Biblio

We report a an experimental study of device-independent quantum random number generation based on an detection-loophole free Bell test with entangled photons. After considering statistical fluctuations and applying an 80 Gb × 45.6 Mb Toeplitz matrix hashing, we achieve a final random bit rate of 114 bits/s, with a failure probability less than 10-5.

The RFID based communication between objects within the framework of IoT is potentially very efficient in terms of power requirements and system complexity. The new design incorporating the emerging chipless RFID tags has the potential to make the system more efficient and simple. However, these systems are prone to privacy and security risks and these challenges associated with such systems have not been addressed appropriately in the broader IoT framework. In this context, a lightweight collision free algorithm based on n-bit pseudo random number generator, X-OR hash function, and rotations for chipless RFID system is presented. The algorithm has been implemented on an 8-bit open-loop resonator based chipless RFID tag based system and is validated using BASYS 2 FPGA board based platform. The proposed scheme has been shown to possess security against various attacks such as Denial of Service (DoS), tag/reader anonymity, and tag impersonation.

Blum-Blum-Shub (BBS) is a less complex pseudorandom number generator (PRNG) that requires very large modulus and a squaring operation for the generation of each bit, which makes it computationally heavy and slow. On the other hand, the concept of elliptic curve (EC) point operations has been extended to PRNGs that prove to have good randomness properties and reduced latency, but exhibit dependence on the secrecy of point P. Given these pros and cons, this paper proposes a new BBS-ECPRNG approach such that the modulus is the product of two elliptic curve points, both primes of length, and the number of bits extracted per iteration is by binary fraction. We evaluate the algorithm performance by generating 1000 distinct sequences of 106bits each. The results were analyzed based on the overall performance of the sequences using the NIST standard statistical test suite. The average performance of the sequences was observed to be above the minimum confidence level of 99.7 percent and successfully passed all the statistical properties of randomness tests.

Cryptographic applications need high-quality random number generator (RNG) for strong security and privacy measures. This paper presents RNG based on a hydrogen gas sensor that is fabricated by using microfabrication techniques. The proposed approach extracts the thermal noise information as an entropy source from the gas sensor that is non-deterministic during its operation and using hash function SHA-256 as post processing. This non-deterministic noise is then processed to acquire a random number set fulfilling the NIST 800-22 statistical randomness test suite and it demonstrates that a gas sensor based RNG can provide high-quality random numbers. Secure data transfer is possible by having this method directly without any other hardware where hydrogen gas sensor needs to be used such as petrochemical field, fuel cells, and nuclear reactors.

Deep neural networks (DNNs) are effective machine learning models to solve a large class of recognition problems, including the classification of nonlinearly separable patterns. The applications of DNNs are, however, limited by the large size and high energy consumption of the networks. Recently, stochastic computation (SC) has been considered to implement DNNs to reduce the hardware cost. However, it requires a large number of random number generators (RNGs) that lower the energy efficiency of the network. To overcome these limitations, we propose the design of an energy-efficient deep belief network (DBN) based on stochastic computation. An approximate SC activation unit (A-SCAU) is designed to implement different types of activation functions in the neurons. The A-SCAU is immune to signal correlations, so the RNGs can be shared among all neurons in the same layer with no accuracy loss. The area and energy of the proposed design are 5.27% and 3.31% (or 26.55% and 29.89%) of a 32-bit floating-point (or an 8-bit fixed-point) implementation. It is shown that the proposed SC-DBN design achieves a higher classification accuracy compared to the fixed-point implementation. The accuracy is only lower by 0.12% than the floating-point design at a similar computation speed, but with a significantly lower energy consumption.

This paper presents a true random number generator that exploits the subthreshold properties of jitter of events propagating in a self-timed ring and jitter of events propagating in an inverter based ring oscillator. Design was implemented in 180nm CMOS flash process. Devices provide high quality random bit sequences passing FIPS 140-2 and NIST SP 800-22 statistical tests which guaranty uniform distribution and unpredictability thanks to the physics based entropy source.

