This work develops a system called CLAP that detects and classifies “potentially unwanted applications” (PUAs) such as adware or remote monitoring tools. Our approach leverages DNS queries made by apps. Using a large sample of Android apps from third-party marketplaces, we first reveal that DNS queries can provide useful information for detection and classification of PUAs. We then show that existing DNS blacklists are limited when performing these tasks. Finally, we demonstrate that the CLAP system performs with high accuracy.

Cloud computing is a unlimited computing resource and storing resource, which provides a lot of convenient services, for example, Internet and education, intelligent transportation system. With the rapid development of cloud computing, more and more people pay attention to reducing the cost of data management. Data sharing is a effective model to decrease the cost of individuals or companies in dealing with data. However, the existing data sharing scheme cannot reduce communication cost under ensuring the security of users. In this paper, an anonymous and traceable data sharing scheme is presented. The proposed scheme can protect the privacy of the user. In addition, the proposed scheme also can trace the user uploading irrelevant information. Security and performance analyses show that the data sharing scheme is secure and effective.

In Stochastic Computing (SC), we need to generate many stochastic numbers (SNs). If we generate one SN conventionally, we need a Stochastic Number Generator (SNG) which consists of a linear-feedback shift register (LFSR) and a comparator. When we calculate an arithmetic function by SC, we need to generate many SNs whose values are equal to constant values used in the arithmetic function. As a consequence, the hardware overhead becomes huge. Accordingly, there has been proposed a method called GMCS (Generating Many Constant SNs from Few SNs) to generate many constant SNs with low hardware overhead. However, if we use GMCS simply, generated constant SNs are correlated highly with each other. This would be a serious problem because the high correlation of SNs make a large error in computation. Therefore, in this paper, we propose efficient methods to generate constant SNs with reasonably low hardware overhead without increasing errors. To reduce the correlations of constant SNs which are generated by GMCS, we use Register based Re-arrangement circuit using a Random bit stream duplicator (RRRD). RRRDs have few influences on the hardware overhead because an RRRD consists of three multiplexers (MUXs) and two 1-bit FFs. We also use a technique to share random number generators with several SNGs to reduce the hardware overhead. We provide some experimental results by which we can confirm that our proposed methods are in general very useful to reduce the hardware overhead for generating constant SNs without increasing errors.

This paper presents the excitation coefficient optimization of slot array antennas for increasing channel capacity in 2×2-mode two-dimensional ROM (rectangular coordinate orthogonal) transmission. Because the ROM transmission is for non-far region communication, the transmission between Tx (transmission) and Rx (reception) antennas increases when the antennas radiate beams inwardly. At first, we design the excitation coefficients of the slot arrays in order to enhance the transmission rate for a given transmission distance. Then, we fabricate monopulse corporate-feed waveguide slot array antennas that have the designed excitation amplitude and phase in the 60-GHz band for the 2×2-mode two-dimensional ROM transmission. The measured transmission between the fabricated Tx and Rx antennas increases at the given propagation distance and agrees with the simulation.

In this paper, we propose secure dictionary learning based on a random unitary transform for sparse representation. Currently, edge cloud computing is spreading to many application fields including services that use sparse coding. This situation raises many new privacy concerns. Edge cloud computing poses several serious issues for end users, such as unauthorized use and leak of data, and privacy failures. The proposed scheme provides practical MOD and K-SVD dictionary learning algorithms that allow computation on encrypted signals. We prove, theoretically, that the proposal has exactly the same dictionary learning estimation performance as the non-encrypted variant of MOD and K-SVD algorithms. We apply it to secure image modeling based on an image patch model. Finally, we demonstrate its performance on synthetic data and a secure image modeling application for natural images.

