Static Assumptions Research Articles

Continuous leakage-resilient identity-based encryption with leakage amplification

In modern computer systems, leakage of private information may cause catastrophic consequences, especially those are related to the secret keys in cryptographic mechanisms. Therefore, it has been widely accepted both in academia and industry that cryptographic schemes should withstand various leakage attacks, including the continuous leakage attacks. Although a lot of researches have been conducted towards this issue and some progresses have been made, there are still many unsolved problems in this area. For example, in the majority of the existing identity-based encryption (IBE) schemes with (continuous) leakage resilience, the upper bound of leakage is required to be fixed. But in many real-world applications, such a requirement is inadequate to protect the schemes against the leakage attacks. Moreover, many previous efforts aiming to build IBE schemes that are secure against the chosen-ciphertext attacks (CCA) need to rely on the q-type assumptions. But these solutions are not desirable, because the q-type assumptions are non-static assumptions. In this paper, in order to address the above mentioned problems, we demonstrate how to construct a continuous leakage-resilient CCA-secure IBE scheme with leakage amplification, in which the leakage parameter has an arbitrary length. The benefit is that the length of permitted leakage in our scheme can be adjusted flexibly according to the leakage requirements. Moreover, the security of our proposed scheme can be proved with static assumptions in the standard model. Compared with the related works in the literature, our scheme enjoys a unique feature that it allows continuous leakage of multiple keys simultaneously, e.g. continuous leakage of the master secret key as well as the user’s private key.

The Mismatch of Intrinsic Fluctuations and the Static Assumptions of Linear Statistics

The social and cognitive science replication crisis is partly due to the limitations of commonly used statistical tools. Inferential statistics require that unsystematic measurement variation is independent of system history, and weak relative to systematic or causal sources of variation. However, contemporary systems research underscores the dynamic, adaptive nature of social, cognitive, and behavioral systems. Variation in human activity includes the influences of intrinsic dynamics intertwined with changing contextual circumstances. Conventional inferential techniques presume milder forms of variability, such as unsystematic measurement error, as in a Gaussian distribution. Inferential statistics indicate an elementary Newtonian cause-effect metaphor for change that is inconsistent with known principles of change in complex systems. Pattern formation in self-organizing systems and quantum probability are used to illustrate theoretical metaphors that instantiate alternative notions of change in complex systems. Inferential statistics and related techniques are crucial scientific resources. However, in the social and behavioral sciences, they must be practiced in conjunction with an appropriate general systems framework that accommodates intrinsic fluctuations and contextual adaptation.

Efficient chosen-ciphertext secure hybrid encryption scheme tolerating continuous leakage attacks

ABSTRACTFor any PPT adversary, most traditional leakage-resilient cryptographic primitives cannot ensure that all elements in ciphertext are random. What’s worse, in a continuous leakage setting, there are few leakage-resilient cryptographic primitives available. Currently, not many researchers are studying leakage-resilient hybrid encryption (LR-HE) scheme. Thus, two continuous leakage-resilient hybrid encryption (CLR-HE) schemes are constructed in this paper, and the schemes’ security are proven based on the standard static assumption. Our constructions not only can maintain their claimed security in a continuous leakage setting, but also enjoy better performances. Because of these good performances, our constructions can provide continuous leakage-resilient security in the Internet of Things.

Hidden Ciphertext Policy Attribute-Based Encryption With Fast Decryption for Personal Health Record System

Since cloud computing has been playing an increasingly important role in real life, the privacy protection in many fields has been paid more and more attention, especially, in the field of personal health record (PHR). The traditional ciphertext-policy attribute-based encryption (CP-ABE) provides the fine-grained access control policy for encrypted PHR data, but the access policy is also sent along with ciphertext explicitly. However, the access policy will reveal the users' privacy, because it contains too much sensitive information of the legitimate data users. Hence, it is important to protect users' privacy by hiding access policies. In most of the previous schemes, although the access policy is hidden, they face two practical problems: 1) these schemes do not support large attribute universe, so their practicality in PHR is greatly limited and 2) the cost of decryption is especially high since the access policy is embedded in the ciphertext. To address these problems, we construct a CP-ABE scheme with efficient decryption, where both the size of public parameters and the cost of decryption are constant. Moreover, we also show that the proposed scheme achieves full security in the standard model under static assumptions by using the dual system encryption method.

