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Ranking on Heterogeneous Manifold for Multimodal Information Retrieval 21

Ranking on Heterogeneous Manifold for Multimodal Information...

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21st IEEE international Symposium on Parallel and distributed Processing with Applications, 13th IEEE international conference on Big Data and Cloud computing, 16th IEEE international conference on Social computing and networking and 13th international conference on Sustainable computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2023

作者： Jin, Zhenkun Wan, Xingshi Nie, Xin Zhou, Xinlei Yi, Yuanyuan Zhou, Gefei Wuhan Business University Wuhan Research Institute of Posts and Telecommunications Wuhan China Wuhan Research Institute of Posts and Telecommunications Wuhan China Huazhong University of Science and Technology Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security Wuhan China Huazhong University of Science and Technology School of Journalism and Information Communication Wuhan China Huazhong University of Science and Technology School of Computer Science & Technology Wuhan China

ISBN: (纸本)9798350329223

In light of recent advancements in Internet of Multimedia things (IoMT) and 5G technology, both the variety and quantity of data have been rapidly increasing. Consequently, handling zero-shot cross-modal retrieval (ZSCMR) of unlabeled multi-modal data has emerged as a prominent research topic. Early models utilized generative adversarial networks and class embeddings to assist in building a common feature space. However, this approach resulted in a loss of reliability in the feature distributions of individual modalities. In this paper, we propose a method called Ranking on Heterogeneous Manifold (RHM) to address the aforementioned issue. Our model comprises three feature extractors, each dedicated to extracting features from text, images and multimodal data. Subsequently, the relationship structures derived from these feature extractors are employed to construct a heterogeneous manifold. A diffusion process is then conducted on this heterogeneous manifold, ultimately yielding the final ranking scores. Comprehensive experiments demonstrate that the proposed modal has the capability to acquire more effective knowledge representation, thus enhancing the effectiveness of ZSCMR. © 2023 IEEE.

关键词： Knowledge representation

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PE-FedAvg: A Privacy-Enhanced Federated Learning for distributed Android Malware Detection 21

PE-FedAvg: A Privacy-Enhanced Federated Learning for Distrib...

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作者： Tang, Junwei Xu, Zilong Ye, Luyao Peng, Tao He, Ruhan Hu, Xinrong Tian, Wenlong Wuhan Textile University Hubei Provincial Engineering Research Center for Intelligent Textile and Fashion China Wuhan Textile University School of Computer Science and Artificial Intelligence China University of South China School of Computer Science China Nanyang Technological University School of Physical and Mathematical Sciences Singapore

ISBN: (纸本)9798350329223

Android malware detection has become research hotspot in mobile security. When security service providers obtain feature information from target samples, they may involve user privacy information such as identity and behavioral habits, creating an urgent need for a distributed machine learning model to carry out malicious application detection with privacy protection. However, the information exchange between clients and servers in basic federated learning still poses risks of model data leakage, and the likelihood of inferring privacy information from the original feature data is high. therefore, this paper propose a privacy-enhanced federated learning system called PE-FedAvg for distributed Android malware detection. Firstly, Gaussian noise is added to the feature data uploaded from the client to the server, satisfying differential privacy characteristics while retaining data distribution for privacy protection. Secondly, an improved homomorphic encryption algorithm based on modular repeated squaring is used to encrypt and transmit the gradient weight information exchanged between federated learning clients and servers, preventing model-targeted attacks. By conducting the experiments on the Drebin and Malgenome datasets, our design has demonstrated exceptional performance compared to the state-of-the-art work, achieving accuracy rates of 98.61% and 99.3%, respectively. this achievement highlights that our approach not only enhances the security of the federated learning system, but also more effectively accomplishes the detection of Android malware. © 2023 IEEE.

关键词： Android malware

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Time Fairness-Based Application Offloading in Mobile Edge computing with Individual QoS Guarantee 21

Time Fairness-Based Application Offloading in Mobile Edge Co...

