scholarly journals 3S-IoT an Algorithm to make the Network Secure and Smart

2021 ◽  
Author(s):  
maneesh pant ◽  
Brijmohan Singh ◽  
Dharam Vir Gupta
Keyword(s):  
Denial Of Service ◽  
Chaotic Map ◽  
High Energy ◽  
Key Generation ◽  
Multicast Traffic ◽  
Proposed Model ◽  
Man In The Middle ◽  
Multicast Communications ◽  
Actuator Control ◽  
And Control

Abstract The growing and widespread presence of Internet of Things (IoT) has made the lives of all comfortable and handy, but poses various challenges, like efficiency, security, and high energy drain, threatening smart IoT-based applications. Small applications rely on Unicast communication. In a group-oriented communication, multicast is better as transmission takes place using fewer resources. Therefore, many IoT applications rely on multicast transmission. To handle sensitive applications, the multicast traffic requires an actuator control. Securing multicast traffic by itself is cumbersome, as it expects an efficient and flexible Group Key Establishment (GKE) protocol. The paper proposes a three-tier model that can control the IoT and control multicast communications. The first authentication is at network linking where we used a 256-bit keyless encryption technique. Machine learning-based chaotic map key generation authenticates the GKE. Finally, MD5 establishes the system key. 3S-IoT is smart to detect any tempering with the devices. It stores signatures of the connected devices. The algorithm reports any attempt to change or temper a device. 3S-IoT can thwart attacks such as Distributed Denial of Service (DDoS), Man-in-the-Middle (MiTM), phishing, and more. We calculated energy consumed, bandwidth, and the time taken to check the robustness of the proposed model. The results establish that 3S-IoT can efficiently deal with the attacks. The paper compares 3S-IoT with Benchmark algorithms.

scholarly journals 3S-IoT an Algorithm to make the Network Secured and Smart

2020 ◽  
Author(s):  
Maneesh Pant ◽  
Brij Mohan Singh ◽  
Dharam Vir Gupta
Keyword(s):  
Denial Of Service ◽  
Chaotic Map ◽  
High Energy ◽  
Key Generation ◽  
Multicast Communication ◽  
Multicast Traffic ◽  
Proposed Model ◽  
Man In The Middle ◽  
Multicast Communications ◽  
Actuator Control

Abstract Internet of Things (IoT) evolving and widespread presence has made the lives of all comfortable and handy, while on the other hand posing various challenges, i.e. less efficiency, less security, and high energy drain, threatening smart IoT-based applications. Compared to unicast communication, multicast communication is considered more powerful in group-oriented systems, because transmission takes place using less resources. This is why many of the IoT applications rely on multicast in their transmission. This multicast traffic needs to be handled explicitly for sensitive applications requiring actuator control. Securing multicast traffic by itself is cumbersome as it requires an efficient and flexible Group Key Establishment (GKE) protocol. We propose a three-tier model that can, not only be used to control the IoT, but also to control multicast communications. The architecture is built with a 256-bit keyless encryption technique to protect the authentication to create the network link. Machine learning-based chaotic map key generation is used to protect GKE. Finally, using MD5, the system key is authenticated. The algorithm is checked for energy used, bandwidth, and time taken. The proposed model is applied and evaluated against numerous benchmark attacks such as Distributed Denial of Service (DDoS), Man in the Middle and Fishing.

Toward More Resilient Cyber Infrastructure

2016 ◽  
pp. 305-351
Author(s):  
Biljana Tanceska ◽  
Mitko Bogdanoski ◽  
Aleksandar Risteski
Keyword(s):  
Operating System ◽  
Network Topology ◽  
Denial Of Service ◽  
Software Tool ◽  
Security Attacks ◽  
Man In The Middle ◽  
Practical Performance ◽  
Mitigation Techniques ◽  
And Control ◽  
Cyber Infrastructure

In this chapter, an analysis of security attacks on network elements along with the appropriate countermeasures is presented. The main goal of this chapter is to present the practical execution of various security attacks and their mitigation techniques due to more resilient cyber infrastructure. The network topology that has been attacked is designed in GNS3 software tool installed on Windows operating system, while the attacks are performed in Kali Linux operating system. Three groups of security attacks (Denial of Service, Man in the Middle, and Control Plane attacks) are observed in simulation scenarios with a detailed analysis on each of them, followed by a presentation of practical performance and ways of prevention (protection) against the attacks.

