Visible to the public Biblio

Filters: Keyword is random key generation  [Clear All Filters]
Liu, Hongbo, Wang, Yan, Ren, Yanzhi, Chen, Yingying.  2021.  Bipartite Graph Matching Based Secret Key Generation. IEEE INFOCOM 2021 - IEEE Conference on Computer Communications. :1—10.
The physical layer secret key generation exploiting wireless channel reciprocity has attracted considerable attention in the past two decades. On-going research have demonstrated its viability in various radio frequency (RF) systems. Most of existing work rely on quantization technique to convert channel measurements into digital binaries that are suitable for secret key generation. However, non-simultaneous packet exchanges in time division duplex systems and noise effects in practice usually create random channel measurements between two users, leading to inconsistent quantization results and mismatched secret bits. While significant efforts were spent in recent research to mitigate such non-reciprocity, no efficient method has been found yet. Unlike existing quantization-based approaches, we take a different viewpoint and perform the secret key agreement by solving a bipartite graph matching problem. Specifically, an efficient dual-permutation secret key generation method, DP-SKG, is developed to match the randomly permuted channel measurements between a pair of users by minimizing their discrepancy holistically. DP-SKG allows two users to generate the same secret key based on the permutation order of channel measurements despite the non-reciprocity over wireless channels. Extensive experimental results show that DP-SKG could achieve error-free key agreement on received signal strength (RSS) with a low cost under various scenarios.
Cheng, Xin, Zhu, Haowen, Xing, Xinyi, Zhang, Yunfeng, Zhang, Yongqiang, Xie, Guangjun, Zhang, Zhang.  2021.  A Feedback Architecture of High Speed True Random Number Generator based on Ring Oscillator. 2021 IEEE Asian Solid-State Circuits Conference (A-SSCC). :1—3.
True random number generators (TRNG) are widely used to generate encryption keys in information security systems [1]–[2]. In TRNG, entropy source is a critical module who provides the source of randomness of output bit stream. The unavoidable electrical noise in circuit becomes an ideal entropy source due to its unpredictability. Among the methods of capturing electrical noise, ring oscillator-based entropy source makes the TRNG most robust to deterministic noise and 1/f noise which means the strongest anti-interference capability, so it is simple in structure and easy to integrate [3]. Thus, great research attention has focused on ring oscillator-based TRNGs [3] –[7]. In [4], a high-speed TRNG with 100Mbps output bit rate was proposed, but it took up too much power and area. A TRNG based on tetrahedral ring oscillator was proposed in [5]. Its power consumption was very low but the output bit rate was also very low. A ring oscillator-based TRNG with low output bit rate but high power was proposed in [7]. In a word, none of the above architectures achieve an appropriate compromise between bit rate and power consumption. This work presents a new feedback architecture of TRNG based on tetrahedral ring oscillator. The output random bit stream generates a relative random control voltage that acts on the transmission gates in oscillator through a feedback loop, thus increasing phase jitter of the oscillator and improving output bit rate. Furthermore, an XOR chain-based post-processing unit is added to eliminate the statistical deviations and correlations between raw bits.
Liu, Yang, Wang, Meng, Xu, Jing, Gong, Shimin, Hoang, Dinh Thai, Niyato, Dusit.  2021.  Boosting Secret Key Generation for IRS-Assisted Symbiotic Radio Communications. 2021 IEEE 93rd Vehicular Technology Conference (VTC2021-Spring). :1—6.
Symbiotic radio (SR) has recently emerged as a promising technology to boost spectrum efficiency of wireless communications by allowing reflective communications underlying the active RF communications. In this paper, we leverage SR to boost physical layer security by using an array of passive reflecting elements constituting the intelligent reflecting surface (IRS), which is reconfigurable to induce diverse RF radiation patterns. In particular, by switching the IRS's phase shifting matrices, we can proactively create dynamic channel conditions, which can be exploited by the transceivers to extract common channel features and thus used to generate secret keys for encrypted data transmissions. As such, we firstly present the design principles for IRS-assisted key generation and verify a performance improvement in terms of the secret key generation rate (KGR). Our analysis reveals that the IRS's random phase shifting may result in a non-uniform channel distribution that limits the KGR. Therefore, to maximize the KGR, we propose both a heuristic scheme and deep reinforcement learning (DRL) to control the switching of the IRS's phase shifting matrices. Simulation results show that the DRL approach for IRS-assisted key generation can significantly improve the KGR.
