Estimating the deadline of a real-time task is a necessary prerequisite to the applications that have strict timing constraints, such as real-time systems design. This paper shows how Monte-Carlo simulation can be used as a space-efficient way of analyzing Timed Petri nets to predict whether the system specified can satisfy its real-time deadlines. For the purpose, Extended Timed Petri Net (XTPN), an extension of conventional Timed Petri net, and its execution rule, using Monte-Carlo technique, are newly defined. A simple simulation scheme with less memory space is presented as a way of estimating the deadline of a real-time task modeled in XTPN. And the comparison between the analytical and simulation results is given. The problem addressed here is to find the probabilities of meeting given deadlines.

This paper presents intelligent memory, a new memory architecture capable of providing efficient lock-free synchronization. In the intelligent memory, a sequence of operations on a shared object associated with that memory module can be processed without any intervention so that an environment for the synchronization can be provided by executing a critical section itself in that memory module. For this, we present a memory architecture for the intelligent memory having minimal instruction set and develop a progtramming model, called Critical Section Procedure (CSP), which consists of shared data structures and operations on them. Intelligent memory is intended to eliminate waste of processing time such as busy waiting in spin lock and the retry due to process contentions in existing lock-free synchronization schemes. Simulation results show that the intelligent memory provides better throughput compared with the spin lock and the existing lock-free synchronization schemes.

Malicious attackers on the Internet use automated attack programs to disrupt the use of services via mass spamming, unnecessary bulletin boarding, and account creation. Completely automated public turing test to tell computers and humans apart (CAPTCHA) is used as a security solution to prevent such automated attacks. CAPTCHA is a system that determines whether the user is a machine or a person by providing distorted letters, voices, and images that only humans can understand. However, new attack techniques such as optical character recognition (OCR) and deep neural networks (DNN) have been used to bypass CAPTCHA. In this paper, we propose a method to generate CAPTCHA images by using the fast-gradient sign method (FGSM), iterative FGSM (I-FGSM), and the DeepFool method. We used the CAPTCHA image provided by python as the dataset and Tensorflow as the machine learning library. The experimental results show that the CAPTCHA image generated via FGSM, I-FGSM, and DeepFool methods exhibits a 0% recognition rate with ε=0.15 for FGSM, a 0% recognition rate with α=0.1 with 50 iterations for I-FGSM, and a 45% recognition rate with 150 iterations for the DeepFool method.

We propose a multi-targeted backdoor that misleads different models to different classes. The method trains multiple models with data that include specific triggers that will be misclassified by different models into different classes. For example, an attacker can use a single multi-targeted backdoor sample to make model A recognize it as a stop sign, model B as a left-turn sign, model C as a right-turn sign, and model D as a U-turn sign. We used MNIST and Fashion-MNIST as experimental datasets and Tensorflow as a machine learning library. Experimental results show that the proposed method with a trigger can cause misclassification as different classes by different models with a 100% attack success rate on MNIST and Fashion-MNIST while maintaining the 97.18% and 91.1% accuracy, respectively, on data without a trigger.

We propose a velocity-based bicasting handover scheme for the efficient utilization of backhaul network resources in fourth-generation mobile systems. The original bicasting handover scheme adopts the mechanism of holding the data of a mobile station (MS) in all potential target base stations in advance, before the actual handover execution of the MS. The scheme minimizes the packet transmission delay caused by handover and achieves the goal of seamless connectivity, however, it results in an aggressive consumption of the backhaul network resources. Moreover, as the scheme gets widely adopted for high data rate real-time services and the demand for these services grows, the amount of the resources consumed due to the bicasting will increase tremendously. In this paper, we present a new bicasting handover scheme that reduces the data bicasting time, thereby improving the backhaul network resource utilization. Our scheme exploits the velocity parameter of MS and introduces a novel concept of bicasting threshold determined for the specific mobile speed groups. Simulations prove the efficiency of our scheme over the original one in overcoming the aggressive resource consumption at the backhaul network.

In a large-scale sensor network, replicated hostile nodes may be used for harsh inner attacks. To detect replicas, this paper presents a distributed, deterministic, and efficient approach robust to node compromise attacks without incurring significant resource overheads.

