The rapid growth of Ethereum has spurred widespread adoption of smart contracts, enabling substantial financial transactions. Once deployed on the blockchain, smart contracts are immutable, rendering them unmodifiable even if vulnerabilities are present. In recent years, numerous attacks exploiting these vulnerabilities have caused significant financial losses. Although prior research has improved vulnerability detection in source code or bytecode before deployment, identifying attacks that exploit vulnerabilities during the execution phase after deployment remains a significant challenge. These challenges arise from the limited adaptability of predefined detection rules and an overreliance on opcode sequence names, which often neglects a comprehensive analysis of opcode sequence properties. In this study, we propose an advanced multidimensional feature fusion technique designed to detect attacks during the execution phase of smart contracts. By leveraging deep learning, our approach enhances detection accuracy through a comprehensive analysis of attack behaviors across four dimensions: operation objects, action behaviors, functional categories, and gas consumption. Extensive experiments demonstrate that our method achieves a detection accuracy of 97.21% and a weighted F1-score of 97.21%, confirming its effectiveness in identifying attacks.

Abstract With the rapid evolution of blockchain technologies, Ethereum has emerged as a central platform for advanced financial applications but has concurrently experienced a rise in security vulnerabilities, particularly from front-running attacks. These attacks exploit transaction sequencing for illegal gains. To combat this, we introduce FRACE (Front-Running Attack Classification using Ensemble Learning), a novel methodology that classifies front-running attacks into displacement, insertion, and suppression using an ensemble learning model. This precise classification facilitates tailored defensive strategies, enhancing the robustness and accuracy of attack detection. Our approach achieves an accuracy of 95.36% and an F1-score of 95.30%, significantly improving the security of decentralized applications. Extensive analysis and validation on Ethereum confirm these results. Future efforts will refine these models and extend their application to other blockchain platforms, striving for a universally secure, transparent, and reliable digital transaction ecosystem.

Real-time fault diagnosis on vehicles can effectively avoid potential accidents, which, however, is difficult and challenging to be widely deployed due to the low computational capability and limited data storage of electric vehicles (EVs). To address this issue, we propose a vehicle-mounted fault diagnosis system with low computational complexity and small data storage, for achieving real-time monitoring of vehicle status. To facilitate the accurate and optimized feature selection, we had been collecting 6.52-GB real data from three EVs in 12 months. Motivated by those data, we first propose a multilabel feature selection algorithm to obtain the feature weights, based on which the optimal number of features is then calculated through the backpropagation neural network (BPNN), thus minimizing the computational cost of real-time fault diagnosis regarding sample dimensions. To further simplify the fault diagnosis system, i.e., reducing the minimum required capacity of data storage, we design a real-time diagnosis sliding window (RDSW) where the window moves forward as new samples arrive and the stale data outside the window are discarded. In particular, we calculate the optimal size of RDSW, which controls the minimum required number of samples to guarantee the accuracy of real-time fault diagnosis. Owing to the mechanism of RDSW, vehicles no longer need to store massive data to guarantee the accuracy of real-time fault diagnosis. In addition, the results of real-time fault diagnosis at each vehicle can be shared with other vehicles in cooperative intelligent transportation systems (C-ITS). Finally, comprehensive simulation is conducted to validate the effectiveness of the proposed diagnosis system in terms of accuracy, complexity and storage capacity.

Neighbor information perception with high accuracy and low overhead is quite essential for vehicular networks, which is accomplished by the neighbor discovery scheme. Following the scheme, nodes exchange short discovery messages for advertising their existence and sensing neighboring vehicles. To combat high vehicle mobility and severe channel fading, the discovery message is always exchanged frequently in vehicular networks. This, however, introduces superabundant communication overhead. In this article, a novel neighbor discovery method with mobility awareness and channel randomness adaptability is proposed for investigating the aforementioned issue. First, a closed-form expression is derived, which captures the quantitive relation of the neighbor discovery performance to the vehicle mobility and channel randomness. Guided by our theoretical analysis, the optimal neighbor discovery scheme is developed to adjust the discovery frequency adaptively based on mobility and channel. Thus, an optimal tradeoff between the discovery accuracy and overhead is achieved in vehicular networks. Simulation results coincide with our analysis results, which further demonstrates that the proposed discovery scheme outperforms the periodic and existing adaptive methods in terms of discovery accuracy and overhead.

Highly dynamic network has a growing demand with the popularization and application of high-speed mobile equipments, such as aircraft, unmanned boat and etc. There are many new features for highly dynamic networks over mobile networks, which include high link failure rate, high frequency enter-and-exit the network and frequent changes of the topology. Therefore, the design of access protocols is more stringent. Particularly, the packets would be invalid when waiting to be sent to the next hop node due to the link breaking with high- speed motion of the nodes in highly dynamic network. In order to better adapt to highly dynamic network scenarios, we propose a novel access protocol based on link validity prediction. Firstly, the protocol obtains the valid time of the packet in the buffer by considering the validity of the next hop link. Further, we designed a backoff mechanism based on packet valid time differentiation. We derive the mathematical expressions for the performance metrics. The performance evaluation exhibits our protocol by providing a lower latency and higher success transmission rate.

