A cyclic quenching treatment (CQT) succeeded in turning a 2.3 GPa maraging steel with a Charpy impact energy of 9 J into a new grade with the same strength but a Charpy impact energy of 20 J upon 4 cyclic treatments. The improvement of mechanical properties is attributed to the refinement and increased chemical heterogeneity of the martensitic substructure, rather than the refinement of prior austenite grain (PAG), as well as the Transformation-Induced Plasticity (TRIP) effect facilitated by small austenite grains. The role of local segregation of Ni during CQT in the formation of Ni-rich austenite grains, Ni-rich martensite laths and Ni-poor martensite laths, was investigated and verified by DICTRA simulations. This study highlights the important influence of Ni partitioning behavior during CQT, providing insights into microstructural evolution and mechanical properties.

The honey password vault is a promising method for managing user passwords and mitigating password-guessing attacks by creating plausible-looking decoy password vaults. Recently, various methods, such as Chatterjee-PCFG (IEEE S&P’15), Golla-Markov (ACM CCS’16), and Cheng-IUV (USENIX Security’21), have been proposed to construct the cornerstone of honey password vaults, known as the distribution transforming encoder (DTE). These innovations significantly enhance the security and functionality of each kind of DTE. However, our findings indicate that when users employ multiple honey password vaults of distinct DTEs to manage their passwords, a passive attacker can easily compromise user passwords by exploiting differences among those DTEs. Consequently, we propose the differential attack targeting existing honey password vaults. The extensive experimental results confirm the effectiveness of this attack, distinguishing real from decoy password vaults with accuracy from 99.13% to 100.00%. In response, we design a novel, collaborative approach to train DTE, called federated DTE model, and construct a secure honey password vault. This strategy markedly bolsters security, reducing the differential attack's distinguishing accuracy to approximately 52.41%, nearing the ideal threshold of 50.00%. Our findings emphasize the need for collaborative strategies to maintain password security to combat advanced cyber threats.

Searchable symmetric encryption schemes often unintentionally disclose certain sensitive information, such as access, volume, and search patterns. Attackers can exploit such leakages and other available knowledge related to the user's database to recover queries. We find that the effectiveness of query recovery attacks depends on the volume/frequency distribution of keywords. Queries containing keywords with high volumes/frequencies are more susceptible to recovery, even when countermeasures are implemented. Attackers can also effectively leverage these “special” queries to recover all others. By exploiting the above finding, we propose a Jigsaw attack that begins by accurately identifying and recovering those distinctive queries. Leveraging the volume, frequency, and co-occurrence information, our attack achieves 90% accuracy in three tested datasets, which is comparable to previous attacks (Oya et al., USENIX' 22 and Damie et al., USENIX' 21). With the same runtime, our attack demonstrates an advantage over the attack proposed by Oya et al (approximately 15% more accuracy when the keyword universe size is 15k). Furthermore, our proposed attack outperforms existing attacks against widely studied countermeasures, achieving roughly 60% and 85% accuracy against the padding and the obfuscation, respectively. In this context, with a large keyword universe (≥3k), it surpasses current state-of-the-art attacks by more than 20%.

Dynamic Searchable Encryption (DSE) has emerged as a solution to efficiently handle and protect large-scale data storage in encrypted databases (EDBs). Volume leakage poses a significant threat, as it enables adversaries to reconstruct search queries and potentially compromise the security and privacy of data. Padding strategies are common countermeasures for the leakage, but they significantly increase storage and communication costs. In this work, we develop a new perspective on handling volume leakage. We start with distinct search and further explore a new concept called distinct DSE (d-DSE). We also define new security notions, in particular Distinct with Volume-Hiding security, as well as forward and backward privacy, for the new concept. Based on d-DSE, we construct the d-DSE designed EDB with related constructions for distinct keyword (d-KW-dDSE), keyword (KW-dDSE), and join queries (JOIN-dDSE) and update queries in encrypted databases. We instantiate a concrete scheme BF-SRE, employing Symmetric Revocable Encryption. We conduct extensive experiments on real-world datasets, such as Crime, Wikipedia, and Enron, for performance evaluation. The results demonstrate that our scheme is practical in data search and with comparable computational performance to the SOTA DSE scheme (MITRA*, AURA) and padding strategies (SEAL, ShieldDB). Furthermore, our proposal sharply reduces the communication cost as compared to padding strategies, with roughly 6.36 to 53.14x advantage for search queries.