In this work, we analyze the feasibility of a physically secure implementation of the quantum-resistant supersingular isogeny Diffie-Hellman (SIDH) protocol. Notably, we analyze the defense against timing attacks, simple power analysis, differential power analysis, and fault attacks. Luckily, the SIDH protocol closely resembles its predecessor, the elliptic curve Diffie-Hellman (ECDH) key exchange. As such, much of the extensive literature in side-channel analysis can also apply to SIDH. In particular, we focus on a hardware implementation that features a true random number generator, ALU, and controller. SIDH is composed of two rounds containing a double-point multiplication to generate a secret kernel point and an isogeny over that kernel to arrive at a new elliptic curve isomorphism. To protect against simple power analysis and timing attacks, we recommend a constant-time implementation with Fermat's little theorem inversion. Differential power analysis targets the power output of the SIDH core over many runs. As such, we recommend scaling the base points by secret scalars so that each iteration has a unique power signature. Further, based on recent oracle attacks on SIDH, we cannot recommend the use of static keys from both parties. The goal of this paper is to analyze the tradeoffs in elliptic curve theory to produce a cryptographically and physically secure implementation of SIDH.

True random numbers have a fair role in modern digital transactions. In order to achieve secured authentication, true random numbers are generated as security keys which are highly unpredictable and non-repetitive. True random number generators are used mainly in the field of cryptography to generate random cryptographic keys for secure data transmission. The proposed work aims at the generation of true random numbers based on CMOS Boolean Chaotic Oscillator. As a part of this work, ASIC approach of CMOS Boolean Chaotic Oscillator is modelled and simulated using Cadence Virtuoso tool based on 45nm CMOS technology. Besides, prototype model has been implemented with circuit components and analysed using NI ELVIS platform. The strength of the generated random numbers was ensured by NIST (National Institute of Standards and Technology) Test Suite and ASIC approach was validated through various parameters by performing various analyses such as frequency, delay and power.

Ransomware has become a very significant cyber threat. The basic idea of ransomware was presented in the form of a cryptovirus in 1995. However, it was considered as merely a conceptual topic since then for over a decade. In 2017, ransomware has become a reality, with several famous cases of ransomware having compromised important computer systems worldwide. For example, the damage caused by CryptoLocker and WannaCry is huge, as well as global. They encrypt victims' files and require user's payment to decrypt them. Because they utilize public key cryptography, the key for recovery cannot be found in the footprint of the ransomware on the victim's system. Therefore, once infected, the system cannot be recovered without paying for restoration. Various methods to deal this threat have been developed by antivirus researchers and experts in network security. However, it is believed that cryptographic defense is infeasible because recovering a victim's files is computationally as difficult as breaking a public key cryptosystem. Quite recently, various approaches to protect the crypto-API of an OS from malicious codes have been proposed. Most ransomware generate encryption keys using the random number generation service provided by the victim's OS. Thus, if a user can control all random numbers generated by the system, then he/she can recover the random numbers used by the ransomware for the encryption key. In this paper, we propose a dynamic ransomware protection method that replaces the random number generator of the OS with a user-defined generator. As the proposed method causes the virus program to generate keys based on the output from the user-defined generator, it is possible to recover an infected file system by reproducing the keys the attacker used to perform the encryption.

The transition effect ring oscillator (TERO) based true random number generator (TRNG) was proposed by Varchola and Drutarovsky in 2010. There were several stochastic models for this advanced TRNG based on ring oscillator. This paper proposed an improved TERO based TRNG and implements both on Altera Cyclone series FPGA platform and on a 0.13um CMOS ASIC process. FPGA experimental results show that this balanced TERO TRNG is in good performance as the experimental data results past the national institute of standards and technology (NIST) test in 1M bit/s. The TRNG is feasible for a security SoC.

In this paper a random number generation method based on a piecewise linear one dimensional (PL1D) discrete time chaotic maps is proposed for applications in cryptography and steganography. Appropriate parameters are determined by examining the distribution of underlying chaotic signal and random number generator (RNG) is numerically verified by four fundamental statistical test of FIPS 140-2. Proposed design is practically realized on the field programmable analog and digital arrays (FPAA-FPGA). Finally it is experimentally verified that the presented RNG fulfills the NIST 800-22 randomness test without post processing.