This paper addresses the minimum network cost problem for survivable virtual optical network mapping in flexible bandwidth optical networks. We develop an ILP model and the LBSD (the largest bandwidth requirement (LB) of virtual links versus the shortest distance (SD)) mapping approach to minimize the network cost for a given set of VONs, and we introduce two baseline mapping approaches, named LCLC (the largest computing resources' requirement versus the largest computing resources' provisioning (LC)) and LCSD (the largest computing resources' requirement versus shortest distance) mapping approaches, for comparison. Simulation results show that LBSD can achieve network cost near the ILP solutions in a 6-node network. Also, LBSD greatly reduces the cost, the spectrum usage, and the number of regenerators compared to LCLC and LCSD in the 6-node and NSFNET networks.

This paper addresses the problem of minimizing spectrum usage for shared-path protection with joint failure probability constraint in flexible bandwidth optical networks. To achieve this goal, we propose an integer linear programming (ILP) model for shared-path protection and a heuristic spectrum-aware shared protection (SASP) algorithm that considers joint failure probability. Simulation results show that the ILP model minimizes the total usage of frequency slots and average hops, but leads to high average joint failure probability. Moreover, the SASP algorithm achieves better trade-off between total usage of frequency slots and average joint failure probability compared to the ILP model and a conventional shared-path protection (CSPP) algorithm. As expected, in a 14-nodes network, the SASP algorithm performs better with respect to total spectrum usage and average hops, but results in much larger average joint failure probability compared to the CSPP algorithm.

A frequency quadrupling scheme for optical mm-wave signal generation is proposed and demonstrated based on dual-electrode dual-parallel integrated Mach-Zehnder modulator (MZM) consisting of three dual-electrodes MZMs. The electrical filters or optical filters are not required in this scheme. The theoretical analysis is presented to configurate the phases and DC biases of the integrated MZM. The simulation and experiment verification are both conducted to evaluate the performance of the proposed scheme. With 9GHz RF drive signal, the optical sideband suppression ratio (OSSR) higher than 35dB is demonstrated experimentally. The 36GHz mm-wave is generated with the RF spurious suppression ratio (RFSSR) over 30dB.

With the emergence of various broadband services, a lot of bandwidth fragments will be generated during the operation of services being mapped into optical channels, which will waste too many bandwidth resources and decrease the transmission performance of optical networks. Traffic grooming strategy in dynamic optical networks can optimise the utilisation of bandwidth resources and reduce the blocking probability. However, in the distributed control plane of automated switched optical networks, all the traffic grooming strategies are implemented in each control node, and resource collision will still occur because the same link resource may be used by two path computation requests or traffic engineering information flooded by open shortest path first-traffic engineering protocol may be not synchronous at each control node or signalling delay time is too long. To reduce the collision of resource, a unified control plane is designed based on path computation element (PCE) for Internet protocol over wavelength division multiplexing networks, and a novel PCE-based traffic grooming strategy is proposed in the framework of unified control plane. Based on this strategy, four PCE-based traffic grooming algorithms are proposed and compared with the distributed traffic grooming strategy without PCE on a simulation platform implemented using disperse event simulation tool OMNET++.

Pre-configured protection cycles (p-cycles) have drawn many attentions due to the fully pre-connected cyclic structures, ring-like speed, mesh-like spare capacity efficiencies and fast switching characteristics. In this paper, we propose a novel removal of loop back (RLB) approach with standard protocol extension (the flooding based distributed cycle pre-configuration (F-DCPC)) to solve the resource inefficiency issue due to long restored paths for symmetric dynamic networks. Meanwhile, distributed cycle pre-configuration (DCPC) is a representative technique for automatic p-cycle configuration. But for the mesh network topology under asymmetric service distribution, it works especially with more network convergence time and larger amount of extra controlling overhead. So in our RLB approach, F-DCPC scheme using generalized multi-protocol label switching (GMPLS) protocol to solve the problems of configurations and reconfigurations with asymmetric digraph in high-speed optical mesh networks is presented. Additionally, to describe the basic idea of traffic splitting strategy in the unidirectional resource distribution, we present the mathematic model with a heuristic algorithm to accelerate resource configuration. We evaluate the performance of F-DCPC utilizing proposed RLB approach with various classical p-cycles enumeration algorithms and allocation strategies by experimental simulations implemented in OPNET modeler, and the simulation results show the effectiveness of the proposed scheme.

In transparent WSON (wavelength switched optical networks), signals are switched optically and propagate thousands of kilometers without electrical regeneration. Over such distances, physical impairments, such as crosstalk, ASE noise and so on, can accumulate along the path and lead to signal quality degradation. If the admission of a lightpath will either cause its BER to be too high, or sufficiently degrade the performance of the already established lightpaths, it must be blocked. Most of recent research only consider the first case, but ignore the second case, which will lead to service interruption. In this paper, a new noise-aware wavelength assignment scheme called NAWA has been proposed, which use IIES (Impairments impact Evaluation Scheme) to solve both problems mentioned above in a distributed way. Simulations have been conducted and numerical results show that: Compared with normal impairment-aware solutions, NAWA can eliminate the occurrence of service interruption, and achieve better performance in total blocking.

