Pub Date : 2022-05-28DOI: 10.1109/SETIT54465.2022.9875592
Simon Hlekisana Muchinenyika, Hippolyte N’sung-Nza Muyingi
Most computing capabilities are fast migrating from hardware to software. Despite this having a tendency of lowering energy consumption within devices, increase in computing capacity, improved display capabilities, and huge memory demands cancel out optimal energy savings. Software developers have to rely on code instrumentation as the sole source of data to apply energy optimisation techniques. However, code instrumentation abstracts hardware features and rely on logs from software modules to represent energy consumption. Test cases have to be carefully planned as well to have meaningful logs, as use cases are usually diverse for mobile. Apart from reviewing techniques used to assess energy consumption on mobile platforms, this paper presents an analysis of hardware advancements on smartphones in an attempt to expose the underlying hardware characteristics which are generally abstracted to software developers. An understanding of such features is essential as software in itself does not consume energy, but does that indirectly through hardware it controls. Software projects can then be planned and designed to match the hardware characteristics without compromising much on energy consumption.
{"title":"An Analysis of Screen Resolution Effects on Battery Endurance: A Case of Smartphones","authors":"Simon Hlekisana Muchinenyika, Hippolyte N’sung-Nza Muyingi","doi":"10.1109/SETIT54465.2022.9875592","DOIUrl":"https://doi.org/10.1109/SETIT54465.2022.9875592","url":null,"abstract":"Most computing capabilities are fast migrating from hardware to software. Despite this having a tendency of lowering energy consumption within devices, increase in computing capacity, improved display capabilities, and huge memory demands cancel out optimal energy savings. Software developers have to rely on code instrumentation as the sole source of data to apply energy optimisation techniques. However, code instrumentation abstracts hardware features and rely on logs from software modules to represent energy consumption. Test cases have to be carefully planned as well to have meaningful logs, as use cases are usually diverse for mobile. Apart from reviewing techniques used to assess energy consumption on mobile platforms, this paper presents an analysis of hardware advancements on smartphones in an attempt to expose the underlying hardware characteristics which are generally abstracted to software developers. An understanding of such features is essential as software in itself does not consume energy, but does that indirectly through hardware it controls. Software projects can then be planned and designed to match the hardware characteristics without compromising much on energy consumption.","PeriodicalId":126155,"journal":{"name":"2022 IEEE 9th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133097458","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-28DOI: 10.1109/SETIT54465.2022.9875494
Mohsen Othmani, T. Ezzedine
Wireless Sensor Network (WSN) localization is still an open topic for improvement and continues to prove its necessity in our daily life in parallel with the technological evolution and our needs in various fields. The issue of energy efficiency and network lifetime extension, localization, secure data communication, latency reduction, efficient quality of service, data communication assurance, high scalability also remain topics for improvement.In a context of indoor localization based on learning a database of collected RSSI values, we detail how to proceed with a refinement approach in order to gain in memory, execution time, and localization accuracy. We took advantage of our previous studies in which dynamic cell structure neural networks (DCSNN) have proven superior performance to apply our approach.The results obtained show a memory gain of 82% relative to the data to be extracted from the training database and to be learned, and consequently a gain in execution time and energy consumed. The precision of the coordinates is about 0.031m.Note that the training database is presented as a matrix of RSSI (Received Signal Strength Indicator) values collected by the anchor nodes for each reference point.
