Egyptian Informatics Journal最新文献

{"title":"A resilient image encryption scheme using Laplace transform","authors":"Fariha Nawaz ,&nbsp;Saba Inam ,&nbsp;Shamsa Kanwal ,&nbsp;Shaha Al-Otaibi ,&nbsp;Fahima Hajjej","doi":"10.1016/j.eij.2024.100512","DOIUrl":"10.1016/j.eij.2024.100512","url":null,"abstract":"<div><p>The importance of image encryption in cryptography has surged due to advancement in image processing technology. Our research presents a novel image encryption technique using advanced image processing and permutation-based S-box generation. Utilizing a sine series expansion, we achieve a pseudorandom distribution of values applicable across various fields. Our systematic method for computing the Laplace transform of symbolic metrices ensures enhanced security. This study integrates core cryptographic principles: permutation, substitution, randomness, symbolic operations, and cyclic encryption. The proposed cryptosystem’s modular nature allows adaptability and customization for specific cryptographic needs, enhancing overall security. Our efforts to improve key generation, introduce randomness, and increase operational complexity drive advancements in secure cryptographic systems. Comprehensive analysis, including key sensitivity, key space, Information Entropy(IE), histogram correlation, Number of Pixel Change Rate (NPCR), Peak Signal Noise Ratio(PSNR), Unified Average Changing Intensity (UACI), and similarity assessments like Mean Square Error (MSE) and Structural Similarity Index Measure (SSIM),</p><p>Validate the efficiency of our encryption scheme. Our results surpass previous efforts, setting a new standard in cryptographic research excellence.</p></div>","PeriodicalId":56010,"journal":{"name":"Egyptian Informatics Journal","volume":null,"pages":null},"PeriodicalIF":5.0,"publicationDate":"2024-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1110866524000756/pdfft?md5=46ef0806ea8e66c0384a7443dd5c8322&pid=1-s2.0-S1110866524000756-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141954244","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"BSDN-HMTD: A blockchain supported SDN framework for detecting DDoS attacks using deep learning method","authors":"Parthasarathy Ramadass ,&nbsp;Raja shree Sekar ,&nbsp;Saravanan Srinivasan ,&nbsp;Sandeep Kumar Mathivanan ,&nbsp;Basu Dev Shivahare ,&nbsp;Saurav Mallik ,&nbsp;Naim Ahmad ,&nbsp;Wade Ghribi","doi":"10.1016/j.eij.2024.100515","DOIUrl":"10.1016/j.eij.2024.100515","url":null,"abstract":"<div><p>The surge in Distributed Denial of Service (DDoS) attacks within SDN environments demands more potent defense strategies. While Moving Target Defense (MTD) holds promise, current MTD approaches against DDoS suffer from security gaps due to overwhelming malicious traffic and static detection areas. In order to tackle these difficulties, we have implemented BSDN-HMTD, a combination of deep learning and blockchain technologies within SDN environments, as a framework. Our strategy starts by employing blockchain technology to authenticate users. We use the NTRU-based Nyberg Rueppel Digital Signature Algorithm for this purpose. This ensures that only authenticated user flows are allowed for validation and forwarding. Within the forwarding layer, Quantum Convolutional Neural Networks (QCNN) evaluate authentic flows by analyzing many characteristics, effectively differentiating between regular, malicious, and dubious flows. Utilizing an Enhanced Spotted Hyena Optimization (EHSO) method to activate switches in real-time modifies the vulnerable points of attack, so impeding attackers and simultaneously decreasing energy usage. The Forwarding Layer Organizer (FLO) oversees the detection of possible attacker surveillance activities and transmits the collected information to local controllers in the control layer. The controllers, functioning in a structured controller network, carry out proactive Moving Target Defense (MTD) techniques, such as host virtual IP hopping, which make attacker plans more complex and raise their operational expenses. Reactive MTD actions are implemented based on the results of flow validation. These actions utilize techniques such as secure honeypots and host virtual IP hopping to effectively prevent attacks. The blockchain securely logs all processed data related to packet validation, authentication, and honeypot activities to ensure the protection of data privacy. Our studies, conducted using Network Simulator-3.26 (NS-3.26), show that our proposed framework outperforms existing techniques in terms of several validation criteria.