Deep neural networks (DNNs) are widely used in many applications such as image, voice, and pattern recognition. However, it has recently been shown that a DNN can be vulnerable to a small distortion in images that humans cannot distinguish. This type of attack is known as an adversarial example and is a significant threat to deep learning systems. The unknown-target-oriented generalized adversarial example that can deceive most DNN classifiers is even more threatening. We propose a generalized adversarial example attack method that can effectively attack unknown classifiers by using a hierarchical ensemble method. Our proposed scheme creates advanced ensemble adversarial examples to achieve reasonable attack success rates for unknown classifiers. Our experiment results show that the proposed method can achieve attack success rates for an unknown classifier of up to 9.25% and 18.94% higher on MNIST data and 4.1% and 13% higher on CIFAR10 data compared with the previous ensemble method and the conventional baseline method, respectively.

We propose an efficient and practical seamless handoff scheme for 4G mobile systems based on IP and OFDM. The seamless handoff scheme obtains the physical channel for handoff in a contention-free manner with pre-synchronization and pre-forwarding IP contexts. As a result, it thoroughly decreases the physical channel blocking time as well as IP layer context-switching time to minimize total handoff delay.

To control various access privileges in group-oriented applications having multiple data streams, we present a novel reactive key management scheme where each member can obtain the key of a data stream from public parameters only when necessary. Compared with the previous schemes, this scheme significantly reduces the amount of rekey messages for dynamic membership change due to its reactive nature.

This letter proposes a novel mobile sensor deployment scheme for maximizing coverage. The basic idea is to force mobile sensors to move to predetermined target points that are the optimal layout in a distributed manner using Voronoi diagram data structure. A simulation shows that the result of the proposed scheme is quite close to the optimal result and outperforms previous works.

Multipath interconnection networks can support higher bandwidth than those of nonblocking networks by passing multiple packets to the same output simultaneously and these packets are buffered in the output buffer. The delay-throughput performance of the output buffer in multipath networks is closely related to output traffic distribution, packet arrival process at each output link connected to a given output buffer. The output traffic distributions are different according to the various input traffic patterns. Focusing on nonuniform output traffic distributions, this paper develops a new, general analytic model of the output buffer in multipath networks, which enables us to investigate the delay-throughput performance of the output buffer under various input traffic patterns. This paper also introduces Multipath Crossbar network as a representative multipath network which is the base architecture of our analysis. It is shown that the output buffer performances such as packet loss probability and delay improve as nonuniformity of the output traffic distribution becomes larger.

In this study, a novel binary image authentication scheme is proposed, which can be used to detect any alteration of the host image. In the proposed scheme, the watermark is embedded into a host image using a Hamming-code-based embedding algorithm. A performance analysis shows that the proposed scheme achieves both smaller distortion and lower false negative rates than the previous schemes.

In this paper, we propose a new handover algorithm to guarantee handover quality in 4G mobile systems. The proposed algorithm limits the handover interruption time by improving the HARQ retransmission latency of the first packet transmitted from new serving cell. Through the simulations, we proved that our algorithm meets the requirement of handover interruption time for TCP services with high rate.

An adaptive channel access control method for CDMA/PRMA protocol is proposed. The proposed method utilizes a load and backlog based access control. Dynamic optimal channel loads by which the required packet loss probability can be satisfied are obtained. The number of contending terminals is also estimated more accurately, using statistical characteristics of source models. Permission probability is then calculated based on the dynamic optimal channel load and the estimated number of contending terminals such that the mean channel load (the mean number of packets transmitted in each time slot) can be maintained at the optimal channel load. By maintaining the mean channel load at the dynamic optimal channel load, the radio channel can be very effectively utilized, satisfying the required packet loss probability. A backlog based data transmission using a mixed mode of contention and reservation mode is also proposed to reduce redundant contention and corruption. Simulations are carried out in an isolated cell environment and a cellular environment. The simulation results show that the system capacity can be improved significantly by the proposed method compared with the conventional permission control methods.