随着技术的发展和各个领域的需求，无线传感器网络(WSN)的定位仍然是一个有待改进的开放话题，并不断证明其在我们日常生活中的必要性。能源效率和网络寿命延长、本地化、安全数据通信、降低延迟、高效服务质量、数据通信保证、高可扩展性等问题也仍有待改进。在基于学习收集的RSSI值数据库进行室内定位的背景下，我们详细介绍了如何使用改进方法来获得内存、执行时间和定位精度。我们利用我们之前的研究，其中动态细胞结构神经网络(DCSNN)已经证明了优越的性能来应用我们的方法。获得的结果显示，相对于从训练数据库中提取和学习的数据，内存增加了82%，因此执行时间和消耗的能量增加了。坐标精度约为0.031m。请注意，训练数据库以锚节点为每个参考点收集的RSSI (Received Signal Strength Indicator，接收信号强度指标)值矩阵的形式呈现。
{"title":"Refinement Approach for Node Localization Using Dynamic Cell Structures Neural Networks","authors":"Mohsen Othmani, T. Ezzedine","doi":"10.1109/SETIT54465.2022.9875494","DOIUrl":"https://doi.org/10.1109/SETIT54465.2022.9875494","url":null,"abstract":"Wireless Sensor Network (WSN) localization is still an open topic for improvement and continues to prove its necessity in our daily life in parallel with the technological evolution and our needs in various fields. The issue of energy efficiency and network lifetime extension, localization, secure data communication, latency reduction, efficient quality of service, data communication assurance, high scalability also remain topics for improvement.In a context of indoor localization based on learning a database of collected RSSI values, we detail how to proceed with a refinement approach in order to gain in memory, execution time, and localization accuracy. We took advantage of our previous studies in which dynamic cell structure neural networks (DCSNN) have proven superior performance to apply our approach.The results obtained show a memory gain of 82% relative to the data to be extracted from the training database and to be learned, and consequently a gain in execution time and energy consumed. The precision of the coordinates is about 0.031m.Note that the training database is presented as a matrix of RSSI (Received Signal Strength Indicator) values collected by the anchor nodes for each reference point.","PeriodicalId":126155,"journal":{"name":"2022 IEEE 9th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124935653","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-28DOI: 10.1109/SETIT54465.2022.9875881
Fatma Hmissi, Sofiane Ouni
MQTT (Message Queuing Telemetry Transport) has become the perfect messaging protocol for IoT (Internet of Things) systems since it is the lightest protocol designed for low bandwidth, high-latency, unreliable networks. Today, the strategy of distributing several MQTT brokers on the networks is widely used because the strategy of using a single broker is no longer efficient. However, in the distributing architectures of MQTT brokers, a subscriber should have prior knowledge about the address of the broker that publishes the data on the topics of interest. In this paper, we tackle this challenge by proposing a mechanism that connects the subscribers to the brokers in a transparent way. The proposed approach, known as TD-MQTT (Transparent Distributed MQTT brokers), requires no prior knowledge of the brokers by the subscribers. The data will be carried automatically from brokers that can change their configuration and location. The transparency will help to use IoT data without worrying about their location and dynamic configuration changes. To evaluate our approach, we compared it with the basic distributed MQTT and the EMMA (MQTT Middle-ware for Edge Computing Applications) approach. The results of the evaluation show that TD-MQTT is much better than the standard MQTT, especially in terms of response time.
{"title":"TD-MQTT: Transparent Distributed MQTT Brokers for Horizontal IoT Applications","authors":"Fatma Hmissi, Sofiane Ouni","doi":"10.1109/SETIT54465.2022.9875881","DOIUrl":"https://doi.org/10.1109/SETIT54465.2022.9875881","url":null,"abstract":"MQTT (Message Queuing Telemetry Transport) has become the perfect messaging protocol for IoT (Internet of Things) systems since it is the lightest protocol designed for low bandwidth, high-latency, unreliable networks. Today, the strategy of distributing several MQTT brokers on the networks is widely used because the strategy of using a single broker is no longer efficient. However, in the distributing architectures of MQTT brokers, a subscriber should have prior knowledge about the address of the broker that publishes the data on the topics of interest. In this paper, we tackle this challenge by proposing a mechanism that connects the subscribers to the brokers in a transparent way. The proposed approach, known as TD-MQTT (Transparent Distributed MQTT brokers), requires no prior knowledge of the brokers by the subscribers. The data will be carried automatically from brokers that can change their configuration and location. The transparency will help to use IoT data without worrying about their location and dynamic configuration changes. To evaluate our approach, we compared it with the basic distributed MQTT and the EMMA (MQTT Middle-ware for Edge Computing Applications) approach. The results of the evaluation show that TD-MQTT is much better than the standard MQTT, especially in terms of response time.","PeriodicalId":126155,"journal":{"name":"2022 IEEE 9th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127759912","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-28DOI: 10.1109/SETIT54465.2022.9875937
Hind El Makhtoum, Youssef Bentaleb
Metering systems in smart grids are the components that store, transmit and process critical data about customers and their energy use. These systems communicate with users’ devices, technicians, and utility control systems, namely MDMS, substations… Consequently, smart meters are a tempting target for intrusion and falsification attacks that may have devastating consequences on the electrical grid and user’s private life. In order to tackle eventual vulnerabilities, the One-Time-Password (OTP) is a promising technique to ensure privacy and access control to smart meters as it is claimed to have better results on safeguarding access. In this paper, we highlight the current existing OTP-based authentication approaches in the metering systems. First, we investigate the privacy issues that are related to smart meters. Additionally, we highlight significant attacks and security parameters that we will include in our evaluation. Furthermore, we will analyze the selected schemes and propose some recommendations. Finally, we will discuss limitations, challenges, and future scopes of the analyzed schemes to help future researchers use the OTP technique securely and efficiently.