</p></div>","PeriodicalId":56010,"journal":{"name":"Egyptian Informatics Journal","volume":null,"pages":null},"PeriodicalIF":5.0,"publicationDate":"2024-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1110866524000781/pdfft?md5=106b56b65cce02c0e4993fa51d38b93a&pid=1-s2.0-S1110866524000781-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141948021","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A multi-dimensional framework for improving data reliability in mobile crowd sensing","authors":"Xu Wu ,&nbsp;Yanjun Song ,&nbsp;Junyu Lai","doi":"10.1016/j.eij.2024.100518","DOIUrl":"10.1016/j.eij.2024.100518","url":null,"abstract":"<div><p>Mobile Crowd Sensing (MCS) has become a promising new data perception paradigm. It is to be able to easily submit the wrong or untrusted data for the malicious attackers in such an environment. This greatly affects the normal operation of the MCS system and the authenticity of task results. Therefore, ensuring the reliability of data is becoming a key research direction in MCS, especially for real-time application scenarios. For this purpose, we propose a multi-dimensional framework for improving data reliability, named MDF. It integrates three dimensions of temporal, spatial context and sensing measurement. Through a series of experiments, it is demonstrated that MDF outperforms existing methods.</p></div>","PeriodicalId":56010,"journal":{"name":"Egyptian Informatics Journal","volume":null,"pages":null},"PeriodicalIF":5.0,"publicationDate":"2024-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1110866524000811/pdfft?md5=69e804913e36635105f08137f4248f43&pid=1-s2.0-S1110866524000811-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141948022","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unmasking vulnerabilities by a pioneering approach to securing smart IoT cameras through threat surface analysis and dynamic metrics","authors":"Akashdeep Bhardwaj ,&nbsp;Salil Bharany ,&nbsp;Ashraf Osman Ibrahim ,&nbsp;Ahmad Almogren ,&nbsp;Ateeq Ur Rehman ,&nbsp;Habib Hamam","doi":"10.1016/j.eij.2024.100513","DOIUrl":"10.1016/j.eij.2024.100513","url":null,"abstract":"<div><p>The concept of the Internet of Things (IoT) threat surface refers to the overall susceptibility of smart devices to potential security risks. This vulnerability includes the combined impact of security weaknesses, gaps in protective measures, and potential vulnerabilities within the device OS, installed libraries, and applications, as well as the infrastructure involved. This comprises both identified and unforeseen risks that could potentially compromise the device’s integrity, data, logs, and hosted applications. By minimizing the extent to which the device’s components are exposed, it becomes possible to reduce the vulnerabilities inherent in the device, thereby decreasing its overall threat surface area. This research introduces an innovative framework for assessing Smart IoT cameras within the ecosystem. This framework involves the identification and categorization of webcam devices, followed by an analysis of potential threats based on various exposure indicators present within each layer. Subsequently, this information is used to determine the possible paths through which a device might be compromised, allowing for the evaluation of severity and both maturity levels. The authors present metrics that aid in reevaluating and recalibrating the security levels, considering the discovered threat surface elements. These refined metrics offer a fresh perspective on security, offering valuable insights for stakeholders who are engaged in the development, deployment, and evaluation of the security aspects of such devices.</p></div>","PeriodicalId":56010,"journal":{"name":"Egyptian Informatics Journal","volume":null,"pages":null},"PeriodicalIF":5.0,"publicationDate":"2024-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1110866524000768/pdfft?md5=a88d28a79564d629367219812b967ee0&pid=1-s2.0-S1110866524000768-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141948024","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Blockchain-supported online banking scheme","authors":"Chien-Hua Tsai ,&nbsp;Dah-Kwei Liou ,&nbsp;Hsiu-Li Lee","doi":"10.1016/j.eij.2024.100516","DOIUrl":"10.1016/j.eij.2024.100516","url":null,"abstract":"<div><p>Online banking not merely enables customers to make transactions within a short time and access transactional information anywhere but also facilitates financial institutions to simplify transaction procedures and reduce their operating expenses. Common concerns by both customers and financial institutions are the secure authentication measures for protecting sensitive financial information from cybersecurity threats and maintaining their trust in a secure environment. This paper presents a blockchain-supported scheme to establish secure authentication and mutual trust for handling online banking processes. The proposed solution’s model design, inference process, proof method, security analysis, and performance evaluation are included in this study. With the decentralized applications and smart contracts, that benefit from disruptive innovations in blockchain technology, the proposed scheme enables financial institutions to provide efficient, immutable, transparent, and secure online financial services for customers. In addition, the computational efforts of the proposed solution show that high performance can be achieved in executing financial transactions while safeguarding sensitive data and retaining trust in a decentralized environment which is some of the most significant weak security of the existing authentication schemes for online banking platforms.