nonce-based authenticated encryption scheme with associated data. The $$\mathsf {SCT}$$ mode combines in a SIV-like manner a Wegman-Carter MAC inspired from $$\mathsf {PMAC}$$ for the authentication part and a new counter-like mode for the encryption part, with the unusual property that the counter is applied on the tweak input of the underlying tweakable block cipher rather than on the plaintext input. Unlike many previous authenticated encryption modes, $$\mathsf {SCT}$$ enjoys provable security beyond the birthday bound and even upi¾?to roughly $$2^n$$ tweakable block cipher calls, where n is the block length, when the tweak length is sufficiently large in the nonce-respecting scenario where nonces are never repeated. In addition, $$\mathsf {SCT}$$ ensures security upi¾?to the birthday bound even when nonces are reused, in the strong nonce-misuse resistance sense MRAE of Rogaway and Shrimpton EUROCRYPTi¾?2006. To the best of our knowledge, this is the first authenticated encryption mode that provides at the same time close-to-optimal security in the nonce-respecting scenario and birthday-bound security for the nonce-misuse scenario. While two passes are necessary to achieve MRAE-security, our mode enjoys a number of desirable features: it is simple, parallelizable, it requires the encryption direction only, it is particularly efficient for small messages compared to other nonce-misuse resistant schemes no precomputation is required and it allows incremental update of associated data.

It has been proved in Eurocrypti¾?2016 by Sun et al. that if the details of the S-boxes are not exploited, an impossible differential and a zero-correlation linear hull can extend over at most 4 rounds of the AES. This paper concentrates on distinguishing properties of AES-like SPN ciphers by investigating the details of both the underlying S-boxes and the MDS matrices, and illustrates some new insights on the security of these schemes. Firstly, we construct several types of 5-round zero-correlation linear hulls for AES-like ciphers that adopt identical S-boxes to construct the round function and that have two identical elements in a column of the inverse of their MDS matrices. We then use these linear hulls to construct 5-round integrals provided that the difference of two sub-key bytes is known. Furthermore, we prove that we can always distinguish 5 rounds of such ciphers from random permutations even when the difference of the sub-keys is unknown. Secondly, the constraints for the S-boxes and special property of the MDS matrices can be removed if the cipher is used as a building block of the Miyaguchi-Preneel hash function. As an example, we construct two types of 5-round distinguishers for the hash function Whirlpool. Finally, we show that, in the chosen-ciphertext mode, there exist some nontrivial distinguishers for 5-round AES. To the best of our knowledge, this is the longest distinguisher for the round-reduced AES in the secret-key setting. Since the 5-round distinguisher for the AES can only be constructed in the chosen-ciphertext mode, the security margin for the round-reduced AES under the chosen-plaintext attack may be different from that under the chosen-ciphertext attack.

In [18] Cramer, Damgard and Schoenmakers (CDS) devise an OR-composition technique for \(\varSigma \)-protocols that allows to construct highly-efficient proofs for compound statements. Since then, such technique has found countless applications as building block for designing efficient protocols.

This work explores the possibilities for practical Threshold Implementation (TI) with only two shares in order for a smaller design that needs less randomness but is still first-order leakage resistant. We present the first two-share Threshold Implementations of two lightweight block ciphers—Simon and Present. The implementation results show that two-share TI improves the compactness but usually further reduces the throughput when compared with first-order resistant three-share schemes. Our leakage analysis shows that two-share TI can retain perfect first-order resistance. However, the analysis also exposes a strong second-order leakage. All results are backed up by simulation as well as analysis of actual implementations.

Robust Video watermarking techniques based on DPCM Encoder and permutated DCT spectrum combined with QIM is introduced. For this purpose the pixels of incoming frames undergo permutation, followed by block wise DCT transform. The DPCM encoder generates differential spectral images. The significant coefficients of these differential spectral images are selected for embedding procedure by quantization index modulation (QIM) method. By this technique the watermark is more robust against attacks and compression. To further increase robustness and to avoid visible degradation additionally the frame order and the watermark pixels were rearranged. To extract the watermark from the video the same operations have to be done on the decoder side. The incoming video frames are permutated followed by block wise DCT transform. After the decoder builds the differential spectral image the embedded coefficients can be selected and watermark extracted by inverse QIM.

