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Joint Optimization Algorithm for Adaptive Bit Allocation Based on Temporal-Spatial Information

Joint Optimization Algorithm for Adaptive Bit Allocation Bas...

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Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA)

作者： Shaokang Wang Songlin Sun School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China Ministry of Education Key Laboratory of Trustworthy Distributed Computing and Service (BUPT) China Ministry of Education Engineering Research Center of Blockchain and Network Convergence Technology China

Versatile Video Coding (VVC) standard further improves the video compression ratio. Despite inter prediction and intra prediction effectively eliminating temporal and spatial residual information, there is still room for further improvement in rate control (RC) accuracy and rate distortion (R-D) performance. In view of the above issues, the joint optimization RC algorithm for adaptive bit allocation for VVC is proposed. In this paper, the proposed algorithm utilizes a specific pre-analysis mechanism so that the Temporal-Spatial Information (TSI) is obtained. And then the TSI is integrated into the RC model so as to optimize adaptive bit allocations for frame-level and coding tree unit level (CTU-level). Experimental results have shown that compared to the default RC under common test conditions (CTC), the proposed RC algorithm achieves obvious 2.26% Bjøntegaard Delta rate (BD-rate) saving, and the RC accuracy can be improved in the Random Access (RA) configuration.

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A Hybrid Routing Mutation Mechanism based on Mutation Cost and Resource Trustworthiness in Network Moving Target Defense 7

A Hybrid Routing Mutation Mechanism based on Mutation Cost a...

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7th IEEE International Conference on Data Science in Cyberspace, DSC 2022

作者： Guo, Kun Gao, Yibo Wang, Dongbin Zhi, Hui Zhang, Tao Lu, Yueming Key Laboratory of Trustworthy Distributed Computing and Service Ministry of Education Beijing University of Posts and Telecommunications Beijing China Beijing University of Posts and Telecommunications Cyberspace Security Research Center Peng Cheng Laboratory Beijing China Beijing University of Posts and Telecommunications National Engineering Laboratory for Mobile Network Beijing China TravelSky Technology Limited Beijing China China Academy of Launch Vehicle Technology Beijing China

ISBN: (数字)9781665474801

ISBN: (纸本)9781665474801

Network moving target defense technology can effectively defend against attacker monitoring of the service. The technology makes it more difficult for attackers to attack and can ensure secure communication for services. However, there may be multiple network attacks in the network. As a result, there may be security problems with the trustworthiness of the network resource mutation space required for network moving target defense technology. The focus of current researches is mostly on the mutation timing and cost optimization of the resource mutation space. It may lead to the possibility that the resources in the resource mutation space have been already under network attacks. In this paper, we propose a hybrid routing mutation mechanism based on mutation cost and resource trustworthiness in SDN networks. The mechanism is able to evaluate the routing mutation space selected by the routing-based network moving target defense technology. In terms of both mutation cost and resource trustworthiness, the optimal weighting ratio of the two factors will be to discovered. Simulation results show that the proposed mechanism can effectively enhance the ability of the routing mutation space to avoid attacked nodes and links and improve the transmission success rate of services. © 2022 IEEE.

关键词： Network routing

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Progressive Evolution Scheme with Socialization Swarm for Privacy Blockchain

Progressive Evolution Scheme with Socialization Swarm for Pr...

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Pacific Rim International Symposium on Dependable computing

作者： Daoqi Han Tao Yu Yueming Lu Key Laboratory of Trustworthy Distributed Computing and Service Ministry of Education Beijing University of Posts and Telecommunications Beijing China Institute of Network Science and Cyberspace Tsinghua University Beijing China

To enhance the dependability of lightweight blockchain, this paper presents a privacy protection mechanism in open networks with a secure ledger for each cell of society. We propose a swarm intelligence scheme called hierarchical RAFT (HRAFT), which accumulates valuable workloads about the credibility of all the nodes to sort for selecting candidates. Thus, the scheme achieves high-performance decentralization by progressive evolution consensus.

