检索结果-内蒙古大学图书馆

A Systematic Literature Review on the Security Attacks and Countermeasures Used in Graphical Passwords

IEEE Access 2024年 12卷 53408-53423页

作者： Por, Lip Yee Ng, Ian Ouii Chen, Yen-Lin Yang, Jing Ku, Chin Soon Universiti Malaya Faculty of Computer Science and Information Technology Department of Computer System and Technology Kuala Lumpur50603 Malaysia National Taipei University of Technology Department of Computer Science and Information Engineering Taipei106344 Taiwan Universiti Tunku Abdul Rahman Department of Computer Science Kampar31900 Malaysia

This systematic literature review delves into the dynamic realm of graphical passwords, focusing on the myriad security attacks they face and the diverse countermeasures devised to mitigate these threats. The core objective of this paper is to identify existing security threats to graphical password schemes and the corresponding countermeasures developed to mitigate these attacks. The study process begins by identifying the usable databases and search engines to identify all the relevant resources. The inclusion and exclusion criteria were carefully selected to prioritize the study, focusing mostly on attacks and countermeasures related to graphical password schemes between 2009 and 2023. After thorough identification and selection progress, 59 studies met all the criteria. Among these studies, 47 mentioned shoulder surfing as a threat to graphical password schemes, while 20 discussed brute force attacks. Additionally, there were 21 papers on dictionary attacks, 13 on smudge attacks, spyware attacks, and social engineering, and 19 that discussed guessing attacks as threats to graphical password schemes. Furthermore, the papers identified several other attacks, including frequency of occurrence analysis attacks, video recording, eavesdropping, computer vision, sonar, and image gallery attacks, with the corresponding numbers of papers being 9, 17, 5, 2, 2, and 1, respectively. The results also highlight the countermeasures proposed in the study papers to mitigate the aforementioned attacks. Among the various countermeasures identified, most revolve around randomization, obfuscation, and password space complexity as the most commonly used techniques for enhancing the security of graphical password schemes. © 2013 IEEE.

关键词： Authentication

来源：评论

学校读者我要写书评

暂无评论

Advancing Bankruptcy Forecasting With Hybrid Machine Learning Techniques: Insights From an Unbalanced Polish Dataset

引用

IEEE Access 2024年 12卷 9369-9381页

作者： Ainan, Ummey Hany Por, Lip Yee Chen, Yen-Lin Yang, Jing Ku, Chin Soon Universiti Malaya Faculty of Computer Science and Information Technology Department of Computer System and Technology Kuala Lumpur50603 Malaysia National Taipei University of Technology Department of Computer Science and Information Engineering Taipei106344 Taiwan Universiti Tunku Abdul Rahman Department of Computer Science Kampar31900 Malaysia

The challenge of bankruptcy prediction, critical for averting financial sector losses, is amplified by the prevalence of imbalanced datasets, which often skew prediction models. Addressing this, our study introduces the innovative hybrid model XGBoost+ANN, designed to leverage the strengths of both ensemble learning and artificial neural networks. This model integrates a comprehensive set of features with parameters optimized through genetic algorithms, eschewing traditional feature selection approaches. Our research focuses on an unbalanced dataset of Polish companies and reveals that the XGBoost+ANN model, in particular, exhibits outstanding performance. Optimized using genetic algorithms and without feature selection, this model achieved the highest AUC (0.958), sensitivity (0.752), and accuracy (0.983) scores, surpassing other models in our study. This remarkable outperformance, along with the robust results, marks a substantial advancement in the field of bankruptcy prediction. It underscores the efficacy of our approach in addressing the persistent challenge of data imbalance, offering a more reliable and accurate solution for financial risk assessment. © 2013 IEEE.

关键词： Feature extraction

来源：评论

学校读者我要写书评

暂无评论

A Review of Wearable Devices for Affective Computing 2

A Review of Wearable Devices for Affective Computing

引用

2nd International Conference on Advancements in Smart, Secure and Intelligent Computing, ASSIC 2024

作者： MacHhi, Vilas S. Shah, Apurva M. The Maharaja Sayajirao University of Baroda Faculty of Technology & Engineering Computer Science & Engineering Department Vadodara India

ISBN: (纸本)9798350370188

Wearable technology is expanding rapidly in recent year. It is used in many applications in various domains, including affective computing. Affective computing is all about understanding and responding to human emotions. This paper will give an overview of a wearable device that was developed specifically for affective computing. It aims to increase the way we can understand user's emotions and allow for more personalized experiences based on their context. Multiple sensors and algorithms work together in this device to capture, analyze, and interpret our feelings through physical or behavioral signals. It can be worn as a smart-watch, wristband, or integrated into clothing or accessories. The device communicates wirelessly with a companion application installed on a smart-phone or a connected device, providing real-time feedback and insights about the user's emotional state. © 2024 IEEE.

