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Nelson H. Carreras Guzman Morten Wied Igor Kozine Mary Ann Lundteigen 《Systems Engineering》2020,23(2):189-210
Many safety‐related systems are evolving into cyber‐physical systems (CPSs), integrating information technologies in their control architectures and modifying the interactions among automation and human operators. Particularly, a promising potential exists for enhanced efficiency and safety in applications such as autonomous transportation systems, control systems in critical infrastructures, smart manufacturing and process plants, robotics, and smart medical devices, among others. However, the modern features of CPSs are ambiguous for system designers and risk analysts, especially considering the role of humans and the interactions between safety and security. The sources of safety risks are not restricted to accidental failures and errors anymore. Indeed, cybersecurity attacks can now cascade into safety risks leading to physical harm to the system and its environment. These new challenges demand system engineers and risk analysts to understand the security vulnerabilities existing in CPS features and their dependencies with physical processes. Therefore, this paper (a) examines the key features of CPSs and their relation with other system types; (b) defines the dependencies between levels of automation and human roles in CPSs from a systems engineering perspective; and (c) applies systems thinking to describe a multi‐layered diagrammatic representation of CPSs for combined safety and security risk analysis, demonstrating an application in the maritime sector to analyze an autonomous surface vehicle. 相似文献
3.
Otto Julio Ahlert Pinno Andr Ricardo Abed Grgio Luis C.E. De Bona 《Concurrency and Computation》2020,32(12)
The IoT is changing the way we interact with the world. Very soon, almost all of our daily tasks will be made through self intelligent systems embedded in devices scattered all around us. Their mission is to turn our cities, transportation systems, buildings, homes, and bodies in smart environments. These environments will bring us more comfort, improve our performance, increase our profits, and take away time‐consuming tasks. However, besides its great benefits, the IoT is also a big source of concerns, mainly because a good part of its devices will handle private and confidential information. Recently, cases of successful IoT invasions only worsen this scenario and show us that the today's adopted access control systems need to be replaced by more efficiently and secure ones. To overcome these access control problems, in this work, we present the ControlChain. The ControlChain is an access control authorization architecture that is heavily based on Blockchain technology. We also demonstrate the viability of the ControlChain through the E‐ControlChain, a proof‐of‐concept developed to run over the Ethereum network. Our proposals follows the IoT tendency requirements and are user‐transparent, user‐friendly, fully decentralized, scalable, fault tolerant, and compatible with a wide range of today's access control models already used in the IoT. Finally, we also make a cost and a performance analysis of E‐ControlChain, using a Raspberry Pi as an IoT device. 相似文献
4.
Azath Mubarakali Karthik Srinivasan Reham Mukhalid Subash C. B. Jaganathan Ninoslav Marina 《Computational Intelligence》2020,36(4):1580-1592
The rapid development of internet of things (IoT) is to be the next generation of the IoT devices are a simple target for attackers due to the lack of security. Attackers can easily hack the IoT devices that can be used to form botnets, which can be used to launch distributed denial of service (DDoS) attack against networks. Botnets are the most dangerous threat to the security systems. Software-defined networking (SDN) is one of the developing filed, which introduce the capacity of dynamic program to the network. Use the flexibility and multidimensional characteristics of SDN used to prevent DDoS attacks. The DDoS attack is the major attack to the network, which makes the entire network down, so that normal users might not avail the services from the server. In this article, we proposed the DDoS attack detection model based on SDN environment by combining support vector machine classification algorithm is used to collect flow table values in sampling time periods. From the flow table values, the five-tuple characteristic values extracted and based on it the DDoS attack can be detected. Based on the experimental results, we found the average accuracy rate is 96.23% with a normal amount of traffic flow. Proposed research offers a better DDoS detection rate on SDN. 相似文献
5.
Pandit Byomakesha
Dash Janmenjoy Nayak Bighnaraj Naik Etuari Oram SK Hafizul Islam 《SECURITY AND PRIVACY》2020,3(5)
Security and threats are growing immensely due to the higher usage of internet of things applications in all aspects. Due to imbalanced nature of IoT security data, the designing of model‐based anomaly detection in IoT network poses a challenge for machine learning model as most of the machine learning model assumes the equal number of samples for each class. Approximately, 2.79% of IoT network profiles are of anomaly types which impose severe imbalance where there are three samples in the anomaly types for hundreds of samples in the majority normal class. This results in poor predictive performance for identification of anomaly type, which is essentially a problem because the anomaly type is more sensitive than the normal activity type. This work proposes a multiclass adaptive boosting ensemble learning‐based model with the synthetic minority oversampling technique for prediction of an anomaly in IoT network. The proposed approaches are simulated with DS2OS data and the performance is compared with other machine learning approaches. The evaluation metrics such as sensitivity, F1‐score, and receiver operating characteristic‐AUC imply the efficiency of the proposed approach in handling the imbalanced nature of the data and found efficient to identify both anomaly types and normal activity. 相似文献
6.
