This paper proposes a couple of multiple-layer message security schemes. The utilization of cryptography as well as steganography allows the attainment of an acceptable standard of information security. In both schemes, the plaintext data is first encrypted using the AES algorithm. Next, a spatial domain steganography technique is employed to conceal the encrypted sensitive data into 3D cover images. These procedures allow us to optimize for capacity. However, if a higher level of security is required, then an extra step of image processing takes place. More specifically, a corner filter is utilized on each of the 2D slides of the 3D cover images, such that LSB embedding only takes place in those corner-detected pixels. Numerical results exhibit superior performance, especially in comparison to counterpart steganography schemes found in the literature.
{"title":"Utilization of Corner Filters, AES and LSB Steganography for Secure Message Transmission","authors":"Wassim Alexan, Abdelrahman Elkhateeb, Eyad Mamdouh, Fahd Al-Seba'ey, Ziad Amr, Hana Khalil","doi":"10.1109/ICM52667.2021.9664947","DOIUrl":"https://doi.org/10.1109/ICM52667.2021.9664947","url":null,"abstract":"This paper proposes a couple of multiple-layer message security schemes. The utilization of cryptography as well as steganography allows the attainment of an acceptable standard of information security. In both schemes, the plaintext data is first encrypted using the AES algorithm. Next, a spatial domain steganography technique is employed to conceal the encrypted sensitive data into 3D cover images. These procedures allow us to optimize for capacity. However, if a higher level of security is required, then an extra step of image processing takes place. More specifically, a corner filter is utilized on each of the 2D slides of the 3D cover images, such that LSB embedding only takes place in those corner-detected pixels. Numerical results exhibit superior performance, especially in comparison to counterpart steganography schemes found in the literature.","PeriodicalId":212613,"journal":{"name":"2021 International Conference on Microelectronics (ICM)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129936805","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 : 2021-12-19DOI: 10.1109/ICM52667.2021.9664959
Ahmed Ibrahim Abdelaal, M. Ghoneima, Bassem A. Abdullah
Vehicular Ad-hoc Networks (VANETs) are getting significant research attention to achieve road safety and limit the increasing number of car accidents caused by high density of vehicles on roads. Besides, modern vehicles are equipped with sensors, cameras, and on-board units that capable of communication with other vehicles, VANETs make use of these capabilities leading to the evolve of new applications and services. Testing vehicular networks protocols and applications requires special attention, since field operational testing is very expensive and even not practical for large scale networks, the software simulation tools are considered to be the best choice to test vehicular ad-hoc networks. In this paper, we will shed light on the most recent advances in vehicular network simulation, we will compare between two modern frameworks that represents state of art VANET simulators, upon this comparison we will suggest a new VANETs simulator framework based on MATLAB & Simulink environment.
{"title":"Towards a Novel MATLAB Framework for VANETs Simulation","authors":"Ahmed Ibrahim Abdelaal, M. Ghoneima, Bassem A. Abdullah","doi":"10.1109/ICM52667.2021.9664959","DOIUrl":"https://doi.org/10.1109/ICM52667.2021.9664959","url":null,"abstract":"Vehicular Ad-hoc Networks (VANETs) are getting significant research attention to achieve road safety and limit the increasing number of car accidents caused by high density of vehicles on roads. Besides, modern vehicles are equipped with sensors, cameras, and on-board units that capable of communication with other vehicles, VANETs make use of these capabilities leading to the evolve of new applications and services. Testing vehicular networks protocols and applications requires special attention, since field operational testing is very expensive and even not practical for large scale networks, the software simulation tools are considered to be the best choice to test vehicular ad-hoc networks. In this paper, we will shed light on the most recent advances in vehicular network simulation, we will compare between two modern frameworks that represents state of art VANET simulators, upon this comparison we will suggest a new VANETs simulator framework based on MATLAB & Simulink environment.","PeriodicalId":212613,"journal":{"name":"2021 International Conference on Microelectronics (ICM)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126370295","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 : 2021-12-19DOI: 10.1109/ICM52667.2021.9664928
Asma Wasfi, M. Atef, F. Awwad
Lately, molybdenum disulfide (MoS2) has drawn massive interest in the biomolecular detection field due to its notable optoelectronic characteristics and its wide surface area. Here, we study a novel monolayer MoS2 sensor with gold electrodes where a nanopore is placed in the middle of the MoS2 sheet which enables quick, selective, and sensitive DNA nucleobase detection. The MoS2 sensor exhibits distinguishable electronic properties for the different DNA nucleobases (Cytosine, Adenine, Thymine, and Guanine). Non-equilibrium Green’s function integrated with density functional theory is utilized to inspect the detection mechanism. This research can promote a novel sensing platform utilizing MoS2.
