Relations among Security Metrics for Template Protection Algorithms

Many biometric template protection algorithms have been proposed mainly in two approaches: biometric feature transformation and biometric cryptosystem. Security evaluation of the proposed algorithms are often conducted in various inconsistent manner. Thus, it is strongly demanded to establish the common evaluation metrics for easier comparison among many algorithms. Simoens et al. and Nagar et al. proposed good metrics covering nearly all aspect of requirements expected for biometric template protection algorithms. One drawback of the two papers is that they are biased to experimental evaluation of security of biometric template protection algorithms. Therefore, it was still difficult mainly for algorithms in biometric cryptosystem to prove their security according to the proposed metrics. This paper will give a formal definitions for security metrics proposed by Simoens et al. and Nagar et al. so that it can be used for the evaluation of both of the two approaches. Further, this paper will discuss the relations among several notions of security metrics

Compiler Provenance Recovery for Multi-CPU Architectures Using a Centrifuge Mechanism

Bit-stream recognition (BSR) has many applications, such as forensic investigations, detection of copyright infringement, and malware analysis. We propose the first BSR that takes a bare input bit-stream and outputs a class label without any preprocessing. To achieve our goal, we propose a centrifuge mechanism, where the upstream layers (sub-net) capture global features and tell the downstream layers (main-net) to switch the focus, even if a part of the input bit-stream has the same value. We applied the centrifuge mechanism to compiler provenance recovery, a type of BSR, and achieved excellent classification. Additionally, downstream transfer learning (DTL), one of the learning methods we propose for the centrifuge mechanism, pre-trains the main-net using the sub-net's ground truth instead of the sub-net's output. We found that sub-predictions made by DTL tend to be highly accurate when the sub-label classification contributes to the essence of the main prediction.Comment: 8 pages, 4 figures, 5 table

Mesenteric follicular lymphoma

When you see a patient with solid mesenteric tumors, malignant lymphoma should be considered as an important differential diagnosis. It is essential to include abdominal CT and F-18-FDG PET/CT examinations in these patients for early diagnosis of malignant lymphoma, giving extra weight on patients' complaints

Probabilistic micropayments with transferability

Micropayments are one of the challenges in cryptocurrencies. The problems in realizing micropayments in the blockchain are the low throughput and the high blockchain transaction fee. As a solution, decentralized probabilistic micropayment has been proposed. The winning amount is registered in the blockchain, and the tickets are issued to be won with probability $p$, which allows us to aggregate approximately $\frac{1}{p}$ transactions into one. Unfortunately, existing solutions do not allow for ticket transferability, and the smaller $p$, the more difficult it is to use them in the real world. We propose a novel decentralized probabilistic micropayment Transferable Scheme. It allows tickets to be transferable among users. By allowing tickets to be transferable, we can make $p$ smaller. We also propose a novel Proportional Fee Scheme. This is a scheme where each time a ticket is transferred, a portion of the blockchain transaction fee will be charged. With the proportional fee scheme, users will have the advantage of sending money with a smaller fee than they would generally send through the blockchain. For example, sending one dollar requires only ten cents

Anonymous probabilistic payment in payment hub

Privacy protection and scalability are significant issues with blockchain. We propose an anonymous probabilistic payment under the general functionality for solving them. We consider the situation that several payers pay several payees through a tumbler. We have mediated the tumbler of the payment channel hub between payers and payees. Unlinkability means that the link, which payer pays which payee via the tumbler, is broken. A cryptographic puzzle plays a role in controlling the intermediation and execution of transactions. Masking the puzzle enables the payer and the payee to unlink their payments. The overview of the proposed protocol is similar to TumbleBit (NDSS 2017). We confirm the protocol realizes the ideal functionalities discussed in TumbleBit. The functionality required for our proposal is the hashed time lock contract that various cryptocurrencies use. This request is general, not restricted to any particular cryptocurrency. Our proposal includes a probabilistic payment. In probabilistic payment, one pays an ordinary mount with a certain probability. One pays a small amount as an expected value. One can run fewer transactions than a deterministic payment. It contributes scalability. We introduce a novel fractional oblivious transfer for probabilistic payment. We call it the ring fractional oblivious transfer (RFOT). RFOT is based on the ring learning with errors (RLWE) encryption. Our trick is based on the fact that an element of the ring is indistinguishable from the circular shifted element. We confirm that RFOT holds the properties of fractional hiding and binding presented in the DAM scheme (Eurocrypt 2017)

Vision loss, tractional retinal detachment, and profound anemia due to rectal carcinoma

Profound anemia can cause severe proliferative retinopathy and tractional retinal detachment; therefore, it is important to closely investigate the cause of anemia. Endoscopy and computed tomography are valuable tools for this purpose

Semi-physical nonlinear circuit model with device/physical parameters for HEMTs

A nonlinear circuit model (NCM) with physical parameters is proposed for direct simulation of the RF characteristics of GaN high-electron-mobility transistors (GaN HEMTs) on the basis of device structure. The physical equations are used for the construction of the model in order to connect strongly the model parameters with the device/physical parameters. Hyperbolic tangent functions are used as the model equations to ensure good model convergence and rapid simulation (short simulation time). The usefulness of these equations is confirmed by technology computer aided design (TCAD) simulation. The number of model parameters for the nonlinear components (Ids, Cgs, Cgd) is reduced to 17 by using common physical parameters for modeling the drain current and capacitance. The accuracy of this model is verified by applying to GaN HEMTs. The modeled I–V and capacitance characteristics agree well with the measurement data over a wide voltage range. Furthermore, this model can be used for the accurate evaluation of S-parameters and large-signal RF characteristics

A human-assisting manipulator teleoperated by EMG signals and arm motions

This paper proposes a human-assisting manipulator teleoperated by electromyographic (EMG) signals and arm motions. The proposed method can realize a new master-slave manipulator system that uses no mechanical master controller. A person whose forearm has been amputated can use this manipulator as a personal assistant for desktop work. The control system consists of a hand and wrist control part and an arm control part. The hand and wrist control part selects an active joint in the manipulator's end-effector and controls it based on EMG pattern discrimination. The arm control part measures the position of the operator's wrist joint or the amputated part using a three-dimensional position sensor, and the joint angles of the manipulator's arm, except for the end-effector part, are controlled according to this position, which, in turn, corresponds to the position of the manipulator's joint. These control parts enable the operator to control the manipulator intuitively. The distinctive feature of our system is to use a novel statistical neural network for EMG pattern discrimination. The system can adapt itself to changes of the EMG patterns according to the differences among individuals, different locations of the electrodes, and time variation caused by fatigue or sweat. Our experiments have shown that the developed system could learn and estimate the operator's intended motions with a high degree of accuracy using the EMG signals, and that the manipulator could be controlled smoothly. We also confirmed that our system could assist the amputee in performing desktop work