The paper considers the general structure of Pseudo-random binary sequence generator based on the numerical solution of chaotic differential equations. The proposed generator architecture divides the generation process in two stages: numerical simulation of the chaotic system and converting the resulting sequence to a binary form. The new method of calculation of normalization factor is applied to the conversion of state variables values to the binary sequence. Numerical solution of chaotic ODEs is implemented using semi-implicit symmetric composition D-method. Experimental study considers Thomas and Rössler attractors as test chaotic systems. Properties verification for the output sequences of generators is carried out using correlation analysis methods and NIST statistical test suite. It is shown that output sequences of investigated generators have statistical and correlation characteristics that are specific for the random sequences. The obtained results can be used in cryptography applications as well as in secure communication systems design.

The extremely rapid development of the Internet of Things brings growing attention to the information security issue. Realization of cryptographically strong pseudo random number generators (PRNGs), is crucial in securing sensitive data. They play an important role in cryptography and in network security applications. In this paper, we realize a comparative study of two pseudo chaotic number generators (PCNGs). The First pseudo chaotic number generator (PCNG1) is based on two nonlinear recursive filters of order one using a Skew Tent map (STmap) and a Piece-Wise Linear Chaotic map (PWLCmap) as non linear functions. The second pseudo chaotic number generator (PCNG2) consists of four coupled chaotic maps, namely: PWLCmaps, STmap, Logistic map by means a binary diffusion matrix [D]. A comparative analysis of the performance in terms of computation time (Generation time, Bit rate and Number of needed cycles to generate one byte) and security of the two PCNGs is carried out.

Radio Frequency IDentification(RFID) is one of the most important sensing techniques for Internet of Things(IoT) and RFID systems have been applied to various different fields. But an RFID system usually uses open wireless radio wave to communicate and this will lead to a serious threat to its privacy and security. The current popular RFID tags are some low-cost passive tags. Their computation and storage resources are very limited. It is not feasible for them to complete some complicated cryptographic operations. So it is very difficult to protect the security and privacy of an RFID system. Lightweight authentication protocol is considered as an effective approach. Many typical authentication protocols usually use Hash functions so that they require more computation and storage resources. Based on CRC function, we propose a lightweight RFID authentication protocol, which needs less computation and storage resources than Hash functions. This protocol exploits an on-chip CRC function and a pseudorandom number generator to ensure the anonymity and freshness of communications between reader and tag. It provides forward security and confidential communication. It can prevent eavesdropping, location trace, replay attack, spoofing and DOS-attack effectively. It is very suitable to be applied to RFID systems.

This paper describes and verifies a method of implementing bit error rate (BER) calculation for FPGA-based physical layer security techniques for Software Defined Radio (SDR). Specifically, we describe an independent source signal processing architecture for an efficient calculation of BER for wireless communication modules across the transmitter and receiver nodes. The source components at the transmitter and the receiver both generate identical random bits independently from each other, allowing for the received data to be compared to the original bit stream to calculate BER completely on hardware. The described method is implemented on a Xilinx Virtex-6 ML605 FPGA and reduces processing time by more than four orders of magnitude less than hardware simulation techniques in regression testing and validation over billions of bits, shortening design turn around times and accelerating Physical layer based security development for wireless communication research. The described independent source approach utilizes a minimal amount of board resources, allowing it to be integrated seamlessly into SDR hardware designs. Experimental validation of the independent source based BER calculation is performed for an Orthogonal Frequency Division Multiplexing signal, and a comparison between different stages of hardware design for the execution time required for BER testing of a large number of bits is provided.

This paper presents an architecture for a discrete, high-entropy hardware random number generator. Because it is constructed out of simple hardware components, its operation is transparent and auditable. Using avalanche noise, a non-deterministic physical phenomenon, the circuit is inherently probabilistic and resists adversarial control. Furthermore, because it compares the outputs from two matched noise sources, it rejects environmental disturbances like RF energy and power supply ripple. The resulting hardware produces more than 0.98 bits of entropy per sample, is inexpensive, has a small footprint, and can be disabled to conserve power when not in use.