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作者： Xie, Mengwei Cui, Lizhen Liu, Jianxiong Guo, Wei Li, Feng Shandong University School of Computer Science and Technology Qindao China Shandong University School of Software Jinan China Aerospace Science & Industry Network Information Development Co. Ltd. Beijing China

ISBN: (纸本)9798350329223

In the area of Mobile Edge computing (MEC), how to offload applications with QoS and fairness guarantees has been attracting increasing attention. Most existing application offloading strategies focus on reducing the average completion time of the applications to fulfill the global QoS requirement. However, when there are a huge number of mobile users for the applications, these strategies cannot guarantee the QoS for the individual users;therefore, the mobile users' experiences differ significantly, resulting in unfairness among the users. To address this problem, this paper presents a time fairness-based application offloading strategy for individual mobile users with individual QoS guarantees. this strategy is designed to achieve two primary objectives. Firstly, it seeks to assess the suitability of offloading each application to edge servers by evaluating its completion time, aiming to maximize the number of applications meeting individual QoS time requirements. Secondly, for applications that meet individual QoS time requirements, this strategy ensures time fairness among multiple users by minimizing the variance between application completion times and individual QoS time requirements. the empirical validation presented in this paper provides robust evidence of the effectiveness of our strategy, surpassing existing approaches, with a particular emphasis on achieving time fairness. © 2023 IEEE.

关键词： Quality of service

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Joint Resource Placement and Service Replica Placement Scheme in Mobile Edge computing 21

Joint Resource Placement and Service Replica Placement Schem...

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作者： Woldeyes, Surafel Kifetew Zhang, Yongmin Wang, Wei Li, Zhaohui Central South University School of Computer Science and Engineering Changsha410083 China

ISBN: (纸本)9798350329223

Optimal resource placement and service placement are key factors for resource utilization and service availability in mobile edge computing (MEC) systems. However, efficiently utilizing the resources of MEC servers for service replica placement becomes a significant challenge due to the servers' limited resource capacity. To overcome this challenge, in this paper, we propose a comprehensive model for jointly addressing resource placement and service replica placement within the MEC system. the proposed model considers various factors, including the limited capacity of edge servers, the presence of service replicas, server failure probabilities, and the heterogeneous resource demand of services in terms of CPU, network bandwidth, and storage capacities. We then formulated the joint resource placement and service replica placement problem as a multi-objective optimization problem from the perspective of minimizing server resource waste, reducing server energy consumption, and ensuring high service availability. To solve this problem, we first proposed a resource-aware algorithm for the initialization process, which generates high-quality initial solutions that satisfy the server resource constraints. then we propose an improved non-dominated sorting genetic algorithm II with two-phase chromosome representation to find a suitable placement solution. Evaluation results show the superiority of our approach compared with other benchmark algorithms in terms of minimizing service unavailability, resource waste, and energy consumption. © 2023 IEEE.

关键词： Energy utilization

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Deep Reinforcement Learning based Dynamic Channel Bonding for Wi-Fi Networks 21

Deep Reinforcement Learning based Dynamic Channel Bonding fo...

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作者： Chen, Hao Liu, Peng You, Lizhao Guo, Ziyang Luo, Jiajun Sun, Xinghua Wang, Taotao Fu, Liqun Xiamen University Department of Information and Communication Engineering China Shenzhen Research Institute of Xiamen University Shenzhen China Huawei Technologies Co. Ltd. Wireless Technology Lab 2012 Laboratories China Sun Yat-sen University School of Electronics and Communication Engineering China Shenzhen University College of Electronics and Information Engineering Shenzhen China

ISBN: (纸本)9798350329223

this paper presents a decentralized Deep Reinforcement Learning (DRL)-based dynamic channel bonding (DCB) algorithm (i.e., drlDCB) for Wi-Fi networks. Most existing RL-based channel bonding algorithms either are centralized (i.e., requiring a central controller and global information for training), or can easily fall into local optimum (e.g., over-using channels for demand) as the number of stations increases. Moreover, they may converge slowly due to the use of measured throughput or delay over a duration as reward. In contrast, drlDCB is a purely distributed algorithm where each access point gets trained using local information, and addresses the local optimum and the slow convergence problems through the following new designs: 1) a new piecewise throughput model to avoid occupying too many channels if demand is satisfied, and 2) a new reward design using estimated throughput. the use of estimated throughput allows per-frame adaptation and fast convergence speed, while the accurate estimation generalizes the application scenarios, allowing an offline-trained model to be used in a dynamic environment. Simulation results in the static scenario with fixed loads and the dynamic scenario with random loads show that drlDCB outperforms state-of-the-art DCB algorithms in terms of network throughput, delay and convergence speed. © 2023 IEEE.