Nariezhnii, Oleksii, Grinenko, Tetiana.  2021.  Method for Increasing the Accuracy of the Synchronization of Generation Random Sequences Using Control and Correction Stations. 2021 IEEE 8th International Conference on Problems of Infocommunications, Science and Technology (PIC S&T). :309—314.
This article describes the process of synchronizing the generation of random sequences by a quantum random number generator (QRNG) that can be used as secret keys for known cryptographic transformations. The subject of the research is a method for synchronizing the generation of random QRNG sequences based on L1 (C/A) signals of the global positioning system (GPS) using control correcting information received from control correcting stations.
Chittala, Abhilash, Bhupathi, Tharun, Alakunta, Durga Prasad.  2021.  Random Number Generation Algorithms for Performance Testing. 2021 5th International Conference on Electronics, Materials Engineering & Nano-Technology (IEMENTech). :1—5.
There are numerous areas relied on random numbers. As one knows, in Cryptography, randomness plays a vital role from key generation to encrypting the systems. If randomness is not created effectively, the whole system is vulnerable to security threats where an outsider can easily predict the algorithm used to generate the random numbers in the system. Another main application where one would not touch is the role of random numbers in different devices mainly storage-related like Solid State Drives, Universal Serial Bus (USB), Secure Digital (SD) cards random performance testing. This paper focuses on various novel algorithms to generate random numbers for efficient performance evaluation of different drives. The main metrics for performance testing is random read and write performance. Here, the biggest challenge to test the random performance of the drive is not only the extent to which randomness is created but also the testing should cover the entire device (say complete NAND, NOR, etc.). So, the random number generator should generate in such a way that the random numbers should not be able to be predicted and must generate the numbers covering the entire range. This paper proposes different methods for such generators and towards the end, discusses the implementation in Field Programmable Gate Array (FPGA).
Henkel, Werner, Namachanja, Maria.  2021.  A Simple Physical-Layer Key Generation for Frequency-Division Duplexing (FDD). 2021 15th International Conference on Signal Processing and Communication Systems (ICSPCS). :1—6.
Common randomness of channels offers the possibility to create cryptographic keys without the need for a key exchange procedure. Channel reciprocity for TDD (time-division duplexing) systems has been used for this purpose many times. FDD (frequency-division duplexing) systems, however, were long considered to not provide any usable symmetry. However, since the scattering transmission parameters S\textbackslashtextlessinf\textbackslashtextgreater12\textbackslashtextless/inf\textbackslashtextgreater and S\textbackslashtextlessinf\textbackslashtextgreater21\textbackslashtextless/inf\textbackslashtextgreater would ideally be the same due to reciprocity, when using neighboring frequency ranges for both directions, they would just follow a continuous curve when putting them next to each other. To not rely on absolute phase, we use phase differences between antennas and apply a polynomial curve fitting, thereafter, quantize the midpoint between the two frequency ranges with the two measurement directions. This is shown to work even with some spacing between the two bands. For key reconciliation, we force the measurement point from one direction to be in the midpoint of the quantization interval by a grid shift (or likewise measurement data shift). Since the histogram over the quantization intervals does not follow a uniform distribution, some source coding / hashing will be necessary. The key disagreement rate toward an eavesdropper was found to be close to 0.5. Additionally, when using an antenna array, a random permutation of antenna measurements can even further improve the protection against eavesdropping.
Kuang, Randy, Barbeau, Michel.  2021.  Performance Analysis of the Quantum Safe Multivariate Polynomial Public Key Algorithm. 2021 IEEE International Conference on Quantum Computing and Engineering (QCE). :351—358.
