In recent years, with the development of Internet technology, the total amount of enterprise data is increasing year by year, which is regarded as the resource core and wealth in enterprises. For the potential value o...
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In recent years, with the development of Internet technology, the total amount of enterprise data is increasing year by year, which is regarded as the resource core and wealth in enterprises. For the potential value of distributed learning, machine learning will continue to play an important core role. The significance of data security is not limited to the data itself, but also directly affects whether the data can be promoted to data assets to serve the business development of enterprises and enhance the core competitiveness. These seemingly normal operations actually contain potential hazards. Based on the above analysis, this paper aims to solve the efficiency bottleneck of distributed system in processing machine learning tasks, design and implement a high-performance distributed machine learning system for heterogeneous environment in data center, and provide good systematic support for large-scale machine learning applications. The actual deployment shows that the distributed training manager module can improve the task processing speed by 4.67 times and reduce the energy cost by 68.92% in the cloud-edge collaborative image classification task scenario.
The existing energy network security defense system uses firewall, intrusion detection, host monitoring, identity authentication, anti-virus software and vulnerability repair to build a fortress type rigid defense sys...
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The existing energy network security defense system uses firewall, intrusion detection, host monitoring, identity authentication, anti-virus software and vulnerability repair to build a fortress type rigid defense system to block or isolate external invasion. This static layered deep defense system is based on prior knowledge and has the advantages of rapid response and effective protection in the face of constant attacks When confronting the unknown attacking opponent, he is not able to do his best, and he is in danger of being attacked easily. In this context, multi-objective decision has more than two decision-making objectives and needs to use multiple criteria to evaluate and optimize the decision-making of alternatives. Due to the objectives of economic benefit, safety in production and environmental protection, it is necessary to use a variety of criteria to evaluate and optimize schemes. In this paper, we propose RBF neural network and weight-based algorithm to achieve multi-objective decision. We leverage RBF neural network to construct objective weight assignment model. The goal of our weight-based algorithm is that the multi-objective optimization problem is formulated as a single-objective optimization problem by assigning certain weights to each objective, and then the non-inferior solution of the multi-objective optimization problem is generated by changing the weights of each objective extensive. (C) 2021 Published by Elsevier B.V.
Live migration of virtual machine is the process of moving VMs from one physical server to another server keeping services running in VMs, and facilitates load balancing, energy saving, hardware dependent, remote migr...
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ISBN:
(纸本)9783319500119;9783319500102
Live migration of virtual machine is the process of moving VMs from one physical server to another server keeping services running in VMs, and facilitates load balancing, energy saving, hardware dependent, remote migration and so on. This novel technology brings a huge convenience, and also presents new security challenges that the security concern is the major factor effecting this technology widely adopted in IT industry. Live migration exposes VM's data as plaintext to the network as a result of vulnerabilities in the migration protocol. The traditional protection way is using the SSL protocol, but that consume too much time and not as safe as it used to be, few users adopt this way. So we design a security algorithm based original migration algorithm making up for the lack of security. In this paper, firstly, we analyze and verify security threats to live migration. Secondly, through the analysis on the live migration mechanism, the bottom driver, and the source code of KVM virtualization system, we design a security algorithm for live migration to meet the security needs of different users. Thirdly, the new security algorithm which we innovatively add three functions to the original algorithm to ensure migration data to remain confidential and unmodified during the transmission. The security algorithm make up the security vulnerabilities of original migration mechanism and take less time than the SSL. Finally, a series of experiments validate the algorithm that could solve the balance of the security and performance in live migration process.
The Internet of Robotic Things (IoRT) integrates robots and autonomous devices, transforming industries such as manufacturing, healthcare, and transportation. However, security vulnerabilities in IoRT systems pose sig...
