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International Workshop on Assurance in distributed systems and Networks

作者： Wang, Zhuo Tang, Zhushou Zhou, Kan Zhang, Ruoyu Qi, Zhengwei Guan, Haibin School of Software Shanghai Key Laboratory of Scalable Computing and Systems Shanghai Jiao Tong University Shanghai China School of Electronic Information and Electrical Engineering Shanghai Key Laboratory of Scalable Computing and Systems Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9780769543499

Dynamic taint analysis based software vulnerability and malware detection is an effective method to detect a wide range of vulnerabilities. Unfortunately, existing systems suffer from requirement of source code, high overhead or shortage of discovery rules, which limit their usage. This paper proposes a low-overhead vulnerability discovery system called DsVD (Dynamic Software Vulnerabilities Discoverer). DsVD works on X86 executables and does not need any hardware change. A new taint state called controlled-taint is introduced to detect more types of vulnerabilities. Our experiments show that DsVD can effectively detect various software vulnerabilities. DsVD incurs very low overhead, only 3.1 times on average for SPECINT2006 benchmarks. With some optimizations such as Irrelevant API Filter and Basic Block Handling, it can reduce runtime overhead by a factor of 4-11 times.

关键词： Dynamic Taint Analysis Software Security Vulnerability Discovery Software safety computer software computer programs Taints Vulnerability Computer hardware

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Improving Speech Emotion Recognition Using Data Augmentation and Balancing Techniques 22

Improving Speech Emotion Recognition Using Data Augmentation...

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22nd International Conference on Cyberworlds, CW 2023

作者： Barhoumi, Chawki Ayed, Yassine Ben National School of Electronics and Telecommunications of Sfax Stax Tunisia Multimedia InfoRmation Systems and Advanced Computing Laboratory Sfax Tunisia

ISBN: (纸本)9798350315653

Speech Emotion Recognition (SER) is a challenging task due to the complexity and variability of human emotions. In this paper, we propose an innovative approach to improve SER performance on the EMODB dataset. Our approach employs data augmentation techniques, such as noise addition and spectrogram shift, as well as balancing techniques, including random oversampling. We also extract five different features from the dataset samples: MFCC, Chroma, Mel Spectrogram, ZCR, and RMS. We compare the performance of four different classifiers MLP, SVM, KNN, and CNN with and without the use of our proposed approach. Our results demonstrate that the proposed approach significantly enhances the accuracy of speech emotion recognition compared to the approach without data augmentation and balancing techniques. Our experiments reveal that the proposed approach achieves higher accuracy and F1-score compared to other approaches, with MLP and CNN models achieving 100% accuracy. These findings highlight the effectiveness of data augmentation and balancing techniques in improving the performance of speech emotion recognition. Moreover, our approach holds great potential for application in various real-life scenarios, including mental health monitoring, human-robot interaction, and speech-based virtual assistants. © 2023 IEEE.

关键词： Support vector machines

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cloud Resource Provisioning and Bottleneck Eliminating for Meshed Web systems

Cloud Resource Provisioning and Bottleneck Eliminating for M...

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IEEE International Conference on cloud computing, cloud

作者： Yamin Lei Zhicheng Cai Hang Wu Rajkumar Buyya School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing China The Cloud Computing and Distributed Systems (CLOUDS) Laboratory School of Computing and Information Systems The University of Melbourne Australia

ISBN: (数字)9781728187808

ISBN: (纸本)9781728187815

Most of existing resource provisioning methods are designed for traditional Web applications with linear structures. However, Web systems with the meshed topology are becoming widespread. Meshed connections among different tiers make Virtual Machine (VM) provisioning and bottleneck elimination complex. In this paper, a Jackson network based Proactive and Reactive VM auto-scaling Method (JPRM) is proposed. In JPRM, request transition behaviors among tiers are modeled as a finite-state Markov stochastic process. A transition probability matrix is studied on-line to predict resource requirements based on M/M/N queuing models as proactive control. For reactive provisioning, the final increased request rate of each tier is determined based on stable state checking and Jackson equilibrium equation solving to eliminate bottleneck tiers and avoid bottleneck shifting. The JPRM is evaluated in a simulation environment established using cloudSim. Experimental results show that JPRM avoids bottleneck shifting with reasonable additional VM rental costs compared with existing methods.

