A Novel Reputation Management Mechanism with Forgiveness in P2P File Sharing Networks

AbstractIn peer-to-peer (P2P) file sharing networks, it is common practice to manage each peer using reputation systems. A reputation system systematically tracks the reputation of each peer and punishes peers for malicious behaviors (like uploading bad file, or virus, etc). However, current reputation systems could hurt the normal peers, since they might occasionally make mistakes. Therefore, in this paper, we introduce forgiveness mechanism into the EigenTrust reputation system to reduce such malicious treatments and give them opportunities to gain reputation back. Particularly, we take four motivations (the severity of current offence, the frequency of offences, the compensation and the reciprocity of the offender) into consideration to measure forgiveness. The simulation work shows that the forgiveness model can repair the direct trust breakdown caused by unintentional mistakes and lead to less invalid downloads, which improves the performance of P2P file sharing systems

Computing Optimal Mixed Strategies for Terrorist Plot Detection Games with the Consideration of Information Leakage

The terrorist’s coordinated attack is becoming an increasing threat to western countries. By monitoring potential terrorists, security agencies are able to detect and destroy terrorist plots at their planning stage. Therefore, an optimal monitoring strategy for the domestic security agency becomes necessary. However, previous study about monitoring strategy generation fails to consider the information leakage, due to hackers and insider threat. Such leakage events may lead to failure of watching potential terrorists and destroying the plot, and cause a huge risk to public security. This paper makes two major contributions. Firstly, we develop a new Stackelberg game model for the security agency to generate optimal monitoring strategy with the consideration of information leakage. Secondly, we provide a double-oracle framework DO-TPDIL for calculation effectively. The experimental result shows that our approach can obtain robust strategies against information leakage with high feasibility and efficiency

A Verifiable E-voting Scheme with Secret Sharing

Abstract Traditional e-voting schemes use centralized and nontransparent count centers, which leads to people's distrust of the centers and doubt of the voting on impartiality and correctness. In this paper, we propose a distributed and verifiable e-voting scheme based on Mignotte's threshold secret sharing scheme, which effectively balances the conflict of interest between voters and count centers. Additionally, this scheme can also resist potential attacks from malicious participants, and satisfy special requirements of e-voting, especially for privacy and accountability, which contradict each other. Moreover, voters take on the major computation load in our scheme, which effectively reduces the computation burden of the vote counter

Computing Optimal Mixed Strategies for Terrorist Plot Detection Games with the Consideration of Information Leakage

The terrorist’s coordinated attack is becoming an increasing threat to western countries. By monitoring potential terrorists, security agencies are able to detect and destroy terrorist plots at their planning stage. Therefore, an optimal monitoring strategy for the domestic security agency becomes necessary. However, previous study about monitoring strategy generation fails to consider the information leakage, due to hackers and insider threat. Such leakage events may lead to failure of watching potential terrorists and destroying the plot, and cause a huge risk to public security. This paper makes two major contributions. Firstly, we develop a new Stackelberg game model for the security agency to generate optimal monitoring strategy with the consideration of information leakage. Secondly, we provide a double-oracle framework DO-TPDIL for calculation effectively. The experimental result shows that our approach can obtain robust strategies against information leakage with high feasibility and efficiency

Computing Optimal Mixed Strategies for Terrorist Plot Detection Games with the Consideration of Information Leakage

The terrorist’s coordinated attack is becoming an increasing threat to western countries. By monitoring potential terrorists, security agencies are able to detect and destroy terrorist plots at their planning stage. Therefore, an optimal monitoring strategy for the domestic security agency becomes necessary. However, previous study about monitoring strategy generation fails to consider the information leakage, due to hackers and insider threat. Such leakage events may lead to failure of watching potential terrorists and destroying the plot, and cause a huge risk to public security. This paper makes two major contributions. Firstly, we develop a new Stackelberg game model for the security agency to generate optimal monitoring strategy with the consideration of information leakage. Secondly, we provide a double-oracle framework DO-TPDIL for calculation effectively. The experimental result shows that our approach can obtain robust strategies against information leakage with high feasibility and efficiency

Impact of Heading Shift of Barley Cultivars on the Weather Patterns around Heading and Yield in Alaska

Barley heading date has advanced in Fairbanks (64.83° N, 147.77° W), Alaska, USA. However, it is unclear if this advance coincidently causes weather pattern changes around heading and leads to yield loss. Using the Variety Trial and weather data in Fairbanks and Delta Junction (64.05° N, 145.60° W) from 1991 to 2018, two barley cultivars were selected to analyze the yield and weather trends, the yield variation explained by weather, and the effect of extreme weather on yield. The results showed that the heading date of ‘Otal’ significantly advanced and yield significantly declined in Fairbanks while there were no heading and yield changes of ‘Otal’ in Delta Junction and of ‘Thual’ in both Fairbanks and Delta Junction. The weather pattern changed around heading due to advanced heading of ‘Otal’ in Fairbanks. The climate factors at 7–10 days around heading explained over 50% of ‘Otal’ yield variation in Fairbanks. The results suggest that ‘Otal’ can still be good to plant in Delta Junction but not in Fairbanks. To cope with the climate change in Alaska, the farmers should increase the diversity of barley cultivars, select non-photoperiod sensitive cultivars and cultivars with longer duration from planting to heading, and sow late to avoid the impact on heading and yield

Secret Image Sharing Scheme with Threshold Changeable Capability

In secret image sharing schemes, the threshold may have to be adjusted in case of changes in the security policy and the adversary structure before recovering the secret image. For example, if participants leave the group, their stego images are useless to them and may not be kept safely. As a result, these images can be easily stolen and utilized by intruders, which reduces the security of the scheme. To solve this problem, we propose a novel threshold changeable secret image sharing scheme with N potential changeable thresholds t1,t2,…,tN. By preparing advance shares for thresholds t1,t2,…,tN and using the two-variable one-way function to generate the identification value, we can change the threshold when necessary. The experiments show that the quality of the stego images in our scheme is satisfactory and the secret image can be recovered without distortion. Moreover, the security analysis shows that we can change the threshold safely