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Full-Text Articles in Physical Sciences and Mathematics
Why Do Smart Contracts Self-Destruct? Investigating The Selfdestruct Function On Ethereum, Jiachi Chen, Xin Xia, David Lo, John C. Grundy
Why Do Smart Contracts Self-Destruct? Investigating The Selfdestruct Function On Ethereum, Jiachi Chen, Xin Xia, David Lo, John C. Grundy
Research Collection School Of Computing and Information Systems
The selfdestruct function is provided by Ethereum smart contracts to destroy a contract on the blockchain system. However, it is a double-edged sword for developers. On the one hand, using the selfdestruct function enables developers to remove smart contracts (SCs) from Ethereum and transfers Ethers when emergency situations happen, e.g., being attacked. On the other hand, this function can increase the complexity for the development and open an attack vector for attackers. To better understand the reasons why SC developers include or exclude the selfdestruct function in their contracts, we conducted an online survey to collect feedback from them and …
Characterizing Malicious Android Apps By Mining Topic-Specific Data Flow Signatures, Xinli Yang, David Lo, Li Li, Xin Xia, Tegawendé F. Bissyande, Jacques Klein
Characterizing Malicious Android Apps By Mining Topic-Specific Data Flow Signatures, Xinli Yang, David Lo, Li Li, Xin Xia, Tegawendé F. Bissyande, Jacques Klein
Research Collection School Of Computing and Information Systems
Context: State-of-the-art works on automated detection of Android malware have leveraged app descriptions to spot anomalies w.r.t the functionality implemented, or have used data flow information as a feature to discriminate malicious from benign apps. Although these works have yielded promising performance,we hypothesize that these performances can be improved by a better understanding of malicious behavior. Objective: To characterize malicious apps, we take into account both information on app descriptions,which are indicative of apps’ topics, and information on sensitive data flow, which can be relevant todiscriminate malware from benign apps. Method: In this paper, we propose a topic-specific approach to …
Tasker: Behavioral Insights Via Campus-Based Experimental Mobile Crowd-Sourcing, Thivya Kandappu, Nikita Jaiman, Randy Tandriansyah Daratan, Archan Misra, Shih-Fen Cheng, Cen Chen, Hoong Chuin Lau, Deepthi Chander, Koustuv Dasgupta
Tasker: Behavioral Insights Via Campus-Based Experimental Mobile Crowd-Sourcing, Thivya Kandappu, Nikita Jaiman, Randy Tandriansyah Daratan, Archan Misra, Shih-Fen Cheng, Cen Chen, Hoong Chuin Lau, Deepthi Chander, Koustuv Dasgupta
Research Collection School Of Computing and Information Systems
While mobile crowd-sourcing has become a game-changer for many urban operations, such as last mile logistics and municipal monitoring, we believe that the design of such crowdsourcing strategies must better accommodate the real-world behavioral preferences and characteristics of users. To provide a real-world testbed to study the impact of novel mobile crowd-sourcing strategies, we have designed, developed and experimented with a real-world mobile crowd-tasking platform on the SMU campus, called TA$Ker. We enhanced the TA$Ker platform to support several new features (e.g., task bundling, differential pricing and cheating analytics) and experimentally investigated these features via a two-month deployment of TA$Ker, …