IMPROVED SOFTWARE ACTIVATION USING MULTITHREADING

Software activation is an anti-piracy technology designed to verify that software products have been legitimately licensed [1]. It is supposed to be quick and simple while simultaneously protecting customer privacy. The most common form of software activation is through the entering of legitimate product serial numbers by users, which sometimes are also known as product keys. This technique is employed by various software, from small shareware programs to large commercial programs such as Microsoft Office. However, software activation based on a serial number appears to be weak, as various cracks for a majority of programs are available and can be found easily on the Internet. Users can use such cracks to bypass the software activation. Generally, the verification logic for checking a serial number executes sequentially in a single thread. Such an approach is weak because attackers can effectively trace this thread from the beginning to the end to understand how the verification logic works. In this paper, we develop a practical multi-threaded verification design. We breakdown the checking logic into smaller pieces and run each piece within a separate thread. Our results show that the amount of traceable code in a debugger is reduced to a low percentage of the code -- especially when junk threads with deadlocks are used -- and the traceable code in each run can differ as well. This makes it more difficult for an attacker to reverse engineer the code and bypass any security check. Finally, we attempt to quantify the increased effort necessary to break out verification logic

Exploiting Amplitude Control in Intelligent Reflecting Surface Aided Wireless Communication with Imperfect CSI

Intelligent reflecting surface (IRS) is a promising new paradigm to achieve high spectral and energy efficiency for future wireless networks by reconfiguring the wireless signal propagation via passive reflection. To reap the potential gains of IRS, channel state information (CSI) is essential, whereas channel estimation errors are inevitable in practice due to limited channel training resources. In this paper, in order to optimize the performance of IRS-aided multiuser systems with imperfect CSI, we propose to jointly design the active transmit precoding at the access point (AP) and passive reflection coefficients of IRS, each consisting of not only the conventional phase shift and also the newly exploited amplitude variation. First, the achievable rate of each user is derived assuming a practical IRS channel estimation method, which shows that the interference due to CSI errors is intricately related to the AP transmit precoders, the channel training power and the IRS reflection coefficients during both channel training and data transmission. Then, for the single-user case, by combining the benefits of the penalty method, Dinkelbach method and block successive upper-bound minimization (BSUM) method, a new penalized Dinkelbach-BSUM algorithm is proposed to optimize the IRS reflection coefficients for maximizing the achievable data transmission rate subjected to CSI errors; while for the multiuser case, a new penalty dual decomposition (PDD)-based algorithm is proposed to maximize the users' weighted sum-rate. Simulation results are presented to validate the effectiveness of our proposed algorithms as compared to benchmark schemes. In particular, useful insights are drawn to characterize the effect of IRS reflection amplitude control (with/without the conventional phase shift) on the system performance under imperfect CSI.Comment: 15 pages, 10 figures, accepted by IEEE Transactions on Communication

Synthesis and optimization of methyl 5-acetyl-1,4-dihydro-2,6-dimethyl-4-(substituent benzylidene)pyridine-3-carboxylate

Two 1,4-dihydro-Hantzsch pyridine derivatives were synthesized by three steps. In the condensation step, the reaction time can be shortened to 1.5 h through using H2SO4-acetic anhydride system as a catalyst rather than the acetic acid-piperidine systemin the cyclization step, the reaction time was shortened from 20 h in ethanol to 15 h in polar aprotic solvent, and the yield of two products also was increased from 43.3% and 39.7% in traditional solvent to 93.2% and 90.1% in polar aprotic solvent

Abrasive Wear of Geometrical Surface Structures of Scapharca Subcrenata and Burnt-end Ark Against Soil

Scapharca subcrenata(Arca subcrenala Lischke）and Burnt-end Ark (Arca inflata Reeve) were selected as the research object. The abrasive wear experiments of three types of surface structures against soil were performed in the abrasive tester. These surface structures include the Scapharca subcrenata node rib pattern shell, Scapharca subcrenata rib pattern shell and Burnt-end Ark. The test results showed that the wear-resistant function of the surface structures of the Scapharca subcrenata node rib pattern shell and the Burnt-end Ark shell was better than that of the surface structure of the Scapharca subcrenata rib pattern shell when the relative sliding velocity was 2.41m/s. When abrasive size was range from 0.380mm to 0.830mm, the wear loss of these three types of surface structures were increased with the relative sliding velocity increasing.Keywords: Scapharca subcrenata; Burnt-end Ark; geometrical surface structure; abrasive wear; wear resistanc

On the Robustness of Dataset Inference

Machine learning (ML) models are costly to train as they can require a significant amount of data, computational resources and technical expertise. Thus, they constitute valuable intellectual property that needs protection from adversaries wanting to steal them. Ownership verification techniques allow the victims of model stealing attacks to demonstrate that a suspect model was in fact stolen from theirs. Although a number of ownership verification techniques based on watermarking or fingerprinting have been proposed, most of them fall short either in terms of security guarantees (well-equipped adversaries can evade verification) or computational cost. A fingerprinting technique, Dataset Inference (DI), has been shown to offer better robustness and efficiency than prior methods. The authors of DI provided a correctness proof for linear (suspect) models. However, in a subspace of the same setting, we prove that DI suffers from high false positives (FPs) -- it can incorrectly identify an independent model trained with non-overlapping data from the same distribution as stolen. We further prove that DI also triggers FPs in realistic, non-linear suspect models. We then confirm empirically that DI in the black-box setting leads to FPs, with high confidence. Second, we show that DI also suffers from false negatives (FNs) -- an adversary can fool DI (at the cost of incurring some accuracy loss) by regularising a stolen model's decision boundaries using adversarial training, thereby leading to an FN. To this end, we demonstrate that black-box DI fails to identify a model adversarially trained from a stolen dataset -- the setting where DI is the hardest to evade. Finally, we discuss the implications of our findings, the viability of fingerprinting-based ownership verification in general, and suggest directions for future work.Comment: 19 pages; Accepted to Transactions on Machine Learning Research 06/202

An algorithm for Melnikov functions and application to a chaotic rotor

In this work we study a dynamical system with a complicated nonlinearity, which describes oscillation of a turbine rotor, and give an algorithm to compute Melnikov functions for analysis of its chaotic behavior. We first derive the rotor model whose nonlinear term brings difficulties to investigating the distribution and qualitative properties of its equilibria. This nonlinear model provides a typical example of a system for which the homoclinic and heteroclinic orbits cannot be analytically determined. In order to apply Melnikov's method to make clear the underlying conditions for chaotic motion, we present a generic algorithm that provides a systematic procedure to compute Melnikov functions numerically. Substantial analysis is done so that the numerical approximation precision at each phase of the computation can be guaranteed. Using the algorithm developed in this paper, it is straightforward to obtain a sufficient condition for chaotic motion under damping and periodic external excitation, whenever the rotor parameters are given