EPC Gen2 tags are working as international RFID standards for the use in the supply chain worldwide, such tags are computationally weak devices and unable to perform even basic symmetric-key cryptographic operations. For this reason, to implement robust and secure pseudo-random number generators (PRNG) is a challenging issue for low-cost Radio-frequency identification (RFID) tags. In this paper, we study the security of LFSR-based PRNG implemented on EPC Gen2 tags and exploit LFSR-based PRNG to provide a better constructions. We provide a cryptanalysis against the J3Gen which is LFSR-based PRNG and proposed by Sugei et al. [1], [2] for EPC Gen2 tags using distinguish attack and make observations on its input using NIST randomness test. We also test the PRNG in EPC Gen2 RFID Tags by using the NIST SP800-22. As a counter-measure, we propose two modified models based on the security analysis results. We show that our results perform better than J3Gen in terms of computational and statistical property.

The Center for Strategic and International Studies estimates the annual cost from cyber crime to be more than \$400 billion. Most notable is the recent digital identity thefts that compromised millions of accounts. These attacks emphasize the security problems of using clonable static information. One possible solution is the use of a physical device known as a Physically Unclonable Function (PUF). PUFs can be used to create encryption keys, generate random numbers, or authenticate devices. While the concept shows promise, current PUF implementations are inherently problematic: inconsistent behavior, expensive, susceptible to modeling attacks, and permanent. Therefore, we propose a new solution by which an unclonable, dynamic digital identity is created between two communication endpoints such as mobile devices. This Physically Unclonable Digital ID (PUDID) is created by injecting a data scrambling PUF device at the data origin point that corresponds to a unique and matching descrambler/hardware authentication at the receiving end. This device is designed using macroscopic, intentional anomalies, making them inexpensive to produce. PUDID is resistant to cryptanalysis due to the separation of the challenge response pair and a series of hash functions. PUDID is also unique in that by combining the PUF device identity with a dynamic human identity, we can create true two-factor authentication. We also propose an alternative solution that eliminates the need for a PUF mechanism altogether by combining tamper resistant capabilities with a series of hash functions. This tamper resistant device, referred to as a Quasi-PUDID (Q-PUDID), modifies input data, using a black-box mechanism, in an unpredictable way. By mimicking PUF attributes, Q-PUDID is able to avoid traditional PUF challenges thereby providing high-performing physical identity assurance with or without a low performing PUF mechanism. Three different application scenarios with mobile devices for PUDID and Q-PUDI- have been analyzed to show their unique advantages over traditional PUFs and outline the potential for placement in a host of applications.

Strength of security and privacy of any cryptographic mechanisms that use random numbers require that the random numbers generated have two important properties namely 1. Uniform distribution and 2. Independence. With the growth of Internet many devices are connected to Internet that host sensors. One idea proposed is to use sensor data as seed for Random Number Generator (RNG) since sensors measure the physical phenomena that exhibit randomness over time. The random numbers generated from sensor data can be used for cryptographic algorithms in Internet activities. These sensor data also pose weaknesses where sensors may be under adversarial control that may lead to generating expected random sequence which breaks the security and privacy. This paper proposes a wash-rinse-spin approach to process the raw sensor data that increases randomness in the seed value. The generated sequences from two sensors are combined by Decimation method to improve unpredictability. This makes the sensor data to be more secure in generating random numbers preventing attackers from knowing the random sequence through adversarial control.

Random numbers represent one of the most sensible part of a cryptographic system, since the cryptographic keys must be entirely based on them. The security of a communication relies on the key that had been established between two users. If an attacker is able to deduce that key, the communication is compromised. This is why key generation must completely rely on random number generators, so that nobody can deduce the. This paper will describe a set of public and free Random Number Generators (RNG) within Android-based Smartphones by exploiting different sensors, along with the way of achieving this scope. Moreover, this paper will present some conclusive tests and results over them.