The success and scale of the Internet and its protocol IP has spurred emergent distributed technologies such as fog/edge computing and new application models based on distributed containerized microservices. The Internet of Things and Connected Communities are poised to build on these technologies and models and to benefit from the ability to communicate in a peer-to-peer (P2P) fashion. Ubiquitous sensing, actuating and computing implies a scale that breaks the centralized cloud computing model. Challenges stemming from limited IPv4 public addresses, the need for transport layer authentication, confidentiality and integrity become a burden on developing new middleware and applications designed for the network's edge. One approach - not reliant on the slow adoption of IPv6 - is the use of virtualized overlay networks, which abstract the complexities of the underlying heterogeneous networks that span the components of distributed fog applications and middleware. This paper describes the evolution of the design and implementation of IP-over-P2P (IPOP) - from its purist P2P inception, to a pragmatic hybrid model which is influenced by and incorporates standards. The hybrid client-server/P2P approach allows IPOP to leverage existing robust and mature cloud infrastructure, while still providing the characteristics needed at the edge. IPOP is networking cyber infrastructure that presents an overlay virtual private network which self-organizes with dynamic membership of peer nodes into a scalable structure. IPOP is resilient to partitioning, supports redundant paths within its fabric, and provides software defined programming of switching rules to utilize these properties of its topology.

Searchable encryption with advanced query function is an important technique in today's cloud environment. To date, in the public key setting, the best query function supported by the previous schemes are conjunctive or disjunctive keyword search, which are elementary but not enough to satisfy the user's query requirements. In this paper, we make a progress for constructing a searchable public key encryption scheme with advanced query function called simple Boolean keyword search. To create our scheme, we proposed a keywords conversion method that projects the index and query keywords into a group of vectors. Based on a combination of these obtained vectors and an adaptively secure inner product encryption scheme, a public key encryption with simple Boolean keyword search scheme is proposed. We also present both theoretical and experimental analysis to show the effectiveness of this scheme. To the best of our knowledge, it is the first time to give a searchable public key encryption scheme supporting queries like q1op1q2op2…opi-1qiopi…opn-1qn, where opi is a logical operator which can be and(∨) or or(∧) and qi is a keyword.

In this paper, we extend the notion of bijective connection graphs to introduce directed bijective connection graphs. We propose algorithms that solve the node-to-set node-disjoint paths problem and the node-to-node node-disjoint paths problem in a directed bijective connection graph. The time complexities of the algorithms are both O(n4), and the maximum path lengths are both 2n-1.

We present an improved constant-round secure two-party protocol for integer comparison functionality, which is one of the most fundamental building blocks in secure computation. Our protocol is in the so-called client-server model, which is utilized in real-world MPC products such as Sharemind, where any number of clients can create shares of their input and distribute to the servers who then jointly compute over the shares and return the shares of the result to the client. In the client-aided client-server model, as mentioned briefly by Mohassel and Zhang (S&P'17), a client further generates and distributes some necessary correlated randomness to servers. Such correlated randomness admits efficient protocols since otherwise, servers have to jointly generate randomness by themselves, which can be inefficient. In this paper, we improve the state-of-the-art constant-round comparison protocols by Damgå rd et al. (TCC'06) and Nishide and Ohta (PKC'07) in the client-aided model. Our techniques include identifying correlated randomness in these comparison protocols. Along the way, we also use tree-based techniques for a building block, which deviate from the above two works. Our proposed protocol requires only 5 communication rounds, regardless of the bit length of inputs. This is at least 5 times fewer rounds than existing protocols. We implement our secure comparison protocol in C++. Our experimental results show that this low-round complexity benefits in high-latency networks such as WAN. We also present secure Min/Argmin protocols using the secure comparison protocol.

Public-key encryption with keyword search (PEKS) is a cryptographic primitive that allows us to search for particular keywords over ciphertexts without recovering plaintexts. By using PEKS in cloud services, users can outsource their data in encrypted form without sacrificing search functionality. Concerning PEKS that can specify logical disjunctions and logical conjunctions as a search condition, it is known that such PEKS can be (generically) constructed from anonymous attribute-based encryption (ABE). However, it is not clear whether it is possible to construct this types of PEKS without using ABE which may require large computational/communication costs and strong mathematical assumptions. In this paper, we show that ABE is crucial for constructing PEKS with the above functionality. More specifically, we give a generic construction of anonymous key-policy ABE from PEKS whose search condition is specified by logical disjunctions and logical conjunctions. Our result implies such PEKS always requires large computational/communication costs and strong mathematical assumptions corresponding to those of ABE.