The use of alkaline activator in alkali-activated materials (AAMs) may pose risk of alkali-silica reaction (ASR), and the variations in the mixture design could have great influence on the performance of AAMs system. In this case, this paper investigated the effects of slag fineness (3000–8000 cm²/g) and water-to-binder (w/b) ratio (0.5–0.8) on ASR behavior of alkali-activated slag (AAS) mortars under accelerated mortar testing conditions as specified in ASTM C1260. The length change, mass gain, microstructure and formation of ASR products were examined to evaluate the degradation caused by ASR. It was found for the first time that slag fineness induces a “pessimum effect” in the ASR expansion of AAS mortars. On the other hand, there is a “pessimum effect” in the influence of w/b ratio on ASR expansion in the early-stage (≤14d), and the induced expansion increased with an increase in w/b ratio in the late-stage (>14d). The mechanism governing the effect of slag fineness and w/b ratio is complicated and cannot be explained solely by the properties of ASR products. This work contributes to the understanding of ASR in AAMs system and could provide a basis for the mixture optimization of AAMs.

Searchable symmetric encryption enables private queries over an encrypted database, but it can also result in information leakages. Adversaries can exploit these leakages to launch injection attacks (Zhang et al., USENIX Security’16) to recover the underlying keywords from queries. The performance of the existing injection attacks is strongly dependent on the amount of leaked information or injection. In this work, we propose two new injection attacks, namely BVA and BVMA, by leveraging a binary volumetric approach. We enable adversaries to inject fewer files than the existing volumetric attacks by using the known keywords and reveal the queries by observing the volume of the query results. Our attacks can thwart well-studied defenses (e.g., threshold countermeasure, padding) without exploiting the distribution of target queries and client databases. We evaluate the proposed attacks empirically in real-world datasets with practical queries. The results show that our attacks can obtain a high recovery rate (> 80%) in the best-case scenario and a roughly 60% recovery even under a large-scale dataset with a small number of injections (< 20 files).

Dynamic searchable symmetric encryption (DSSE) has been widely recognized as a promising technique to delegate update and search queries over an outsourced database to an untrusted server while guaranteeing the privacy of data. Many efforts on DSSE have been devoted to obtaining a good tradeoff between security and performance. However, it appears that all existing DSSE works miss studying on what will happen if the DSSE client issues irrational update queries carelessly, such as duplicate update queries and delete queries to remove non-existent entries (that have been considered by many popular database system in the setting of plaintext). In this scenario, we find that (1) most prior works lose their claimed correctness or security, and (2) no single approach can achieve correctness, forward and backward security, and practical performance at the same time. To address this problem, we study for the first time the notion of robustness of DSSE. Generally, we say that a DSSE scheme is robust if it can keep the same correctness and security even in the case of misoperations. Then, we introduce a new cryptographic primitive named key-updatable pseudo-random function and apply this primitive to constructing ROSE, a robust DSSE scheme with forward and backward security. Finally, we demonstrate the efficiency of ROSE and give the experimental comparisons.

