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The Metric for Automatic Code Generation Based on Dynamic Abstract Syntax Tree 基于动态抽象语法树的代码自动生成度量
IF 0.7
International Journal of Digital Crime and Forensics Pub Date : 2023-06-27 DOI: 10.4018/ijdcf.325062
Wenjun Yao, Ying Jiang, Yang Yang
{"title":"The Metric for Automatic Code Generation Based on Dynamic Abstract Syntax Tree","authors":"Wenjun Yao, Ying Jiang, Yang Yang","doi":"10.4018/ijdcf.325062","DOIUrl":"https://doi.org/10.4018/ijdcf.325062","url":null,"abstract":"In order to improve the efficiency and quality of software development, automatic code generation technology is the current focus. The quality of the code generated by the automatic code generation technology is also an important issue. However, existing metrics for code automatic generation ignore that the programming process is a continuous dynamic changeable process. So the metric is a dynamic process. This article proposes a metric method based on dynamic abstract syntax tree (DAST). More specifically, the method first builds a DAST through the interaction in behavior information between the automatic code generation tool and programmer. Then the measurement contents are extracted on the DAST. Finally, the metric is completed with contents extracted. The experiment results show that the method can effectively realize the metrics of automatic code generation. Compared with the MAST method, the method in this article can improve the convergence speed by 80% when training the model, and can shorten the time-consuming by an average of 46% when doing the metric prediction.","PeriodicalId":44650,"journal":{"name":"International Journal of Digital Crime and Forensics","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2023-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43006709","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}
引用次数: 0
Latest Trends in Deep Learning Techniques for Image Steganography 用于图像隐写的深度学习技术的最新趋势
IF 0.7
International Journal of Digital Crime and Forensics Pub Date : 2023-02-24 DOI: 10.4018/ijdcf.318666
Vijay Kumar, Sahil Sharma, Chandan Kumar, A. Sahu
{"title":"Latest Trends in Deep Learning Techniques for Image Steganography","authors":"Vijay Kumar, Sahil Sharma, Chandan Kumar, A. Sahu","doi":"10.4018/ijdcf.318666","DOIUrl":"https://doi.org/10.4018/ijdcf.318666","url":null,"abstract":"The development of deep convolutional neural networks has been largely responsible for the significant strides forward made in steganography over the past decade. In the field of image steganography, generative adversarial networks (GAN) are becoming increasingly popular. This study describes current development in image steganographic systems based on deep learning. The authors' goal is to lay out the various works that have been done in image steganography using deep learning techniques and provide some notes on the various methods. This study proposed a result that could open up some new avenues for future research in deep learning based on image steganographic methods. These new avenues could be explored in the future. Moreover, the pros and cons of current methods are laid out with several promising directions to define problems that researchers can work on in future research avenues.","PeriodicalId":44650,"journal":{"name":"International Journal of Digital Crime and Forensics","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2023-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48569718","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}
引用次数: 4
Key Node Identification Based on Vulnerability Life Cycle and the Importance of Network Topology 基于脆弱性生命周期的关键节点识别及网络拓扑的重要性
IF 0.7
International Journal of Digital Crime and Forensics Pub Date : 2023-01-20 DOI: 10.4018/ijdcf.317100
Yuwen Zhu, Lei Yu
{"title":"Key Node Identification Based on Vulnerability Life Cycle and the Importance of Network Topology","authors":"Yuwen Zhu, Lei Yu","doi":"10.4018/ijdcf.317100","DOIUrl":"https://doi.org/10.4018/ijdcf.317100","url":null,"abstract":"The key network node identification technology plays an important role in comprehending unknown terrains and rapid action planning in network attack and defense confrontation. The conventional key node identification algorithm only takes one type of relationship into consideration; therefore, it is incapable of representing the characteristics of multiple relationships between nodes. Additionally, it typically disregards the periodic change law of network node vulnerability over time. In order to solve the above problems, this paper proposes a network key node identification method based on the vulnerability life cycle and the significance of the network topology. Based on the CVSS score, this paper proposes the calculation method of the vulnerability life cycle risk value, and identifies the key nodes of the network based on the importance of the network topology. Finally, it demonstrates the effectiveness of the method in the selection of key nodes through network instance analysis.","PeriodicalId":44650,"journal":{"name":"International Journal of Digital Crime and Forensics","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2023-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48131380","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}