{"title":"Review and evaluation of OTP-Based authentication schemes in the metering systems of smart grids","authors":"Hind El Makhtoum, Youssef Bentaleb","doi":"10.1109/SETIT54465.2022.9875937","DOIUrl":"https://doi.org/10.1109/SETIT54465.2022.9875937","url":null,"abstract":"Metering systems in smart grids are the components that store, transmit and process critical data about customers and their energy use. These systems communicate with users’ devices, technicians, and utility control systems, namely MDMS, substations… Consequently, smart meters are a tempting target for intrusion and falsification attacks that may have devastating consequences on the electrical grid and user’s private life. In order to tackle eventual vulnerabilities, the One-Time-Password (OTP) is a promising technique to ensure privacy and access control to smart meters as it is claimed to have better results on safeguarding access. In this paper, we highlight the current existing OTP-based authentication approaches in the metering systems. First, we investigate the privacy issues that are related to smart meters. Additionally, we highlight significant attacks and security parameters that we will include in our evaluation. Furthermore, we will analyze the selected schemes and propose some recommendations. Finally, we will discuss limitations, challenges, and future scopes of the analyzed schemes to help future researchers use the OTP technique securely and efficiently.","PeriodicalId":126155,"journal":{"name":"2022 IEEE 9th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT)","volume":"115 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116598093","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-28DOI: 10.1109/SETIT54465.2022.9875471
Intissar Sayahi, Sarra Ismail
Nowadays, the advantages offered by image processing and deep learning increased their efficiency popularity. Thus, vision systems are widely motivating researchers to develop new protocols and features to optimize existing ones. Of course, technical challenges do not lack since the integration of image acquisition and processing units industrial environment poses considerable problems. In context, we adopted in our work the hybrid approach combining hardware design and software development. This approach makes the system compact, robust and reliable, especially in industrial field to ensure several operations quality inspection and verification. The proposed solution is to design an industrial embedded vision system that matches scalable hardware architectures to adaptable algorithms. this paper, we propose an efficient model to automate quality control in an industrial production line. This work aims to integrate the concept of the multi-tasking image processing in the manufacturing field by offering a whole pack of various inspection operations, from surface to dimensional inspections, based on simple hardware implementations, optical setups, and deep learning algorithms.
{"title":"Design and Implementation of an Embedded Vision System for Industrial Inspection","authors":"Intissar Sayahi, Sarra Ismail","doi":"10.1109/SETIT54465.2022.9875471","DOIUrl":"https://doi.org/10.1109/SETIT54465.2022.9875471","url":null,"abstract":"Nowadays, the advantages offered by image processing and deep learning increased their efficiency popularity. Thus, vision systems are widely motivating researchers to develop new protocols and features to optimize existing ones. Of course, technical challenges do not lack since the integration of image acquisition and processing units industrial environment poses considerable problems. In context, we adopted in our work the hybrid approach combining hardware design and software development. This approach makes the system compact, robust and reliable, especially in industrial field to ensure several operations quality inspection and verification. The proposed solution is to design an industrial embedded vision system that matches scalable hardware architectures to adaptable algorithms. this paper, we propose an efficient model to automate quality control in an industrial production line. This work aims to integrate the concept of the multi-tasking image processing in the manufacturing field by offering a whole pack of various inspection operations, from surface to dimensional inspections, based on simple hardware implementations, optical setups, and deep learning algorithms.","PeriodicalId":126155,"journal":{"name":"2022 IEEE 9th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT)","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114862134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-28DOI: 10.1109/SETIT54465.2022.9875516
Nadia Gargouri, M. Samet, Z. Sakka
This paper presents an Injection Locked Ring Oscillator (ILRO) for use in biomedical implants applications. A pulse injection locking method has been desired for ring oscillator performance enhancement and phase noise cancellation. In addition, the frequency is controlled independently of the biasing circuit using an inversion mode MOS voltage controlled capacitor (varactor).Designed in a 0.18-μm CMOS, this ILRO works inthe ISM band of 902–928 GHz and consumes a lowpower of 4.62 mW under 1.8V power supply. The phase noise of -121.6dBc /Hz at 1MHzoffset frequency was obtained at 76 MHz inputinjection pulse.The proposed circuit can achieve a FoM of -174.19 dBc/Hz.