关键词： cloud computing Network topology Predictive models Markov processes Virtual machining Topology Mathematical model

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Computational Intelligence and Data Analytics 1

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丛书名： Lecture Notes on Data Engineering and Communications Technologies

1000年

作者： Rajkumar Buyya Susanna Munoz Hernandez Ram Mohan Rao Kovvur T. Hitendra Sarma

ISBN: (数字)9789811933912

ISBN: (纸本)9789811933905

The book presents high-quality research papers presented at the International Conference on Computational Intelligence and Data Analytics (ICCIDA 2022), organized by the Department of information Technology, Vasavi College of Engineering, Hyderabad, India in January 2022. ICCIDA provides an excellent platform for exchanging knowledge with the global community of scientists, engineers, and educators. This volume covers cutting-edge research in two prominent areas – computational intelligence and data analytics, and allied research areas.

关键词： Computational Intelligence Artificial Intelligence Statistics, general Cyber-physical systems, IoT Professional computing Communications Engineering, Networks

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Comprehensive information Security Evaluation Model Based on Multi-Level Decomposition Feedback for IoT

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Computers, Materials & Continua 2020年第10期65卷 683-704页

作者： Jinxin Zuo Yueming Lu Hui Gao Ruohan Cao Ziyv Guo Jim Feng School of Cyberspace Security Beijing University of Posts and TelecommunicationsBeijing100876China School of Information and Communication Engineering Beijing University of Posts and Telecommunica-tionsBeijing100876China Key Laboratory of Trustworthy Distributed Computing and Service(BUPT) Ministry of EducationBeijing100876China Amphenol Global Interconnect Systems San JoseCA 95131USA

The development of the Internet of Things(IoT)calls for a comprehensive in-formation security evaluation framework to quantitatively measure the safety score and risk(S&R)value of the network *** this paper,we summarize the architecture and vulnerability in IoT and propose a comprehensive information security evaluation model based on multi-level decomposition *** evaluation model provides an idea for information security evaluation of IoT and guides the security decision maker for dynamic ***,we establish an overall evaluation indicator system that includes four primary indicators of threat information,asset,vulnerability,and management,*** also includes eleven secondary indicators of system protection rate,attack detection rate,confidentiality,availability,controllability,identifiability,number of vulnerabilities,vulnerability hazard level,staff organization,enterprise grading and service continuity,***,we build the core algorithm to enable the evaluation model,wherein a novel weighting technique is developed and a quantitative method is proposed to measure the S&R ***,in order to better supervise the performance of the proposed evaluation model,we present four novel indicators includes residual risk,continuous conformity of residual risk,head-to-tail consistency and decrease ratio,*** results show the advantages of the proposed model in the evaluation of information security for IoT.

关键词： IoT information security quantitative evaluation safety score residual risk

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An analysis of provisioning and allocation policies for infrastructure-as-a-service clouds 12

An analysis of provisioning and allocation policies for infr...

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12th IEEE/ACM International Symposium on Cluster, cloud and Grid computing, CCGrid 2012

作者： Villegas, David Antoniou, Athanasios Sadjadi, Seyed Masoud Iosup, Alexandru School of Computing and Information Sciences Florida International University Miami FL United States Parallel and Distributed Systems Group Delft University of Technology Delft Netherlands

ISBN: (纸本)9780769546919

Today, many commercial and private cloud computing providers offer resources for leasing under the infrastructure as a service (IaaS) paradigm. Although an abundance of mechanisms already facilitate the lease and use of single infrastructure resources, to complete multi-job workloads IaaS users still need to select adequate provisioning and allocation policies to instantiate resources and map computational jobs to them. While such policies have been studied in the past, no experimental investigation in the context of clouds currently exists that considers them jointly. In this paper we present a comprehensive and empirical performance-cost analysis of provisioning and allocation policies in IaaS clouds. We first introduce a taxonomy of both types of policies, based on the type of information used in the decision process, and map to this taxonomy eight provisioning and four allocation policies. Then, we analyze the performance and cost of these policies through experimentation in three clouds, including Amazon EC2. We show that policies that dynamically provision and/or allocate resources can achieve better performance and cost. Finally, we also look at the interplay between provisioning and allocation, for which we show preliminary results. © 2012 IEEE.

关键词： Taxonomies

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A translation framework for virtual execution environment on CPU/GPU architecture

A translation framework for virtual execution environment on...