SOF-SLAM: A Semantic Visual SLAM for Dynamic Environments

Simultaneous Localization and Mapping (SLAM) plays an important role in the computer vision and robotics field. The traditional SLAM framework adopts a strong static world assumption for analysis convenience. How to cope with dynamic environments is of vital importance and attracts more attentions. Existing SLAM systems toward dynamic scenes either solely utilize semantic information, solely utilize geometry information, or naively combine the results from them in a loosely coupled way. In this paper, we present SOF-SLAM: Semantic Optical Flow SLAM, a visual semantic SLAM system toward dynamic environments, which is built on RGB-D mode of ORB-SLAM2. A new dynamic features detection approach called semantic optical flow is proposed, which is a kind of tightly coupled way and can fully take advantage of feature's dynamic characteristic hidden in semantic and geometry information to remove dynamic features effectively and reasonably. The pixel-wise semantic segmentation results generated by SegNet serve as mask in the proposed semantic optical flow to get a reliable fundamental matrix, which is then used to filter out the truly dynamic features. Only the remaining static features are reserved in the tracking and optimization module to achieve accurate camera pose estimation in dynamic environments. Experiments on public TUM RGB-D dataset and in real-world environment are conducted. Compared with ORB-SLAM2, the proposed SOF-SLAM achieves averagely 96.73% improvements in high-dynamic scenarios. It also outperforms the other four state-of-the-art SLAM systems which cope with the dynamic environments.

Identity-Based Revocation From Subset Difference Methods Under Simple Assumptions

Identity-based revocation (IBR) is a specific kind of broadcast encryption that can effectively send ciphertext to a set of receivers. In IBR, a ciphertext is associated with a set of revoked users instead of a set of receivers and the maximum number of users in the system can be an exponential value in the security parameter. In this paper, we reconsider the general method of Lee et al. (ESORICS 2014) that constructs a public-key revocation (PKR) scheme by combining the subset difference (SD) method of Naor, Naor, and Lotspiech (CRYPTO 2001) and a single revocation encryption (SRE) scheme. Lee et al. left it as an open problem to construct an SRE scheme under the standard assumption without random oracles. In this paper, we first propose a selectively secure SRE scheme under the standard assumption without random oracles. We also propose a fully secure SRE scheme under simple static assumptions without random oracles. Next, we present an efficient IBR scheme that supports fast decryption by combining the SD method and our SRE scheme. The security of our IBR scheme depends on that of the underlying SRE scheme. Finally, we implemented our SRE and IBR schemes and measured the performance.

Stitching the cloths of serial migrant life: The quilts of Barbara James

Abstract In this article, I study the quilting practice of Barbara James to investigate the making of serial migrant subjects. Serial migrants are not from a single place, nor do they travel in the same direction. They have moved beyond a first experience of immigration and in so doing, step beyond the home/host dualities of immigration. One might see the project of following their paths as a move from accounts of the creative, imaginative ‘third space’ produced by immigrants’ arrival in their new homes, toward a consideration of the concrete ‘third place’ of the second or third-time immigrant. Exile, economic migrant, love migrant, exchange student, refugee: a serial migrant adds up not just several identities but systems of categorisation over time. This migratory subject often changes ‘positions’ not only geographically but socially, making us question the static assumptions of social theory with their experiences of diverse approaches to nationality, class, race, ethnicity and gender.

Privacy-Preserving Aggregation of Time-Series Data with Public Verifiability from Simple Assumptions and Its Implementations

Aggregator oblivious encryption was proposed by Shi et al. (NDSS 2011). In this method, an aggregator can compute an aggregated sum of data and is unable to learn anything else (aggregator obliviousness). Since the aggregator does not learn individual data that may reveal users’ habits and behaviors, several applications including privacy-preserving smart metering have been considered. In this paper, we propose an aggregator oblivious encryption scheme with public verifiability where the aggregator is required to generate a proof of an aggregated sum, and anyone can verify whether the aggregated sum has been correctly computed by the aggregator. Although Leontiadis et al. (CANS 2015) considered verifiability, their scheme requires an interactive complexity assumption to provide the unforgeability of the proof. Our scheme is proven to be unforgeable under a static and simple assumption (a variant of the Computational Diffie–Hellman assumption). Moreover, our scheme inherits the tightness of the reduction of the Benhamouda et al. scheme (ACM TISSEC 2016) for proving aggregator obliviousness. This tight reduction allows us to employ elliptic curves of a smaller order and leads to efficient implementation. Specifically, for 112-bit security, we can employ Barreto–Naehrig (BN) curves with a 383-bit prime order, whereas we need to employ curves with a 1031-bit prime order to implement the Leontiadis et al. scheme. We give implementations of two schemes and evaluate their performances under those curves. We employ a Raspberry-Pi as a power-constrained device such as a smart meter. Consequently, we demonstrate that the running time of the data encryption, data aggregation and verification in our scheme are reduced by approximately 74%, 64% and 89%, respectively, compared to those of the Leontiadis et al. scheme.

