3,015 research outputs found

    Block encryption of quantum messages

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    In modern cryptography, block encryption is a fundamental cryptographic primitive. However, it is impossible for block encryption to achieve the same security as one-time pad. Quantum mechanics has changed the modern cryptography, and lots of researches have shown that quantum cryptography can outperform the limitation of traditional cryptography. This article proposes a new constructive mode for private quantum encryption, named EHE\mathcal{EHE}, which is a very simple method to construct quantum encryption from classical primitive. Based on EHE\mathcal{EHE} mode, we construct a quantum block encryption (QBE) scheme from pseudorandom functions. If the pseudorandom functions are standard secure, our scheme is indistinguishable encryption under chosen plaintext attack. If the pseudorandom functions are permutation on the key space, our scheme can achieve perfect security. In our scheme, the key can be reused and the randomness cannot, so a 2n2n-bit key can be used in an exponential number of encryptions, where the randomness will be refreshed in each time of encryption. Thus 2n2n-bit key can perfectly encrypt O(n2n)O(n2^n) qubits, and the perfect secrecy would not be broken if the 2n2n-bit key is reused for only exponential times. Comparing with quantum one-time pad (QOTP), our scheme can be the same secure as QOTP, and the secret key can be reused (no matter whether the eavesdropping exists or not). Thus, the limitation of perfectly secure encryption (Shannon's theory) is broken in the quantum setting. Moreover, our scheme can be viewed as a positive answer to the open problem in quantum cryptography "how to unconditionally reuse or recycle the whole key of private-key quantum encryption". In order to physically implement the QBE scheme, we only need to implement two kinds of single-qubit gates (Pauli XX gate and Hadamard gate), so it is within reach of current quantum technology.Comment: 13 pages, 1 figure. Prior version appears in eprint.iacr.org(iacr/2017/1247). This version adds some analysis about multiple-message encryption, and modifies lots of contents. There are no changes about the fundamental result

    An IoT Endpoint System-on-Chip for Secure and Energy-Efficient Near-Sensor Analytics

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    Near-sensor data analytics is a promising direction for IoT endpoints, as it minimizes energy spent on communication and reduces network load - but it also poses security concerns, as valuable data is stored or sent over the network at various stages of the analytics pipeline. Using encryption to protect sensitive data at the boundary of the on-chip analytics engine is a way to address data security issues. To cope with the combined workload of analytics and encryption in a tight power envelope, we propose Fulmine, a System-on-Chip based on a tightly-coupled multi-core cluster augmented with specialized blocks for compute-intensive data processing and encryption functions, supporting software programmability for regular computing tasks. The Fulmine SoC, fabricated in 65nm technology, consumes less than 20mW on average at 0.8V achieving an efficiency of up to 70pJ/B in encryption, 50pJ/px in convolution, or up to 25MIPS/mW in software. As a strong argument for real-life flexible application of our platform, we show experimental results for three secure analytics use cases: secure autonomous aerial surveillance with a state-of-the-art deep CNN consuming 3.16pJ per equivalent RISC op; local CNN-based face detection with secured remote recognition in 5.74pJ/op; and seizure detection with encrypted data collection from EEG within 12.7pJ/op.Comment: 15 pages, 12 figures, accepted for publication to the IEEE Transactions on Circuits and Systems - I: Regular Paper

    Universal Hashing for Ultra-Low-Power Cryptographic Hardware Applications

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    Message Authentication Codes (MACs) are valuable tools for ensuring the integrity of messages. MACs may be built around a keyed hash function. Our main motivation was to prove that universal hash functions can be employed as underlying primitives of MACs in order to provide provable security in ultra-low-power applications such as the next generation self-powered sensor networks. The idea of using a universal hash function (NH) was explored in the construction of UMAC. This work presents three variations on NH, namely PH, PR and WH. The first hash function we propose, PH, produces a hash of length 2w and is shown to be 2^(-w)-almost universal. The other two hash functions, i.e. PR and WH, reach optimality and are proven to be universal hash functions with half the hash length of w. In addition, these schemes are simple enough to allow for efficient constructions. To the best of our knowledge the proposed hash functions are the first ones specifically designed for low-power hardware implementations. We achieve drastic power savings of up to 59% and speedup of up to 7.4 times over NH. Note that the speed improvement and the power reduction are accomplished simultaneously. Moreover, we show how the technique of multi- hashing and the Toeplitz approach can be combined to reduce the power and energy consumption even further while maintaining the same security level with a very slight increase in the amount of key material. At low frequencies the power and energy reductions are achieved simultaneously while keeping the hashing time constant. We develope formulae for estimation of leakage and dynamic power consumptions as well as energy consumption based on the frequency and the Toeplitz parameter t. We introduce a powerful method for scaling WH according to specific energy and power consumption requirements. This enables us to optimize the hash function implementation for use in ultra-low-power applications such as Smart Dust motes, RFIDs, and Piconet nodes. Our simulation results indicate that the implementation of WH-16 consumes only 2.95 ìW 500 kHz. It can therefore be integrated into a self- powered device. By virtue of their security and implementation features mentioned above, we believe that the proposed universal hash functions fill an important gap in cryptographic hardware applications