The Multivariate Polynomial Public Key (MPPK) algorithm, over a prime Galois field, takes a multiplier multivariate polynomial and two multiplicand univariate solvable polynomials to create two product multivariate polynomials. One of variables is for secret message and all others are for noises. The public key consists of all coefficients of the product multivariate polynomials, except the two constant terms for the message variable. The private key is made of both multiplicands. Encryption takes a list of random numbers, over the prime Galois field. The first number is the secret to exchange. The other random numbers generate noise automatically cancelled by decryption. The secret is easily extracted from the evaluation of a solvable equation. The level of security provided by MPPK is adaptable. The algorithm can be used in several different ways. In this paper, we review the performance achieved by MPPK for several combinations of polynomial configurations and Galois field sizes. For every combination, we calculated key generation time, encryption time and decryption time. We also compare the effectiveness of MPPK with the performance of all four NIST PQC finalists. For MPPK, the data has been collected from the execution of an implementation in Java. In comparison to the NIST PQC finalists, MPPK key generation, encryption and decryption performance is excellent.
Perez, John Paul G., Sigua, Sean Kevin P., Cortez, Dan Michael A., Mata, Khatalyn E., Regala, Richard C., Alipio, Antolin J., Blanco, Mark Christopher R., Sison, Ariel M..  2021.  A Modified Key Generation Scheme of Vigenère Cipher Algorithm using Pseudo-Random Number and Alphabet Extension. 2021 7th International Conference on Computer and Communications (ICCC). :565—569.
In recent years, many modifications have been done to combat the weaknesses of the Vigenère Cipher Algorithm. Several studies have been carried out to rectify the flaw of the algorithm’s repeating key nature by increasing the key length equal to that of the plain text. However, some characters cannot be encrypted due to the limited set of characters in the key. This paper modified the algorithm’s key generation process using a Pseudo-Random Number Generator to improve the algorithm’s security and expanded the table of characters to up to 190 characters. The results show that based on Monobit examination and frequency analysis, the repeating nature of the key is non-existent, and the generated key can be used to encrypt a larger set of characters. The ciphertext has a low IC value of 0.030, which is similar to a random string and polyalphabetic cipher with an IC value of 0.038 but not equal to a monoalphabetic cipher with an IC value of 0.065. Results show that the modified version of the algorithm performs better than some of the recent studies conducted on it
Ji, Zhigang, Brown, James, Zhang, Jianfu.  2020.  True Random Number Generator (TRNG) for Secure Communications in the Era of IoT. 2020 China Semiconductor Technology International Conference (CSTIC). :1—5.
True Random number Generator (TRNG) is critical for secure communications. In this work, we explain in details regarding our recent solution on TRNG using random telegraph noise (RTN) including the benefits and the disadvantages. Security check is performed using the NIST randomness tests for both the RTN-based TRNG and various conventional pseudo random umber generator. The newly-proposed design shows excellent randomness, power consumption, low design complexity, small area and high speed, making it a suitable candidate for future cryptographically secured applications within the internet of things.
Yu, Wei, Zhou, Yuanyuan, Zhou, Xuejun, Wang, Lei, Chen, Shang.  2020.  Study on Statistical Analysis Method of Decoy-state Quantum Key Distribution with Finite-length Data. 2020 IEEE 4th Information Technology, Networking, Electronic and Automation Control Conference (ITNEC). 1:2435—2440.
In order to solve the statistical fluctuation problem caused by the finite data length in the practical quantum key distribution system, four commonly used statistical methods, DeMoivre-Laplace theorem, Chebyshev inequality, Chernoff boundary and Hoeffding boundary, are used to analyze. The application conditions of each method are discussed, and the effects of data length and confidence level on quantum key distribution security performance are simulated and analyzed. The simulation results show that the applicable conditions of Chernoff boundary are most consistent with the reality of the practical quantum key distribution system with finite-length data. Under the same experimental conditions, the secure key generation rate and secure transmission distance obtained by Chernoff boundary are better than those of the other three methods. When the data length and confidence level change, the stability of the security performance obtained by the Chernoff boundary is the best.
