The widespread presence of Corona virus (COVID-19) is causing organizations and individuals major economics downsizing.The way this virus is transmitted from one individual to another is the real cause of the problem.For that, researchers in different fields started seriously looking for touch-less and contact-less exchange.Particularly in the finance world, cash transactions and key pad based transactions are becoming obsolete because they are some of the major causes of the spread of this virus (and other viruses and bacteria).Cryptocurrency could be one of the solutions to the above mentioned situation.This novel money is based on Blockchain technology, which is based on cryptography algorithms for the safety and the security of the transactions.This paper exhibits a comparative study of the asymmetric cryptography algorithms.This helps the user to best choose the most secure, safe and reliable method to encrypt/decrypt the transactions created in the Blockchain.
Open access
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
Traditional elections satisfy neither citizens nor political authorities in recent years. They are not fully secure since it is easy to attack votes. It threatens also privacy and transparency of voters. Additionally, it takes too much time to count the votes. This paper proposes a solution using Blockchain to eliminate all the disadvantages of conventional elections. Security and data integrity of votes are absolutely provided theoretically. Voter privacy is another requirement that is ensured in the system. Lastly, the waiting time for results decreased significantly in the proposed Blockchain voting system.
Blockchain is the underlying technology of Bitcoin that allows a peer-to-peer distributed ledger with security and immutability. The core of a blockchain is the consensus mechanism that sets the rule for nodes in handling the shared data. Implementation of the consensus algorithm depends on the nature of targeted business environment. In this research, the performance of two consensus algorithms, Proof-of-Work (PoW) and Proof-of-Collatz Conjecture (PCC), are studied in the context of a private blockchain. A quantitative analysis on the execution time, deployment time, and latency time are done for 1, 10, 100, 1000, and 10000 transactions and the results are presented. The results shows that PCC takes only (1/1000)thof the execution time that is required for PoW for these different sets of transactions. In addition, these timings are recorded for ten repeated executions for the same sets of transactions, and found that PCC has a nearly consistent execution time.
Bitcoin and other cryptocurrencies received a lot of criticism during the last 9 years. It is not surprising that this criticism came from organizations that are threatened by the crypto revolution (banks, government, central banks, finance companies, etc.). Nevertheless, it is very surprising to hear criticism from economics schools, which oppose central banking and advocate free choice in currencies (such as the Austrian school of economics). Unlike the ordinary criticism (that Bitcoin is a scam, a bubble, etc.), which can easily be refuted, the criticism of part of the Austrian school economists is based on interesting arguments, which requires a different level of explanation. For example, it was claimed that Bitcoin should be worthless; otherwise, it contradicts Mises’ regression theorem. The object of the chapter is twofold: first to explain why the criticism is unfounded and second to analyze the origin of the value of Bitcoin and other cryptocoins from the perspective of the Austrian school of economics. In particular, it is explained that Bitcoin does not contradict the regression theorem for two reasons. First, the initial value estimation can be a random event, and second, the Bitcoin network (even now) has a nonmonetary value.
We suggest that flexible majority rules for currency issuance decisions foster the stability of a cryptocurrency. With flexible majority rules, the voteshare needed to approve a particular currency issuance growth is increasing with this growth rate. By choosing suitable parameters for these flexible majority rules, we show that optimal growth rates can be achieved in simple settings. Moreover, with flexible majority rules, changes in the composition of growth-friendly and growth-adverse agents only have a comparatively moderate impact on growth rates, and extreme growth rates are avoided. Finally, we show that optimal money growth rates are realized if agents entering financial contracts anticipate ensuing inflation rates determined by these flexible majority rules.
We consider zero-knowledge proofs, a class of cryptographic protocols by which an agent (a Prover) can prove to another agent (a Verifier) that a statement is true without revealing any additional information. For example, a zero-knowledge proof allows one to prove knowledge of a password to somebody at the other end of the communication without actually revealing the password. \nWe present an introduction to and survey literature on zero-knowledge proofs, covering the history, formal definition, and classical applications of zero-knowledge proofs. In addition, we consider connections to complexity, demonstrating that all problems in the complexity class NP have zero-knowledge proofs, and also discuss more exotic applications of zero-knowledge, namely in electronic voting and nuclear disarmament. \nWe then consider applications of zero-knowledge to financial regulation, specifically in balancing transparency and confidentiality in financial reporting. Namely, we polled professionals in the financial industry to identify three major classes of regulatory problems. We then utilize zero-knowledge proofs to develop and present cryptographic protocols/mechanisms and solutions to these regulatory problems: (1) An employer verifying an employee has no financial holdings on a blacklist without revealing the other (allowed) holdings of the employee, (2) A fund convincing its investors that its holdings subscribe to particular risk constraints, without disclosing the actual holdings, (3) A collection of investors of a fund verifying aggregate information provided by the fund, while preserving pairwise anonymity. Applications (1) and (3) are novel applications developed in this paper, while (2) is drawn from [47].