关键词： Human computer interaction

来源：评论

学校读者我要写书评

暂无评论

Intrusion Detection Based on Bidirectional Long Short-Term Memory with Attention Mechanism

引用

computers, Materials & Continua 2023年第1期74卷 801-815页

作者： Yongjie Yang Shanshan Tu Raja Hashim Ali Hisham Alasmary Muhammad Waqas Muhammad Nouman Amjad Engineering Research Center of Intelligent Perception and Autonomous Control Faculty of Information TechnologyBeijing University of TechnologyBeijing100124China Faculty of Computer Science and Engineering GIK Institute of Engineering Sciences and TechnologyTopi23460Pakistan Department of Computer Science College of Computer ScienceKing Khalid UniversityAbhaSaudi Arabia Information Security and Cybersecurity Unit King Khalid UniversityAbhaSaudi Arabia Computer Engineering Department College of Information TechnologyUniversity of Bahrain32038Bahrain School of Engineering Edith Cowan UniversityJoondalup PerthWA6027Australia School of Engineering University of Management and TechnologyLahorePakistan

With the recent developments in the Internet of Things(IoT),the amount of data collected has expanded tremendously,resulting in a higher demand for data storage,computational capacity,and real-time processing *** computing has traditionally played an important role in establishing ***,fog computing has recently emerged as a new field complementing cloud computing due to its enhanced mobility,location awareness,heterogeneity,scalability,low latency,and geographic ***,IoT networks are vulnerable to unwanted assaults because of their open and shared *** a result,various fog computing-based security models that protect IoT networks have been developed.A distributed architecture based on an intrusion detection system(IDS)ensures that a dynamic,scalable IoT environment with the ability to disperse centralized tasks to local fog nodes and which successfully detects advanced malicious threats is *** this study,we examined the time-related aspects of network traffic *** presented an intrusion detection model based on a twolayered bidirectional long short-term memory(Bi-LSTM)with an attention mechanism for traffic data classification verified on the UNSW-NB15 benchmark *** showed that the suggested model outperformed numerous leading-edge Network IDS that used machine learning models in terms of accuracy,precision,recall and F1 score.

关键词： Fog computing intrusion detection bi-LSTM attention mechanism

来源：评论

学校读者我要写书评

暂无评论

Incentivizing Recycling Behavior: Repro-A Reward Based CNN-Enabled Framework for Smart Waste Collection

Incentivizing Recycling Behavior: Repro-A Reward Based CNN-E...

引用

2024 International Conference on engineering and Computing, ICECT 2024

作者： Irfan, Haider Arshad, Usama Anwer, Hammad Ghulam Ishaq Khan Institute of Engineering Sciences and Technology Faculty of Computer Science and Engineering Topi Pakistan

ISBN: (纸本)9798350349719

Efficient waste management together with certain measures to promote the recycling process are essential for over-coming global environmental issues. In this study, we describe Repro an app, which is targeted at transforming how we collect waste and recycle by integrating CNN technology and a reward-based system. Users, with the Repro app, take pictures of any trash they discard and rely on the underlying CNN model to identify the type of trash correctly. If a user's trash accumulation reaches beyond a given limit the system sends a notification to the trash collectors via the riders app to direct for a timely waste collection. User tokens are provided to users after trash collection, which can be redeemed within the Repro app for various product items and coupons. Moreover, this motivating approach encourages responsible waste management which goes along with the development of environmental custodianship among users. We describe the technical implementation of the CNN-based framework, assess the performance of the level of waste classification accuracy, and predict the behavioral implications of the reward system on recycling behavior. The study illustrates that Repro is a scalable solution for smarter waste collection and recycling endeavors, consequently creating a more eco-minded and sustainable environment. © 2024 IEEE.