Flash memory is widely used in portable devices and storage system. But flash memory has its own characteristics compared to traditional hard disk. This feature is erase-before-write and different unit of read/write and erase. For these reasons, flash memory has FTL (Flash Translation Layer) system software. Up to now many FTL algorithms have been suggested, but power off recovery scheme has not been considered. In this paper, we suggest a power off recovery scheme for block-mapping FTL. And this recovery scheme can be applied to many FTL algorithms.

As in the conventional databases, an index can be used to improve performance in MapReduce when processing OLAP queries with it. Regarding this, Hadoop++ suggested Trojan index to reduce network I/O by storing a partitioned data and its index together into a same data block, which is a data storage unit in MapReduce. However, this approach requires complex computation to put the data and index into the same block, from which index generation time can significantly increase. In this paper, we propose a new indexing method to resolve this issue. The basic idea of the proposed method is to insert the data and index into separate blocks, and force them to be co-located in the same node. Our experimental results show that the proposed method provides better performance than the existing indexing scheme, including the Trojan index.

To reversibly embed the secret data into the host image, the histogram shifting (HS) technique was proposed by embedding 1-bit secret data into the pixels in the peak points. To improve the hiding capacity of the histogram shifting technique, the residual histogram shifting (RHS) technique had been proposed. The prediction errors in the peak points of the residual histogram are used to embed the secret data. To further improve the hiding capacity, an improved block-based residual histogram shifting technique is proposed in this paper. The cascading prediction mechanism is employed in the proposed technique to generate the prediction errors for each image block. Experimental results reveal that the proposed technique provides higher hiding capacity than HS and RHS while keeping good image qualities of the embedded images.

In this paper, we propose a tracking method via structure rearrangement and multi-scale block based appearance model, plus a dynamic template mechanism within a two-stage search framework. Firstly, a wide range sampling is performed then confidence value of each candidate is calculated via a discriminative reverse sparse coefficient vote method, a part of candidates with large confidence value are selected to join in next stage. After a small range resampling in stage two, the candidates and target templates are divided into multi-scale patches, in addition, the background information is used to model the error term. Furthermore, a labeled template pool is maintained in the tracking process to dynamically generate an appropriate template set for next frame according to the occlusion map of current tracking result. Both qualitative and quantitative evaluations on challenging image sequences demonstrate that the proposed tracking algorithm performs favorably against several state-of-the-art methods.

This paper presents a new image encryption algorithm based on Chua’s chaos with the combination of baker transformation. First, we divide the original image into blocks with size 8\(\times \)8 and transform each block into three-dimensional image of binary number with size 8\(\times \)8\(\times \)8. Then, preprocess the real chaotic sequences output by Chua’s system and revise grey level of the pixel in three-dimensional image according to sequences value. Finally, use baker’s transformation to scramble image blocks and an encryption image will be obtained by this algorithm. The experimental results show that this algorithm has good encryption performance and high security.

In this article, we describe a novel collision attack for up to 5 rounds of the Grostl hash function. This significantly improves upon the best previously published results on 3 rounds. By using a new type of differential trail spanning over more than one message block we are able to construct collisions for Grostl-256 on 4 and 5 rounds with complexity of \(2^{67}\) and \(2^{120}\), respectively. Both attacks need \(2^{64}\) memory. Due to the generic nature of our attack we can even construct meaningful collisions in the chosen-prefix setting with the same attack complexity.

Bitcoin is a disruptive new crypto-currency based on a decentralized open-source protocol which has been gradually gaining momentum. Perhaps the most important question that will affect Bitcoin’s success, is whether or not it will be able to scale to support the high volume of transactions required from a global currency system. We investigate the implications of having a higher transaction throughput on Bitcoin’s security against double-spend attacks. We show that at high throughput, substantially weaker attackers are able to reverse payments they have made, even well after they were considered accepted by recipients. We address this security concern through the GHOST rule, a modification to the way Bitcoin nodes construct and re-organize the block chain, Bitcoin’s core distributed data-structure. GHOST has been adopted and a variant of it has been implemented as part of the Ethereum project, a second generation distributed applications platform.