Effect of Head Types on the Free Vibration and Fatigue for Horizontal LPG Pressure Vessels

Pressure vessels are the heart of plants and oil refineries stations. In many engineering applications such vessels can be subjected to periodic loading either internally due to the charging and discharging process or externally due to the excitation from other nearby components such as pumps, compressors or from seismic. So that in spite of a good design according static assumption it may be critical in dynamics. In this work a horizontal pressure vessel with accessories subjected to liquefied petroleum gas pressure LPG is considered. Three models of different head types are investigated herein namely; Deep torispherical, Elliptical 2:1 and Hemispherical. The design and material selections are chosen as per ASME. For practical service many accessories are attached to the vessel such as manhole, supports, inlet and outlet opining. Finite Element method via ANSYS R18.2 is introduced for the numerical analysis. The fatigue life in case of fully reversed cyclic loading are estimated and located. Vibration characteristics such as mode shapes and natural frequencies for the lowest five modes are evaluated and compared. It is found that the fatigue life can be increased as higher as 180% for hemi- spherical head as compared with deep torispherical head pressure vessel and the lowest four natural frequencies are nearly identical for all models, however significant change observed in the fifth natural frequency.

Linguistic landscapes as pornoheterotopias

Abstract Drawing on multimodal analysis of graffiti in male public restrooms at the Faculdade de Letras of the Universidade Federal do Rio de Janeiro, this paper investigates how notions of place and gendered/sexualized subjects are discursively (re)constructed in interactions with the materiality and historicity of the public realm. The analysis focuses on the indexicalities of public signage and the ways they (in)form understandings of and access to certain spaces. By investigating the fragmented history of entextualizations of these toilet graffiti as well as the indexicalities of their lexical, graphic, and co(n)textual aspects, we argue that places can be queered since they are semiotically constructed and discursively performed. The paper illustrates how static assumptions about place, gender, and sexuality can be disrupted and ressignified which highlights the pornoheterotopic character of these public restrooms in which semiotic processes that (de)regulate gender and sexual dissidence are emplaced.

The generic construction of continuous leakage-resilient identity-based cryptosystems

In the leakage setting, the adversary is allowed to access the internal secret states of a cryptosystem, such as the private key of user and the master secret key. In the continuous leakage model, there is no predetermined bound on the leakage of internal secret states; therefore, it is more challenging. In this paper, we present a new primitive called updatable identity-based hash proof system (U-IB-HPS), which can serve as a fundamental tool for constructing continuous leakage-resilient identity-based cryptosystems. With the U-IB-HPS, we obtain the generic constructions of identity-based cryptosystem with continuous leakage-resilience, such as the continuous leakage-resilient identity-based encryption with leakage amplification, the continuous leakage-resilient identity-based hybrid encryption with leakage amplification, etc. As a feature of our generic constructions, we allow the leakage of multiple keys, i.e., leakage of the master secret key and the private key of user. In addition, we present a generic framework of one-round identity-based authenticated key exchange (AKE) protocol with continuous leakage resilience, which ensures the session key security even if the adversary performs continuous leakage attacks during the execution of a session. We also present instantiations of U-IB-HPS from bilinear groups and composite order bilinear groups, respectively. The security of our instantiations is based on the standard static assumptions, such as the decisional bilinear Diffie–Hellman assumption, the corresponding complexity assumptions over composite order bilinear groups, etc. Our instantiations can be easily extended to construct the updatable hierarchical identity-based hash proof system.