{"title":"A Low-Noise Injection-Locked Ring Oscillator for biomedical implants applications","authors":"Nadia Gargouri, M. Samet, Z. Sakka","doi":"10.1109/SETIT54465.2022.9875516","DOIUrl":"https://doi.org/10.1109/SETIT54465.2022.9875516","url":null,"abstract":"This paper presents an Injection Locked Ring Oscillator (ILRO) for use in biomedical implants applications. A pulse injection locking method has been desired for ring oscillator performance enhancement and phase noise cancellation. In addition, the frequency is controlled independently of the biasing circuit using an inversion mode MOS voltage controlled capacitor (varactor).Designed in a 0.18-μm CMOS, this ILRO works inthe ISM band of 902–928 GHz and consumes a lowpower of 4.62 mW under 1.8V power supply. The phase noise of -121.6dBc /Hz at 1MHzoffset frequency was obtained at 76 MHz inputinjection pulse.The proposed circuit can achieve a FoM of -174.19 dBc/Hz.","PeriodicalId":126155,"journal":{"name":"2022 IEEE 9th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129894902","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-28DOI: 10.1109/SETIT54465.2022.9875757
Boulerial Dalila, Kechar Bouabdellah, Benzerbadj Ali
The 21st century is marked by a remarkable expansion of IoT. This technology that allows us to connect with our objects permanently and thus monitor each interaction that may be crucial in our daily life. And among the most important bronchi of this technology we are interested in wireless sensor networks with mobile sink (WSN-MS1 for short). These networks, while being very useful and efficient in the world of internet of things (IoT)[33],[34], they face serious challenges, particularly that of the battery which ensures them a very limited lifetime, as well as the problem of the broken links between the transmitting nodes and the mobile sink. In this paper, we have proposed a new approach EH-HXMAC that solves the first problem by collecting ambient energy from the two most powerful sources (the sun and the wind), and by acting on the duty cycle of the emitting nodes. To remedy the second problem, we have resorted to the Handover technique which ensures data transmission integrity between the sensor and the mobile sink. The results of the simulation carried out by the Cooja Contiki simulator show that the combination of these three techniques provides an improvement in terms of network lifetime , throughput and received packets number.