A single character cannot describe palmprint features accurately and affect recognition results. To solve this problem, a palmprint recognition method based on fusion of contour feature and edge texture information is proposed. Firstly, mean filter is used to decompose palmprint images to obtain low frequency layer and high frequency layer. Next, the block-based idea is utilized in the two layer images, where gray histogram is used to extract counter features from the low frequency layer, at the same time differential box counting is used to extract texture information from the high frequency layer. Then, these obtained features are fused in order to further improve recognition accuracy. Finally, a common Chi-square measure is used to measure the simlarity. Experimental results on PolyU palmprint database are compared with traditional palmprint recognition algorithm, the proposed method can obtain 99.56% recognition accuracy, the time of feature extraction and matching is only 55.641ms, the effectiveness of the method is proved by lower algorithm complexity and faster speed.

Domain fluxing is a general method for botnet operators to control the victims and escape detection. Botnets based on domain fluxing, such as Conficker, Torpig, Kraken, generate a unique list of domain names based on a predefined domain generation algorithm (DGA). If the algorithm is known in advance, it is easy to identify and block botnet traffic. Unfortunately, exploiting details about the algorithm requires reverse-engineering technology and that is not always feasible.

Recent advances in block-cipher theory deliver security analyses in models where one or more underlying components e.g., a function or a permutation are ideal i.e., randomly chosen. This paper addresses the question of finding new constructions achieving the highest possible security level under minimal assumptions in such ideal models. We present a new block-cipher construction, derived from the Swap-or-Not construction by Hoang et al. CRYPTO '12. With n-bit block length, our construction is a secure pseudorandom permutation PRP against attackers making $$2^{n - O\log n}$$ block-cipher queries, and $$2^{n - O1}$$ queries to the underlying component which has itself domain size roughly n. This security level is nearly optimal. So far, only key-alternating ciphers have been known to achieve comparable security using On independent random permutations. In contrast, we only use a singlefunction or permutation, and still achieve similar efficiency. Our second contribution is a generic method to enhance a block cipher, initially only secure as a PRP, to additionally withstand related-key attacks without substantial loss in terms of concrete security.

Distributed cryptographic protocols such as Bitcoin and Ethereum use a data structure known as the block chain to synchronize a global log of events between nodes in their network. Blocks, which are batches of updates to the log, reference the parent they are extending, and thus form the structure of a chain. Previous research has shown that the mechanics of the block chain and block propagation are constrained: if blocks are created at a high rate compared to their propagation time in the network, many conflicting blocks are created and performance suffers greatly. As a result of the low block creation rate required to keep the system within safe parameters, transactions take long to securely confirm, and their throughput is greatly limited.

General cargo terminal operation system is a discrete event dynamic system with low operating efficiency. Aiming at solving the problem of low loading efficiency, this paper studied it from the perspective of yard layout. First, the yard’s handling characteristics were analyzed and the status of the yard was summarized. Second, the current situations of terminals in China and abroad were reviewed. Then a simulation model was established using the block-based design method, whose research object is handling time. Lastly, it took an actual port cargo terminal as an example to test the simulation model. Based on the cargo layout and equipment configuration of the port, two kinds of yard layout schemes based on storage strategies were proposed. Analysis results show that allocating storage space can improve operation efficiency and save time.

With the development of computer network, security has become more and more important. Intrusion Detection Systems (IDS) and firewalls have been used to detect and block malicious applications and specific protocols. As a result, some malicious applications begin to mimic common application protocol or obfuscate themselves to get rid of detection, which is called Network Evasion. Evasion hazards the Internet security seriously. So it is necessary to find a method to detect behavior of network evasion and protocol obfuscation. In this paper, we analyzed and listed some common network evasion techniques and protocol obfuscation examples. We proposed a method based on measurement and statistics to find protocol obfuscation behavior. We took web crawler as an example. We measured massive of traffic in the real high speed network, found the differences of statistical characteristics between Google web crawlers and the private web crawlers. A model was proposed to detect obfuscation of web crawlers. With this model, we found some web crawlers with the behavior of protocol obfuscation. And we think this method is useful to discover and verify other behaviors of network evasion and protocol obfuscation.