Investigating the Filtration Characteristics of Direct Driven Hydraulics

2021 ◽  
Author(s):  
Xu Han ◽  
Jussi Välimaa ◽  
Abdullokh Orifjonov ◽  
Damiano Padovani ◽  
Tatiana Minav
Keyword(s):  
High Energy ◽  
Oil Contamination ◽  
Time Varying ◽  
Control Performance ◽  
Filter Performance ◽  
Proposed Model ◽  
Contamination Management ◽  
Efficiency Control ◽  
And Control ◽  
Oil Filtration

Abstract Direct driven hydraulics (DDH) is receiving increasing attention due to its advantages such as high energy efficiency, easy maintenance, and compactness. However, its oil contamination management has not been surveyed in detail, whereas uncontrolled oil contamination might result in extra maintenance efforts or even downtime. Therefore, this research paper analyzes the oil filtration in direct driven hydraulics through modeling and simulation to predict the filtration effects and support the filtration design. Firstly, model blocks of the filtration characteristics are built to be added to the basic DDH dynamic model. The model can hereby include the coupling effects between fluid degradation and component wear, the filtering process, and the time-varying filter performance. Secondly, the proposed model is applied to a DDH that incorporates filtration and simulated under a duty cycle for 960 hours. The DDH efficiency and control performance when considering the contaminant are revealed. Thirdly, the results are compared between different filter selections and a filtration solution is finally proposed. In conclusion, this paper illustrates the filtration effects on the efficiency, control performance, and oil contaminant level of DDH by simulation, which can hereby support the design of the DDH filtration solution. According to the simulations, the filtered DDH resulted in 96% degradation of the pump’s volumetric efficiency after 960-hour running compared to 92% when not using any filters. The extra pressure drop introduced by the filter is below 2 bar, suggesting that the introduction of a filter with 6 μm filtration level is beneficial.

scholarly journals Current Knowledge and Future Directions for Improving Subsoiling Quality and Reducing Energy Consumption in Conservation Fields

Agriculture ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 575
Author(s):  
Shangyi Lou ◽  
Jin He ◽  
Hongwen Li ◽  
Qingjie Wang ◽  
Caiyun Lu ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Cover Crops ◽  
Current Knowledge ◽  
High Energy ◽  
Field Application ◽  
Research Progress ◽  
Monitoring And Control ◽  
Future Directions ◽  
Tillage Depth ◽  
And Control

Subsoiling has been acknowledged worldwide to break compacted hardpan, improve soil permeability and water storage capacity, and promote topsoil deepening and root growth. However, there exist certain factors which limit the wide in-field application of subsoiling machines. Of these factors, the main two are poor subsoiling quality and high energy consumption, especially the undesired tillage depth obtained in the field with cover crops. Based on the analysis of global adoption and benefits of subsoiling technology, and application status of subsoiling machines, this article reviewed the research methods, technical characteristics, and developing trends in five key aspects, including subsoiling shovel design, anti-drag technologies, technologies of tillage depth detection and control, and research on soil mechanical interaction. Combined with the research progress and application requirements of subsoiling machines across the globe, current problems and technical difficulties were analyzed and summarized. Aiming to solve these problems, improve subsoiling quality, and reduce energy consumption, this article proposed future directions for the development of subsoiling machines, including optimizing the soil model in computer simulation, strengthening research on the subsoiling mechanism and comprehensive effect, developing new tillage depth monitoring and control systems, and improving wear-resisting properties of subsoiling shovels.