Since Bitcoin was launched in 2009, several new cryptocurrencies have been initiated with variations to Bitcoin's original design. Although Bitcoin still remains the most prominent actor in the market, some technical problems have been raised to the design of the protocol. The objective of this thesis is to determine whether the newer cryptocurrencies handle the technical problems of Bitcoin, or if they also suffer from the same issues. Instead of evaluating several cryptocurrencies for this comparison, the cryptocurrency Ethereum has been chosen as a proxy for the others. Ethereum was started in 2014, is widely backed in the community and is second in line to Bitcoin when it comes to market capitalization. \n\nAs a basis for the comparative analysis a rigorous study of the Bitcoin and Ethereum protocols have been performed, and parallel descriptions of the systems have been devised. Three technical problem have shaped the focus of the analysis: computational waste, concentration of power and ambiguity of transactions. Real world statistical data has been gathered and synthesized to enlighten the findings in the comparison. The main result of the comparison is that both systems suffer from the same problems to a certain degree, due to the fact that they utilize the same consensus mechanism. However, Ethereum utilizes several newer techniques to try and reduce the severity of these problems compared to Bitcoin, with varying degrees of success.
Abstract The philosophy of blockchain technology is concerned, among other things, with blockchain ontology, how it might be characterised, how it is being created, implemented, and adopted, how it operates in the world, and how it evolves over time. This paper concentrates on whether Bitcoin/blockchain can be considered a complex system and, if so, whether it is a chaotic one. Beyond mere academic curiosity, a positive response would raise concerns about the likelihood of Bitcoin/blockchain entering a 2010‐Flash‐Crash‐type of chaotic regime, with catastrophic consequences for financial systems based on it. The paper starts by highlighting the relevant details of the Bitcoin/blockchain ecosystem formed by the blockchain itself, bitcoin end users (payers and payees), capital gains seekers, miners, full nodes maintainers, and developers, and their interactions. Then the Information Theory of Complex Systems is briefly discussed for later use. Finally, the blockchain is investigated with the help of Crutchfield's Statistical Complexity measure. The low non‐null statistical complexity value obtained suggests that the blockchain may be considered algorithmically complicated but hardly a complex system and unlikely to enter a chaotic regime.
We examine the power of statistical zero knowledge proofs (captured by the complexity class SZK) and their variants. First, we give the strongest known relativized evidence that SZK contains hard problems, by exhibiting an oracle relative to which SZK (indeed, even NISZK) is not contained in the class UPP, containing those problems solvable by randomized algorithms with unbounded error. This answers an open question of Watrous from 2002 [Aar]. Second, we "lift" this oracle separation to the setting of communication complexity, thereby answering a question of Göös et al. (ICALP 2016). Third, we give relativized evidence that perfect zero knowledge proofs (captured by the class PZK) are weaker than general zero knowledge proofs. Specifically, we exhibit oracles relative to which SZK is not contained in PZK, NISZK is not contained in NIPZK, and PZK is not equal to coPZK. The first of these results answers a question raised in 1991 by Aiello and Håstad (Information and Computation), and the second answers a question of Lovett and Zhang (2016). We also describe additional applications of these results outside of structural complexity. The technical core of our results is a stronger hardness amplification theorem for approximate degree, which roughly says that composing the gapped-majority function with any function of high approximate degree yields a function with high threshold degree.
Artykuł porusza problem identyfikacji (w oparciu o rozkład Benforda) nietypowych transakcji w sieci Bitcoin. Dla przykładowo wybranych adresów portfeli Bitcoin porównano rozkład Benforda z rozkładem częstotliwości występowania poszczególnych cyfr na pierwszej najbardziej znaczącej pozycji w kwotach transakcji związanych z tymi adresami. Rozkłady te nie były zgodne z rozkładem Benforda. Zwrócono uwagę na konieczność zachowania dużej ostrożności przy analizowaniu transakcji za pomocą narzędzi statystycznych takich jak rozkład Benforda. Brak zgodności z rozkładem Benforda w żadnym wypadku nie jest równoznaczny z prowadzeniem działalności niezgodnej z prawem. Z drugiej strony, zgodność z rozkładem Benforda nie stanowi gwarancji tego, że nie występują nieprawidłowości.