Key-policy attribute-based encryption against continual auxiliary input leakage

Attribute-based encryption mechanism can achieve very flexible access control, so it has a wide range of applications in the distributed environment, such as fine-grained access control, audit log applications, cloud storage systems. Key-policy attribute-based encryption (KP-ABE) scheme is especially suitable for video on demand, pay TV, etc. Most of the existing KP-ABE schemes do not consider the side channel attacks which probably leak some secret information about the cryptosystems. In the paper, we present the formal definition and security model of key-policy attribute-based encryption scheme which is resilient to continual auxiliary input (CAI) leakage. What is more, we present a concrete KP-ABE scheme. The proposed scheme is proved secure under the static assumptions.

Valuing the unknown: could the real options have redeemed the ailing Western Australian junior iron ore operations in 2013–2016 iron price crash

ABSTRACTThe inability of existing analytical models to accurately predict future events has, at times, led to the economic failure of mining operations whose financial viabilities were determined based on static assumptions, leaving operational managers with little room to make future decisions. Therefore, the application of a robust decision-making tool, such as Real Options (RO) can minimise losses and more accurately express uncertainty. This paper has considered a stochastic simulation to analyse ROs for a real case iron ore mine, which closed in April 2016. In comparing the net present value from the traditional discounted cash flow (DCF) method to delay, to abandon the operations and to stage the investment options, the ROs method increased the project value by between 56% and 195% depending on the volatility. As a new contribution, a managerial flexibility domain map is proposed in this paper. Thus, flexibility in mining operations creates agility, increases value and mitigates financial losses.

Climate Change and Future Wildfire in the Western United States: An Ecological Approach to Nonstationarity

AbstractWe developed ecologically based climate‐fire projections for the western United States. Using a finer ecological classification and fire‐relevant climate predictors, we created statistical models linking climate and wildfire area burned for ecosections, which are geographic delineations based on biophysical variables. The results indicate a gradient from purely fuel‐limited (antecedent positive water balance anomalies or negative energy balance anomalies) to purely flammability‐limited (negative water balance anomalies or positive energy balance anomalies) fire regimes across ecosections. Although there are other influences (such as human ignitions and management) on fire occurrence and area burned, seasonal climate significantly explains interannual fire area burned. Differences in the role of climate across ecosections are not random, and the relative dominance of climate predictors allows objective classification of ecosection climate‐fire relationships. Expected future trends in area burned range from massive increases, primarily in flammability limited systems near the middle of the water balance deficit distribution, to substantial decreases, in fuel‐limited nonforested systems. We predict increasing area burned in most flammability‐limited systems but predict decreasing area burned in primarily fuel‐limited systems with a flammability‐limited (“hybrid”) component. Compared to 2030–2059 (2040s), projected area burned for 2070–2099 (2080s) increases much more in the flammability and flammability‐dominated hybrid systems than those with equal control and continues to decrease in fuel‐limited hybrid systems. Exceedance probabilities for historical 95th percentile fire years are larger in exclusively flammability‐limited ecosections than in those with fuel controls. Filtering the projected results using a fire‐rotation constraint minimizes overprojection due to static vegetation assumptions, making projections more conservative.

Connecting discrete particle mechanics to continuum granular micromechanics: Anisotropic continuum properties under compaction

A systematic and mechanistic connection between granular materials’ macroscopic and grain level behaviors is developed for monodisperse systems of spherical elastic particles under die compaction. The Granular Micromechanics Approach (GMA) with static assumption is used to derive the stiffness tensor of transversely isotropic materials, from the average behavior of particle-particle interactions in all different directions at the microscale. Two particle-scale directional density distribution functions, namely the directional distribution of a combined mechano-geometrical property and the directional distribution of a purely geometrical property, are proposed and parametrized by five independent parameters. Five independent components of the symmetrized tangent stiffness tensor are also determined from discrete particle mechanics (PMA) calculations of nine perturbations around points of the loading path. Finally, optimal values for these five GMA parameters were obtained by minimizing the error between PMA calculations and GMA closed-form predictions of stiffness tensor during the compaction process. The results show that GMA with static assumption is effective at capturing the anisotropic evolution of microstructure during loading, even without describing contacts independently but rather accounting for them in an average sense.

Evolution of the United States Energy System and Related Emissions under Varying Social and Technological Development Paradigms: Plausible Scenarios for Use in Robust Decision Making.

