The Progress, Challenges, and Perspectives of Directed Greybox Fuzzing

Most greybox fuzzing tools are coverage-guided as code coverage is strongly correlated with bug coverage. However, since most covered codes may not contain bugs, blindly extending code coverage is less efficient, especially for corner cases. Unlike coverage-guided greybox fuzzers who extend code coverage in an undirected manner, a directed greybox fuzzer spends most of its time allocation on reaching specific targets (e.g., the bug-prone zone) without wasting resources stressing unrelated parts. Thus, directed greybox fuzzing (DGF) is particularly suitable for scenarios such as patch testing, bug reproduction, and specialist bug hunting. This paper studies DGF from a broader view, which takes into account not only the location-directed type that targets specific code parts, but also the behaviour-directed type that aims to expose abnormal program behaviours. Herein, the first in-depth study of DGF is made based on the investigation of 32 state-of-the-art fuzzers (78% were published after 2019) that are closely related to DGF. A thorough assessment of the collected tools is conducted so as to systemise recent progress in this field. Finally, it summarises the challenges and provides perspectives for future research.Comment: 16 pages, 4 figure

Extenics-based Study on Evaluation of Urban Community Home-care Service for the Elderly

AbstractThis paper tries to introduce extenics theory into the evaluation of the urban community home-care service for the elderly. The paper analyzes the feasibility of using extenics to evaluate the service, uses analytic hierarchy process to decide the weight of index and constructs a comprehensive evaluation model for the service on the basis of extenics. Based on the case study of communities in Ningbo, the paper has completed the evaluation of home-care service in operation and put forward countermeasures to the existing problems

An empirical analysis of regional disparity of influence factors on financial exclusion based on types and levels of financial institution in China

We make an empirical analysis of regional characteristics of influence factors on financial exclusion by using the data of types and levels of financial institutions in the nation from 1998 to 2012. The study shows the number of financial institution nodes continues to increase, but with uneven distributions; the density of financial institutions increases steadily and the gap between the eastern and the Midwest is huge; the commercial banks of the eastern region account for the highest but the rate of the commercial bank basic outlets is low and the rate of the rural institution bank basic outlets is relatively higher, in addition the proportion of the Midwest rural banks is high. Even though the financial exclusion eases, large differences still exist in different areas and the situation is rather critical in rural areas, especially the financial exclusion in western rural areas is the wors

Focal Inverse Distance Transform Maps for Crowd Localization and Counting in Dense Crowd

In this paper, we propose a novel map for dense crowd localization and crowd counting. Most crowd counting methods utilize convolution neural networks (CNN) to regress a density map, achieving significant progress recently. However, these regression-based methods are often unable to provide a precise location for each person, attributed to two crucial reasons: 1) the density map consists of a series of blurry Gaussian blobs, 2) severe overlaps exist in the dense region of the density map. To tackle this issue, we propose a novel Focal Inverse Distance Transform (FIDT) map for crowd localization and counting. Compared with the density maps, the FIDT maps accurately describe the people's location, without overlap between nearby heads in dense regions. We simultaneously implement crowd localization and counting by regressing the FIDT map. Extensive experiments demonstrate that the proposed method outperforms state-of-the-art localization-based methods in crowd localization tasks, achieving very competitive performance compared with the regression-based methods in counting tasks. In addition, the proposed method presents strong robustness for the negative samples and extremely dense scenes, which further verifies the effectiveness of the FIDT map. The code and models are available at https://github.com/dk-liang/FIDTM.Comment: The code and models are available at https://github.com/dk-liang/FIDT

The Impact of User Heterogeneity on Knowledge Collaboration Performance

Existing research showed that the social Q & A community is centred on user participation and can improve knowledge collaboration performance by means of heterogeneous knowledge, but it did not reveal the process and mechanism. This paper takes the user behaviours of the Zhihu which is the largest social Q & A community in China as the research object. From an interactive perspective, it builds a research model of the relationship between user heterogeneity and knowledge collaboration performance by establishing measurement indicators for relationship analysis according to the user behaviours data of Zhihu. The results show that there is an inverted Ushaped relationship between user heterogeneity and knowledge collaboration performance, and the interpersonal interaction of users plays a mediating role in the relationship between user heterogeneity and knowledge collaboration performance, while the mediating effect of machine interaction is not significant. This paper, based on this, puts forward some suggestions for better development of social Q & A community

Research status and progress of intelligent wearable system for first aid based on body area network

With the rise of electronic health services, wireless body area network (WBAN) technology has attracted great international attention. The body area network can obtain human vital sign parameters in its natural state, and support applications in areas such as clinical diagnosis and treatment, emergency rescue and treatment, and health information services. This article introduces the concept of body area network and the electronic medical architecture of body area network, summarizes the advantages of body area network: in low data rate scenarios, the system power consumption of body area network is much lower than that of other wireless communication standards, providing more choices for special frequency bands for medical equipment (500 MHz to 5 GHZ), thereby reducing the interference problem between different communications; proposing bottlenecks and hot spots of body area network: ultra-low power consumption requirements of sensor nodes and hardware resource constraints with limited computing power, and data security protection problems in body area network sensor nodes; the application of body area network in emergency scenarios was analyzed, and the hot spots of body area network research in the field of emergency were summarized and predicted: the development of ultra-low-power chips, wearable wireless nodes, intelligent medical terminals, health and monitoring instruments and other devices and equipment