关键词： Reinforcement learning

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A Firmware Vulnerability Detection Method Based on Feature Filtering 21

A Firmware Vulnerability Detection Method Based on Feature F...

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作者： Xia, Bing Tang, Chongjun Liu, Wenbo Chu, Shihao Dong, Yu ZhongYuan University of Technology Key Laboratory of Mathematical Engineering and Advanced Computing Dept Zhengzhou China ZhongYuan University of Technology Henan Key Laboratory on Public Opinion Intelligent Analysis Dept Zhengzhou China ZhongYuan University of Technology Dept Zhengzhou China

ISBN: (纸本)9798350329223

Open source code reuse and code cross-platform deployment accelerate the spread of software vulnerabilities, and pose challenges for accurate detection of cross-platform vulnerabilities. the binary vulnerability similarity detection method based on machine learning lacks a fine-grained vulnerability similarity feature filtering mechanism, and cannot solve cross-function vulnerabilities triggered by data dependencies, resulting in a high vulnerability false positive rate in existing solutions, which limits practical applications. Software code vulnerabilities are usually caused by function key statements. therefore, based on binary function decompilation, we identify the key statement that causes the vulnerability, analyze the cross-function data dependency of the key statements, extract the code similarity features and code vulnerability features of the key statements, and propose a feature filtering-based Binary vulnerability detection method SimFilter. SimFilter calculates the similarity of key statements by comparing the characteristics of function key statements, and infers the similarity of binary function vulnerabilities based on the similarity of key statements. the experimental results show that the vulnerability semantic features extracted by SimFilter are highly interpretable, and the accuracy rate is increased by 10.8% compared with other models. At the same time, we analyzed and evaluated the impact of different similarity features on the accuracy of SimFilter, and gave the best empirical value of the SimFilter model in firmware vulnerability detection. © 2023 IEEE.

关键词： Firmware

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Discrete Geometric Coded Data Layout for Large-scale Object Storage Systems 21

Discrete Geometric Coded Data Layout for Large-scale Object ...

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作者： Tian, Yi Xu, Guangping Yang, Hongzhang Ni, Yue Cao, JiaXin Yang, Lei Tianjin University of Technology School of Computer Science and Engineering Tianjin China Novel Software Technology Tianjin Key Laboratory of Intelligence Computing Tianjin China Key Laboratory of Computer Vision and System Ministry of Education China Information Technology Co. Ltd. China

ISBN: (纸本)9798350329223

Regenerating codes are new network codes proposed to reduce the data required for fault repair, which can improve the recovery efficiency of faulty nodes in data storage systems. However, unlike Reed-Solomon code, which repairs at the granularity of bytes, regenerating codes require data stored in large chunks but leads to severe read amplification, which reads out excess data when degraded read objects and increases degraded read time. that reflects a mutual constraint between improving recovery efficiency and degraded read performance, as manifested in the amplification of data reads, a vital issue considered in this *** solve this problem, we propose a new type of data layout - discrete geometric, which splits the object into a series of geometric sequences of data blocks. they are placed discretely into corresponding containers on the disks at different nodes, with containers of the same size made into a strip for encoding. the discrete characteristic ensures lower repair costs for degraded reads. the geometric characteristic ensures the repair performance of regenerating codes by large blocks, and read amplification can be mitigated through small blocks. To reduce IOPS for discrete geometric, we propose Discrete Geometric-Locally Regenerating Codes (DG-LRCs), guaranteeing lower degraded read latency while improving recovery *** results show that the degraded read time of DG-LRCs compared to regenerating codes combined with geometric partitioning is 22.56% lower at 2Gbpsand 60.56% lower at 4Gbps, and the recovery performance is 7.04 times better than that of RS code. © 2023 IEEE.

关键词： Efficiency

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Enhanced DDoS Defense in SDN: Double-Layered Strategy with Blockchain Integration 13

Enhanced DDoS Defense in SDN: Double-Layered Strategy with B...