Salimboyevich, Olimov Iskandar, Absamat ugli, Boriyev Yusuf, Akmuratovich, Sadikov Mahmudjon.  2020.  Making algorithm of improved key generation model and software. 2020 International Conference on Information Science and Communications Technologies (ICISCT). :1—3.
In this paper is devoted methods for generating keys for cryptographic algorithms. Hash algorithms were analysed and learned linear and nonlinear. It was made up improved key generation algorithm and software.
Lei, Lei, Ma, Ping, Lan, Chunjia, Lin, Le.  2020.  Continuous Distributed Key Generation on Blockchain Based on BFT Consensus. 2020 3rd International Conference on Hot Information-Centric Networking (HotICN). :8—17.
VSS (Verifiable Secret Sharing) protocols are used in a number of block-chain systems, such as Dfinity and Ouroboros to generate unpredicted random number flow, they can be used to determine the proposer list and the voting powers of the voters at each height. To prevent random numbers from being predicted and attackers from corrupting a sufficient number of participants to violate the underlying trust assumptions, updatable VSS protocol in distributed protocols is important. The updatable VSS universal setup is also a hot topic in zkSNARKS protocols such as Sonic [19]. The way that we make it updatable is to execute the share exchange process repeatedly on chain, this process is challenging to be implemented in asynchronous network model, because it involves the wrong shares and the complaints, it requires the participant has the same view towards the qualified key generators, we take this process on chain and rely on BFT consensus mechanism to solve this. The group secret is thus updatable on chain. This is an enhancement to Dfinity. Therefore, even if all the coefficients of the random polynomials of epoch n are leaked, the attacker can use them only in epoch n+2. And the threshold group members of the DKG protocol can be updated along with the updates of the staked accounts and nodes.
Zhang, Liuming, Hajomer, Adnan, Yang, Xuelin, Hu, Weisheng.  2020.  Secure Key Generation and Distribution Using Polarization Dynamics in Fiber. 2020 22nd International Conference on Transparent Optical Networks (ICTON). :1—4.
Dynamic properties of optical signals in fiber channel provide a unique, random and reciprocal source for physical-layer secure key generation and distribution (SKGD). In this paper, an inherent physical-layer SKGD scheme is proposed and demonstrated, where the random source is originated from the dynamic fluctuation of the instant state of polarization (SOP) of optical signals in fiber. Due to the channel reciprocity, highly-correlated fluctuation of Stokes parameter of SOP is shared between the legal partners, where an error-free key generation rate (KGR) of 196-bit/s is successfully demonstrated over 25-km standard single-mode fiber (SSMF). In addition, an active polarization scrambler is deployed in fiber to increase the KGR, where an error-free KGR of 200-kbit/s is achieved.
Sannidhan, M S, Sudeepa, K B, Martis, Jason E, Bhandary, Abhir.  2020.  A Novel Key Generation Approach Based on Facial Image Features for Stream Cipher System. 2020 Third International Conference on Smart Systems and Inventive Technology (ICSSIT). :956—962.
Security preservation is considered as one of the major concerns in this digital world, mainly for performing any online transactions. As the time progress, it witnesses an enormous amount of security threats and stealing different kind of digital information over the online network. In this regard, lots of cryptographic algorithms based on secret key generation techniques have been implemented to boost up the security aspect of network systems that preserve the confidentiality of digital information. Despite this, intelligent intruders are still able to crack the key generation technique, thus stealing the data. In this research article, we propose an innovative approach for generating a pseudo-pseudo-random key sequence that serves as a base for the encryption/decryption process. The key generation process is carried out by extracting the essential features from a facial image and based on the extracted features; a pseudo-random key sequence that acts as a primary entity for the efficient encryption/decryption process is generated. Experimental findings related to the pseudo-random key is validated through chi-square, runs up-down and performs a period of subsequence test. Outcomes of these have subsequently passed in achieving an ideal key.