Several structured peer-to-peer networks have been created to solve the scalability problem of previous peer-to-peer systems such as Gnutella and Napster. These peer-to-peer networks which support distributed hash table functionality construct a sort of structured overlay network, which can cause a topology mismatch between the overlay and the underlying physical network. To solve this mismatch problem, we propose a topology-aware hierarchical overlay framework for DHTs. The hierarchical approach for the overlay is based on the concept that the underlying global Internet is also a hierarchical architecture, that is, a network of networks. This hierarchical approach for the overlay puts forth two benefits: finding data in a physically near place with a high probability, and smaller lookup time. Our hierarchical overlay framework is different from other hierarchical architecture systems in a sense that it provides a specific self-organizing grouping algorithm. Our additional optimization schemes complete the basic algorithm which constructs a hierarchical structure without any central control.

The crucial handover elements in wireless ATM networks are handover delay and handover efficiency. Since the research about the handover in wireless ATM has until now focused mainly on minimizing handover delay, the results have shown the inefficiency of network resources. In broadband wireless ATM networks, handover efficiency is critical to network capacity. In this paper, we propose a new handover scheme based on a partial path rerouting scheme called the delay limited best-fit backtracking scheme. The scheme searches for the crossover switch that limits handover delay and at the same time maximizes handover efficiency. It uses a new crossover switch searching method, which is an adaptive backtracking searching method that uses a best-fit search manner, to search for the optimal crossover switch that satisfies the given crossover switch condition. We evaluated the performance of proposed handover scheme, and show that the suggested scheme can improve handover efficiency more than other handover schemes.

In this paper, we present a faster (wall-clock time) sorting method for numerical data subjected to fully homomorphic encryption (FHE). Owing to circuit-based construction and the FHE security property, most existing sorting methods cannot be applied to encrypted data without significantly compromising efficiency. The proposed algorithm utilizes the cryptographic single-instruction multiple-data (SIMD) operation, which is supported by most existing FHE algorithms, to reduce the computational overhead. We conducted a careful analysis of the number of required recryption operations, which are the computationally dominant operations in FHE. Accordingly, we verified that the proposed SIMD-based sorting algorithm completes the given task more quickly than existing sorting methods if the number of data items and (or) the maximum bit length of each data item exceed specific thresholds.

We propose a rootkit installation method inside a GPU kernel execution process which works through GPU context manipulation. In GPU-based applications such as deep learning computations and cryptographic operations, the proposed method uses the feature by which the execution flow of the GPU kernel obeys the GPU context information in GPU memory. The proposed method consists of two key ideas. The first is GPU code manipulation, which is able to hijack the execution flow of the original GPU kernel to execute an injected payload without affecting the original GPU computation result. The second is a self-page-table update execution during which the GPU kernel updates its page table to access any location in system memory. After the installation, the malicious payload is executed only in the GPU kernel, and any no evidence remains in system memory. Thus, it cannot be detected by conventional rootkit detection methods.

Duty-cycle MAC protocols have been proposed for wireless sensor networks (WSNs) to reduce the energy consumed by idle listening, but they introduce significant end-to-end delivery latency. Several works have attempted to mitigate this latency, but they still have a problem on handling the packet loss. The quality of the wireless channel in WSNs is quite bad, so packets are frequently lost. In this letter, we present a novel duty-cycle MAC protocol, called REMAC (Retransmission-Enhanced duty-cycle MAC), which exploits both the network layer and the physical layer information. REMAC estimates the quality of the wireless channel and properly reserves the wireless channel to handle the packet loss. It can reduce the end-to-end packet delivery latency caused by the packet loss without sacrificing the energy efficiency. Simulation results show that REMAC outperforms RMAC in terms of the end-to-end packet delivery latency.

This paper analyzes the user-perceived QoS (Quality of Service) of interactive data application, the most notable being web browsing, in a shared wireless packet access network. We present elaborate analytical results regarding the mean page delay, the Equivalent Circuit Rate (ECR), and the system saturation point for interactive data users with different channel conditions. The ECR for a user in a shared access network is the channel rate that a dedicated connection would need in order to offer an equivalent user experience. The system saturation point is the maximum number of users that can be served with a given tolerable service delay in a shared packet access system. These analytical results are useful in the performance prediction of a real wireless environment with multiple user groups that are served with different service rates due to multiple channel conditions. Therefore, our analytical results can be used in the network planning, admission control, and service differentiation for different user groups. Our analysis is demonstrated to be in good accord with computer simulations performed on model systems based on EDGE TDMA and IEEE 802.16 OFDMA.