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13th IEEE international conference on Communications, Circuits and Systems (ICCCAS)

作者： Tian, Jialin Shu, Zhaogang Chen, Shuwu Xie, Haihui Liu, Xiaolong Qiu, Caiyu Fujian Agr & Forestry Univ Comp & Informat Coll Fuzhou Peoples R China

ISBN: (纸本)9798350386288;9798350386271

With the development of technologies such as cloud computing, big data, and the Internet of things (IoT), Software-Defined networking (SDN) has emerged as a novel network architecture in today's Internet era. It can separate the control plane from the data plane, allowing rapid packet forwarding in the Internet through a centralized controller. However, SDN environments are vulnerable to traditional distributed Denial of Service (DDoS) attacks. this paper proposes a new dual layer strategy to try to mitigate the question. First, by using blockchain technology and smart contract in the northbound interface to store the flow tables required for SDN networks, security is increased. then, we use the Token Bucket algorithm and Time Window algorithm to build the first-tier strategy to defend against obvious DDoS attacks. To detect unobvious DDoS attacks, we design the second-tier strategy that uses a composite data feature correlation coefficient calculation method and the Isolation Forest algorithm to perform binary classification on data, thereby identifying abnormal traffic. We use the currently publicly available DDoS dataset CIC-DDoS2019 for experimental verification. the results show that using this strategy in SDN networks results in an average deviation of data Round-Rip Time (RTT) approximately 38.86% lower than in the original SDN networks without this strategy. Additionally, the accuracy of DDoS attack identification reaches 91.29%. this means that with the implementation of this strategy, DDoS attacks can be effectively identified without compromising the stability of data transmission in SDN network environments.

关键词： Software Defined Networks distributed Denial of Service Blockchain Machine learning

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Keynote Talk: Deployment and Management of Edge Microservices 23

Keynote Talk: Deployment and Management of Edge Microservice...

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24th international conference on distributed computing and networking (icdcn)

作者： Chiasserini, Carla Fabiana Politecn Torino Turin Italy

ISBN: (纸本)9781450397964

Edge computing is an emerging technology for present and next generation mobile networks, which, unlike the cloud, can meet the low latency or bandwidth consumption requirements of time- and mission-critical services. One essential component of edge computing is service virtualization, with each service being often defined as a set of virtual functions implemented through containers. this talk introduces the main scientific challenges in microservice deployment and management at the edge, including microservice interference avoidance, migration, and retention. Specifically, interference among microservices arises whenever the associated containers run on the same server and, hence, compete for memory resources, even if they are allocated dedicated cores. Such interference can lead to severe throughput degradation, thus harming the microservices performance [1]. Microservice migration is instead pivotal to continuously meeting low-latency requirements, as users or devices move from one access point to another [2]. Characterizing container migration is therefore critical for guaranteeing that the expected QoE is ensured, while minimizing the migration cost for the system. Finally, microservice retention becomes relevant in the presence of serverless computing platforms that can launch multiple isolated containers to fulfill service requests by mobile users. the creation of a new container implementing a microservice may require fetching the corresponding image from the remote repository and fetching and loading essential libraries and dependencies before executing the actual function. this long delay involved in the initialization setup is known as cold-start latency, which represents one of the main performance issues faced by the serverless computing platforms [3]. Reducing the cold-start latency is a hard task due to the infrequent function invocations and their unpredictable patterns. For each of these aspects, we present possible approaches and solutions, providi

关键词： Edge computing Service virtualization Service interference Migration Container retention

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Traceable Ring Signature Scheme in Internet of Vehicles Based on Lattice Cryptography 21

Traceable Ring Signature Scheme in Internet of Vehicles Base...

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作者： Liao, Wei Han, Lansheng Chen, Peng Huazhong University of Science and Technology Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Wuhan China

ISBN: (纸本)9798350329223

Lattice cryptography, as a recognized Cryptosystem that can resist quantum computation, has great potential for development. Lattice based signature scheme is currently a research focus. In this paper, the traceable ring signature scheme based on lattice cryptography in the Internet of Vehicles (IoV) environment is studied. Firstly, users' public and private keys are generated on the lattice, which effectively reduces the key size and time cost. Secondly, the scheme also achieves traceability by adding additional information. the scheme satisfies strong unforgeability, traceability, and anonymity. In addition, the traceable ring signature scheme based on lattice cryptography is applied in the IoV environment to effectively protect user privacy. Model communication can not only protect user privacy, but also trace the signer when necessary, achieving a balance between security and privacy. the simulation results show that the average delay of IoV of our scheme is better than that of similar schemes. the research in this paper improves the security of data transmission in the IoV environment, enables it to adapt to the complex and changeable new network environment, and effectively guarantees the information security of vehicles and owners. © 2023 IEEE.

关键词： Cryptography

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