Chosen-ciphertext security is a central goal in designing a secure public-key encryption scheme, and it is also important that the chosen-ciphertext security is tightly reduced to some well-established hard problem. Moreover, it is more important to have a tight reduction in the multi-user multi-challenge setting, since a tight security reduction in the single-user single-challenge setting generally does not imply a tight reduction to the multi-user multi-challenge setting. We propose the first fully tightly secure and practical public-key encryption scheme which is chosen-ciphertext secure in the multi-user multi-challenge setting in the random oracle model. The scheme is proven secure under the decisional Diffie-Hellman assumption in a pairing-free group. The ciphertext overhead of our scheme is two group elements and two exponents.

Promoting the use of public transport (PT) is considered to be an effective way to reduce the number of passenger cars. The concept of Mobility-as-a-Service (MaaS), which began in Europe and is now spreading rapidly around the world, is expected to help to improve the convenience of PT on the viewpoint of users, using the latest information communication technology and Internet of Things technologies. This paper outlines the concept of MaaS in Europe and the efforts made at the policy level. It also focuses on the development of MaaS from the viewpoint of promoting the use of PT in Japan.

Because of its high throughput potentiality on short-range communications and inherent superiority of high precision on ranging and localization, ultra-wideband (UWB) technology has been attracting attention continuously in research and development (R&D) as well as in commercialization. The first domestic regulation admitting indoor UWB in Japan was released by the Ministry of Internal Affairs and Communications (MIC) in 2006. Since then, several revisions have been made in conjunction with UWB commercial penetration, emerging new trends of industrial demands, and coexistence evaluation with other wireless systems. However, it was not until May 2019 that MIC released a new revision to admit outdoor UWB. Meanwhile, the IEEE 802 LAN/MAN Standards Committee has been developing several UWB related standards or amendments accordingly for supporting different use cases. At the time when this paper is submitted, a new amendment known as IEEE 802.15.4z is undergoing drafting procedure which is expected to enhance ranging ability for impulse radio UWB (IR-UWB). In this paper, we first review the domestic UWB regulation and some of its revisions to get a picture of the domestic regulation transition from indoor to outdoor. We also foresee some anticipating changes in future revisions. Then, we overview several published IEEE 802 standards or amendments that are related to IR-UWB. Some features of IEEE 802.15.4z in drafting are also extracted from open materials. Finally, we show with our recent research results that time bias internal a transceiver becomes important for increasing localization accuracy.

Advanced information-processing services based on cloud computing are in great demand. However, users want to be able to customize cloud services for their own purposes. To provide image-processing services that can be optimized for the purpose of each user, we propose a technique for chaining image-processing functions in a CPU-field programmable gate array (FPGA) coupled server architecture. One of the most important requirements for combining multiple image-processing functions on a network, is low latency in server nodes. However, large delay occurs in the conventional CPU-FPGA architecture due to the overheads of packet reordering for ensuring the correctness of image processing and data transfer between the CPU and FPGA at the application level. This paper presents a CPU-FPGA server architecture with a real-time packet reordering circuit for low-latency image processing. In order to confirm the efficiency of our idea, we evaluated the latency of histogram of oriented gradients (HOG) feature calculation as an offloaded image-processing function. The results show that the latency is about 26 times lower than that of the conventional CPU-FPGA architecture. Moreover, the throughput decreased by less than 3.7% under the worst-case condition where 90 percent of the packets are randomly swapped at a 40-Gbps input rate. Finally, we demonstrated that a real-time video monitoring service can be provided by combining image processing functions using our architecture.

In this article, we propose a data framework for edge computing that allows developers to easily attain efficient data transfer between mobile devices or users. We propose a distributed key-value storage platform for edge computing and its explicit data distribution management method that follows the publish/subscribe relationships specific to applications. In this platform, edge servers organize the distributed key-value storage in a uniform namespace. To enable fast data access to a record in edge computing, the allocation strategy of the record and its cache on the edge servers is important. Our platform offers distributed objects that can dynamically change their home server and allocate cache objects proactively following user-defined rules. A rule is defined in a declarative manner and specifies where to place cache objects depending on the status of the target record and its associated records. The system can reflect record modification to the cached records immediately. We also integrate a push notification system using WebSocket to notify events on a specified table. We introduce a messaging service application between mobile appliances and several other applications to show how cache rules apply to them. We evaluate the performance of our system using some sample applications.