引用次数: 0
Design and Implementation of Identity Verification Software Based on Deep Learning 基于深度学习的身份验证软件的设计与实现
IF 0.7
International Journal of Digital Crime and Forensics Pub Date : 2022-11-30 DOI: 10.4018/ijdcf.315796
Runde Yu, Xianwei Zhang, Yimeng Zhang, Jianfeng Song, Kang Liu, Q. Miao
{"title":"Design and Implementation of Identity Verification Software Based on Deep Learning","authors":"Runde Yu, Xianwei Zhang, Yimeng Zhang, Jianfeng Song, Kang Liu, Q. Miao","doi":"10.4018/ijdcf.315796","DOIUrl":"https://doi.org/10.4018/ijdcf.315796","url":null,"abstract":"Identity verification, a noncontact biometric identification technology, has important scientific significance in theoretical research and shows great practical value in national security, public safety, and finance. In view of this situation, this paper designs an identity verification software based on deep learning, which has been successfully applied to real-world applications. The central idea of the software can be summarized as follows: First, the lightweight multi-task cascaded convolutional network (MTCNN), which can learn correlations between face detection and alignment, is employed for face detection. The software then conducts face recognition with MobileFaceNet which is an efficient and lightweight neural network, reducing the hardware cost. The test results show that the software meets the design requirements and can complete the corresponding identity confirmation function.","PeriodicalId":44650,"journal":{"name":"International Journal of Digital Crime and Forensics","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2022-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78014899","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}
引用次数: 0
Golden Eye: An OS-Independent Algorithm for Recovering Files From Hard-Disk Raw Images 黄金眼:从硬盘原始图像中恢复文件的操作系统独立算法
IF 0.7
International Journal of Digital Crime and Forensics Pub Date : 2022-11-30 DOI: 10.4018/ijdcf.315793
Fan Zhang, Wei Chen, Yongqiong Zhu
{"title":"Golden Eye: An OS-Independent Algorithm for Recovering Files From Hard-Disk Raw Images","authors":"Fan Zhang, Wei Chen, Yongqiong Zhu","doi":"10.4018/ijdcf.315793","DOIUrl":"https://doi.org/10.4018/ijdcf.315793","url":null,"abstract":"File systems are important sources of intelligence information and digital evidence. They have long attracted the interest of researchers in recovering files that are deleted from a hard disk. Existing file recovery studies rely heavily on an operating system (OS). However, it is often encountered that OS services are not available, making existing file recovery approaches unusable. To address this issue, the authors design and implement an OS-independent file recovery algorithm named Golden Eye (GE) by targeting the EXT4 file system. Fed the raw image obtained from a (sanitized) hard disk, GE can automatically recover any designated file or even the whole EXT4 file system. GE is based on the understanding of the file disk layout of EXT4 and does not need any support from additional hardware or software. Experimental results prove the feasibility and correctness of GE. This work not only solves the OS dependency problem that most existing file recovery work suffers from but also reveals the fact that even sanitized hard disks are still at risk of leaking sensitive data.","PeriodicalId":44650,"journal":{"name":"International Journal of Digital Crime and Forensics","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2022-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86325408","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}
引用次数: 0
Semisupervised Surveillance Video Character Extraction and Recognition With Attentional Learning Multiframe Fusion 基于注意学习多帧融合的半监督监控视频字符提取与识别
IF 0.7
International Journal of Digital Crime and Forensics Pub Date : 2022-11-30 DOI: 10.4018/ijdcf.315745
Guiyan Cai, Liang Qu, Yongdong Li, Guoan Cheng, Xin Lu, Yiqi Wang, Fengqin Yao, Shengke Wang