Patnala, Tulasi Radhika, Jayanthi, D., Majji, Sankararao, Valleti, Manohar, Kothapalli, Srilekha, Karanam, Santoshachandra Rao.  2020.  A Modernistic way for KEY Generation for Highly Secure Data Transfer in ASIC Design Flow. 2020 6th International Conference on Advanced Computing and Communication Systems (ICACCS). :892—897.
Present day's data security plays a vital role in digital human life. Data is a valuable asset to any organization and hence its security from external attacks is very important. Information security is not only an important aspect but essential, to secure data from unapproved access. Data encryption, decryption and key management are the key factors in data protection. It is very important to have the right data security solution to meet the challenging threats. Cryptosystem implementation and random number generators are crucial for Cryptosystem applications such as security applications, space applications, military applications and smart cards et al. In this paper, we present the implementation of hybrid cryptosystem based on the True Random number Generator, pseudo Random number Generator and whitening the data by using the ASIC design flow.
Xu, Peng, Hu, Dongyang, Chen, Gaojie.  2020.  Physical-Layer Cooperative Key Generation with Correlated Eavesdropping Channels in IoT. 2020 International Conferences on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData) and IEEE Congress on Cybermatics (Cybermatics). :29—36.
With a massive amount of wireless sensor nodes in Internet of Things (IoT), it is difficult to establish key distribution and management mechanism for traditional encryption technology. Alternatively, the physical layer key generation technology is promising to implement in IoT, since it is based on the principle of information-theoretical security and has the advantage of low complexity. Most existing key generation schemes assume that eavesdropping channels are independent of legitimate channels, which may not be practical especially when eavesdropper nodes are near to legitimate nodes. However, this paper investigates key generation problems for a multi-relay wireless network in IoT, where the correlation between eavesdropping and legitimate channels are considered. Key generation schemes are proposed for both non-colluding and partially colluding eavesdroppers situations. The main idea is to divide the key agreement process into three phases: 1) we first generate a secret key by exploiting the difference between the random channels associated with each relay node and the eavesdropping channels; 2) another key is generated by integrating the residual common randomness associated with each relay pair; 3) the two keys generated in the first two phases are concatenated into the final key. The secrecy key performance of the proposed key generation schemes is also derived with closed-forms.
Vokić, Nemanja, Milovančev, Dinka, Pacher, Christoph, Hübel, Hannes, Schrenk, Bernhard.  2020.  True Random Number Generation in an Optical I/Q Modulator. 2020 European Conference on Optical Communications (ECOC). :1—4.
We re-use a polarization-multiplexed I/Q modulator to acquire the quantum randomness of its seed laser light for the purpose of quantum random number generation. We obtain 9×104 256-bit AES keys/second after randomness extraction. Time-interleaved random number generation is demonstrated for PM-QPSK transmission.
Wang, Yazhou, Li, Bing, Zhang, Yan, Wu, Jiaxin, Yuan, Pengwei, Liu, Guimiao.  2020.  A Biometric Key Generation Mechanism for Authentication Based on Face Image. 2020 IEEE 5th International Conference on Signal and Image Processing (ICSIP). :231—235.
Facial biometrics have the advantages of high reliability, strong distinguishability and easily acquired for authentication. Therefore, it is becoming wildly used in identity authentication filed. However, there are stability, security and privacy issues in generating face key, which brings great challenges to face biometric authentication. In this paper, we propose a biometric key generation scheme based on face image. On the one hand, a deep neural network model for feature extraction is used to improve the stability of identity authentication. On the other hand, a key generation mechanism is designed to generate random biometric key while hiding original facial biometrics to enhance security and privacy of user authentication. The results show the FAR reach to 0.53% and the FRR reach to 0.57% in LFW face database, which achieves the better performance of biometric identification, and the proposed method is able to realize randomness of the generated biometric keys by NIST statistical test suite.