The energy system is the primary source of air pollution. Thus, evolution of the energy system into the future will affect society's ability to maintain air quality. Anticipating this evolution is difficult because of inherent uncertainty in predicting future energy demand, fuel use, and technology adoption. We apply scenario planning to address this uncertainty, developing four very different visions of the future. Stakeholder engagement suggested that technological progress and social attitudes toward the environment are critical and uncertain factors for determining future emissions. Combining transformative and static assumptions about these factors yields a matrix of four scenarios that encompass a wide range of outcomes. We implement these scenarios in the U.S. Environmental Protection Agency MARKet ALlocation (MARKAL) model. Results suggest that both shifting attitudes and technology transformation may lead to emission reductions relative to the present, even without additional policies. Emission caps, such as the Cross-State Air-Pollution Rule, are most effective at protecting against future emission increases. An important outcome of this work is the scenario-implementation approach, which uses technology-specific discount rates to encourage scenario-specific technology and fuel choices. End-use energy demands are modified to approximate societal changes. This implementation allows the model to respond to perturbations in manners consistent with each scenario.

Identity-based encryption with hierarchical key-insulation in the standard model

A key exposure problem is unavoidable since it seems human error can never be eliminated completely, and key-insulated encryption is one of the cryptographic solutions to the problem. At Asiacrypt’05, Hanaoka et al. introduced hierarchical key-insulation functionality, which is attractive functionality that enhances key exposure resistance, and proposed an identity-based hierarchical key-insulated encryption (hierarchical IKE) scheme in the random oracle model. In this paper, we first propose the hierarchical IKE scheme in the standard model (i.e., without random oracles). Our hierarchical IKE scheme is secure under the symmetric external Diffie–Hellman ( $$\mathsf{SXDH}$$ ) assumption, which is a static assumption. Particularly, in the non-hierarchical case, our construction is the first IKE scheme that achieves constant-size parameters including public parameters, secret keys, and ciphertexts. Furthermore, we also propose the first public-key-based key-insulated encryption (PK-KIE) in the hierarchical setting by using our technique.

A rotary radiation structure for microwave heating uniformity improvement

A novel microwave heating method with rotary radiation structure has been proposed to improve heating uniformity. Through time division of the whole heating process, static heating assumption of each time step and temperature inheritance between time steps, a simulation model has been built and computed based on the finite element method combined with programming. A quantitative validation of simulation results has been performed with physical experiments. Heating uniformity and heating efficiency of the proposed method has been compared with those of two traditional methods, by which a potato slice is heated with a turntable and heated statically. The results show that the rotary radiation structure has an obvious superiority. What is more, influences of positions of the waveguide that feeds microwave and its placing directions of the proposed method have also been discussed.

Monitoring the Number of Vehicles on Highway Using Frame Difference Method

<p>Indonesia is a country with the third largest motorcycle rider in the world after China and India. One of the biggest cities in Indonesia is Bandung is a city that often experience traffic congestion, especially during peak hours and weekends because of population growth, urbanization and transmigration has increased and not comparable with the growth and development of adequate infrastructure so that frequent traffic jams.</p><p>In this study, the authors developed a traffic monitoring system to calculate the number of vehicles using the Frame Difference method. To implement the method contained in this paper in calculating the number of vehicles passing on a highway by using two different points of view. The assumption in this research is using static background assumption.</p><p>Based on the result of the research, it is found that the performance of video from Toll Pasteur with the viewing angle has 8.21% error and Purbaleunyi Toll with vertical angle has 4.43% error by using some filter and morphological operation. Conversely, if without using filters and morphological operations have an error of 175.22% in Pasteur Toll and 115.44% at Purbaleunyi Toll.</p>

When Good Machine Learning Leads to Bad Security

While machine learning has proven to be promising in several application domains, our understanding of its behavior and limitations is still in its nascent stages. One such domain is that of cybersecurity, where machine learning models are replacing traditional rule based systems, owing to their ability to generalize and deal with large scale attacks which are not seen before. However, the naive transfer of machine learning principles to the domain of security needs to be taken with caution. Machine learning was not designed with security in mind and as such is prone to adversarial manipulation and reverse engineering. While most data based learning models rely on a static assumption of the world, the security landscape is one that is especially dynamic, with an ongoing never ending arms race between the system designer and the attackers. Any solution designed for such a domain needs to take into account an active adversary and needs to evolve over time, in the face of emerging threats. We term this as the "Dynamic Adversarial Mining" problem, and this paper provides motivation and foundation for this new interdisciplinary area of research, at the crossroads of machine learning, cybersecurity, and streaming data mining.