Decentralized Inner-Product Encryption with Constant-Size Ciphertext

With the rise of technology in recent years, more people are studying distributed system architecture, such as the e-government system. The advantage of this architecture is that when a single point of failure occurs, it does not cause the system to be invaded by other attackers, making the entire system more secure. On the other hand, inner product encryption (IPE) provides fine-grained access control, and can be used as a fundamental tool to construct other cryptographic primitives. Lots of studies for IPE have been proposed recently. The first and only existing decentralized IPE was proposed by Michalevsky and Joye in 2018. However, some restrictions in their scheme may make it impractical. First, the ciphertext size is linear to the length of the corresponding attribute vector; second, the number of authorities should be the same as the length of predicate vector. To cope with the aforementioned issues, we design the first decentralized IPE with constant-size ciphertext. The security of our scheme is proven under the ℓ-DBDHE assumption in the random oracle model. Compared with Michalevsky and Joye’s work, ours achieves better efficiency in ciphertext length and encryption/decryption cost.

PSII-5 Effect of progressive limit feeding in feedlot steers: A pilot study

The objective was to analyze the effect of progressive limit feeding on growth and performance during the finishing phase in feedlot steers. Thirty-nine steers (BW = 469 ± 31 kg) were divided into three blocks by weight. In each block, five steers were randomly assigned to a pen to be progressively limit fed (PLF), while the remaining eight steers were fed a common finishing diet ad libitum in a control (CON) pen. Progressive limit feeding refers to maintaining a previously growing animal at constant size by reducing the amount of feed offered by 3.29% daily for 14 consecutive days. Thus, on d 14, PLF steers were consuming 63% of original dry matter intake (DMI). All steers were fed ad libitum from d 15 until slaughter (d 106). Steers were fed a finishing diet, consisting primarily of dry-rolled corn, corn silage, and modified wet distillers grains. Data were analyzed using the MIXED procedure of SAS 9.4. Final BW was not affected (P = 0.82) by treatment; PLF and CON steers were 665 and 669 kg, respectively. Treatment did not affect overall ADG (P = 0.73); however, treatment did affect (P = 0.01) d 15–83 ADG as PLF steers gained 2.28 kg/d compared with 1.90 kg/d for CON steers. Overall DMI of PLF steers was 9% less (P = 0.02) than for CON steers (9.9 and 10.9 kg/d, respectively). Treatment did not affect (P = 0.10) DMI from d 15–106. Overall gain:feed (0.183 and 0.173 for PLF and CON steers, respectively) was not affected (P = 0.46) by treatment. Carcass characteristics were not affected (P ≥ 0.24) by treatment. A similar overall growth performance and reduced DMI for PLF steers suggests that progressive limit feeding may be a cost-effective approach to finishing feedlot steers.

Efficient access control with traceability and user revocation in IoT

With the universality and availability of Internet of Things (IoT), data privacy protection in IoT has become a hot issue. As a branch of attribute-based encryption (ABE), ciphertext policy attribute-based encryption (CP-ABE) is widely used in IoT to offer flexible one-to-many encryption. However, in IoT, different mobile devices share messages collected, transmission of large amounts of data brings huge burdens to mobile devices. Efficiency is a bottleneck which restricts the wide application and adoption of CP-ABE in Internet of things. Besides, the decryption key in CP-ABE is shared by multiple users with the same attribute, once the key disclosure occurs, it is non-trivial for the system to tell who maliciously leaked the key. Moreover, if the malicious mobile device is not revoked in time, more security threats will be brought to the system. These problems hinder the application of CP-ABE in IoT. Motivated by the actual need, a scheme called traceable and revocable ciphertext policy attribute-based encryption scheme with constant-size ciphertext and key is proposed in this paper. Compared with the existing schemes, our proposed scheme has the following advantages: (1) Malicious users can be traced; (2) Users exiting the system and misbehaving users are revoked in time, so that they no longer have access to the encrypted data stored in the cloud server; (3) Constant-size ciphertext and key not only improve the efficiency of transmission, but also greatly reduce the time spent on decryption operation; (4) The storage overhead for traceability is constant. Finally, the formal security proof and experiment has been conducted to demonstrate the feasibility of our scheme.