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The Internet of Robotic Things (IoRT) integrates robots and autonomous devices, transforming industries such as manufacturing, healthcare, and transportation. However, security vulnerabilities in IoRT systems pose significant challenges to data privacy and system integrity. To address these issues, encryption is essential for protecting sensitive data transmitted between devices. By converting data into ciphertext, encryption ensures confidentiality and integrity, reducing the risk of unauthorized access and data breaches. Blockchain technology also enhances IoRT security by offering decentralized, tamper-proof data storage solutions. By offering comprehensive insights, practical recommendations, and future directions, this paper aims to contribute to the advancement of knowledge and practice in securing interconnected robotic systems, thereby ensuring the integrity and confidentiality of data exchanged within IoRT ecosystems. Through a thorough examination of encryption requisites, scopes, and current implementations in IoRT, this paper provides valuable insights for researchers, engineers, and policymakers involved in IoRT security efforts. By integrating encryption and blockchain technologies into IoRT systems, stakeholders can foster a secure and dependable environment, effectively manage risks, bolster user confidence, and expedite the widespread adoption of IoRT across diverse sectors. The findings of this study underscore the critical role of encryption and blockchain technology in IoRT security enhancement and highlight potential avenues for further exploration and innovation. Furthermore, this paper suggests future research areas, such as threat intelligence and analytics, security by design, multi-factor authentication, and AI for threat detection. These recommendations support ongoing innovation in securing the evolving IoRT landscape.
Resource-constrained devices equipped with multiple sensors to exchange data over the network are called the Internet of Things (IoT). The major limitations of IoT devices are limited resources, low computational powe...
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Resource-constrained devices equipped with multiple sensors to exchange data over the network are called the Internet of Things (IoT). The major limitations of IoT devices are limited resources, low computational power, low communication capacity, and low bandwidth. Therefore, ensuring proper security while using these low resources is challenging. In contrast, the conventional cryptographic algorithm has higher complexity and high resource requirements, making it incompetent for IoT devices. However, lightweight cryptographic algorithms have limited resource requirements and limited complexity, making them eligible for use in low-resource devices. This paper proposed a lightweight hybrid cellular automata-based algorithm for IoT applications. The encryption algorithm uses multiple layers of hybrid cellular automata and a secondary secret key. For key randomization, omega-flip permutation and cellular automata are used. The experimental result shows that the algorithm outperforms existing ciphers such as DES and 3DES in the context of simplicity, encryption, and decryption time. In addition, this algorithm successfully meets the randomness criteria set by the National Institute of Standards and Technology (NIST). The algorithm also meets the criteria of passing all of the DIEHARD tests which ensures the security requirements of this algorithm. This algorithm can be used for resource-limited devices and can be upscaled to use for higher-complexity devices.
It was analyzed an environment between the references of certain security models and algorithms based on improving cybersecurity in distributed architectures. The problem is the lack of application of appropriate secu...
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ISBN:
(纸本)9781728168234
It was analyzed an environment between the references of certain security models and algorithms based on improving cybersecurity in distributed architectures. The problem is the lack of application of appropriate security algorithms aimed at the cybersecurity service within a distributed architecture;cyberattacks are on the rise in distributed environments and the lack of follow-up or monitoring to prevent anomalies. The objective is to analyze adequate security algorithms oriented to cybersecurity management for a distributed architecture. It was used the exploratory research and deductive method to analyze the information of the references in security algorithms, cybersecurity and distributed architectures. It resulted a Prototype of security scheme, a Prototype of distributed and hybrid architecture with cybersecurity, and a Generic algorithm for cybersecurity management. It was concluded that the AES and RC5 security algorithms increase security in important information assets such as the database;encryption guarantees the information integrity on a distributed architecture and continuous monitoring generates early alarms for anomalies;the architecture prototype has 92.06% performance.
Nowadays, cloud computing is rapid growth in the IT industry, which provides a new way to manage the different information systems. The rapid development of technology makes it essential to use this technology and to ...
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Nowadays, cloud computing is rapid growth in the IT industry, which provides a new way to manage the different information systems. The rapid development of technology makes it essential to use this technology and to benefit from its advantages. With raising awareness and worries about cloud services and information security, understanding and knowledge are growing for the usage of algorithms security into the processes and data systems. The primary purpose of this research work is to undertake a security analysis and performance assessment of a new lightweight cryptographic algorithm for enhancing data security in cloud computing. It focuses on studying the performance and security analysis algorithm architecture base on computational time and key sensitivity, statistical analysis, image histogram, and entropy change analysis in cloud computing environment. It also, provides a performance comparison of general symmetric algorithms used to secure the cloud services: DES, AES, Blowfish, RC4, HIGH, SF, and SIT.