关键词： Privacy Schedules Blockchains Particle swarm optimization

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Communication Encryption Scheme of 5G Power Trading Private Network Based on Dynamic key

Communication Encryption Scheme of 5G Power Trading Private ...

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Electrical, Power and Computer Engineering (EPCE), Asia Conference on

作者： Rui Zhou Yiyang Song Ying Xu Electrical Engineering and Automation School Harbin Institute of Technology Harbin China Information Data Department Guangdong Power Exchange Center Guangzhou China Key Laboratory of Trustworthy Distributed Computing and Service Beijing University of Posts and Telecommunications Beijing China

Security has been the primary concern for the 5G power trading private network, which involves a large amount of power trading information. The communication must be encrypted to prevent the leakage of important information. The communication encryption scheme for 5G power trading private network should meet the characteristics of small communication overhead, low storage space requirement and strong resistance to attack. Based on these characteristics, the dynamic key-based encryption scheme is designed. To ensure the security and reduce the computation overhead, the optimized symmetric encryption algorithm is used to update the shared key. And the dynamic key generation method is improved by adding random numbers to solve the problem that the correct transmission of the data link does not have true randomness. The encryption mode used can generate dynamic keys directly and synchronously at both ends of the communication, reducing the overhead of key exchange and eliminating the need for trusted third parties. The algorithm is also analyzed for security and efficiency and compared with other algorithms. The experimental results show that the improved algorithm enhances security with guaranteed efficiency.

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Blockchain Storage Method Based on Erasure Code

Blockchain Storage Method Based on Erasure Code

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IEEE International Conference on Data Science in Cyberspace (DSC)

作者： Fanyao Meng Jin Li Jiaqi Gao Junjie Liu Junpeng Ru Yueming Lu Key Lab of Trustworthy Distributed Computing and Service Ministry of Education School of Cyberspace Security Beijing University of Posts and Telecommunications Beijing China The State Key Laboratory of Information Photonics and Optical Communications School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China

Blockchain, as an emerging distributed database, effectively addresses the issue of centralized storage in IoT data, where storage capacity cannot match the explosive growth in devices and data scale, as well as the contradictions arising from centralized data management concerning data privacy and security concerns. To alleviate the problem of excessive pressure on single-point storage and ensure data security, a blockchain data storage method based on erasure codes is proposed. This method involves constructing mathematical functions that describe the data to split the original block data into multiple fragments and add redundant slices. These fragments are then encoded and stored in different locations using a circular hash space with the addition of virtual nodes to ensure load balancing among nodes and reduce situations where a single node stores too many encoded data blocks, effectively enhancing the storage space utilization efficiency of the distributed storage database. The blockchain storage method stores encoded data digest information such as storage location, creation time, and hashes, allowing for the tracing of the origin of encoded data blocks. In case of accidental loss or malicious tampering, this enables effective recovery and ensures the integrity and availability of data in the network. Experimental results indicate that compared to traditional blockchain approaches, this method effectively reduces the storage pressure on nodes and exhibits a certain degree of disaster recovery capability.

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IWRN:A Robust Blind Watermarking Method for Artwork Image Copyright Protection Against Noise Attack 39

IWRN:A Robust Blind Watermarking Method for Artwork Image Co...