Seymen, B., Altop, D. K., Levi, A..  2020.  Augmented Randomness for Secure Key Agreement using Physiological Signals. 2020 IEEE Conference on Communications and Network Security (CNS). :1—9.

With the help of technological advancements in the last decade, it has become much easier to extensively and remotely observe medical conditions of the patients through wearable biosensors that act as connected nodes on Body Area Networks (BANs). Sensitive nature of the critical data captured and communicated via wireless medium makes it extremely important to process it as securely as possible. In this regard, lightweight security mechanisms are needed to overcome the hardware resource restrictions of biosensors. Random and secure cryptographic key generation and agreement among the biosensors take place at the core of these security mechanisms. In this paper, we propose the SKA-PSAR (Augmented Randomness for Secure Key Agreement using Physiological Signals) system to produce highly random cryptographic keys for the biosensors to secure communication in BANs. Similar to its predecessor SKA-PS protocol by Karaoglan Altop et al., SKA-PSAR also employs physiological signals, such as heart rate and blood pressure, as inputs for the keys and utilizes the set reconciliation mechanism as basic building block. Novel quantization and binarization methods of the proposed SKA-PSAR system distinguish it from SKA-PS by increasing the randomness of the generated keys. Additionally, SKA-PSAR generated cryptographic keys have distinctive and time variant characteristics as well as long enough bit sizes that provides resistance against cryptographic attacks. Moreover, correct key generation rate is above 98% with respect to most of the system parameters, and false key generation rate of 0% have been obtained for all system parameters.

Park, Jungmin, Cho, Seongjoon, Lim, Taejin, Bhunia, Swarup, Tehranipoor, Mark.  2019.  SCR-QRNG: Side-Channel Resistant Design using Quantum Random Number Generator. 2019 IEEE/ACM International Conference on Computer-Aided Design (ICCAD). :1–8.
Random number generators play a pivotal role in generating security primitives, e.g., encryption keys, nonces, initial vectors, and random masking for side-channel countermeasures. A quantum entropy source based on radioactive isotope decay can be exploited to generate random numbers with sufficient entropy. If a deterministic random bit generator (DRBG) is combined for post-processing, throughput of the quantum random number generator (QRNG) can be improved. However, general DRBGs are susceptible to side-channel attacks. In this paper, we propose a framework called SCR-QRNG framework, which offers Side-Channel Resistant primitives using QRNG. The QRNG provides sources of randomness for modulating the clock frequency of a DRBG to obfuscate side-channel leakages, and to generate unbiased random numbers for security primitives. The QRNG has robustness against power side-channel attacks and is in compliance with NIST SP 800-22/90B and BSI AIS 31. We fabricate a quantum entropy chip, and implement a PCB module for a random frequency clock generator and a side-channel resistant QRNG on an FPGA.
Korenda, Ashwija Reddy, Afghah, Fatemeh, Cambou, Bertrand, Philabaum, Christopher.  2019.  A Proof of Concept SRAM-based Physically Unclonable Function (PUF) Key Generation Mechanism for IoT Devices. 2019 16th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON). :1–8.
This paper provides a proof of concept for using SRAM based Physically Unclonable Functions (PUFs) to generate private keys for IoT devices. PUFs are utilized, as there is inadequate protection for secret keys stored in the memory of the IoT devices. We utilize a custom-made Arduino mega shield to extract the fingerprint from SRAM chip on demand. We utilize the concepts of ternary states to exclude the cells which are easily prone to flip, allowing us to extract stable bits from the fingerprint of the SRAM. Using the custom-made software for our SRAM device, we can control the error rate of the PUF to achieve an adjustable memory-based PUF for key generation. We utilize several fuzzy extractor techniques based on using different error correction coding methods to generate secret keys from the SRAM PUF, and study the trade-off between the false authentication rate and false rejection rate of the PUF.