</p></div>","PeriodicalId":56010,"journal":{"name":"Egyptian Informatics Journal","volume":null,"pages":null},"PeriodicalIF":5.0,"publicationDate":"2024-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1110866524000793/pdfft?md5=38c266d4181a770d317d945cf02d397f&pid=1-s2.0-S1110866524000793-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141948023","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"YOLO-HyperVision: A vision transformer backbone-based enhancement of YOLOv5 for detection of dynamic traffic information","authors":"Shizhou Xu,&nbsp;Mengjie Zhang ,&nbsp;Jingyu Chen,&nbsp;Yiming Zhong","doi":"10.1016/j.eij.2024.100523","DOIUrl":"10.1016/j.eij.2024.100523","url":null,"abstract":"<div><p>With the increase of traffic flow in modern urban areas, traffic congestion has become a serious problem that affects people’s normal production and life. Using target detection technology instead of manual labor can quickly detect the road traffic situation and provide timely information about the traffic flow. However, when using drones to observe the traffic flow in the air, the perspective effect will cause the detected vehicles and pedestrians to be very small, and the scale difference between different categories of targets is large, which increases the detection difficulty of a single convolutional neural network model. In order to solve the problem of low accuracy of traditional single-stage target detection models, this study proposes an improved Yolov5 vehicle target detection model with Vision Transformer (VIT) backbone, You Only Look Once-HyperVision (YOLO-HV), which aims to solve the problem of poor multi-scale target recognition performance caused by the inability of traditional CNN networks to integrate contextual information, and help drones achieve more efficient and accurate traffic flow recognition functions. This study deeply integrates the Vision Transformer (VIT) backbone and Convolutional Neural Network (CNN), effectively combining the multi-scale detection advantages of Vision Transformer and the inductive bias ability of Convolutional Neural Network, and adds multi-scale residual modules and context correlation enhancement modules, which greatly improves the recognition accuracy of single-stage detectors for drone images. Through comparative experiments on the VisDrone dataset, it is found that the detection performance of this model is improved compared with several commonly used detection models. YOLO-HV can increase the mean average precision (mAP) by 3.3% compared with the pure convolutional network of the same model size. YOLO-HV model has achieved excellent performance in the task of traffic flow image detection taken by drones, and can more accurately identify and classify road vehicles than various target detection models.</p></div>","PeriodicalId":56010,"journal":{"name":"Egyptian Informatics Journal","volume":null,"pages":null},"PeriodicalIF":5.0,"publicationDate":"2024-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1110866524000860/pdfft?md5=50b127ef84d8fdf25c77f2d161914ee0&pid=1-s2.0-S1110866524000860-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141962489","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Proactive threat hunting to detect persistent behaviour-based advanced adversaries","authors":"Akashdeep Bhardwaj ,&nbsp;Salil Bharany ,&nbsp;Ahmad Almogren ,&nbsp;Ateeq Ur Rehman ,&nbsp;Habib Hamam","doi":"10.1016/j.eij.2024.100510","DOIUrl":"10.1016/j.eij.2024.100510","url":null,"abstract":"<div><p>Persistence behavior is a tactic advanced adversaries use to maintain unauthorized access and control of compromised assets over extended periods. Organizations can efficiently detect persistent adversaries and reduce the growing risks posed by highly skilled cyber threats by embracing creative techniques and utilizing sophisticated tools. By taking a proactive stance, businesses may increase their entire cybersecurity posture by anticipating and mitigating possible risks before they escalate. Security analysts perform thorough investigations and extract meaningful insights from large datasets with greater technical advantage by using Elasticsearch in conjunction with a variety of linguistic tools. This research presents a novel methodology for proactive threat intelligence to identify and mitigate advanced adversaries that use persistent behaviors. The authors designed and set up an Elasticsearch-based advanced Security Information and Event Management platform to offer a proactive threat-hunting strategy. This enables comprehensive analysis and detection by integrating Lucene, Kibana, and domain-specific languages. The goal of this research is to locate hidden advanced enemies who exhibit persistent behavior during cyberattacks. The framework can help improve the organization’s resilience to identify and respond to threats by closely examining activities like boot or logon auto-start execution in registry keys, tampering with system processes and services, and unauthorized creation of local accounts on compromised assets. This study emphasizes proactive actions over reactive reactions, which advances danger detection techniques. This technical study provides security practitioners seeking to improve defenses against new advanced attacks to stay ahead in a dynamic threat landscape.