    A Survey on Wireless Sensor Network Security

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    Wireless sensor networks (WSNs) have recently attracted a lot of interest in the research community due their wide range of applications. Due to distributed nature of these networks and their deployment in remote areas, these networks are vulnerable to numerous security threats that can adversely affect their proper functioning. This problem is more critical if the network is deployed for some mission-critical applications such as in a tactical battlefield. Random failure of nodes is also very likely in real-life deployment scenarios. Due to resource constraints in the sensor nodes, traditional security mechanisms with large overhead of computation and communication are infeasible in WSNs. Security in sensor networks is, therefore, a particularly challenging task. This paper discusses the current state of the art in security mechanisms for WSNs. Various types of attacks are discussed and their countermeasures presented. A brief discussion on the future direction of research in WSN security is also included.Comment: 24 pages, 4 figures, 2 table

    Towards the AlexNet Moment for Homomorphic Encryption: HCNN, theFirst Homomorphic CNN on Encrypted Data with GPUs

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    Deep Learning as a Service (DLaaS) stands as a promising solution for cloud-based inference applications. In this setting, the cloud has a pre-learned model whereas the user has samples on which she wants to run the model. The biggest concern with DLaaS is user privacy if the input samples are sensitive data. We provide here an efficient privacy-preserving system by employing high-end technologies such as Fully Homomorphic Encryption (FHE), Convolutional Neural Networks (CNNs) and Graphics Processing Units (GPUs). FHE, with its widely-known feature of computing on encrypted data, empowers a wide range of privacy-concerned applications. This comes at high cost as it requires enormous computing power. In this paper, we show how to accelerate the performance of running CNNs on encrypted data with GPUs. We evaluated two CNNs to classify homomorphically the MNIST and CIFAR-10 datasets. Our solution achieved a sufficient security level (> 80 bit) and reasonable classification accuracy (99%) and (77.55%) for MNIST and CIFAR-10, respectively. In terms of latency, we could classify an image in 5.16 seconds and 304.43 seconds for MNIST and CIFAR-10, respectively. Our system can also classify a batch of images (> 8,000) without extra overhead

    Cryptography for Ultra-Low Power Devices

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    Ubiquitous computing describes the notion that computing devices will be everywhere: clothing, walls and floors of buildings, cars, forests, deserts, etc. Ubiquitous computing is becoming a reality: RFIDs are currently being introduced into the supply chain. Wireless distributed sensor networks (WSN) are already being used to monitor wildlife and to track military targets. Many more applications are being envisioned. For most of these applications some level of security is of utmost importance. Common to WSN and RFIDs are their severely limited power resources, which classify them as ultra-low power devices. Early sensor nodes used simple 8-bit microprocessors to implement basic communication, sensing and computing services. Security was an afterthought. The main power consumer is the RF-transceiver, or radio for short. In the past years specialized hardware for low-data rate and low-power radios has been developed. The new bottleneck are security services which employ computationally intensive cryptographic operations. Customized hardware implementations hold the promise of enabling security for severely power constrained devices. Most research groups are concerned with developing secure wireless communication protocols, others with designing efficient software implementations of cryptographic algorithms. There has not been a comprehensive study on hardware implementations of cryptographic algorithms tailored for ultra-low power applications. The goal of this dissertation is to develop a suite of cryptographic functions for authentication, encryption and integrity that is specifically fashioned to the needs of ultra-low power devices. This dissertation gives an introduction to the specific problems that security engineers face when they try to solve the seemingly contradictory challenge of providing lightweight cryptographic services that can perform on ultra-low power devices and shows an overview of our current work and its future direction

    Design and simulation a video steganography system by using FFT­turbo code methods for copyrights application

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    Protecting information on various communication media is considered an essential requirement in the present information transmission technology. So, there is a continuous search around different modern techniques that may be used to protect the data from the attackers. Steganography is one of those techniques that can be used to maintain the copyright by employing it to cover the publisher logo image inside the video frames. Nowadays, most of the popular known of the Video-Steganography methods become a conventional technique to the attacker, so there is a requirement for a modern and smart strategy to protect the copyright of the digital video file. Where this proposed system goal to create a hybrid system that combines the properties of Cryptography and Steganography work to protect the copyright hidden data from different attack types with maintaining of characteristics of the original video (quality and resolution). In this article, a modern Video-Steganography method is presented by employing the benefits of TC (Turbo code) to encrypt the pixels of logo image and Least two Significant Bit Technique procedure to embed the encryption pixels inside the frames of the video file. The insertion is performed in the frequency domain by applying the Fast Fourier Transform (FFT)on the video frames. The examination of the suggested architecture is done by terms of Structural Similarity Index, MSE (mean squared error), and PSNR (peak signal-to-noise ratio) by comparing between an original and extracted logo as well as between original and Steganographic video (averaged overall digital frames in the video). The simulation results show that this method proved high security, robustness, capacity and produces a substantial performance enhancement over the present known ways with fewer distortions in the quality of the vide
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