The objective of this paper is to give a comprehensive introduction to applied cryptography with an engineer or computer scientist in mind. The emphasis is on the knowledge needed to create practical systems which supports integrity, confidentiality, or authenticity. Topics covered includes an introduction to the concepts in cryptography, attacks against cryptographic systems, key use and handling, random bit generation, encryption modes, and message authentication codes. Recommendations on algorithms and further reading is given in the end of the paper. This paper should make the reader able to build, understand and evaluate system descriptions and designs based on the cryptographic components described in the paper.

[서평]「Applied Cryptography」

The security issue impacting the Internet-of-Things (IoT) paradigm has recently attracted significant attention from the research community. To this end, several surveys were put forward addressing various IoT-centric topics, including intrusion detection systems, threat modeling, and emerging technologies. In contrast, in this paper, we exclusively focus on the ever-evolving IoT vulnerabilities. In this context, we initially provide a comprehensive classification of state-of-the-art surveys, which address various dimensions of the IoT paradigm. This aims at facilitating IoT research endeavors by amalgamating, comparing, and contrasting dispersed research contributions. Subsequently, we provide a unique taxonomy, which sheds the light on IoT vulnerabilities, their attack vectors, impacts on numerous security objectives, attacks which exploit such vulnerabilities, corresponding remediation methodologies and currently offered operational cyber security capabilities to infer and monitor such weaknesses. This aims at providing the reader with a multidimensional research perspective related to IoT vulnerabilities, including their technical details and consequences, which is postulated to be leveraged for remediation objectives. Additionally, motivated by the lack of empirical (and malicious) data related to the IoT paradigm, this paper also presents a first look on Internet-scale IoT exploitations by drawing upon more than 1.2 GB of macroscopic, passive measurements’ data. This aims at practically highlighting the severity of the IoT problem, while providing operational situational awareness capabilities, which undoubtedly would aid in the mitigation task, at large. Insightful findings, inferences and outcomes in addition to open challenges and research problems are also disclosed in this paper, which we hope would pave the way for future research endeavors addressing theoretical and empirical aspects related to the imperative topic of IoT security.

Demystifying IoT Security: An Exhaustive Survey on IoT Vulnerabilities and a First Empirical Look on Internet-Scale IoT Exploitations

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Bioelectrical Signal Processing In Cardiac And Neurological Applications

Authentication is an essential cryptographic primitive that confirms the identity of parties during communications. For security, it is important that these identities are complex, in order to make them difficult to clone or guess. In recent years, physically unclonable functions (PUFs) have emerged, in which identities are embodied in structures, rather than stored in memory elements. PUFs provide “digital fingerprints,” where information is usually read from the static entropy of a system, rather than having an identity artificially programmed in, preventing a malicious party from making a copy for nefarious use later on. Many concepts for the physical source of the uniqueness of these PUFs have been developed for multiple different applications. While certain types of PUF have received a great deal of attention, other promising suggestions may be overlooked. To remedy this, we present a review that seeks to exhaustively catalogue and provide a complete organisational scheme towards the suggested concepts for PUFs. Furthermore, by carefully considering the physical mechanisms underpinning the operation of different PUFs, we are able to form relationships between PUF technologies that previously had not been linked and look toward novel forms of PUF using physical principles that have yet to be exploited.

A PUF taxonomy

A physical unclonable function (PUF) is a device that exploits inherent randomness introduced during manufacturing to give a physical entity a unique ‘fingerprint’ or trust anchor. These devices are .of potential use in a variety of applications from anti-counterfeiting, identification, authentication and key generation to advanced protocols such as oblivious transfer, key exchange, key renovation and virtual proof of reality. Here we review the development of PUFs, including those that exploit optical, circuit time-delay and volatile/non-volatile memory characteristics. We examine the various applications of PUFs, and consider the security issues that they must confront, highlighting known attacks to date and potential countermeasures. We also consider the key areas for future development such as bit-specific reliability, reconfigurability and public key infrastructure. This Review Article examines the development of physical unclonable functions, which exploit inherent randomness to give a physical entity a unique ‘fingerprint’ or trust anchor, considering the various potential applications of these devices and the security issues that they must confront.

Physical unclonable functions

A physically unclonable function (PUF) is an irreversible probabilistic function that produces a random bit string. It is simple to implement but hard to predict and emulate. PUFs have been widely proposed as security primitives to provide device identification and authentication. In this paper, we propose a novel dynamic-memory-based PUF [dynamic RAM PUF (DRAM PUF)] for the authentication of electronic hardware systems. The DRAM PUF relies on the fact that the capacitor in the DRAM initializes to random values at startup time. Most PUF designs require custom circuits to convert unique analog characteristics into digital bits, but using our method, no extra circuitry is required to achieve a reliable 128-bit PUF. The results show that the proposed DRAM PUF provides a large number of input patterns (challenges) compared with other memory-based PUF circuits such as static RAM PUFs. Our DRAM PUFs provide highly unique PUFs with a 0.4937 average interdie Hamming distance. We also propose an enrollment algorithm to achieve highly reliable results to generate PUF identifications for system-level security. This algorithm has been validated on real DRAMs with an experimental setup to test different operating conditions.