{"title":"Maximizing The Lifetime of WSN Using Hybrid Energy Harvesting Approach","authors":"Boulerial Dalila, Kechar Bouabdellah, Benzerbadj Ali","doi":"10.1109/SETIT54465.2022.9875757","DOIUrl":"https://doi.org/10.1109/SETIT54465.2022.9875757","url":null,"abstract":"The 21st century is marked by a remarkable expansion of IoT. This technology that allows us to connect with our objects permanently and thus monitor each interaction that may be crucial in our daily life. And among the most important bronchi of this technology we are interested in wireless sensor networks with mobile sink (WSN-MS1 for short). These networks, while being very useful and efficient in the world of internet of things (IoT)[33],[34], they face serious challenges, particularly that of the battery which ensures them a very limited lifetime, as well as the problem of the broken links between the transmitting nodes and the mobile sink. In this paper, we have proposed a new approach EH-HXMAC that solves the first problem by collecting ambient energy from the two most powerful sources (the sun and the wind), and by acting on the duty cycle of the emitting nodes. To remedy the second problem, we have resorted to the Handover technique which ensures data transmission integrity between the sensor and the mobile sink. The results of the simulation carried out by the Cooja Contiki simulator show that the combination of these three techniques provides an improvement in terms of network lifetime , throughput and received packets number.","PeriodicalId":126155,"journal":{"name":"2022 IEEE 9th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125900998","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-28DOI: 10.1109/SETIT54465.2022.9875643
Salma Laazizi, Jihan Ben Azzouz, A. Jemai
Cyberinfrastructure is characterized by a large amount of emerging and dynamic information, requiring a large number of cyber-criminals trying to acquire information, data mining, machine learning, measurements, and other interdisciplinary skills to meet the cybersecurity issues in Industry 4.0. Machine learning and information mining play an important role in cybersecurity, and unstable information frequently has a high-dimensional feature space. The presence of several noisy characteristics among high-dimensional features might impede and degrade classifier performance. To address this issue, feature selection and subspace methods have been put out and assessed during the past few years. In this paper, four classification techniques and a feature selection strategy are implemented to detect attacks that threaten Industry 4.0. These techniques are Random Forest (RF), Decision Trees (J48), Support Vector Machines (SVM), and Naive Bayes (NB) with Feature Selection Strategy (CFS). Several experiments have been performed using the train and test NSL-KDD datasets with good results. These are based on four categories: Denial of Service (DoS) attack, Probing Attack, User-to-Root (U2R) attack, and Remote-to-Local (R2L) attack. To improve the detection rate of these attacks, a strategy combining multiple classification algorithms is implemented.
{"title":"cybclass: classification approach for cybersecurity in industry 4.0","authors":"Salma Laazizi, Jihan Ben Azzouz, A. Jemai","doi":"10.1109/SETIT54465.2022.9875643","DOIUrl":"https://doi.org/10.1109/SETIT54465.2022.9875643","url":null,"abstract":"Cyberinfrastructure is characterized by a large amount of emerging and dynamic information, requiring a large number of cyber-criminals trying to acquire information, data mining, machine learning, measurements, and other interdisciplinary skills to meet the cybersecurity issues in Industry 4.0. Machine learning and information mining play an important role in cybersecurity, and unstable information frequently has a high-dimensional feature space. The presence of several noisy characteristics among high-dimensional features might impede and degrade classifier performance. To address this issue, feature selection and subspace methods have been put out and assessed during the past few years. In this paper, four classification techniques and a feature selection strategy are implemented to detect attacks that threaten Industry 4.0. These techniques are Random Forest (RF), Decision Trees (J48), Support Vector Machines (SVM), and Naive Bayes (NB) with Feature Selection Strategy (CFS). Several experiments have been performed using the train and test NSL-KDD datasets with good results. These are based on four categories: Denial of Service (DoS) attack, Probing Attack, User-to-Root (U2R) attack, and Remote-to-Local (R2L) attack. To improve the detection rate of these attacks, a strategy combining multiple classification algorithms is implemented.","PeriodicalId":126155,"journal":{"name":"2022 IEEE 9th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121872499","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-28DOI: 10.1109/SETIT54465.2022.9875712
Aymen Ramadhan Ghilen, Amel Mohamed Zahou, Wiem Abedelmonem Ben Khalifa
To cope with the unauthorized access to the cloud treasure of resources and services, several cloud service providers implement the API-based access control approach and grant thus a full authentication of any client application. Once called, each cloud API (Application Programming Interface) is required to authenticate through a secret access key, commonly termed API key. A plethora of security risks is associated with these keys whether during their generation, storage, or utilization. The hardware secure element-based proposal aims for an end-to-end security between a cloud service provider and a client application. To ensure a reliable and secure API key exchange, the concerned entities rely on Public Key Infrastructure (PKI). As soon as an adversary acquires an unbounded computing power, it would be easy to intercept the keys and then unlock the gate behind the valuables over the cloud. In this paper, we propose a revised scheme that discards the PKI and installs a quantum mechanism to mutually authenticate the secure element and the cloud service provider by establishing a set of shared keys. A pioneering absolute security of the presented approach is warranted by the principles of quantum physics. To analyze the security of the quantum technology, we establish a formal verification based on PRISM model checking tool. We outstandingly focus on satisfying two prominent properties: (i) both the parties engaged in the quantum protocol are able to detect any disallowed eavesdropping and (ii) the valid amount of information caught by an adversary on the installed key must be negligible.