关键词： Waste management

来源：评论

学校读者我要写书评

暂无评论

DialTest-EA: An Enhanced Fuzzing Approach With Energy Adjustment for Dialogue Systems via Metamorphic Testing

DialTest-EA: An Enhanced Fuzzing Approach With Energy Adjust...

引用

作者： Chen, Haibo Chen, Jinfu Wu, Yucheng Cai, Saihua Ahmad, Bilal Huang, Rubing Wang, Shengran Zhang, Chi School of Computer Science and Communication Engineering Jiangsu Key Laboratory of Security Technology Industrial Cyberspace Jiangsu University Zhenjiang China School of Computer Science and Engineering Faculty of Innovation Engineering Macau University of Science and Technology China

Deep neural networks (DNNs) possess potent feature learning capability, enabling them to comprehend natural language, which strongly support developing dialogue systems. However, dialogue systems usually perform incorrect behaviours in some corner cases, which may cause misunderstanding or economic loss. To test and debug dialogue systems, a popular fuzzing framework by metamorphic testing with Gini impurity guidance is proposed, namely, DialTest. However, DialTest treats all seeds (the initial test inputs to generate the mutated test inputs) equally during the fuzzing process and does not differentiate seeds, resulting in a certain limitation to its incorrect behaviour detection capability. In this paper, we propose to enhance the DialTest by applying a lightweight energy adjustment strategy called DialTest with Energy Adjustment (DialTest-EA). DialTest-EA employs the ant colony optimization algorithm (ACO) to adjust the mutation energy of each seed adaptively, ensuring that potential seeds have more opportunities to generate subsequent test inputs. To evaluate the effectiveness of the proposed DialTest-EA, we conduct a series of comparisons with the original DialTest and random mutation strategy. The experimental results show that the proposed DialTest-EA outperforms the compared methods both in the intent detection and slot filling tasks. Compared with the original DialTest, the intent detection accuracy of generated test cases by the proposed method is reduced by more than 14%, and the slot filling accuracy is reduced by more than 8%. © 2024 John Wiley & Sons Ltd.

关键词： Ant colony optimization

来源：评论

学校读者我要写书评

暂无评论

Malicious Activity Monitoring and Preventing in WSN Using Network Screening 5th

Malicious Activity Monitoring and Preventing in WSN Using Ne...

引用

5th International Conference on Trends in Computational and Cognitive engineering, TCCE 2023

作者： Dwivedi, Pushpendra Raghuvanshi, C.S. Sharan, Hari Om Department of Computer Science and Engineering Faculty of Engineering and Technology Rama University Uttar Pradesh Kanpur India

ISBN: (纸本)9789819719228

Wireless sensor network is a rapidly growing and challenging field as they are constrained by energy utilization, computation cost, network capacity, and security. Hence conventional network security schemes cannot be employed in it. The lightweight and low-capability sensors raise the risk of unauthorized communication access. In the communication phase, security risks including routing malicious activity (blackhole, grayhole), undesired floods, DoS, packet injection, etc., are considered. Numerous researchers have attempted to address the issue of sensor network security in the past using a variety of strategies, but the subject remains open since new attacks and other irregularities are discovered daily. This paper proposed a scheme to identify and prohibit malicious activity in wireless sensor networks using packet analysis and filtering approaches to resolve the security issue. The proposed approach improves performance with lesser delay, higher throughput, and packet delivery ratio and found successful in protecting wireless sensor networks (WSNs) against malicious incidents like flooding and DoS and improves overall performance. In the event of an attack the network performance goes down, however, the proposed scheme increases performance to almost normal routing and route overhead is less than 1, the PDR improvement is 4% when compared with the previous M-AODV scheme, and the rest of the metrics are also showing performance improvement. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Wireless sensor networks

来源：评论

学校读者我要写书评

暂无评论

A Novel Genetic Algorithm Based Timetable Generator for Optimized University Timetable Solution

A Novel Genetic Algorithm Based Timetable Generator for Opti...