引用

39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Kou, Feifei Yao, Yuhan Yao, Siyuan Wang, Jiahao Shi, Lei Li, Yawen Kang, Xuejing School of Computer Science National Pilot School of Software Engineering BUPT Beijing 100876 China Key Laboratory of Trustworthy Distributed Computing and Service BUPT Ministry of Education Beijing 100876 China School of Economics and Management BUPT Beijing 100876 China State Key Laboratory of Media Convergence and Communication CUC Beijing 100024 China State Key Laboratory of Intelligent Game Yangtze River Delta Research Institute of NPU Taicang 215400 China

ISBN: (纸本)157735897X

Adding imperceptible watermarks to artwork images, such as paintings and photographs, can effectively safeguard the copyright of these images without compromising their usability. However, existing blind watermarking techniques encounter two major challenges in addressing this task: imperceptibility and robustness, particularly when subjected to various noise attacks. In this paper, we propose a blind watermarking method for artwork image copyright protection, IWRN, which can ensure both the Imperceptibility of the Watermark and Robustness against Noise attacks. For imperceptibility, we design a Learnable Wavelet Network (LWN) to adaptively embed the watermark into the high-frequency region where the watermark has better invisibility. For robustness, we establish a Deform-Attention based Invertible Neural Network (DA-INN) with a decoding optimization, which offers the advantage of computational reversion, and combines the deform-attention mechanism and decoding optimization to enhance the model’s resistance against noises. Additionally, we design a Joint Contrast Learning (JCL) mechanism to improve imperceptibility and robustness simultaneously. Experiments show that our IWRN outperforms other state-of-the-art blind watermarking methods, achieves an average performance of 46.74 PSNR and 99.91% accuracy across three datasets when facing 12 kinds of noise attacks. © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Contrastive Learning

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PMU-Spill: Performance Monitor Unit Counters Leak Secrets in Transient Executions

PMU-Spill: Performance Monitor Unit Counters Leak Secrets in...

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IEEE Asian Hardware-Oriented Security and Trust (AsianHOST)

作者： Pengfei Qiu Qiang Gao Dongsheng Wang Yongqiang Lyu Chang Liu Xiaoyong Li Chunlu Wang Gang Qu Key Laboratory of Trustworthy Distributed Computing and Service (BUPT) Ministry of Education Tsinghua University Beijing China Department of Computer Science and Technology Beijing National Research Center for Information Science and Technology Tsinghua University Beijing China Ministry of Education Key Laboratory of Trustworthy Distributed Computing and Service (BUPT) Beijing China Department of Electrical and Computer Engineering Institute for Systems Research University of Maryland Maryland USA

ISBN: (纸本)9781665461153

The processor's Performance Monitor Unit (PMU) allows the recording of architectural and microarchitectural events for profiling purposes. In this study, we reveal a security issue caused by the fact that current PMU implementations are capable of recording some events that happened during transient executions. We propose the PMU -Spill attack, a new kind of attack that enables attackers to maliciously leak the secret data in transient executions. We demonstrate on real hardware that PMU -Spill attack can leak the secret data stored in Intel Software Guard Extensions (SGX). In addition, we perform a thorough study to reveal all the vulnerable PMU counters and find that 20 of them can be used to achieve PMU -Spill attack. Our experiments suggest that the throughput of PMU -Spill attack is up to 575.3 bytes per second (Bps) with an average error rate of 1.89% when leaking the SGX-protected secret data.

关键词： Side-channel attacks Throughput Phasor measurement units Hardware Software Recording Security

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EML-Based IM/DD Transmission over Dispersion-Uncompensated Links Using Low-Complexity Optimized Detection

EML-Based IM/DD Transmission over Dispersion-Uncompensated L...

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2021 Asia Communications and Photonics Conference, ACP 2021

作者： Liu, Shuangyue Cui, Han Tang, Xizi Lu, Yueming Qiao, Yaojun State Key Laboratory of Information Photonics and Optical Communications School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China Key Laboratory of Trustworthy Distributed Computing and Service Ministry of Education School of Cyberspace Security Beijing University of Posts and Telecommunications Beijing100876 China

We experimentally demonstrate an EML-based 40-Gbit/s OOK IM/DD transmission over 120-km SSMF using a low-complexity optimized detection algorithm, which requires no multiplication during the update of survival path, s... 详细信息

ISBN: (纸本)9781957171005

关键词： Chromatic dispersion

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Automated Vulnerability Discovery System Based on Hybrid Execution 7

Automated Vulnerability Discovery System Based on Hybrid Exe...