On modeling and dynamics of a multiple launch rocket system

2021 ◽  
pp. 095441002098224
Author(s):  
Bo Li ◽  
Xiaoting Rui ◽  
Guoping Wang ◽  
Jianshu Zhang ◽  
Qinbo Zhou
Keyword(s):  
Monte Carlo ◽  
Multibody Systems ◽  
Euler Method ◽  
Dynamics Analysis ◽  
Analysis Problem ◽  
Dynamic Design ◽  
Proposed Model ◽  
And Control ◽  
Rocket System ◽  
Complete Process

Dynamics analysis is currently a key technique to fully understand the dynamic characteristics of sophisticated mechanical systems because it is a prerequisite for dynamic design and control studies. In this study, a dynamics analysis problem for a multiple launch rocket system (MLRS) is developed. We particularly focus on the deductions of equations governing the motion of the MLRS without rockets by using a transfer matrix method for multibody systems and the motion of rockets via the Newton–Euler method. By combining the two equations, the differential equations of the MLRS are obtained. The complete process of the rockets’ ignition, movement in the barrels, airborne flight, and landing is numerically simulated via the Monte Carlo stochastic method. An experiment is implemented to validate the proposed model and the corresponding numerical results.

scholarly journals An Investigation into the Application of Deep Learning in the Detection and Mitigation of DDOS Attack on SDN Controllers

Technologies ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 14
Author(s):  
James Dzisi Gadze ◽  
Akua Acheampomaa Bamfo-Asante ◽  
Justice Owusu Agyemang ◽  
Henry Nunoo-Mensah ◽  
Kwasi Adu-Boahen Opare
Keyword(s):  
Deep Learning ◽  
Network Architecture ◽  
Learning Algorithm ◽  
Single Point ◽  
Denial Of Service ◽  
Specific Work ◽  
Learning Models ◽  
Ddos Attack ◽  
Deep Learning Algorithm ◽  
Proposed Model

Software-Defined Networking (SDN) is a new paradigm that revolutionizes the idea of a software-driven network through the separation of control and data planes. It addresses the problems of traditional network architecture. Nevertheless, this brilliant architecture is exposed to several security threats, e.g., the distributed denial of service (DDoS) attack, which is hard to contain in such software-based networks. The concept of a centralized controller in SDN makes it a single point of attack as well as a single point of failure. In this paper, deep learning-based models, long-short term memory (LSTM) and convolutional neural network (CNN), are investigated. It illustrates their possibility and efficiency in being used in detecting and mitigating DDoS attack. The paper focuses on TCP, UDP, and ICMP flood attacks that target the controller. The performance of the models was evaluated based on the accuracy, recall, and true negative rate. We compared the performance of the deep learning models with classical machine learning models. We further provide details on the time taken to detect and mitigate the attack. Our results show that RNN LSTM is a viable deep learning algorithm that can be applied in the detection and mitigation of DDoS in the SDN controller. Our proposed model produced an accuracy of 89.63%, which outperformed linear-based models such as SVM (86.85%) and Naive Bayes (82.61%). Although KNN, which is a linear-based model, outperformed our proposed model (achieving an accuracy of 99.4%), our proposed model provides a good trade-off between precision and recall, which makes it suitable for DDoS classification. In addition, it was realized that the split ratio of the training and testing datasets can give different results in the performance of a deep learning algorithm used in a specific work. The model achieved the best performance when a split of 70/30 was used in comparison to 80/20 and 60/40 split ratios.

scholarly journals Overfeeding Extends the Period of Annual Cyclicity but Increases the Risk of Early Embryonic Death in Shetland Pony Mares

Animals ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 361
Author(s):  
Nicky M. M. D’Fonseca ◽  
Charlotte M. E. Gibson ◽  
Iris Hummel ◽  
David A. van Doorn ◽  
Ellen Roelfsema ◽  
...  
Keyword(s):  
Embryo Transfer ◽  
Reproductive Activity ◽  
High Energy ◽  
Morphometric Parameters ◽  
Net Energy ◽  
Conceptus Development ◽  
And Control ◽  
Annual Duration ◽  
Embryonic Death