{"title":"Semisupervised Surveillance Video Character Extraction and Recognition With Attentional Learning Multiframe Fusion","authors":"Guiyan Cai, Liang Qu, Yongdong Li, Guoan Cheng, Xin Lu, Yiqi Wang, Fengqin Yao, Shengke Wang","doi":"10.4018/ijdcf.315745","DOIUrl":"https://doi.org/10.4018/ijdcf.315745","url":null,"abstract":"Character extraction in the video is very helpful to the understanding of the video content, especially the artificially superimposed characters such as time and place in the surveillance video. However, the performance of the existing algorithms does not meet the needs of application. Therefore, the authors improve semisupervised surveillance video character extraction and recognition with attentional learning multiframe feature fusion. First, the multiframe fusion strategy based on an attention mechanism is adopted to solve the target missing problem, and the Dense ASPP network is introduced to solve the character multiscale problem. Second, a character image denoising algorithm based on semisupervised fuzzy C-means clustering is proposed to isolate and extract clean binary character images. Finally, for some video characters that may involve privacy, traditional and deep learning-based video restoration algorithms are used for characteristic elimination.","PeriodicalId":44650,"journal":{"name":"International Journal of Digital Crime and Forensics","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2022-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74265008","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}
引用次数: 0
Improvement of the PBFT Algorithm Based on Grouping and Reputation Value Voting 基于分组和声誉值投票的PBFT算法改进
IF 0.7
International Journal of Digital Crime and Forensics Pub Date : 2022-11-30 DOI: 10.4018/ijdcf.315615
Shannan Liu, Ronghua Zhang, Changzheng Liu, Chenxi Xu, Jie Zhou, Jiaojiao Wang
{"title":"Improvement of the PBFT Algorithm Based on Grouping and Reputation Value Voting","authors":"Shannan Liu, Ronghua Zhang, Changzheng Liu, Chenxi Xu, Jie Zhou, Jiaojiao Wang","doi":"10.4018/ijdcf.315615","DOIUrl":"https://doi.org/10.4018/ijdcf.315615","url":null,"abstract":"An improved practical Byzantine fault tolerance (Practical Byzantine Fault Tolerant consensus algorithm based on reputation, RPBFT) algorithm based on grouping and reputation value voting is proposed for the problems of high communication complexity, poor scalability, and random selection of master nodes of the practical Byzantine fault tolerance (PBFT) consensus algorithm of the consortium chain. First, the consistency process is optimized to take the response speed of nodes to each group leader as the basis of grouping, and the intragroup consensus is performed. The group leader then takes the result of intragroup consensus and participates in extra-group consensus to reduce the frequency and time of internode communication. Second, the reputation model and voting mechanism are proposed, and the group leader is generated by node reputation value voting, which enhances the initiative and reliability of trusted nodes and reduces the abnormal nodes as group leader. Finally, a simulation and performance testing system based on this improved scheme is built to prove the effectiveness as well as the usability of the scheme through simulation experiments. The experimental results show that when the number of network nodes is 36, the throughput of the RPBFT algorithm is six times that of PBFT. Therefore, the consensus delay is reduced by 91.7%, and the communication overhead is reduced by 37.8%.","PeriodicalId":44650,"journal":{"name":"International Journal of Digital Crime and Forensics","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2022-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79645674","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}
引用次数: 1
An Unhealthy Webpage Discovery System Based on Convolutional Neural Network 基于卷积神经网络的不良网页发现系统
IF 0.7
International Journal of Digital Crime and Forensics Pub Date : 2022-11-30 DOI: 10.4018/ijdcf.315614
Zengyu Cai, Chunchen Tan, Jianwei Zhang, Tengteng Xiao, Yuan Feng
{"title":"An Unhealthy Webpage Discovery System Based on Convolutional Neural Network","authors":"Zengyu Cai, Chunchen Tan, Jianwei Zhang, Tengteng Xiao, Yuan Feng","doi":"10.4018/ijdcf.315614","DOIUrl":"https://doi.org/10.4018/ijdcf.315614","url":null,"abstract":"Currently, with the popularity of the internet, people are surrounded by a large number of unhealthy pages which have a serious impact on the physical and mental health of visitors. To protect the legitimate rights and interests of internet users from infringement and maintain the harmonious and stable development of society, a new unhealthy webpage discovery system is needed. First, this paper proposed the knowledge of unhealthy webpages and web crawlers, and