Deepfake is a sort of fake media made by advanced AI methods like Generative Adversarial Networks(GANs).Deepfake technology has many useful uses in education and entertainment,but it also raises a lot of ethical,socia...Deepfake is a sort of fake media made by advanced AI methods like Generative Adversarial Networks(GANs).Deepfake technology has many useful uses in education and entertainment,but it also raises a lot of ethical,social,and security issues,such as identity theft,the dissemination of false information,and privacy violations.This study seeks to provide a comprehensive analysis of several methods for identifying and circumventing Deepfakes,with a particular focus on image-based Deepfakes.There are three main types of detection methods:classical,machine learning(ML)and deep learning(DL)-based,and hybrid methods.There are three main types of preventative methods:technical,legal,and moral.The study investigates the effectiveness of several detection approaches,such as convolutional neural networks(CNNs),frequency domain analysis,and hybrid CNN-LSTM models,focusing on the respective advantages and disadvantages of each method.We also look at new technologies like Explainable Artificial Intelligence(XAI)and blockchain-based frameworks.The essay looks at the use of algorithmic protocols,watermarking,and blockchain-based content verification as possible ways to stop certain things from happening.Recent advancements,including adversarial training and anti-Deepfake data generation,are essential because of their potential to alleviate rising concerns.This reviewshows that there aremajor problems,such as the difficulty of improving the capabilities of existing systems,the high running expenses,and the risk of being attacked by enemies.It stresses the importance of working together across fields,including academia,business,and government,to create robust,scalable,and ethical solutions.Themain goals of futurework should be to create lightweight,real-timedetection systems,connect them to large language models(LLMs),and put in place worldwide regulatory frameworks.This essay argues for a complete and varied plan to keep digital information real and build confidence in a time when media is driven by artificial intelligence.It uses both technical and non-technical means.展开更多
Improving the quality assurance (QA) processes and acquiring accreditation are top priorities for academic programs. The learning outcomes (LOs)assessment and continuous quality improvement represent core components o...Improving the quality assurance (QA) processes and acquiring accreditation are top priorities for academic programs. The learning outcomes (LOs)assessment and continuous quality improvement represent core components ofthe quality assurance system (QAS). Current assessment methods suffer deficiencies related to accuracy and reliability, and they lack well-organized processes forcontinuous improvement planning. Moreover, the absence of automation, andintegration in QA processes forms a major obstacle towards developing efficientquality system. There is a pressing need to adopt security protocols that providerequired security services to safeguard the valuable information processed byQAS as well. This research proposes an effective methodology for LOs assessment and continuous improvement processes. The proposed approach ensuresmore accurate and reliable LOs assessment results and provides systematic wayfor utilizing those results in the continuous quality improvement. This systematicand well-specified QA processes were then utilized to model and implement automated and secure QAS that efficiently performs quality-related processes. Theproposed system adopts two security protocols that provide confidentiality, integrity, and authentication for quality data and reports. The security protocols avoidthe source repudiation, which is important in the quality reporting system. This isachieved through implementing powerful cryptographic algorithms. The QASenables efficient data collection and processing required for analysis and interpretation. It also prepares for the development of datasets that can be used in futureartificial intelligence (AI) researches to support decision making and improve thequality of academic programs. The proposed approach is implemented in a successful real case study for a computer science program. The current study servesscientific programs struggling to achieve academic accreditation, and gives rise tofully automating and integrating the QA processes and adopting modern AI andsecurity technologies to develop effective QAS.展开更多
Developing a high-performance public key cryptosystem is crucial for numerous modern security applications.The Elliptic Curve Cryptosystem(ECC)has performance and resource-saving advantages compared to other types of ...Developing a high-performance public key cryptosystem is crucial for numerous modern security applications.The Elliptic Curve Cryptosystem(ECC)has performance and resource-saving advantages compared to other types of asymmetric ciphers.However,the sequential design implementation for ECC does not satisfy the current applications’performance requirements.Therefore,several factors should be considered to boost the cryptosystem performance,including the coordinate system,the scalar multiplication algo-rithm,and the elliptic curve form.The tripling-oriented(3DIK)form is imple-mented in this work due to its minimal computational complexity compared to other elliptic curves forms.This experimental study explores the factors playing an important role in ECC performance to determine the best combi-nation that leads to developing high-speed ECC.The proposed cryptosystem uses parallel software implementation to speed up ECC performance.To our knowledge,previous studies have no similar software implementation for 3DIK ECC.Supported by using parallel design,projective coordinates,and a fast scalar multiplication algorithm,the proposed 3DIK ECC improved the speed of the encryption process compared with other counterparts and the usual sequential implementation.The highest performance level for 3DIK ECC was achieved when it was implemented using the Non-Adjacent Form algorithm and homogenous projection.Compared to the costly hardware implementations,the proposed software implementation is cost effective and can be easily adapted to other environments.In addition,the power con-sumption of the proposed ECC is analyzed and compared with other known cryptosystems.thus,the current study presents a detailed overview of the design and implementation of 3DIK ECC.展开更多
基金funded by the Arab Open University,Riyadh,Saudi Arabia.
