A multi-step targeted cyberattack refers to a sophisticated, systematic, and persistent form of attack aiming to compromise the security and integrity of a complex network system. These attacks exhibit spatial and tem...
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ISBN:
(纸本)9798350381993;9798350382006
A multi-step targeted cyberattack refers to a sophisticated, systematic, and persistent form of attack aiming to compromise the security and integrity of a complex network system. These attacks exhibit spatial and temporal correlations in their execution sequences. However, conventional anomaly detection methods, which often focus on single facets such as network traffic or host behavior, lack the capacity to correlate and validate these steps. To address this deficiency, we introduce HiSec, a cyber threat correlation and discovery framework that leverages dynamic graph modeling and hierarchical graph neural networks. HiSec enhances the modeling of complex network systems and the analysis of spatio-temporal characteristics of multi-step targeted cyberattacks. Specifically, we introduce a novel dynamic graph modeling algorithm that employs overlapping samplers and sliding windows to establish long-term correlations among system activities. Aided by graph attention networks and the Transformer, HiSec uniquely exploits the spatio-temporal correlated edge feature representation, a capability inaccessible to traditional algorithms. Evaluation results reveal that HiSec surpasses existing benchmarks in unsupervised detection, achieving a high degree of accuracy (93.10%) and recall (94.77%). When deployed in our intranet for two rounds of evaluation, HiSec demonstrated remarkable efficiency, taking only 0.15 seconds to model 10,000 system activities occurring within approximately an hour.
In recent years, 5G/5G-A technology has fast developed and found widespread deployment, meeting the diverse requirements of application scenarios across various industries. In this paper, we introduce the principle an...
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ISBN:
(纸本)9798350381993;9798350382006
In recent years, 5G/5G-A technology has fast developed and found widespread deployment, meeting the diverse requirements of application scenarios across various industries. In this paper, we introduce the principle and advantages of 5G/5G-A private network Then, we introduce the construction of 5G/5G-A private network. Furthermore, we design an intelligent operation system of 5G/5G-A private network, which includes six key modules with over twenty functionalities. This intelligent operation system can effectively support the operation of 5G/5G-A private network Lastly, this paper introduces the 5G/5G-A private network applications in a realistic vehicle factory.
To satisfy the increasing demand for ubiquitous networks, Satellite Internet has attracted considerable attention from both academia and industry. This innovative modality, comparing with terrestrial 4G/5G networks, p...
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ISBN:
(纸本)9798350381993;9798350382006
To satisfy the increasing demand for ubiquitous networks, Satellite Internet has attracted considerable attention from both academia and industry. This innovative modality, comparing with terrestrial 4G/5G networks, provides expedient network services while achieving complex and inventive network architectures. Despite the Satellite Internet generates and retains an enormous amount of data every day, it is not completely employed due to security concerns. Hence, data coordination is still a fledgling area without effective data security protection mechanisms in place. This paper aims to introduce confidential computing into Satellite Internet to impart secured data coordination capability to it.
Image hiding task is an important task in the field of informationsecurity, where the main objectives are to ensure image quality, payload, and undetectability while hiding secret images. Nowadays, deep learning-base...
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ISBN:
(纸本)9798400716751
Image hiding task is an important task in the field of informationsecurity, where the main objectives are to ensure image quality, payload, and undetectability while hiding secret images. Nowadays, deep learning-based image steganography methods have surpassed most traditional methods, and among these deep learning-based methods, the utilization of a reversible network for image hiding has shown excellent performance. A reversible network is a type of neural network with special properties that enable bidirectional mapping between input and output. It possesses unique advantages in image hiding tasks, ensuring the integrity of hidden information while simultaneously preserving image quality. However, existing reversible neural networks used for image hiding still face security concerns. In this paper, we propose an image hiding method based on a reversible and a scoring network that uses gradient computation to improve the network training process and to achieve higher embedding capacity, lower distortion, and higher security. Further, in the stage of image hiding and recovery, we use dynamic convolution blocks to improve the visual quality to a certain extent while the recovery accuracy is improved. We conducted experiments on the ImageNet, COCO, and DIV2K datasets, and the results indicate that our method improves both image quality and security in terms of comprehensive
Cloud computing adoption has increased dramatically over the past few years, making the protection of sensitive data on the cloud a major concern. In this paper networksecurity is presented as an effective way to ens...