This paper proposes a visual analytics (VA) interface for time-series data so that it can solve the problems arising from the property of time-series data: a collision between interaction and animation on the temporal aspect, collision of interaction between the temporal and spatial aspects, and the trade-off of exploration accuracy, efficiency, and scalability between different visualization methods. To solve these problems, this paper proposes a VA interface that can handle temporal and spatial changes uniformly. Trajectories can show temporal changes spatially, of which direct manipulation enables to examine the relationship among objects either at a certain time point or throughout the entire time range. The usefulness of the proposed interface is demonstrated through experiments.

Cloud computing enables computational resource-limited devices to economically outsource much computations to the cloud. Modular exponentiation is one of the most expensive operations in public key cryptographic protocols, and such operation may be a heavy burden for the resource-constraint devices. Previous works for secure outsourcing modular exponentiation which use one or two untrusted cloud server model or have a relatively large computational overhead, or do not support the 100% possibility for the checkability. In this letter, we propose a new efficient and verifiable algorithm for securely outsourcing modular exponentiation in the two untrusted cloud server model. The algorithm improves efficiency by generating random pairs based on EBPV generators, and the algorithm has 100% probability for the checkability while preserving the data privacy.

Recently proposed irregular networks can reduce the latency for both on-chip and off-chip systems with a large number of computing nodes and thus can improve the performance of parallel applications. However, these networks usually suffer from deadlocks in routing packets when using a naive minimal path routing algorithm. To solve this problem, we focus attention on a lately proposed theory that generalizes the turn model to maintain the network performance with deadlock-freedom. The theorems remain a challenge of applying themselves to arbitrary topologies including fully irregular networks. In this paper, we advance the theorems to completely general ones. Moreover, we provide a feasible implementation of a deadlock-free routing method based on our advanced theorem. Experimental results show that the routing method based on our proposed theorem can improve the network throughput by up to 138 % compared to a conventional deterministic minimal routing method. Moreover, when utilized as the escape path in Duato's protocol, it can improve the throughput by up to 26.3 % compared with the conventional up*/down* routing.

In this paper, we propose an acceleration method for the Held-Karp algorithm that solves the symmetric traveling salesman problem by dynamic programming. The proposed method achieves acceleration with two techniques. First, we locate data-independent subproblems so that the subproblems can be solved in parallel. Second, we reduce the number of subproblems by a meet in the middle (MITM) technique, which computes the optimal path from both clockwise and counterclockwise directions. We show theoretical analysis on the impact of MITM in terms of the time and space complexities. In experiments, we compared the proposed method with a previous method running on a single-core CPU. Experimental results show that the proposed method on an 8-core CPU was 9.5-10.5 times faster than the previous method on a single-core CPU. Moreover, the proposed method on a graphics processing unit (GPU) was 30-40 times faster than that on an 8-core CPU. As a side effect, the proposed method reduced the memory usage by 48%.

Approximate computing has emerged as a promising approach for error-tolerant applications to improve hardware performance at the cost of some loss of accuracy. Multiplication is a key arithmetic operation in these applications. In this paper, we propose a low-cost approximate multiplier design by employing new probability-driven inexact compressors. This compressor design is introduced to reduce the height of partial product matrix into two rows, based on the probability distribution of the sum result of partial products. To compensate the accuracy loss of the multiplier, a grouped error recovery scheme is proposed and achieves different levels of accuracy. In terms of mean relative error distance (MRED), the accuracy losses of the proposed multipliers are from 1.07% to 7.86%. Compared with the Wallace multiplier using 40nm process, the most accurate variant of the proposed multipliers can reduce power by 59.75% and area by 42.47%. The critical path delay reduction is larger than 12.78%. The proposed multiplier design has a better accuracy-performance trade-off than other designs with comparable accuracy. In addition, the efficiency of the proposed multiplier design is assessed in an image processing application.