Obesity has been associated with altered reproductive activity in mares, and may negatively affect fertility. To examine the influence of long-term high-energy (HE) feeding on fertility, Shetland pony mares were fed a diet containing 200% of net energy (NE) requirements during a three-year study. The incidence of hemorrhagic anovulatory follicles (HAF) and annual duration of cyclicity were compared to those in control mares receiving a maintenance diet. Day-7 embryos were flushed and transferred between donor and recipient mares from both groups; the resulting conceptuses were collected 21 days after transfer to assess conceptus development. HE mares became obese, and embryos recovered from HE mares were more likely to succumb to early embryonic death. The period of annual cyclicity was extended in HE compared to control mares in all years. The incidence of HAFs did not consistently differ between HE and control mares. No differences in embryo morphometric parameters were apparent. In conclusion, consuming a HE diet extended the duration of cyclicity, and appeared to increase the likelihood of embryos undergoing early embryonic death following embryo transfer.

Reduced substrate oxidation in postischemic myocardium: 13C and 31P NMR analyses

1990 ◽  
Vol 258 (5) ◽  
pp. H1357-H1365 ◽  
Author(s):  
E. D. Lewandowski ◽  
D. L. Johnston
Keyword(s):  
Steady State ◽  
31P Nmr ◽  
Tca Cycle ◽  
High Energy ◽  
Substrate Oxidation ◽  
High Energy Phosphates ◽  
Atp Content ◽  
And Control ◽  
13C And 31P Nmr ◽  
Postischemic Myocardium

13C and 31P nuclear magnetic resonance (NMR) spectra were used to assess substrate oxidation and high-energy phosphates in postischemic (PI) isolated rabbit hearts. Phosphocreatine (PCr) increased in nonischemic controls on switching from glucose perfusion to either 2.5 mM [3-13C]pyruvate (120%, n = 7) or [2-13C]acetate (114%, n = 8, P less than 0.05). ATP content, oxygen consumption (MVO2), and hemodynamics (dP/dt) were not affected by substrate availability in control or PI hearts. dP/dt was 40-60% lower in PI hearts during reperfusion after 10 min ischemia. Hearts reperfused with either pyruvate (n = 11) or acetate (n = 8) regained preischemic PCr levels within 45 s. Steady-state ATP levels were 55-70% of preischemia with pyruvate and 52-60% with acetate. Percent maximum [4-13C]glutamate signal showed reduced conversion of pyruvate to glutamate via the tricarboxylic acid (TCA) cycle at 4-min reperfusion (PI = 24 +/- 4%, means +/- SE; Control = 48 +/- 4%). The increase in 13C signal from the C-4 position of glutamate was similar to control hearts within 10.5 min. The increase in [4-13C]glutamate signal from acetate was not different between PI and control hearts. The ratio of [2-13C]Glu:[4-13C]Glu, reflecting TCA cycle activity, was reduced in PI hearts with acetate for at least 10 min (Control = 0.76 +/- 0.03; PI = 0.51 +/- 0.09) until steady state was reached. Despite rapid recovery of oxidative phosphorylation, contractility remained impaired and substrate oxidation was significantly slowed in postischemic hearts.

Power Reserve Classification and Control for Peaking Balance with Intermittent Generation Grid

2014 ◽  
Vol 521 ◽  
pp. 252-255
Author(s):  
Jian Yuan Xu ◽  
Jia Jue Li ◽  
Jie Jun Zhang ◽  
Yu Zhu
Keyword(s):  
Real Time ◽  
Balance Control ◽  
Control Model ◽  
Intermediate Variable ◽  
Proposed Model ◽  
Grid Operators ◽  
Period Constant ◽  
Grid Operation ◽  
And Control ◽  
Time Reserve

The problem of intermittent generation peaking is highly concerned by the grid operator. To build control model for solving unbalance of peaking is great necessary. In this paper, we propose reserve classification control model which contain constant reserve control model with real-time reserve control model to guide the peaking balance of the grid with intermittent generation. The proposed model associate time-period constant reserve control model with real-time reserve control model to calculate, and use the peaking margin as intermediate variable. Therefore, the model solutions which are the capacity of reserve classification are obtained. The grid operators use the solution to achieve the peaking balance control. The proposed model was examined by real grid operation case, and the results of the case demonstrate the validity of the proposed model.

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