Many practical secure systems have been designed to prevent real-world attacks via maximizing the attacking cost so as to reduce attack intentions. Inspired by this philosophy, we propose a new concept named delay encryption with keyword search (DEKS) to resist the notorious keyword guessing attack (KGA), in the context of secure cloud-based searchable services. Avoiding the use of complex (and unreasonable) assumptions, as compared to existing works, DEKS optionally leverages a catalyst that enables one (e.g., a valid data user) to easily execute encryption; without the catalyst, any unauthenticated system insiders and outsiders take severe time consumption on encryption. By this, DEKS can overwhelm a KGA attacker in the encryption stage before it obtains any advantage. We leverage the repeated squaring function, which is the core building block of our design, to construct the first DEKS instance. The experimental results show that DEKS is practical in thwarting KGA for both small and large-scale datasets. For example, in the Wikipedia, a KGA attacker averagely takes 7.23 years to break DEKS when the delay parameter T= 2 ²⁴. The parameter T can be flexibly adjusted based on practical needs, and theoretically, its upper bound is infinite.

Mo is widely used as an effective microalloying element to improve mechanical performance of interphase precipitation steels, but the precise role of Mo in interphase precipitation behavior is not fully understood. In this contribution, interphase precipitation behavior in a series of Ti-Mo-bearing low carbon steels is systematically studied, and the role of Mo in interphase precipitates and its coarsening behavior is revisited. It is found that (Ti, Mo)C precipitates instead of TiC are formed in the Mo-containing alloys, and the average site fraction of Mo in (Ti, Mo)C is almost independent of the bulk Mo content. Moreover, the number density of interphase precipitates can be substantially enhanced by a minor addition of Mo, albeit it does not further rise with increasing the bulk Mo content. This is because the Mo fraction in (Ti, Mo)C rather than the bulk Mo content governs the driving force for precipitation nucleation and the interfacial energy of the (Ti, Mo)C/α and (Ti, Mo)C/γ interfaces. In addition to the reduced interfacial energy, decrease of Ti trans-interface diffusivity has been identified as another key reason for the enhanced carbide coarsening resistance in Mo-containing alloys.

Existing approaches to defending Use-After-Free (UAF) exploits are usually done using static or dynamic analysis. However, both static and dynamic analysis suffer from intrinsic deficiencies. The existing static analysis is limited in handling loops, optimization of memory representation. The existing dynamic analysis, which is characterized by lacking the maintenance of pointer information, may lead to flaws that the relationships between pointers and memory cannot be precisely identified. In this work, we propose a new method called UAF-GUARD without the above barriers, in the aim to defending against UAF exploits using fine-grained memory permission management. In particular, we design a key data structure to support the fine-grained memory permission management, which can maintain more information to capture the relationship between pointers and memory. Moreover, we design code instrumentation to enable UAF-GUARD to precisely locate the position of UAF vulnerabilities to further terminate malicious programs when anomalies are detected. We implement UAF-GUARD on a 64-bit Linux system. We carry out experiments to compare UAF-GUARD with the main existing approaches. The experimental results demonstrate that UAF-GUARD is able to effectively and efficiently defend against three types of UAF exploits with acceptable space overhead and time overhead.

Membrane fouling is still the main obstacle that hinders the development and implementation of anaerobic membrane bioreactor (AnMBR). In conventional upflow anaerobic reactors, sludge at different height usually presents certain differences in characteristics in terms of particle size, etc. The immersion depth of membrane modules in anaerobic reactors can also influence the fouling of membrane. Thus, it is of great interest to investigate the fouling mechanism with the membrane installed at different heights in reactors. The filtration performance and sludge properties were investigated at different heights of AnMBR. The fouling of membrane in the middle position was severer than that in the top and bottom positions. The total resistance of membrane in the top, middle, and bottom positions was 27.31 × 10¹¹ m⁻¹, 34.67 × 10¹¹ m⁻¹, and 25.29 × 10¹¹ m⁻¹, respectively. By comparing the characteristics and structure of bulk sludge and cake layer at three heights, the bulk sludge in the middle position presented higher content of soluble microbial products (SMP) and finer flocs, and the cake layer was also denser. The results obtained in this study indicated that small size of sludge flocs as well as adhesion of SMP might be the major factors governing membrane fouling at different height in the AnMBR.