This paper addresses the problem of distortion modeling for video transmission over burst-loss channels characterized by a finite state Markov chain. A distortion trellis model is proposed, enabling us to estimate at the frame level the expected mean-square error (MSE) distortion caused by Markov-model bursty packet losses. A sliding window algorithm is developed to perform the MSE estimation with low complexity. Simulation results show that the proposed models are accurate for all tested average loss rates and average burst lengths. Based on the experimental results, the proposed techniques are used to analyze the impact of average burst length on the average decoded video quality. The proposed model is further extended to a more general form, and the modeled distortion is compared with simulation data. These experiments demonstrate that the extended model is also accurate for all tested loss rates.

Multi-granularity optical cross-connect (MG-OXC)-based optical network is a promising optical network architecture as it is capable of flexible switching at different granularity levels. In MG-OXC-based optical networks, wavelength conversion (WC) capability and the number of usable add/drop ports of the nodes are two key factors affecting its performance. Two analytical models of blocking probability for MG-OXC-based optical networks both without WC capability and with sparse WC capability are proposed, exploiting Erlang's loss formula and birth–death process. Based on the models and simulation, the impact of WC capability and the number of add/drop ports on the blocking probability are investigated. Three kinds of granularities (i.e. fibre, waveband and wavelength) are considered in MG-OXC nodes to reduce the complexity and size of switch fabric. Both the analytical and simulation results are given on two network topologies under dynamic traffic patterns. Simulation results show that the proposed models are accurate and effective for the analysis of blocking probability in MG-OXC-based optical networks.

This paper addresses the problem of distortion modeling for video transmission over burst-loss channels characterized by a finite-state Markov chain. Based on a detailed analysis of the error propagation and the bursty losses, a distortion trellis model is proposed, enabling us to estimate at the both the frame level and sequence level the expected mean-square error (MSE) distortion caused by Markov-model burst packet losses. The model takes into account the temporal dependencies induced by both the motion-compensated coding scheme and the Markov-model channel losses. The model is applicable to most block-based motion-compensated encoders, and most Markov-model lossy channels as long as the loss pattern probabilities for that channel is computable. Based on the study of the decaying behavior of the error propagation, a sliding window algorithm is developed to perform the MSE estimation with low complexity. Simulation results show that the proposed models are accurate for all tested average loss rates and average burst lengths. Based on the experimental results, the proposed techniques are used to analyze the impact of factors such as average burst length on the average decoded video quality. The proposed model is further extended to a more general form, and the modeled distortion is compared with the data produced from realistic networks loss traces. The experiment results demonstrate that the proposed model is also accurate in estimating the expected distortion for video transmission in real networks.

Translucent WDM networks use a set of sparsely but strategically placed 2R or/and 3R regenerators to overcome physical impairments and wavelength collision introduced by fully transparent networks. In this paper, we concentrate on the study of control architectures and management approaches for connection establishment in translucent networks. A hybrid OCP (optical control plane) has been proposed, which needs the extensions of both routing and signaling protocol. In hybrid OCP, we combine the best features of routing based information updating and signaling based data collection and path evaluation, in order to achieve better performance. Simulations are conducted to compare hybrid OCP with two existing control architectures: signaling based OCP and routing based OCP. Numerical results show that hybrid OCP keeps a lower blocking probability than the other approaches, and also minimize the stability and scalability problems under various traffic conditions.

In this Comments, two typos in Li and Somani's paper are pointed out. These errors may puzzle readers or even prevent them from drawing the right conclusion. In the second part of this Comments, the authors propose a correction to these errors.

The routing and wavelength assignment (RWA) problem is very important to a wavelength-routed network especially when lacking of wavelength converters. Conventional RWA algorithms use alternated routing method to improve the blocking performance by providing multi possible routes between node pairs. But among these algorithms, there are two other crucial factors, which influence the network performance dramatically, are neglected: they are the hops of each alternative routes and the position of each link in this network. Based on this viewpoint, two new concepts are introduced to determine these characters accurately. Following these concepts, one novel RWA algorithm named less influence path first (LIPF) algorithm is proposed. It has been proved that by taking these two factors into account, the LIPF algorithm outperforms the conventional heuristic RWA algorithms.

The harmonic and intermodulation distortions induced by fiber dispersions are analyzed. The concept of the common frequency (or common period) is introduced for the analyses of intermodulation. It is shown that both the magnitude and shape of the sum terms of the intermodulation are quite similar to those of the harmonic distortions of the same order. The difference terms of the intermodulation are much smaller if the subcarrier frequencies are not far apart from one another. It is concluded that the influence of dispersion-induced distortions depends on the subcarrier frequency, the dispersion constant, the length of the fiber, and the modulation indexes. Accompanied by the development of high-frequency and large capacity systems and single-mode lasers with extra narrow spectrum, the dispersion-induced distortions may become one of the most important factors in determining information capacity and transmission distance.>