Zhuang, Ziyi, Jiang, Shengming, Xu, Yanli, Luo, Xiang, Cheng, Xin.  2019.  A Physical Layer Key Generation Scheme Based on Full-duplex Mode in Wireless Networks without Fixed Infrastructure. 2019 International Conference on Computer, Information and Telecommunication Systems (CITS). :1–5.
Encryption schemes for network security usually require a key distribution center to share or distribute the secret keys, which is difficult to deploy in wireless networks without fixed infrastructure. A novel key generation scheme based on the physical layer can generate a shared key between a pair of correlated parties by sharing random sources. The existing physical layer key generation scheme is based on the half-duplex mode with time division duplex (TDD) mode, which makes it impossible for the correlated communication parties to detect the channel simultaneously in order to improve the channel coherence. In this paper, we propose a full-duplex physical layer key generation scheme, which allows each legal communication nodes to transmit and receive signals at the same time, in order to reduce channel probing time and increase channel coherence performance. The simulation experiments show that the proposed scheme can much outperform some typical existing schemes in terms of the key performance evaluation indicators, key disagreement rate, key generation rate, entropy of the scheme improved, and the randomness of generated keys passed the National Institute of Standards and Technology (NIST) test.
Hayashi, Masahito.  2019.  Semi-Finite Length Analysis for Secure Random Number Generation. 2019 IEEE International Symposium on Information Theory (ISIT). :952–956.
To discuss secure key generation from imperfect random numbers, we address the secure key generation length. There are several studies for its asymptotic expansion up to the order √n or log n. However, these expansions have errors of the order o(√n) or o(log n), which does not go to zero asymptotically. To resolve this problem, we derive the asymptotic expansion up to the constant order for upper and lower bounds of these optimal values. While the expansions of upper and lower bonds do not match, they clarify the ranges of these optimal values, whose errors go to zero asymptotically.
Aguilar, Eryn, Dancel, Jevis, Mamaud, Deysaree, Pirosch, Dorothy, Tavacoli, Farin, Zhan, Felix, Pearce, Robbie, Novack, Margaret, Keehu, Hokunani, Lowe, Benjamin et al..  2019.  Highly Parallel Seedless Random Number Generation from Arbitrary Thread Schedule Reconstruction. 2019 IEEE International Conference on Big Knowledge (ICBK). :1–8.
Security is a universal concern across a multitude of sectors involved in the transfer and storage of computerized data. In the realm of cryptography, random number generators (RNGs) are integral to the creation of encryption keys that protect private data, and the production of uniform probability outcomes is a revenue source for certain enterprises (most notably the casino industry). Arbitrary thread schedule reconstruction of compare-and-swap operations is used to generate input traces for the Blum-Elias algorithm as a method for constructing random sequences, provided the compare-and-swap operations avoid cache locality. Threads accessing shared memory at the memory controller is a true random source which can be polled indirectly through our algorithm with unlimited parallelism. A theoretical and experimental analysis of the observation and reconstruction algorithm are considered. The quality of the random number generator is experimentally analyzed using two standard test suites, DieHarder and ENT, on three data sets.
Manucom, Emraida Marie M., Gerardo, Bobby D., Medina, Ruji P..  2019.  Analysis of Key Randomness in Improved One-Time Pad Cryptography. 2019 IEEE 13th International Conference on Anti-counterfeiting, Security, and Identification (ASID). :11–16.
In cryptography, one-time pad (OTP) is claimed to be the perfect secrecy algorithm in several works if all of its features are applied correctly. Its secrecy depends mostly on random keys, which must be truly random and unpredictable. Random number generators are used in key generation. In Psuedo Random Number Generator (PRNG), the possibility of producing numbers that are predictable and repeated exists. In this study, a proposed method using True Random Number Generator (TRNG) and Fisher-Yates shuffling algorithm are implemented to generate random keys for OTP. Frequency (monobit) test, frequency test within a block, and runs tests are performed and showed that the proposed method produces more random keys. Sufficient confusion and diffusion properties are obtained using Pearson correlation analysis.