Private Set Intersection (PSI) is one of the most important functions in secure multiparty computation (MPC). PSI protocols have been a practical cryptographic primitive and there are many privacy-preserving applicati...
Private Set Intersection (PSI) is one of the most important functions in secure multiparty computation (MPC). PSI protocols have been a practical cryptographic primitive and there are many privacy-preserving applications based on PSI protocols such as computing conversion of advertising and distributed computation. Private Set Intersection Cardinality (PSI-CA) is a useful variant of PSI protocol. PSI and PSI-CA allow several parties, each holding a private set, to jointly compute the intersection and cardinality, respectively without leaking any additional information. Nowadays, most PSI protocols mainly focus on two-party settings, while in multiparty settings, parties are able to share more valuable information and thus more desirable. On the other hand, with the advent of cloud computing, delegating computation to an untrusted server becomes an interesting problem. However, most existing delegated PSI protocols are unable to efficiently scale to multiple clients. In order to solve these problems, this paper proposes MDPPC, an efficient PSI protocol which supports scalable multiparty delegated PSI and PSI-CA operations. Security analysis shows that MDPPC is secure against semi-honest adversaries and it allows any number of colluding clients. For 15 parties with set size of 2 20 on server side and 2 16 on clients side, MDPPC costs only 81 seconds in PSI and 80 seconds in PSI-CA, respectively. The experimental results show that MDPPC has high scalability.
In software-defined networks(SDNs),controller placement is a critical factor in the design and planning for the future Internet of Things(IoT),telecommunication,and satellite communication *** research has concentrate...
详细信息
In software-defined networks(SDNs),controller placement is a critical factor in the design and planning for the future Internet of Things(IoT),telecommunication,and satellite communication *** research has concentrated largely on factors such as reliability,latency,controller capacity,propagation delay,and energy ***,SDNs are vulnerable to distributed denial of service(DDoS)attacks that interfere with legitimate use of the *** ever-increasing frequency of DDoS attacks has made it necessary to consider them in network design,especially in critical applications such as military,health care,and financial services networks requiring high *** propose a mathematical model for planning the deployment of SDN smart backup controllers(SBCs)to preserve service in the presence of DDoS *** a number of input parameters,our model has two distinct ***,it determines the optimal number of primary controllers to place at specific locations or nodes under normal operating ***,it recommends an optimal number of smart backup controllers for use with different levels of DDoS *** goal of the model is to improve resistance to DDoS attacks while optimizing the overall cost based on the *** simulated results demonstrate that the model is useful in planning for SDN reliability in the presence of DDoS attacks while managing the overall cost.
Existing smart contract vulnerability identification approaches mainly focus on complete program detection. Consequently, lots of known potentially vulnerable locations need manual verification, which is energy-exhaus...
详细信息
As an important node in the dismantling and grouping of freight trains, the operational tasks of the railway technical station are increasingly busy. Various business activities involve a large number of field personn...
详细信息
ISBN:
(数字)9798350349252
ISBN:
(纸本)9798350349269
As an important node in the dismantling and grouping of freight trains, the operational tasks of the railway technical station are increasingly busy. Various business activities involve a large number of field personnel, and ensuring the personal safety and operational efficiency of these personnel is one of these issues that railway operations need to *** ensure the operational safety and standardization at the railway technical station, high-precision positioning system for the personnel is required. However, typical operational scenarios at railway technical stations often involve problems such as the carriage obstruction and the electromagnetic interference. Only rely on GNSS for positioning is often insufficient to meet practical requirements. Addressing the need of the high-precision positioning for the operational personnel at railway technical stations, this paper constructs a integrated navigation system based on RTK and IMU . It utilizes a Discrete Error State Kalman Filtering algorithm to fuse the solution data from RTK and IMU, thereby obtaining high-precision pedestrian positioning data. Compared to relying solely on GNSS positioning system, the integrated navigation system significantly improves its resistance to the interference and positioning accuracy. Experimental results demonstrate that this positioning system can achieve centimeter-level positioning in obstructed scenarios typical of railway technical stations, meeting the positioning requirements of the operational personnel at railway technical station work sites.
The features used in many image analysis-based applications are frequently of very high dimension. Feature extraction offers several advantages in high-dimensional cases, and many recent studies have used multi-task f...
详细信息
Microservice architectures are increasingly used to modularize IoT applications and deploy them in distributed and heterogeneous edge computing environments. Over time, these microservice-based IoT applications are su...
详细信息
Microservice architectures are increasingly used to modularize IoT applications and deploy them in distributed and heterogeneous edge computing environments. Over time, these microservice-based IoT applications are susceptible to performance anomalies caused by resource hogging (e.g., CPU or memory), resource contention, etc., which can negatively impact their Quality of Service and violate their Service Level Agreements. Existing research on performance anomaly detection for edge computing environments focuses on model training approaches that either achieve high accuracy at the expense of a time-consuming and resource-intensive training process or prioritize training efficiency at the cost of lower accuracy. To address this gap, while considering the resource constraints and the large number of devices in modern edge platforms, we propose two clustering-based model training approaches: (1) intra-cluster parameter transfer learning-based model training (ICPTL) and (2) cluster-level model training (CM). These approaches aim to find a trade-off between the training efficiency of anomaly detection models and their accuracy. We compared the models trained under ICPTL and CM to models trained for specific devices (most accurate, least efficient) and a single general model trained for all devices (least accurate, most efficient). Our findings show that ICPTL’s model accuracy is comparable to that of the model per device approach while requiring only 40% of the training time. In addition, CM further improves training efficiency by requiring 23% less training time and reducing the number of trained models by approximately 66% compared to ICPTL, yet achieving a higher accuracy than a single general model.
This paper describes the implementation of transmission-line matrix (TLM) method algorithms on a massively parallelcomputer (DECmpp 12000), the technique of distributed computing in the UNIX environment, and the comb...
详细信息
This paper describes the implementation of transmission-line matrix (TLM) method algorithms on a massively parallelcomputer (DECmpp 12000), the technique of distributed computing in the UNIX environment, and the combination of TLM analysis with Prony's method as well as with autoregressive moving average (ARMA) digital signal processing for electromagnetic field modelling. By combining these advanced computation techniques, typical electromagnetic field modelling of microwave structures by TLM analysis can be accelerated by a few orders of magnitude.
Data mining tools are widely used in computer networks. The well-known and mostly used tools to secure computers and network systems are WEKA and TANAGRA. The purpose of this study is to compare these two tools in ter...
详细信息
ISBN:
(纸本)9781665478250
Data mining tools are widely used in computer networks. The well-known and mostly used tools to secure computers and network systems are WEKA and TANAGRA. The purpose of this study is to compare these two tools in terms of detection accuracy and computation time. This comparison was conducted using a well-known NSL-KDD dataset. Experiments show that TANAGRA achieves better results than WEKA in detection accuracy. But, TANAGRA is competitive with WEKA in terms of computation time.
暂无评论