{"title":"Quantum cryptography for the benefit of API keys safety","authors":"Aymen Ramadhan Ghilen, Amel Mohamed Zahou, Wiem Abedelmonem Ben Khalifa","doi":"10.1109/SETIT54465.2022.9875712","DOIUrl":"https://doi.org/10.1109/SETIT54465.2022.9875712","url":null,"abstract":"To cope with the unauthorized access to the cloud treasure of resources and services, several cloud service providers implement the API-based access control approach and grant thus a full authentication of any client application. Once called, each cloud API (Application Programming Interface) is required to authenticate through a secret access key, commonly termed API key. A plethora of security risks is associated with these keys whether during their generation, storage, or utilization. The hardware secure element-based proposal aims for an end-to-end security between a cloud service provider and a client application. To ensure a reliable and secure API key exchange, the concerned entities rely on Public Key Infrastructure (PKI). As soon as an adversary acquires an unbounded computing power, it would be easy to intercept the keys and then unlock the gate behind the valuables over the cloud. In this paper, we propose a revised scheme that discards the PKI and installs a quantum mechanism to mutually authenticate the secure element and the cloud service provider by establishing a set of shared keys. A pioneering absolute security of the presented approach is warranted by the principles of quantum physics. To analyze the security of the quantum technology, we establish a formal verification based on PRISM model checking tool. We outstandingly focus on satisfying two prominent properties: (i) both the parties engaged in the quantum protocol are able to detect any disallowed eavesdropping and (ii) the valid amount of information caught by an adversary on the installed key must be negligible.","PeriodicalId":126155,"journal":{"name":"2022 IEEE 9th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121931630","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-28DOI: 10.1109/SETIT54465.2022.9875912
R. Ayachi, Mouna Afif, Y. Said, A. B. Abdelali
The concept of smart vehicles is becoming an essential feature that ensures driver comfort and security. Smart vehicles are equipped with intelligent systems based on advanced technologies that perform a set of tasks for the mentioned purposes. Recognizing Traffic sign is one the most important systems that guarantee a high-security level. However, it is difficult to develop the best traffic sign recognition system due to numerous obstacles. such as weather conditions, geometric deformation, and most important is the material limitation. In this work, we proposed the implementation of a lightweight convolutional neural network (CNN) model on a mobile device to overcome the mentioned challenges. The proposed CNN combines high performances and low computation complexity. Evaluating the proposed model on publicly available datasets proved its efficiency. Besides, the implementation of the CNN model on the pynq platform demonstrates the possibility of using a wide range of mobile devices for the inference of the proposed model.
{"title":"Traffic Sign recognition for smart vehicles based on lightweight CNN implementation on mobile devices","authors":"R. Ayachi, Mouna Afif, Y. Said, A. B. Abdelali","doi":"10.1109/SETIT54465.2022.9875912","DOIUrl":"https://doi.org/10.1109/SETIT54465.2022.9875912","url":null,"abstract":"The concept of smart vehicles is becoming an essential feature that ensures driver comfort and security. Smart vehicles are equipped with intelligent systems based on advanced technologies that perform a set of tasks for the mentioned purposes. Recognizing Traffic sign is one the most important systems that guarantee a high-security level. However, it is difficult to develop the best traffic sign recognition system due to numerous obstacles. such as weather conditions, geometric deformation, and most important is the material limitation. In this work, we proposed the implementation of a lightweight convolutional neural network (CNN) model on a mobile device to overcome the mentioned challenges. The proposed CNN combines high performances and low computation complexity. Evaluating the proposed model on publicly available datasets proved its efficiency. Besides, the implementation of the CNN model on the pynq platform demonstrates the possibility of using a wide range of mobile devices for the inference of the proposed model.","PeriodicalId":126155,"journal":{"name":"2022 IEEE 9th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126550429","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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