In recent years, in order to be secure, more and more Intrusion Detection Systems (IDS) and firewalls have been used to detect and block malicious applications or even unknown protocols. As a result, some malicious applications begin to shape themselves as common application protocols to get rid of detection. Being an important protocol for many Internet services, HTTP is responsible more than half of the total traffic volume. As a result, many applications choose HTTP protocol as their shaping object, leading to many abnormal behaviors. In the paper, we study the problem of discovering these abnormal behaviors in HTTP protocol. A method based on HTTP header fields’ measurement is proposed. We measure HTTP header fields’ information from HTTP traffic from normal application such as IE-8, find some characteristics and we use them to find abnormal behaviors of shaping HTTP protocol.

It takes time for theoretical advances to get used in practical schemes. Anonymous credential schemes are no exception. For instance, existing schemes suited for real-world use lack formal, composable definitions, partly because they do not support straight-line extraction and rely on random oracles for their security arguments. To address this gap, we propose unlinkable redactable signatures URS, a new building block for privacy-enhancing protocols, which we use to construct the first efficient UC-secure anonymous credential system that supports multiple issuers, selective disclosure of attributes, and pseudonyms. Our scheme is one of the first such systems for which both the size of a credential and its presentation proof are independent of the number of attributes issued in a credential. Moreover, our new credential scheme does not rely on random oracles. As an important intermediary step, we address the problem of building a functionality for a complex credential system that can cover many different features. Namely, we design a core building block for a single issuer that supports credential issuance and presentation with respect to pseudonyms and then show how to construct a full-fledged credential system with multiple issuers in a modular way. We expect this definitional approach to be of independent interest.

This study proposes a novel method for multipurpose image watermarking for both ownership verification and tampered region localization. Two watermarks (robust and fragile) are inserted into the host image. Robust watermark insertion is done by PSO (particle swarm optimization) optimized scaling of the singular values; utilizing the singular value decomposition (SVD). Doing so, leads to reduction in visibility changes (better imperceptibility) of host image as well as enhanced performance of watermarked image towards attacks (better robustness). Fragile watermark insertion is done by making use of SVD and chaotic sequence (block feature’s dependent). The image is first divided into non overlapped blocks and block based Arnold transformed is performed. Then after, block grouping is done of scrambled blocks to breakdown their independence in order to sustain the vector quantization and collage attacks. The proposed scheme is tested against various signal processing attacks and results shows a good performance.

Multi-robots are often better choices to complete search-and-rescue tasks in some large-scale disasters, such as earthquakes, mine accidents, forest fires, etc. However, effects such as shadowing and fading for GNSS signals limit the positioning ability which is most important for search-and-rescue robots. To improve positioning availability and reliability, the article proposes a GNSS Peer-to-Peer cooperation positioning system for multi-robots search-and-rescue. The peers share GNSS-only data among neighbors as aiding information under light block scenario, and share both GNSS and terrestrial ranging data under deep indoor scenario. A particle filtering algorithm, the Monte Carlo numerical approximation of Bayesian filtering, is proposed to estimate position of peers utilizing both the prior information coming from robot motion model and posterior information provided by pseudo-range and terrestrial range observations, and the algorithm flow chart is presented. As a result, the acquisition time could be reduced and sensitivity could be improved for peers under light block scenario, and position could be solved under deep indoor scenario with fewer than 4 visible satellites. Simulation results show that the positioning error of particle filtering is less than that of Non-Bayesian filtering, and the error is about 5 m for low-cost receivers.

The IEEE 802.11 standard provides multiple transmission rates. When using multiple transmission rates, the capacity of wireless LAN improves, but the performance anomaly problem may occur. Cooperative communications were introduced to alleviate the performance anomaly problem with the help of relay nodes with higher transmission rates. Previous cooperative communications protocols are based on the IEEE 802.11 DCF MAC protocol. In this paper, we apply the IEEE 802.11e EDCA features such as TXOP and block ACK for cooperative communications. Simulation results show that the proposed protocol works well and improves network performance.