Due to the vulnerability of the Internet of Things (IoT), it is indispensable to provide adequate security services. These services are generally implemented through security protocols or algorithms and running on ene...
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ISBN:
(纸本)9781728195056
Due to the vulnerability of the Internet of Things (IoT), it is indispensable to provide adequate security services. These services are generally implemented through security protocols or algorithms and running on energy-sensitive IoT devices. In order to design energy-efficient algorithms to prolong the lifetime of IoT devices, the energy characteristics of those algorithms should be analyzed primarily. In this paper, we conduct an integrated static analysis method with dynamic tracing to provide a quantitative energy profile for popular security algorithms such as AES128, RSA, and SHA256. Specifically, binary instructions executed in the invoked function are measured and counted through remotely debugging each program on the Arm development board. Then, the fine-grained energy consumption inside a program is revealed by combining the instruction statistics and instruction-level energy model. The experimental results show that the energy consumption of a program is mainly consumed by a few primary functions and CPU-memory interaction instructions, and hence the functions can be implemented in different ways to reduce energy consumption. This meaningful energy consumption evaluation method for security algorithms is able to guide to optimizing existing algorithms for embedded security.
Microgrids (MGs) use renewable sources to meet the growing demand for energy with increasing consumer needs and technological advancement. They operate independently as small-scale energy networks using distributed en...
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Microgrids (MGs) use renewable sources to meet the growing demand for energy with increasing consumer needs and technological advancement. They operate independently as small-scale energy networks using distributed energy resources. However, the intermittent nature of renewable energy sources and poor power quality are essential operational problems that must be mitigated to improve the MG's performance. To address these challenges, researchers have introduced heuristic optimization mechanisms for MGs. However, local minima and the inability to find a global minimum in heuristic methods create errors in non-linear and nonconvex optimization, posing challenges in dealing with several operational aspects of MG such as energy management optimization, cost-effective dispatch, dependability, storage sizing, cyber-attack minimization, and grid integration. These challenges affect MG's performance by adding complexity to the management of storage capacity, cost minimization, reliability assurance, and balance of renewable sources, which accelerates the need for meta-heuristic optimization algorithms (MHOAs). This paper presents a state-of-the-art review of MHOAs and their role in improving the operational performance of MGs. Firstly, the fundamentals of MG optimization are discussed to explore the scopes, requisites, and opportunities of MHOAs in MG networks. Secondly, several MHOAs in the MG domain are described, and their recent trends in MG's techno-economic analysis, load forecasting, resiliency improvement, control operation, fault diagnosis, and energy management are summarized. The summary reveals that nearly 25% of the research in these areas utilizes the particle swarm optimization method, while the genetic and grey wolf algorithms are utilized by nearly 10% and 5% of the works studied in this paper, respectively, for optimizing the MG's performance. This result summarizes that MHOA presents a system-agnostic optimization approach, offering a new avenue for enhanc
Nowadays the Internet of Things (IoT) still does not have global policies and standards to deal with the interaction and the development of applications. There are huge of security issues relevant to the application l...
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Nowadays the Internet of Things (IoT) still does not have global policies and standards to deal with the interaction and the development of applications. There are huge of security issues relevant to the application layer of IoT becoming very urgent. On the other hand, it is important for addressing the development of security algorithm to protect the IoT system from malicious attack. In this article, a fusion diversity scheme adopts maximum ratio combining (MRC) and selection combining (SC) schemes with trust management (TM) security algorithm are proposed. In MRC stage, specified parameters first extracted and they weighted by one estimation value before combined with the control information. The fused information generated from MRC passed forward to the SC in order to calculate the final trust value. What degree of the quality of service (QoS) will provide with IoT technologies is dependent on the trust value comes from the previously step. The simulation results from experiments deployed with physical assessment show that the security has more reliability after the MRC and SC schemes fused into the TM procedure. That is, the proposed fusion diversity scheme is more reliable in terms of security. Furthermore, the mechanism fusing MRC and SC methods with the TM can enhance the efficiency and solve the security problem of application layer. Alternatively, the reducing in QoS degree, such as the data rate, the packet capacity for the requester is the penalty.
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