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 ...
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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.
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 app...
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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 diff...
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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.
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 Co...
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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.
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 sum...
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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.
Today, many commercial and private cloudcomputing providers offer resources for leasing under the infrastructure as a service (IaaS) paradigm. Although an abundance of mechanisms already facilitate the lease and use ...
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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 pap...
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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 mana...
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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.
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 Insti...
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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, cloudcomputing, 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.
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