Exact simulation of the genealogical tree for a stationary branching population and application to the asymptotics of its total length

We consider a model of a stationary population with random size given by a continuous-state branching process with immigration with a quadratic branching mechanism. We give an exact elementary simulation procedure for the genealogical tree of n individuals randomly chosen among the extant population at a given time. Then we prove the convergence of the renormalized total length of this genealogical tree as n goes to infinity; see also Pfaffelhuber, Wakolbinger and Weisshaupt (2011) in the context of a constant-size population. The limit appears already in Bi and Delmas (2016) but with a different approximation of the full genealogical tree. The proof is based on the ancestral process of the extant population at a fixed time, which was defined by Aldous and Popovic (2005) in the critical case.

SIS Epidemic Model Birth-and-Death Markov Chain Approach

We are interested in describing the dynamics of the infected size of the SIS Epidemic model using the Birth-Death Markov process. The Susceptible-Infected-Susceptible (SIS) model is defined within a population of constant size $M$; the size is kept constant by replacing each death with a newborn healthy individual. The life span of each individual in the population is modelled by an exponential distribution with parameter $\alpha$; the disease spreads within the population is modelled by a Poisson process with a rate $\lambda_{I}$. $\lambda_{I}=\beta I(1-\frac{I}{M}) $ is similar to the instantaneous rate in the logistic population growth model. The analysis is focused on the disease outbreak, where the reproduction number $R=\frac{\beta} {\alpha} $ is greater than one. As methodology, we use both numerical and analytical approaches. The numerical approach shows that the infected size dynamics converge to a stationary stochastic process. And the analytical results determine the distribution of the stationary stochastic process as a normal distribution with mean $(1-\frac{1}{R}) M$ and Variance $\frac{M}{R} $ when $M$ becomes larger.

Multi-Blockchain-Based IoT Data Processing Techniques to Ensure the Integrity of IoT Data in AIoT Edge Computing Environments

As the development of IoT technologies has progressed rapidly recently, most IoT data are focused on monitoring and control to process IoT data, but the cost of collecting and linking various IoT data increases, requiring the ability to proactively integrate and analyze collected IoT data so that cloud servers (data centers) can process smartly. In this paper, we propose a blockchain-based IoT big data integrity verification technique to ensure the safety of the Third Party Auditor (TPA), which has a role in auditing the integrity of AIoT data. The proposed technique aims to minimize IoT information loss by multiple blockchain groupings of information and signature keys from IoT devices. The proposed technique allows IoT information to be effectively guaranteed the integrity of AIoT data by linking hash values designated as arbitrary, constant-size blocks with previous blocks in hierarchical chains. The proposed technique performs synchronization using location information between the central server and IoT devices to manage the cost of the integrity of IoT information at low cost. In order to easily control a large number of locations of IoT devices, we perform cross-distributed and blockchain linkage processing under constant rules to improve the load and throughput generated by IoT devices.

UPAYA MENINGKATKAN HASIL BELAJAR MENGGUNAKAN MODEL TALKING STICK PADA MATA PELAJARAN PAI DI SMP

This study aims to improve the learning value of class VII A students of SMP Negeri 4 Pontianak. This research was conducted in two cycles, each of which had planning, implementation, observation and reflection. Data anatysis techniques that guide data management use a percentage (%) with a constant size of 100. Learning values are obtained from students test score of formative tests in the evaluation activities of each cycle. The result of study in cycle I showed that the average of learning value of students was 76.8 dan in cycle II showed that the average of learneng value of students increased to 80.9. Keywords : Enhancement, Learning Value, PAI, Talking Stick Model,