Pisces: Private and Compliable Cryptocurrency Exchange

Cryptocurrency exchange platforms such as Coinbase, Binance, enable users to purchase and sell cryptocurrencies conveniently just like trading stocks/commodities. However, because of the nature of blockchain, when a user withdraws coins (i.e., transfers coins to an external on-chain account), all future transactions can be learned by the platform. This is in sharp contrast to conventional stock exchange where all external activities of users are always hidden from the platform. Since the platform knows highly sensitive user private information such as passport number, bank information etc, linking all (on-chain) transactions raises a serious privacy concern about the potential disastrous data breach in those cryptocurrency exchange platforms. In this paper, we propose a cryptocurrency exchange that restores user anonymity for the first time. To our surprise, the seemingly well-studied privacy/anonymity problem has several new challenges in this setting. Since the public blockchain and internal transaction activities naturally provide many non-trivial leakages to the platform, internal privacy is not only useful in the usual sense but also becomes necessary for regaining the basic anonymity of user transactions. We also ensure that the user cannot double spend, and the user has to properly report accumulated profit for tax purposes, even in the private setting. We give a careful modeling and efficient construction of the system that achieves constant computation and communication overhead (with only simple cryptographic tools and rigorous security analysis); we also implement our system and evaluate its practical performance.Comment: 27 pages, 8 figures, 2 tables. To be published in NDSS'24. This is the full version of the conference pape

Mining Large-scale Event Knowledge from Web Text

AbstractThis paper addresses the problem of automatic acquisition of semantic relations between events. While previous works on semantic relation automatic acquisition relied on annotated text corpus, it is still unclear how to develop more generic methods to meet the needs of identifying related event pairs and extracting event-arguments (especially the predicate, subject and object). Motivated by this limitation, we develop a three-phased approach that acquires causality from the Web text. First, we use explicit connective markers (such as “because”) as linguistic cues to discover causal related events. Next, we extract the event-arguments based on local dependency parse trees of event expressions. At the last step, we propose a statistical model to measure the potential causal relations. The results of our empirical evaluations on a large-scale Web text corpus show that (a) the use of local dependency tree extensively improves both the accuracy and recall of event-arguments extraction task, and (b) our measure improves the traditional PMI method

Delisheng, a Chinese medicinal compound, exerts anti-proliferative and pro-apoptotic effects on HepG2 cells through extrinsic and intrinsic pathways

The anti-proliferative, cytotoxic and apoptogenic activities of delisheng, a Chinese medicinal compound, has been investigated. In this study, the hepatocarcinoma cell line (HepG2) and the liver cell line (L-02) were exposed to delisheng (6.25, 50 and 100 μl/ml). Delisheng suppressed the proliferation and viability of normal liver L-02 cells slightly, but strongly inhibited the proliferation and viability of hepatocarcinoma HepG2 cells. The flow cytometric analysis of HepG2 cells demonstrated that delisheng primarily arrested the HepG2 cells at the G1 phase of the cell cycle. Annexin V-FITC/PI staining corroborates the apoptogenic nature of delisheng on HepG2 cells. The anti-proliferative and pro-apoptotic effect of delisheng in HepG2 cells was associated with changes in the Bcl-2/Bax ratio and the induction of caspase-mediated apoptosis. Upregulation of DR5 expression was observed in HepG2 cells after treatment with delisheng. The findings from the present study suggest that delisheng has selective cytotoxic activities against HepG2 cells. Delisheng triggered time- and dose-dependent apoptosis in HepG2 cells by activating the mitochondria-mediated and death receptor-mediated apoptotic pathways

A Parametric Sharpe Ratio Optimization Approach for Fuzzy Portfolio Selection Problem

When facing to make a portfolio decision, investors may care more about every portfolio’s performance on a return and risk trade-off. In this paper, a new low partial moment measurement that only punishes the loss risk is defined for selection variables based on L-S integral. Furthermore, a new performance measure for portfolio evaluation is proposed to generalize the Sharpe ratio in the fuzzy context. With the optimal performance criterion, a new parametric Sharpe ratio portfolio optimization model is developed wherein uncertain returns are presented as parametric interval-valued fuzzy variables. To make the proposed model easy to solve, we transform the fractional programming into an equivalent form and solve it with domain decomposition method (DDM). Finally, we apply the proposed performance measure into a portfolio selection problem, compare the computational results in different cases, and analyze the influence of different parameters on the optimal portfolio