Network Supplier Credit Management: Models Based on Petri Net

In current credit evaluation methods, the credit condition of the network supplier and the credit degree of each index cannot be described well, and the credit evaluation data only source of the transaction platform have much limitation. This research proposes the method of calculating the importance and the value of the credit evaluation indexes, and proposes to put credit evaluation into big data environment. This research uses the transaction process of B2C as the case, and constructs multiple attribute weighted Petri net credit index subnet (CWPSN) for realizing the credit evaluation of the network supplier, and for presenting the correlations among the evaluation results of the credit evaluation indexes, and for presenting the importance of the indexes and the credit degree of each index, and describes the cost optimization process with credit cost optimization investment process Petri net (CCOIPPN). By the case to verify the credit evaluation method based on Petri net and the cost optimization method based on Petri net. The researches have provided methods for clearly and concretely describing the process of credit evaluation and cost optimization of network supplier, and have guidance significance for similar other researches

EavesDroid: Eavesdropping User Behaviors via OS Side-Channels on Smartphones

As the Internet of Things (IoT) continues to evolve, smartphones have become essential components of IoT systems. However, with the increasing amount of personal information stored on smartphones, user privacy is at risk of being compromised by malicious attackers. Although malware detection engines are commonly installed on smartphones against these attacks, attacks that can evade these defenses may still emerge. In this paper, we analyze the return values of system calls on Android smartphones and find two never-disclosed vulnerable return values that can leak fine-grained user behaviors. Based on this observation, we present EavesDroid, an application-embedded side-channel attack on Android smartphones that allows unprivileged attackers to accurately identify fine-grained user behaviors (e.g., viewing messages and playing videos) via on-screen operations. Our attack relies on the correlation between user behaviors and the return values associated with hardware and system resources. While this attack is challenging since these return values are susceptible to fluctuation and misalignment caused by many factors, we show that attackers can eavesdrop on fine-grained user behaviors using a CNN-GRU classification model that adopts min-max normalization and multiple return value fusion. Our experiments on different models and versions of Android smartphones demonstrate that EavesDroid can achieve 98% and 86% inference accuracy for 17 classes of user behaviors in the test set and real-world settings, highlighting the risk of our attack on user privacy. Finally, we recommend effective malware detection, carefully designed obfuscation methods, or restrictions on reading vulnerable return values to mitigate this attack.Comment: 15 pages, 25 figure

Operation Mechanism for G2B System Based on Blockchain

The characteristics of blockchain as decentralization, transparency, business activity undeniable proof mechanism etc. have achieved extensive attention from the academic circles and industrial circles. In view of the current deficiency of poor data sharing in G2B system, data authenticity, data security, and transaction subject identity’s confidentiality cannot be effectively guaranteed, and the lack of authentication for government management departments (organization institutions) providing service or implementing management to enterprise businesses, this paper proposed to construct G2B system based on blockchain. Based on maintaining the architecture of traditional G2B system and the serviced or managed characteristics of enterprise businesses, was constructed respective G2B system based on blockchain for each section of enterprise business process. Each G2B system was based on blockchain correlated by the virtual links of enterprises and serviced or managed data for enterprises’ business, and constituted blockchain interconnection network. The protocol was designed and the characteristics of G2B system analyzed based on blockchain. Application mode for G2B system was designed based on blockchain. A case based on blockchain was designed, including business operation principle, consensus mechanism, and supervision to government (organization)

CPS Information Security Risk Evaluation Based on Blockchain and Big Data

CPS (Cyber Physical Systems) have got wide application and research, and information security risk evaluation became the key for CPS greatly developing. In view of the physical structure and business characteristics of CPS, this paper constructs an information security risk evaluation system for CPS. In the process of risk evaluation, colligating the analysis results from experts and the analysis results of external data sources’ related big data for information security risk evaluation of CPS, by experts confirming the index system and indexes’ weight values for CPS information security risk evaluation, further through using evaluation model to realize the quantitative calculation to CPS information security risks. This paper proposes using blockchain technology to construct the data’s authenticity and reliability guarantee system for CPS and CPS related external systems, and constructing blockchain’s layered model structure based on CPS. In the part of case analysis, comparing and analysing the evaluation system based on blockchain and big data and the evaluation system based on traditional mode, to confirm the research value of this paper

Enhancing Child Sexual Abuse Prevention Knowledge With an Educational Toolkit -Evaluation of the Chinese Doll Program

Objective: In countries with conservative attitudes towards sex and limited resources to prevent child sexual abuse, culturally adapted CSA prevention programs are essential. This study outlines a randomized controlled trial evaluating the effectiveness of the Doll program for preventing CSA in the specific context of China.Method: 181 children were pre-tested and post-tested (5 weeks later) for knowledge of sexual abuse prevention. Children were assigned to one of three groups; 1) child only (n = 60); 2) child and parent (n = 60); and 3) control (n = 61).Results: Children in groups 1 and 2 showed significant increases (p < 0.001) in scores on the Appropriate Touch Scale (ATS) and the Inappropriate Touch Scale (ITS), whereas those in the control group did not show a significant increase in ATS scores, but their scores on ITS significantly increased (p < 0.001). Children in group 2 showed significantly increased ITS scores compared to group 1 (p = 0.016).Conclusion: Doll program effectively enhances children’s CSA prevention knowledge, with parental engagement demonstrating a positive impact on the program