引用

2024 International Conference on engineering and Computing, ICECT 2024

作者： Khan, Ali Hasan Imtiaz, Talha Ghulam Ishaq Khan Institute of Engineering Sciences and Technology Faculty of Computer Science and Engineering Topi Pakistan

ISBN: (纸本)9798350349719

In educational institutes, efficient timetable generation is critical for optimizing resource utilization and fostering a conducive learning environment. Timetable challenges, such as clashes among faculty schedules and lack of real-Time updates, underscore the need for innovative solutions in the field. The problem lies in addressing clashes, transparency issues, and inflexibility in manual scheduling systems, leading to disruptions and impacting both students and faculty. We employed a genetic algorithm, combining one-point crossover and mutation operations, to iteratively evolve and adapt timetables to enhances genetic diversity, addresses scheduling conflicts, and promotes the creation of optimal timetables. The results exhibit dynamic and evolving timetables that prioritize efficiency, clash prevention, and overall optimization. The significance lies in fostering an environment conducive to effective teaching and learning, emphasizing fairness, adaptability, and overall well-being. Our work introduces a genetic algorithm-based methodology that not only addresses existing challenges in educational timetable generation but also significantly contributes to fostering a more efficient, transparent, and adaptable scheduling system. © 2024 IEEE.

关键词： Genetic algorithms

来源：评论

学校读者我要写书评

暂无评论

High-Efficiency Asymmetrically Designed Three-Phase Virtual 48-Pulse Power Supply for Electrolytic Hydrogen

引用

IEEE Transactions on Power Electronics 2025年第8期40卷 10335-10342页

作者： Tian, Hanlei Cui, Haoran Han, Wei Sathik M, Jagabar Liang, Guozhuang Chen, Maolin Mekhilef, Saad Electrical Engineering School of Hebei University of Science and Technology Shijiazhuang050091 China Sustainable Energy and Environment Thrust Guangzhou511453 China The Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Hong Kong Hong Kong SRM Institute of Science and Technology Faculty of Engineering and Technology Kattankulathur603203 India Sichuan University College of Electrical Engineering Chengdu610065 China Swinburne University of Technology School of Science Computing and Engineering Technologies MelbourneVIC3122 Australia

To address the low-voltage, high-current requirements in hydrogen production applications, a virtual 48-pulse three-phase rectifier is proposed, and achieves the equivalent performance of four parallel 12-pulse rectifiers (12-PR). The proposed approach builds upon the conventional 12-PR design and incorporates novel asymmetric current injection units (ACIU). The ACIU is installed on the dc side of the ac-dc converter, generating a specific current at the dc link to modulate and enhance the operating modes of the 12-PR. Consequently, the 12-pulse is extended to 48, resulting in an almost sinusoidal input current with a total harmonic distortion of 3.2% and an output current with a ripple rate of 2.3%, thus significantly improving power quality. Furthermore, the asymmetric design of the current injection units eliminates the need for a phase-shifting transformer. The efficacy of the proposed rectifier for electrolytic hydrogen production is validated using a 2.2-kW experimental prototype. © 1986-2012 IEEE.

关键词： Voltage Hydrogen Rectifiers Production Windings Circuits Inductors Transformers Harmonic analysis Electrochemical processes

来源：评论

学校读者我要写书评

暂无评论

A Systematic Literature Review of Food Recommender Systems

引用

SN computer science 2024年第1期5卷 174页

作者： Mahajan, Pratibha Kaur, Pankaj Deep Department of Computer Engineering Faculty of Science and Technology Vishwakarma University Pune India Computer Science and Engineering Department Guru Nanak Dev University Regional Campus Jalandhar India

The enormous variations in food choices and lifestyle in today’s world have given rise to the demand of using recommender system as a suitable tool in making appropriate food choices. Need for choosing nutritious food items is becoming important in today’s modern lifestyle as people are getting indulged in eating unhealthy food and thus leading to miserable health status. Many lifestyle-related diseases, such as diabetes and obesity, can also be reversed by proper diet. Filtering techniques in recommender system use a dataset of items and user’s preferences as input to discover a list of well-judged items as suggestions. In light of the above said, this paper presents an exploratory study of the recommendation approaches and methods utilized for food and recipe recommendations in the past decade. For this purpose, several relevant papers published in the food domain from 2006 to 2023 have been extensively studied. Further, the research articles are categorized based on the filtering techniques, methods, functionalities and data sources used by the researchers. A comparative study of the recommendation approaches revealed the advantages and disadvantages of different approaches. Also, the paper emphasizes the importance of food recommendation techniques in health and nutrition management of an individual. The review highlights the need to further explore the implementation of recommender systems in the food industry. Furthermore, the findings of this survey provide researchers with insights and future directions on recommender systems in the domain. © 2024, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

关键词： Food Food/Recipe/Menu recommender system Information retrieval Menu Recipe Recommender system

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：