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7th IEEE International Conference on Data Science in Cyberspace, DSC 2022

作者： Liu, Tong Wang, Zhongru Zhang, Yuntao Liu, Zhehui Fang, Binxing Pang, Zhengyuan Ministry of Education Key Laboratory of Trustworthy Distributed Computing and Service Beijing China Chinese Academy of Cyberspace Studies Beijing China North China University of Technology School of Information Science and Technology Beijing100144 China Beijing DigApis Technology Co. Ltd Beijing100871 China JiangSu DigApis Technology Co. Ltd Jiangsu Nantong226000 China

ISBN: (数字)9781665474801

ISBN: (纸本)9781665474801

At present, program vulnerabilities occur frequently, which seriously threatens the security of cyberspace. Automated vulnerability discovery technology has attracted more and more attention because of its efficiency and universality. In the current field of vulnerability discovery, it is common to combine fuzzing with symbolic execution technology. Symbolic execution technology is often used to solve the input of complex paths and help fuzzing improve the program coverage, so as to detect vulnerabilities better. However, the symbolic execution has no goals in the process of hybrid execution exploration path, it is easy to cause the execution path to deviate from the expected target points. And generating the test case of the corresponding path requires frequently calling the solver for solution, while the current solver has low efficiency and poor solvability for nonlinear operation. In order to solve the above problems, we propose an automated vulnerability discovery system based on hybrid execution. In the system, we propose the symbolic execution guidance algorithm based on dynamic and static combination to guide the symbolic execution to solve the input reaching the target points, so as to avoid exploring in useless paths and avoid consuming a lot of time and computing resources. In addition we hook some nonlinear functions to optimize the nonlinear function constraint solving, so as to improve the hybrid execution efficiency. We have conducted extensive experiments on the RHG 2019 challenge dataset and the RHG 2021 challenge dataset. The experimental results show the effectiveness and scalability of the system. © 2022 IEEE.

关键词： Efficiency

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Decode the Dark Side of the Language: Applications of LLMs in the Dark Web

Decode the Dark Side of the Language: Applications of LLMs i...

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IEEE International Conference on Data Science in Cyberspace (DSC)

作者： Hongfan Chen Yigang Diao Hui Xiang Yixuan Huo Xiaqing Xie Jiapeng Zhao Xuebin Wang Yanwei Sun Jinqiao Shi School of Cyberspace Security Beijing University of Posts and Telecommunications Beijing China The State Key Laboratory of Blockchain and Data Security Zhejiang University Hangzhou China Key Laboratory of Trustworthy Distributed Computing and Service (BUPT) Ministry of Education Beijing China Cyberspace Administration of China Data and Technology Support Center Beijing China Institute of Information Engineering Chinese Academy of Sciences Beijing China

ISBN: (数字)9798350391367

ISBN: (纸本)9798350391374

Previous studies have discovered that Transformers pre-trained on large scale datasets have a great advantage over traditional methods and can achieve human-level performance in many NLP tasks. Various encoder-only models like BERT and RoBERTa are used in the researches of the language in the Dark Web and most of them have achieved state-of-the-art performance. However, decoder-only models are not frequently used as they were considered to be unsuitable for NLU tasks until recent advancements in large language models. In this paper, we discuss the application of large scale decoder-only models in NLP tasks of real-world Dark Web research. We explore the capabilities of these models with the most realistic datasets in this specific domain. Surprisingly, results show that decoder-only models can achieve similar or better performance compared with state-of-the-art encoder-only model in some cases and show their own unique advantages in such field. We also discuss the limitations of these models and the challenges associated with their application in such field. Our study unveils the potential of decoder-only models in NLP tasks of real-world Dark Web research.

关键词： Dark Web Large language models Text categorization Zero shot learning Cyberspace Data science Transformers Natural language processing Data models Encoding

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