We show that the behaviour of Bitcoin has interesting similarities to stock\nand precious metal markets, such as gold and silver. We report that whilst\nLitecoin, the second largest cryptocurrency, closely follows Bitcoin's\nbehaviour, it does not show all the reported properties of Bitcoin. Agreements\nbetween apparently disparate complexity measures have been found, and it is\nshown that statistical, information-theoretic, algorithmic and fractal measures\nhave different but interesting capabilities of clustering families of markets\nby type. The report is particularly interesting because of the range and novel\nuse of some measures of complexity to characterize price behaviour, because of\nthe IRS designation of Bitcoin as an investment property and not a currency,\nand the announcement of the Canadian government's own electronic currency\nMintChip.\n
Joachim von zur Gathen, Oded Goldreich, Madhu Sudan
The workshop Complexity Theory was organized by Joachim von zur Gathen (Universität Bonn), Oded Goldreich (Weizmann Institute), and Madhu Sudan (MIT). The workshop was held on June 24th–30th 2007, and attended by approximately 50 participants spanning a wide range of interests within the field of Computational Complexity. The plenary program, attended by all participants, featured eight long lectures as well as short (10-minute) reports by almost all participants. In addition, extensive interaction took place in smaller groups. The Oberwolfach Meeting on Complexity Theory is marked by a long tradition and a continuous transformation. Originally starting with a focus on algebraic and Boolean complexity, the meeting has continuously evolved to cover a wide variety of areas, most of which were not even in existence at the time of the first meeting (in 1972). While inviting many of the most prominent researchers in the field, the organizers try to identify and invite a fair number of promising young researchers. Computational complexity (a.k.a. complexity theory) is a central field of computer science with a remarkable list of celebrated achievements as well as a vibrant research activity. The field is concerned with the study of the intrinsic complexity of computational tasks, and this study tends to aim at generality : it focuses on natural computational resources, and considers the effect of limiting these resources on the class of problems that can be solved. Computational complexity is related to and has substantial interaction with other areas of mathematics such as number theory, algebra, combinatorics, coding theory, and optimization. The workshop focused on several sub-areas of complexity theory and its nature may be best illustrated by a brief survey of some of the meeting's highlights. Connections to the Theory of Error-Correcting Codes. The interplay between coding theory and complexity theory first emerged in the context of “hardness amplification” (almost two decades ago) and other connections are less than a decade old (e.g., the connection to probabilistic checking of proofs and extraction of pure randomness). Several applications of the known connections were presented in the current meeting, and in addition a new connection to algebraic complexity was presented. While previous applications of the aforementioned connections went in the direction of coding theory to complexity theory, a recent result reported by Venkat Guruswami goes in the opposite direction. This work, by Guruswami and his graduate student (Rudra), resolves a decades-old central problem in coding theory by presenting an explicit error-correcting code of constant-size alphabet that approaches the capacity bound (under worst-case errors, using list decoding). Extracting randomness. Extracting almost-perfect randomness from weak sources of (imperfect) randomness is crucial for the actual use of randomized procedures. Typical analyses of randomized procedures assume that the procedures have access to a perfect random source. However, in reality one only has access to sources of weak randomness (e.g., having constant entropy rate). Indeed, the problem has attracted a lot of attention in the last couple of decades. In the meeting, Chris Umans has presented recent work with Guruswami and Vadhan, which utilizes recent algebraic and coding theoretic techniques to the construction of (single-source) randomness extractors. This construction meets (and actually improves) the best known parameters for the problem (which are almost optimal), but does so by a relatively simple construction rather than by a complex combination of numerous constructs (as done in prior work). Furthermore, the new work introduces improved constructions for an intermediate primitive (called randomness condenser), which is of independent interest. While single-source randomness extractors must utilize an auxiliary random seed (which may be very short), some applications do not allow for such a seed. In this case, extraction from several (e.g., two) independent sources of weak randomness is called for. An important step in the study of this direction was made by Anup Rao, and presented by him in the meeting. Algebraic complexity and modular polynomial composition. An important task in algebraic computation is modular polynomial composition; that is, given three univariate polynomials f,g and h , one is required to obtain the coefficients of the polynomial f \circ g \bmod h . This task has many applications, most notably as an ingredient in algorithms for polynomial factorization. The previously best algorithm was presented 30 years ago and uses O(n^{1.7}) arithmetic operations, where n denotes the maximum degree of the polynomials. In the