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International Symposium on Parallel Architectures, Algorithms, and Programming

作者： Dong, Guoxing Chen, Kai Zhu, Erzhou Zhang, Yichao Qi, Zhengwei Guan, Haibing School of Software Shanghai Key Laboratory of Scalable Computing and Systems Shanghai Jiaotong University Shanghai 200240 China School of Information Security Engineering Shanghai Key Laboratory of Scalable Computing and Systems Shanghai Jiaotong University Shanghai 200240 China Department of Computer Science and Engineering Shanghai Key Laboratory of Scalable Computing and Systems Shanghai Jiaotong University Shanghai 200240 China

ISBN: (纸本)9780769543123

GPUs are many-core processors with tremendous computational power. However, as automatic parallelization has not been realized yet, developing high-performance parallel code for GPUs is still very challenging. The paper presents a novel translation framework designed for virtual execution environment based on CPU/GPU architecture. It addresses two major challenges of taking advantage of general purpose computation on graphics processing units (GPGPU) to improve performance: no rewriting the existing source code and resolving binary compatibility issues between different GPUs. The translation framework uses semi-automatic parallelization technology to port existing code to explicitly parallel programming models. It not only offers a mapping strategy from X86 platform to CUDA programming model, but also synchronizes the execution between the CPU and the GPUs. The input to our translation framework is parallelizable part of the program within binary code. With an additional information related to the parallelizable part, the translation framework transforms the sequential code into PTX code and execute it on GPUs. Experimental results on several programs from CUDA SDK Code Samples and Parboil Benchmark Suite show that our translation framework could achieve very high performance, even up to several tens of times speedup over the X86 native version. © 2010 IEEE.

关键词： Graphics processing unit

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SecBCS: a secure and privacy-preserving blockchain-based crowdsourcing system

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Science China(information Sciences) 2020年第3期63卷 20-33页

作者： Chao LIN Debiao HE Sherali ZEADALLY Neeraj KUMAR Kim-Kwang Raymond CHOO Key Laboratory of Aerospace Information Security and Trusted Computing Ministry of EducationSchool of Cyber Science and Engineering Wuhan University State Key Laboratory of Cryptology College of Communication and Information University of Kentucky Department of Computer Science and Engineering Thapar University Department of Information Systems and Cyber Security and Department of Electrical and Computer Engineering University of Texas at San Antonio

A robust and scalable crowd management infrastructure is crucial in addressing operational challenges when deploying high-density sensors and actuators in a smart city. While crowdsourcing is widely used in crowd management, conventional solutions, such as Upwork and Amazon Mechanical Turk, generally depend on a trusted third-party platform. There exist several potential security concerns(e.g., sensitive leakage, single point of failure and unfair judgment) in such a centralized paradigm. Hence, a recent trend in crowdsourcing is to leverage blockchain(a decentralized ledger technology) to address some of the existing limitations. A small number of blockchain-based crowdsourcing systems(BCSs) with incentive mechanisms have been proposed in the literature, but they are generally not designed with security in mind. Thus, we study the security and privacy requirements of a secure BCS and propose a concrete solution(i.e., SecBCS)with a prototype implementation based on JUICE.

关键词： crowdsourcing blockchain secure privacy-preserving smart contract

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Progress in Advanced computing and Intelligent Engineering 1

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丛书名： Advances in Intelligent systems and computing

1000年

作者： Chhabi Rani Panigrahi Bibudhendu Pati Prasant Mohapatra Rajkumar Buyya Kuan-Ching Li

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Innovations in Computer Science and Engineering 1

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丛书名： Lecture Notes in Networks and systems

1000年

作者： H. S. Saini Rishi Sayal A. Govardhan Rajkumar Buyya

ISBN: (数字)9789811689871

ISBN: (纸本)9789811689864

This book features a collection of high-quality, peer-reviewed research papers presented at the 9th International Conference on Innovations in Computer Science & Engineering (ICICSE 2021), held at Guru Nanak Institutions, Hyderabad, India, on September 3–4, 2021. It covers the latest research in data science and analytics, cloud computing, machine learning, data mining, big data and analytics, information security and privacy, wireless and sensor networks and IoT applications, artificial intelligence, expert systems, natural language processing, image processing, computer vision, and artificial neural networks.

关键词： Computational Intelligence Artificial Intelligence Communications Engineering, Networks Professional computing

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