then the whole system's plan and design were introduced. The test results show that the unhealthy webpage discovery system can meet the needs of users. This experiment uses a CNN algorithm to classify the text and completes the collection and classification of unhealthy information through URL acquisition and URL filtering. The experimental results show that the unhealthy webpage discovery system based on a convolutional neural network can greatly improve the accuracy of unhealthy webpage discovery and reduce the omission rate, which can meet the needs of users for unhealthy webpage discovery.","PeriodicalId":44650,"journal":{"name":"International Journal of Digital Crime and Forensics","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2022-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75773379","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}
引用次数: 0
Research and Application of Warship Multiattribute Threat Assessment Based on Improved TOPSIS Gray Association Analysis 基于改进TOPSIS灰色关联分析的舰船多属性威胁评估研究与应用
IF 0.7
International Journal of Digital Crime and Forensics Pub Date : 2022-11-30 DOI: 10.4018/ijdcf.315288
D. Zang, Xinlei Sheng, Liya Wang, Aimin Yang, Tao Xue, Jie Li
{"title":"Research and Application of Warship Multiattribute Threat Assessment Based on Improved TOPSIS Gray Association Analysis","authors":"D. Zang, Xinlei Sheng, Liya Wang, Aimin Yang, Tao Xue, Jie Li","doi":"10.4018/ijdcf.315288","DOIUrl":"https://doi.org/10.4018/ijdcf.315288","url":null,"abstract":"Multitarget threat evaluation of warship air attacks is one of the most urgent problems in warship defense operations. To evaluate the target threat quickly and accurately, an air attack multitarget threat evaluation method based on improved TOPSIS gray relational analysis is proposed. This method establishes threat assessment system of five attributes of target type, anti-jamming ability, heading angle, altitude, and speed. The weight coefficient of each index of the warship is obtained by combining the entropy weight method with the analytic hierarchy process. Topsis can make full use of the information of the original data, and its results can accurately reflect the gap between various evaluation schemes. The weighted Mahalanobis distance and comprehensive gray correlation between the attribute to be evaluated and the positive and negative ideal states are calculated by the improved TOPSIS gray correlation method. The target threat degree to be evaluated is obtained by combining the two methods. Finally, an example is given to prove the effectiveness of the evaluation model.","PeriodicalId":44650,"journal":{"name":"International Journal of Digital Crime and Forensics","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2022-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90196825","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}
引用次数: 0
SRGM Decision Model Considering Cost-Reliability 考虑成本-可靠性的SRGM决策模型
IF 0.7
International Journal of Digital Crime and Forensics Pub Date : 2022-07-01 DOI: 10.4018/ijdcf.302873
W. Jiang, Ce Zhang, Di Liu, Kaiwei Liu, Zhichao Sun, Jianyuan Wang, Zhongyin Qiu, W. Lv
{"title":"SRGM Decision Model Considering Cost-Reliability","authors":"W. Jiang, Ce Zhang, Di Liu, Kaiwei Liu, Zhichao Sun, Jianyuan Wang, Zhongyin Qiu, W. Lv","doi":"10.4018/ijdcf.302873","DOIUrl":"https://doi.org/10.4018/ijdcf.302873","url":null,"abstract":"Aiming at the current software cost model and optimal release research, which does not fully consider the actual faults in the testing phase, a cost-reliability SRGM evaluation and selection algorithm SESABCRC is proposed. From the perspective of incomplete debugging, introducing new faults, and considering testing effort, the imperfect debugging SRGM is established. The proposed SRGM can be used to describe the testing process of the software through the actual failure data set verification, and is superior to other models. Based on the proposed SRGM, the corresponding cost function is given, which explicitly considers the impact of imperfect debugging on the cost. Furthermore, an optimal release strategy is proposed when given restricted reliability target requirements and when considering the uncertainty that the actual cost may exceed the expected cost. Finally, an experimental example is given to illustrate and verify the optimal publishing problem, and parameter sensitivity analysis is carried out.","PeriodicalId":44650,"journal":{"name":"International Journal of Digital Crime and Forensics","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85817015","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}
引用次数: 0
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