DRAM-Based Intrinsic Physically Unclonable Functions for System-Level Security and Authentication

Physical Unclonable Functions (PUF) are the result of random uncontrollable variables in the manufacturing process. A PUF can be used as a source of random but reliable data for applications such as generating chip identification and encryption keys. Among various types of PUFs, an intrinsic PUF is the result of a preexisting manufacturing process, does not require any additional circuitry, and is cost effective. In this paper, we introduce an intrinsic PUF based on dynamic random access memories (DRAM). DRAM PUFs can be used in low cost identification applications and also have several advantages over other PUFs such as large input patterns. The DRAM PUF relies on the fact that the capacitor in the DRAM initializes to random values at startup. We demonstrate real DRAM PUFs and describe an experimental setup to test different operating conditions on three DRAMs to achieve the highest reliable results. Finally, we select the most stable bits to use as chip ID using our enrollment algorithm.

DRAM based Intrinsic Physical Unclonable Functions for System Level Security

Traditional passwords are inadequate as cryptographic keys, as they are easy to forge and are vulnerable to guessing. Human biometrics have been proposed as a promising alternative due to their intrinsic nature. Electrocardiogram (ECG) is an emerging biometric that is extremely difficult to forge and circumvent, but has not yet been heavily investigated for cryptographic key generation. ECG has challenges with respect to immunity to noise, abnormalities, etc. In this paper, we propose a novel key generation approach that extracts keys from real-valued ECG features with high reliability and entropy in mind. Our technique, called interval optimized mapping bit allocation (IOMBA), is applied to normal and abnormal ECG signals under multiple session conditions. We also investigate IOMBA in the context of different feature extraction methods, such as wavelet, discrete cosine transform, etc., to find the best method for feature extraction. Experiments of IOMBA show that 217-, 38-, and 100-bit keys with 99.9%, 97.4%, and 95% average reliability and high entropy can be extracted from normal, abnormal, and multiple session ECG signals, respectively. By allowing more errors or lowering entropy, key lengths can be further increased by tunable parameters of IOMBA, which can be useful in other applications. While IOMBA is demonstrated on ECG, it should be useful for other biometrics as well.

Highly Reliable Key Generation From Electrocardiogram (ECG)

Robust authentication and identification methods become an indispensable urgent task to protect the integrity of the devices and the sensitive data Passwords have provided access control and authentication, but have shown their inherent vulnerabilities The speed and convenience factor are what makes biometrics the ideal authentication solution as they could have a low probability of circumvention To overcome the limitations of the traditional biometric systems, electrocardiogram (ECG) has received the most attention from the biometrics community due to the highly individualized nature of the ECG signals and the fact that they are ubiquitous and difficult to counterfeit However, one of the main challenges in ECG-based biometric development is the lack of large ECG databases In this paper, we contribute to creating a new large gallery off-the-person ECG datasets that can provide new opportunities for the ECG biometric research community We explore the impact of filtering type, segmentation, feature extraction, and health status on ECG biometric by using the evaluation metrics Our results have shown that our ECG biometric authentication outperforms existing methods lacking the ability to efficiently extract features, filtering, segmentation, and matching This is evident by obtaining 100% accuracy for PTB, MIT-BHI, CEBSDB, CYBHI, ECG-ID, and in-house ECG-BG database in spite of noisy, unhealthy ECG signals while performing five-fold cross-validation In addition, an average of 211% EER among 1,694 subjects is obtained

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ECG Biometric Authentication: A Comparative Analysis

Biometrics have a great deal of potential in healthcare applications, most notably authentication for medical record privacy and fraud prevention. In this paper, we examine, for the first time, non-fiducial feature extraction for photo-plethysmography (PPG) based authentication. PPG signals have unique identity properties for human authentication, and are becoming easier to capture by emerging IoT sensors such as MaxFast. Different machine learning techniques are used to compare non-fiducial and fiducial feature extractions. Our experimental results show that 99.84% accuracy with EER of 1.31% can be achieved based on non-fiducial feature extraction.

Nima Karimian

Papers

DRAM-Based Intrinsic Physically Unclonable Functions for System-Level Security and Authentication

DRAM based Intrinsic Physical Unclonable Functions for System Level Security

Highly Reliable Key Generation From Electrocardiogram (ECG)

ECG Biometric Authentication: A Comparative Analysis

Non-fiducial PPG-based authentication for healthcare application