{"title":"First-Principles Modeling for DNA Bases via Monolayer MoS2 Sensor with a Nanopore","authors":"Asma Wasfi, M. Atef, F. Awwad","doi":"10.1109/ICM52667.2021.9664928","DOIUrl":"https://doi.org/10.1109/ICM52667.2021.9664928","url":null,"abstract":"Lately, molybdenum disulfide (MoS2) has drawn massive interest in the biomolecular detection field due to its notable optoelectronic characteristics and its wide surface area. Here, we study a novel monolayer MoS2 sensor with gold electrodes where a nanopore is placed in the middle of the MoS2 sheet which enables quick, selective, and sensitive DNA nucleobase detection. The MoS2 sensor exhibits distinguishable electronic properties for the different DNA nucleobases (Cytosine, Adenine, Thymine, and Guanine). Non-equilibrium Green’s function integrated with density functional theory is utilized to inspect the detection mechanism. This research can promote a novel sensing platform utilizing MoS2.","PeriodicalId":212613,"journal":{"name":"2021 International Conference on Microelectronics (ICM)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125271715","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 : 2021-12-19DOI: 10.1109/ICM52667.2021.9664912
Ahmed Omar Elgharib, M. Alhasheem, R. Swief, A. Naamane
PI Controller integrating genetic algorithm has a great impact on the efficiency and the performance of the wind turbine applications and their whole system. This paper proposes generating the optimized power utilizing wind turbine. A boost converter is connected to the turbine in order to get the proper output voltage. The boost converter has been controlled using Maximum power point tracking (MPPT) control strategy. This paper discusses three parts: first part is the steady state performance which is validated for the studied system, the studied system can produce output power that varies depends on the rated wind speed, rotor diameter of the wind turbine, and the wind turbine generator rating. Second one is the effect of fault occurrence on the system. Third part is the efficiency enhancement based on the genetic algorithm used in such a system, and how it can improve the power output by reducing the transient state as much as possible at different operating ranges.
{"title":"Wind Turbine Performance Assessment Boost Converter Based Applying PI Controller Integrating Genetic Algorithm","authors":"Ahmed Omar Elgharib, M. Alhasheem, R. Swief, A. Naamane","doi":"10.1109/ICM52667.2021.9664912","DOIUrl":"https://doi.org/10.1109/ICM52667.2021.9664912","url":null,"abstract":"PI Controller integrating genetic algorithm has a great impact on the efficiency and the performance of the wind turbine applications and their whole system. This paper proposes generating the optimized power utilizing wind turbine. A boost converter is connected to the turbine in order to get the proper output voltage. The boost converter has been controlled using Maximum power point tracking (MPPT) control strategy. This paper discusses three parts: first part is the steady state performance which is validated for the studied system, the studied system can produce output power that varies depends on the rated wind speed, rotor diameter of the wind turbine, and the wind turbine generator rating. Second one is the effect of fault occurrence on the system. Third part is the efficiency enhancement based on the genetic algorithm used in such a system, and how it can improve the power output by reducing the transient state as much as possible at different operating ranges.","PeriodicalId":212613,"journal":{"name":"2021 International Conference on Microelectronics (ICM)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125289281","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 : 2021-12-19DOI: 10.1109/ICM52667.2021.9664950
C. Ukwuoma, Md Belal Bin Heyat, Mahmoud Masadeh, F. Akhtar, Zhi-Quang Qin, Emmanuel Bondzie-Selby, Omar Alshorman, Fahad Alkahtani
What distinguishes the field of artificial intelligence (AI) from others is to develop fully independent agents that learn optimal behavior, change, and evolve solely through the communication of trial and error with the surrounding environment. Reinforcement learning (RL) can be seen in multiple aspects of Machine Learning (ML), provided the environment, reward, actions, the state will be defined. Agent training in previous years is seen to only relate to robotics, games, and self-driving cars. While trying to divert the focus of researchers from the view of self-driving cars, games, robots, etc. Here, we investigated using reinforcement learning in the aspect of task completion. We deployed our architecture in an inpainting task where the agent generates the distorted or missing image content into an eminent fidelity completed the image by using reinforcement learning to influence the generative model utilized. The Generative Adversary Network (GAN) problem of not being steady and challenging to train was overwhelmed by utilizing latent space representation. The dimension is reduced compared to the distorted or corrupted image in training the GAN. Then reinforcement learning was deployed to pick the correct GAN input to get the image’s latent space representation that is most suitable for the current input of the missing or distorted image region. In this paper, we also learned that the trained agent enhances the accuracy in a classification task of images with missing data. We successfully examined the classification enhancement on images missing 30%, 50%, and 70%.
{"title":"Image Inpainting and Classification Agent Training Based on Reinforcement Learning and Generative Models with Attention Mechanism","authors":"C. Ukwuoma, Md Belal Bin Heyat, Mahmoud Masadeh, F. Akhtar, Zhi-Quang Qin, Emmanuel Bondzie-Selby, Omar Alshorman, Fahad Alkahtani","doi":"10.1109/ICM52667.2021.9664950","DOIUrl":"https://doi.org/10.1109/ICM52667.2021.9664950","url":null,"abstract":"What distinguishes the field of artificial intelligence (AI) from others is to develop fully independent agents that learn optimal behavior, change, and evolve solely through the communication of trial and error with the surrounding environment. Reinforcement learning (RL) can be seen in multiple aspects of Machine Learning (ML), provided the environment, reward, actions, the state will be defined. Agent training in previous years is seen to only relate to robotics, games, and self-driving cars. While trying to divert the focus of researchers from the view of self-driving cars, games, robots, etc. Here, we investigated using reinforcement learning in the aspect of task completion. We deployed our architecture in an inpainting task where the agent generates the distorted or missing image content into an eminent fidelity completed the image by using reinforcement learning to influence the generative model utilized. The Generative Adversary Network (GAN) problem of not being steady and challenging to train was overwhelmed by utilizing latent space representation. The dimension is reduced compared to the distorted or corrupted image in training the GAN. Then reinforcement learning was deployed to pick the correct GAN input to get the image’s latent space representation that is most suitable for the current input of the missing or distorted image region. In this paper, we also learned that the trained agent enhances the accuracy in a classification task of images with missing data. We successfully examined the classification enhancement on images missing 30%, 50%, and 70%.","PeriodicalId":212613,"journal":{"name":"2021 International Conference on Microelectronics (ICM)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128375031","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：