meeting, Chris Umans presented significant progress on this celebrated open problem in the form of an almost linear-time algorithm that works for fields of small characteristic. This major progress on a purely algebraic problem is essentially based on methods that were introduced into coding theory by Guruswami and Rudra, and then applied to complexity theory in the context of randomness extractors (see foregoing paragraphs). All three results, which are major achievements in their respective areas, were presented at the meeting. Cryptography and Zero-Knowledge. Zero-knowledge proofs are fascinating concepts and extremely useful constructs. Their fascinating nature is due to their seemingly contradictory definition that mandates that they be convincing and yet yield nothing beyond the validity of the assertion being proved. Their applicability in the domain of cryptography is vast; they are typically used to force malicious parties to behave according to a predetermined protocol. In addition to their direct applicability in cryptography, zero-knowledge proofs serve as a good bench-mark for the study of various problems regarding cryptographic protocols. Zero-knowledge proofs come in many flavors, and it is of great theoretical and practical importance to investigate the relationship among them. A central problem in this area, which has been open since 1986, refers to the gap between the known results regarding two dual notions: the notion of general zero-knowledge proofs (in which the secrecy condition holds with respect to feasible adversaries) and the notion of statistical zero-knowledge arguments (in which the soundness condition holds with respect to feasible adversaries). This gap was bridged in a recent work of Salil Vadhan, jointly with his graduate students (Nguyen and Ong), and was presented by Vadhan in this meeting. A problem related to both cryptography and coding theory is the problem of constructing private information retrieval schemes and/or locally decodable codes. In the context of error-correcting codes, such schemes should allow the recovery of any bit in the original message based on a constant number (e.g., three) probes to the corrupted codeword. For more than a decade it was believed that the length of such codewords must be (weakly) exponential in the length of the message. In the meeting, Sergey Yekhanin (PhD student) presented his recent result that refutes this belief. Delegating your work to an untrusted entities. Needless to say, it is nice to delegate your work to others, but what if you don't trust the others? The very definition of a proof system refers to such a possibility – the hard task of finding a proof is delegated to the outside while you make sure that the proof is valid by performing the easier task of verification. However, facilitating verification may mean making the task of finding adequate proofs even harder. In the context of program checking this phenomenon is explicitly disallowed: wishing to solve some problem you may use an untrusted program that supposedly solves this problem (but not a program that solve more complex problems). Needless to say, the aim is allowing the delegator, called a checker, to use significantly few
To provide a high level of security guarantee cryptography is introduced into the design of the voting machine. The voting machine based on cryptography is vulnerable to attacks through covert channels. An adversary may inject malicious codes into the voting machine and make it leak vote information unnoticeably by exploiting the randomness used in encryptions and zero-knowledge proofs. In this paper a voting machine resistant to covert channels is designed. It has the following properties: Firstly, it is tamper-evident. The randomness used by the voting machine is generated by the election authority. The inconsistent use of the randomness can be detected by the voter from examining a destroyable verification code. Even if malicious codes are run in the voting machine attacks through subliminal channels are thwarted. Next, it is voter-verifiable. The voter has the ability to verify if the ballot cast by the machine is consistent with her intent without doing complicated cryptographic computation. Finally, the voting system is receipt-free. Vote-buying and coercion are prevented.
2 source records
Internet Traffic Analysis and Secure E-voting
Cryptography and Data Security
Advanced Steganography and Watermarking Techniques
Let r v (N) denote the number of representations of the integer N as a sum
of v square-free numbers. We obtain unconditional and conditional bounds for
the error term in the asymptotic formula for rv (N), when v > 3. The conditional
bounds are essentially best possible for v > 4. The unconditional bounds are,
for v > 3, essentially best possible with respect to the present knowledge on
the distribution of the zeros of the Riemann zeta function. Proofs are based on
the circle method. The main ingredients are a new pointwise estimate for the
exponential sum S(a) over square-free numbers and a recent bound (see [3]) for
the L2-norm of S(a) restricted to the minor arcs.
We study the computational complexity of languages which have interactive proofs of logarithmic knowledge complexity. We show that all such languages can be recognized in ${\cal BPP}^{\cal NP}$. Prior to this work, for languages with greater-than-zero knowledge complexity only trivial computational complexity bounds were known. In the course of our proof, we relate statistical knowledge complexity to perfect knowledge complexity; specifically, we show that, for the honest verifier, these hierarchies coincide up to a logarithmic additive term.