文摘Deepfake is a sort of fake media made by advanced AI methods like Generative Adversarial Networks(GANs).Deepfake technology has many useful uses in education and entertainment,but it also raises a lot of ethical,social,and security issues,such as identity theft,the dissemination of false information,and privacy violations.This study seeks to provide a comprehensive analysis of several methods for identifying and circumventing Deepfakes,with a particular focus on image-based Deepfakes.There are three main types of detection methods:classical,machine learning(ML)and deep learning(DL)-based,and hybrid methods.There are three main types of preventative methods:technical,legal,and moral.The study investigates the effectiveness of several detection approaches,such as convolutional neural networks(CNNs),frequency domain analysis,and hybrid CNN-LSTM models,focusing on the respective advantages and disadvantages of each method.We also look at new technologies like Explainable Artificial Intelligence(XAI)and blockchain-based frameworks.The essay looks at the use of algorithmic protocols,watermarking,and blockchain-based content verification as possible ways to stop certain things from happening.Recent advancements,including adversarial training and anti-Deepfake data generation,are essential because of their potential to alleviate rising concerns.This reviewshows that there aremajor problems,such as the difficulty of improving the capabilities of existing systems,the high running expenses,and the risk of being attacked by enemies.It stresses the importance of working together across fields,including academia,business,and government,to create robust,scalable,and ethical solutions.Themain goals of futurework should be to create lightweight,real-timedetection systems,connect them to large language models(LLMs),and put in place worldwide regulatory frameworks.This essay argues for a complete and varied plan to keep digital information real and build confidence in a time when media is driven by artificial intelligence.It uses both technical and non-technical means.
基金Author extends his appreciation to the Deanship of Scientific Research at Imam Mohammad Ibn Saud Islamic University for funding and supporting this work through Graduate Student Research Support Program.
文摘Improving the quality assurance (QA) processes and acquiring accreditation are top priorities for academic programs. The learning outcomes (LOs)assessment and continuous quality improvement represent core components ofthe quality assurance system (QAS). Current assessment methods suffer deficiencies related to accuracy and reliability, and they lack well-organized processes forcontinuous improvement planning. Moreover, the absence of automation, andintegration in QA processes forms a major obstacle towards developing efficientquality system. There is a pressing need to adopt security protocols that providerequired security services to safeguard the valuable information processed byQAS as well. This research proposes an effective methodology for LOs assessment and continuous improvement processes. The proposed approach ensuresmore accurate and reliable LOs assessment results and provides systematic wayfor utilizing those results in the continuous quality improvement. This systematicand well-specified QA processes were then utilized to model and implement automated and secure QAS that efficiently performs quality-related processes. Theproposed system adopts two security protocols that provide confidentiality, integrity, and authentication for quality data and reports. The security protocols avoidthe source repudiation, which is important in the quality reporting system. This isachieved through implementing powerful cryptographic algorithms. The QASenables efficient data collection and processing required for analysis and interpretation. It also prepares for the development of datasets that can be used in futureartificial intelligence (AI) researches to support decision making and improve thequality of academic programs. The proposed approach is implemented in a successful real case study for a computer science program. The current study servesscientific programs struggling to achieve academic accreditation, and gives rise tofully automating and integrating the QA processes and adopting modern AI andsecurity technologies to develop effective QAS.
文摘Developing a high-performance public key cryptosystem is crucial for numerous modern security applications.The Elliptic Curve Cryptosystem(ECC)has performance and resource-saving advantages compared to other types of asymmetric ciphers.However,the sequential design implementation for ECC does not satisfy the current applications’performance requirements.Therefore,several factors should be considered to boost the cryptosystem performance,including the coordinate system,the scalar multiplication algo-rithm,and the elliptic curve form.The tripling-oriented(3DIK)form is imple-mented in this work due to its minimal computational complexity compared to other elliptic curves forms.This experimental study explores the factors playing an important role in ECC performance to determine the best combi-nation that leads to developing high-speed ECC.The proposed cryptosystem uses parallel software implementation to speed up ECC performance.To our knowledge,previous studies have no similar software implementation for 3DIK ECC.Supported by using parallel design,projective coordinates,and a fast scalar multiplication algorithm,the proposed 3DIK ECC improved the speed of the encryption process compared with other counterparts and the usual sequential implementation.The highest performance level for 3DIK ECC was achieved when it was implemented using the Non-Adjacent Form algorithm and homogenous projection.Compared to the costly hardware implementations,the proposed software implementation is cost effective and can be easily adapted to other environments.In addition,the power con-sumption of the proposed ECC is analyzed and compared with other known cryptosystems.thus,the current study presents a detailed overview of the design and implementation of 3DIK ECC.