Sludge morphology considerably affects the mechanism underlying microbial anaerobic degradation of phenol. Here, we assessed the phenol degradation rate, specific methanogenic activity, electron transport activity, coenzyme F₄₂₀ concentration, and microbial community structure of five phenol-degrading sludge of varying particle sizes (i.e., < 20, 20–50, 50–100, 100–200, and > 200 μm). The results indicated an increase in phenol degradation rate and microbial community structure that distinctly correlated with an increase in sludge particle size. Although the sludge with the smallest particle size (< 20 μm) showed the lowest phenol degradation rate (9.3 mg COD·gVSS⁻¹ day⁻¹), its methanogenic activity with propionic acid, butyric acid, and H₂/CO₂ as substrates was the best, and the concentration of coenzyme F₄₂₀ was the highest. The small particle size sludge did not contain abundant syntrophic bacteria or hydrogenotrophic methanogens, but contained abundant acetoclastic methanogens. Moreover, the floc sizes of the different sludge varied in important phenol-degrading bacteria and archaea, which may dominate the synergistic mechanism. This study provides a new perspective on the role of sludge floc size on the anaerobic digestion of phenol.

Anammox process is considered as a promising technology for removing total nitrogen from low-strength ammonium and phenol-containing wastewater. However, it is still a challenge for the anammox process to treat high-strength ammonium and phenol-containing wastewater. A completely separated partial nitritation and anammox (CSPN/A) process was developed to remove total nitrogen from high-strength phenol-containing wastewater. About 92% of COD, 100% of phenol, and 82.4% of total nitrogen were successfully removed at a NH₄ ⁺-N concentration of 200 mg L⁻¹ with a phenol/NH₄ ⁺-N mass ratio of 0.5 in the CSPN/A process. Furthermore, a shock loading of 300 mg phenol L⁻¹ with a phenol/NH₄ ⁺-N mass ratio of 1.5 led to a complete failure of partial nitritation, but the performance was rapidly recovered by the increase of NH₄ ⁺-N concentration. Although the activities of ammonium-oxidizing bacteria and anammox bacteria were severely inhibited at a phenol/NH₄ ⁺-N mass ratio of 1.5, the enrichment of efficient phenol degraders in the CSPN stage could strengthen the performance robustness of partial nitritation and anammox process. Therefore, this study presented a new insight on the feasibility of the anammox process for treating high-strength ammonium and phenol-containing wastewater.

For traffic flow models, calibration and validation are essential. Cellular automaton (CA) models are a special class of models, describing the movement of vehicles in discretised space and time. However, the previous work on calibration and validation does not discuss CA models systematically. This study calibrates and validates a stochastic CA model. The authors use a simple CA model, which only has two important parameters to be calibrated. The methodology for optimisation is to minimise the relative root mean square error between two properties: The averaged velocity and the variation of velocities in a platoon at a given density. Three different sites are used as cases to show the methodology, for which different types of data (video trajectories or GPS data) are available. The authors find that the best model parameters vary for the different locations. This may result from various driving strategies and potential tendencies. Thus, it is concluded that for CA models, various traffic flow phenomena need to be simulated by various parameters.

The interaction between moving α/γ interfaces and interphase precipitated (IPd) carbides during the austenite (γ) to ferrite (α) and the ferrite (α) to austenite (γ) transformation has been systematically investigated through cyclic phase transformation experiments for a 0.1C-1.5Mn alloy containing 0.1 wt% Niobium (Nb) and its Nb-free counterpart. Shifts in the critical reaction temperatures during continuous heating and cooling are observed, which are attributed to the pinning force (PF) originating from the IPd carbides present. By applying the Gibbs energy balance (GEB) model to analyze experimental results, the PF was derived to be about 15 J/mol for the α→γ transformation and about 5 J/mol for the γ→α transformation, respectively, both of which are quite small compared to chemical driving force of phase transformations. Moreover, various modified Zener pinning equations have also been used to predict the PF, and it was found that these values are comparable with those obtained from experiments, which suggests that the classical Zener theory still has promising potential for carbide-interface interaction analysis.