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Cloud computing is a significant leap in the development process of the information industry. It integrates computing, storage, network, and other information resources organically, providing more convenient means for...
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When the data service latency of mobile network is too large, it will cause problems such as slow page opening, game stuck, video stuck and seriously affect user perception. Therefore, optimizing the network and reduc...
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ISBN:
(纸本)9798350381993;9798350382006
When the data service latency of mobile network is too large, it will cause problems such as slow page opening, game stuck, video stuck and seriously affect user perception. Therefore, optimizing the network and reducing latency become one of the main tasks in mobile network. This paper researches on the analysis method of 5G data service latency problem. A set of analysis methods, which are for problem demarcation and localization, are provided to support network operation and maintenance personnel in improving user perception, focusing on the key performance of wireless and core networknetworks that affect the service.
Vehicular Cloud (VC) computing is described as a network of vehicles capable of sharing information and various resources, including computational power, storage, and bandwidth, among drivers. Vehicles in a connected ...
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ISBN:
(纸本)9798350385328;9798350385335
Vehicular Cloud (VC) computing is described as a network of vehicles capable of sharing information and various resources, including computational power, storage, and bandwidth, among drivers. Vehicles in a connected network can not only share their own data and processing power, but also distribute them as customized services for others to use on-demand. The Vehicular Cloud computing concept, while promising, raises significant security and privacy concerns that must be addressed before widespread adoption. Safeguarding the confidentiality, integrity, and availability of data and services in this framework, along with ensuring the privacy of users and their sensitive information, poses significant challenges that must be addressed. Implementing a trust-based authentication strategy stands out as a viable solution for addressing security and privacy issues in vehicular clouds. This paper evaluates the performance of a trust-based authentication model for vehicular cloud computing. Notably, the model operates autonomously, eliminating the need for a central server to monitor vehicle trust scores. Another significant feature of this model lies in the collaboration among different node types, a novel approach that enhances the model's performance. In our work, we use comprehensive set of simulations to evaluate the performances of the model.
Pattern matching is a crucial technique for network traffic detection applications. As a fundamental computation model used by pattern matching, the finite state automata execute sequential matching due to the state d...
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ISBN:
(纸本)9798350381993;9798350382006
Pattern matching is a crucial technique for network traffic detection applications. As a fundamental computation model used by pattern matching, the finite state automata execute sequential matching due to the state dependence among transitions. Meanwhile, most services tend to compress their data to improve transmission or storage efficiency. The increased compressed data challenges the straightforward method of matching the whole decompressed data and incurs data dependence among the compression encodings. The related approaches either leverage techniques to break the state dependence of matching uncompressed data or accelerate matching compressed data in a single-threaded manner without considering the state and data dependence. None of them can perform parallel matching over compressed data. This paper provides PETALS, a parallel pattern matching method over Broth compressed network traffic. PETALS partitions the original compressed traffic into fixed-length blocks for parallel matching and patches the broken compression encodings crossing blocks to break the data dependence. Then, it merges the compressed traffic matching method into path fusion, an enumerative parallelization of finite state automata, to present parallel matching over compressed traffic. Evaluation using real-world network traffic and regular expressions shows that PETALS can raise the speedup from 1.53x to 3.53x of the state-of-the-art parallelization schemes on a 56-cores machine.
Against the backdrop of continuous development of computer technology, the service scope of the network system is constantly expanding, and the service capability is significantly improving to meet the growing materia...
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