Li Xingjun Shao Zhiwei Cheng Hongping Bayan Omar Mohammed 《International Journal of Communication Systems》2020,33(8)
Cloud computing provides high accessibility, scalability, and flexibility in the era of computing for different practical applications. Internet of things (IoT) is a new technology that connects the devices and things to provide user required services. Due to data and information upsurge on IoT, cloud computing is usually used for managing these data, which is known as cloud‐based IoT. Due to the high volume of requirements, service diversity is one of the critical challenges in cloud‐based IoT. Since the load balancing issue is one of the NP‐hard problems in heterogeneous environments, this article provides a new method for response time reduction using a well‐known grey wolf optimization algorithm. In this paper, we supposed that the response time is the same as the execution time of all the tasks that this parameter must be minimized. The way is determining the status of virtual machines based on the current load. Then the tasks will be removed from the machine with the additional load depending on the condition of the virtual machine and will be transferred to the appropriate virtual machine, which is the criterion for assigning the task to the virtual machine based on the least distance. The results of the CloudSim simulation environment showed that the response time is developed in compared to the HBB‐LB and EBCA‐LB algorithm. Also, the load imbalancing degree is improved in comparison to TSLBACO and HJSA. 相似文献
7.
Lylia Alouache Nga Nguyen Makhlouf Aliouat Rachid Chelouah 《International Journal of Communication Systems》2020,33(15)
We propose in this paper a Hybrid Software‐Defined Networking‐based Geographical Routing Protocol (HSDN‐GRA) with a clustering approach. It takes into account three different criteria to select the best relay to send data: (1) the contact duration between vehicles, (2) the available load of each vehicle, (3) and the log of encountered communication errors embedded in each cluster head. The multi‐criteria strategy allows the selection of the most reliable vehicles by avoiding communication problems and ensuring connection availability. Once the hybrid control plane has found out the next eligible neighbor, the data plane will be in charge of dividing and sending data. To validate our approach, HSDN‐GRA has been modeled and implemented in JADE, a multi‐agent platform, to be compared to other multi‐agent based protocols. Simulation results show that HSDN‐GRA achieves good performance with respect to the average routing overhead, the packet drop rate, and the throughput. 相似文献
8.
P. Venkata Krishna Sumanth Yenduri Ezendu Ariwa 《International Journal of Communication Systems》2020,33(13)
The emergence of data engineering along with the support of Online Social Networks is growing by millions every day due to the introduction of wireless systems and Internet of Things. The rapid growth of usage of smart devices helps to create new generation knowledge sharing platforms. Data Analytics has a major role to play in the growth and success of wireless and IoT applications. The growth of data has become exponential and is difficult to analyze. Many researchers depend on the data available on Wireless Systems and IoT for developing new generation services and applications. With the opportunity of information and communication technologies like heterogeneous networking, cloud computing, web services, crowd sensing and data mining, ubiquitous and asynchronous information sharing is feasible. But this also brings out a lot of provocations with respect to conflicting standards, data portability, data aggregation, data distribution, differential context and communication overhead. The smart information and communication technology has changed many features of human lifestyle: personal and work places. 相似文献
9.
Gerges M. Salama Alshimaa H. Ismail Tarek Abed Soliman Hesham F.A. Hamed Nirmeen A. El‐Bahnasawy 《International Journal of Communication Systems》2020,33(12)
In 5G cloud computing, the most notable and considered design issues are the energy efficiency and delay. The majority of the recent studies were dedicated to optimizing the delay issue by leveraging the edge computing concept, while other studies directed its efforts towards realizing a green cloud by minimizing the energy consumption in the cloud. Active queue management‐based green cloud model (AGCM) as one of the recent green cloud models reduced the delay and energy consumption while maintaining a reliable throughput. Multiaccess edge computing (MEC) was established as a model for the edge computing concept and achieved remarkable enhancement to the delay issue. In this paper, we present a handoff scenario between the two cloud models, AGCM and MEC, to acquire the potential gain of such collaboration and investigate its impact on the cloud fundamental constraints; energy consumption, delay, and throughput. We examined our proposed model with simulation showing great enhancement for the delay, energy consumption, and throughput over either model when employed separately. 相似文献
10.
The rapid and unprecedented technological advancements are currently dominated by two technologies. At one hand, we witness the rise of the Internet of Things (IoT) as the next evolution of the Internet. At the other hand, we witness a vast spread of social networks that connects people together socially and opens the door for people to share and express ideas, thoughts, and information. IoT is overpopulated by a vast number of objects, millions of multimedia services, and interactions. Therefore, the search of the right object that can provide the specific multimedia service is considered as an important issue. The merge of these two technologies resulted in new paradigm called Social IoT (SIoT). The main idea in SIoT is that every object can mine IoT in search for certain multimedia service. We investigate the issue of friends' management in SIoT and propose a framework to manage friends' requests. The proposed framework employs several mechanisms to better manage friends' relationships. The proposed framework consists of friend selection, friendship removal, and an update module. It proposes a weight-based algorithm and Naïve Bayes Classifier-based algorithm for the selection component. Moreover, a random service allocation model is proposed to construct service-specific network model. This model is then used in the simulation setup to examine the performance of different friends' management algorithms. The performance of the proposed framework is evaluated using simulation under different scenarios. The obtained simulation results show improvement over other strategies in terms of average degree of connections, average path length, local cluster coefficients, and throughput. 相似文献