</p></div>","PeriodicalId":56010,"journal":{"name":"Egyptian Informatics Journal","volume":null,"pages":null},"PeriodicalIF":5.0,"publicationDate":"2024-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1110866524000732/pdfft?md5=5d43ebeef057712932891f9a0b45f511&pid=1-s2.0-S1110866524000732-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141952094","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"‘Retraction notice to “ODRNN: Optimized deep recurrent neural networks for automatic detection of leukaemia” [Egypt. Inform. J. 26 (2024) 100453]’","authors":"K. Dhana Shree ,&nbsp;S. Logeswari","doi":"10.1016/j.eij.2024.100506","DOIUrl":"10.1016/j.eij.2024.100506","url":null,"abstract":"","PeriodicalId":56010,"journal":{"name":"Egyptian Informatics Journal","volume":null,"pages":null},"PeriodicalIF":5.0,"publicationDate":"2024-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1110866524000690/pdfft?md5=f4c6447b293e61bde85052f39b49a908&pid=1-s2.0-S1110866524000690-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141948025","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A hybrid contextual framework to predict severity of infectious disease: COVID-19 case study","authors":"M. Mehran Bin Azam ,&nbsp;Fahad Anwaar ,&nbsp;Adil Mehmood Khan ,&nbsp;Muhammad Anwar ,&nbsp;Hadhrami Bin Ab Ghani ,&nbsp;Taiseer Abdalla Elfadil Eisa ,&nbsp;Abdelzahir Abdelmaboud","doi":"10.1016/j.eij.2024.100508","DOIUrl":"10.1016/j.eij.2024.100508","url":null,"abstract":"<div><p>Infectious disease is a particular type of disorder triggered by organisms and transmitted directly or indirectly from an infected one like COVID-19. The global economy and public health are immensely affected by COVID-19, a recently emerging infectious disease. Artificial Intelligence can be helpful to predict the severity rating of COVID-19 which assists authorities to take appropriate measures to mitigate its spread in different regions, hence it results in economic reopening and reduces the degree of mortality. In this paper, a hybrid contextual framework is proposed which incorporates content embedding of Standard Operating Procedure’s (SOPs) auxiliary description along with COVID-19 temporal features of the respective region as side information. The word embedding techniques are incorporated to generate distributed representation of SOPs auxiliary description. The higher representation of auxiliary description is obtained by utilizing content embedding and then combined with temporal features to build counties profiles. These county profiles are fed into a profile learner based on an ensemble algorithm to predict the severity level of COVID-19 in different regions. The proposed contextual framework is evaluated on public datasets provided by healthdata.gov and the National Centers for Environmental Information. A comparison of the proposed contextual framework with other state-of-the-art approaches has demonstrated its ability to accurately predict the severity level of COVID-19 in different regions.</p></div>","PeriodicalId":56010,"journal":{"name":"Egyptian Informatics Journal","volume":null,"pages":null},"PeriodicalIF":5.0,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1110866524000719/pdfft?md5=45d14bdeb53bb3adf53255b853a0e964&pid=1-s2.0-S1110866524000719-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141952093","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A single-individual based variable neighborhood search algorithm for the blocking hybrid flow shop group scheduling problem","authors":"Zhongyuan Peng ,&nbsp;Haoxiang Qin","doi":"10.1016/j.eij.2024.100509","DOIUrl":"10.1016/j.eij.2024.100509","url":null,"abstract":"<div><p>The Blocking Hybrid Flow Shop Group Scheduling Problem (BHFGSP) is prevalent within the manufacturing industry, where the ordering of groups poses a significant challenge for dispatchers. Moreover, the blocking constraints associated with jobs significantly influence energy consumption, yet these constraints are often overlooked in algorithm design. To address these issues effectively, a single-individual-based variable neighborhood search strategy is introduced. For the challenge of group ordering, a group-based neighborhood search strategy is proposed. This strategy is complemented by a job-based neighborhood search strategy to tackle the issues of blocking and job sequencing. These two neighborhood search strategies are designed to enhance the performance of the algorithm significantly. Furthermore, to augment the local search abilities of the proposed algorithm, the concept of a single-individual approach from the iterated greedy algorithm is integrated. The performance of the proposed algorithm is validated through 36 instances, demonstrating its efficiency in solving BHFGSPs compared to state-of-the-art algorithms. Notably, the proposed algorithm achieves a reduction in energy consumption by an average of 58% to 63.4% compared to previous best solutions.</p></div>","PeriodicalId":56010,"journal":{"name":"Egyptian Informatics Journal","volume":null,"pages":null},"PeriodicalIF":5.0,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1110866524000720/pdfft?md5=86d11b8fb46e088f06d359540af8c42e&pid=1-s2.0-S1110866524000720-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141948026","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}