Biblio
The paper contains the results of perspective digital signatures algorithms based on hash functions analysis. Several aspects of their implementation are presented. The comparative analysis was carried out by the method of hierarchies. Some problems of implementation in the existing infrastructure are described. XMSS algorithm implementation with Ukrainian hash function national standard is presented.
Existing data management and searching system for Internet of Things uses centralized database. For this reason, security vulnerabilities are found in this system which consists of server such as IP spoofing, single point of failure and Sybil attack. This paper proposes data management system is based on blockchain which ensures security by using ECDSA digital signature and SHA-256 hash function. Location that is indicated as IP address of data owner and data name are transcribed in block which is included in the blockchain. Furthermore, we devise data manegement and searching method through analyzing block hash value. By using security properties of blockchain such as authentication, non-repudiation and data integrity, this system has advantage of security comparing to previous data management and searching system using centralized database or P2P networks.
Trust in SSL-based communications is provided by Certificate Authorities (CAs) in the form of signed certificates. Checking the validity of a certificate involves three steps: (i) checking its expiration date, (ii) verifying its signature, and (iii) ensuring that it is not revoked. Currently, such certificate revocation checks are done either via Certificate Revocation Lists (CRLs) or Online Certificate Status Protocol (OCSP) servers. Unfortunately, despite the existence of these revocation checks, sophisticated cyber-attackers, may trick web browsers to trust a revoked certificate, believing that it is still valid. Consequently, the web browser will communicate (over TLS) with web servers controlled by cyber-attackers. Although frequently updated, nonced, and timestamped certificates may reduce the frequency and impact of such cyber-attacks, they impose a very large overhead to the CAs and OCSP servers, which now need to timestamp and sign on a regular basis all the responses, for every certificate they have issued, resulting in a very high overhead. To mitigate this overhead and provide a solution to the described cyber-attacks, we present CCSP: a new approach to provide timely information regarding the status of certificates, which capitalizes on a newly introduced notion called signed collections. In this paper, we present the design, preliminary implementation, and evaluation of CCSP in general, and signed collections in particular. Our preliminary results suggest that CCSP (i) reduces space requirements by more than an order of magnitude, (ii) lowers the number of signatures required by 6 orders of magnitude compared to OCSP-based methods, and (iii) adds only a few milliseconds of overhead in the overall user latency.
Cryptography and encryption is a topic that is blurred by its complexity making it difficult for the majority of the public to easily grasp. The focus of our research is based on SSL technology involving CAs, a centralized system that manages and issues certificates to web servers and computers for validation of identity. We first explain how the certificate provides a secure connection creating a trust between two parties looking to communicate with one another over the internet. Then the paper goes into what happens when trust is compromised and how information that is being transmitted could possibly go into the hands of the wrong person. We are proposing a browser plugin, Certificate Authority Rescue Engine (CAre), to serve as an added source of security with simplicity and visibility. In order to see why CAre will be an added benefit to average and technical users of the internet, one must understand what website security entails. Therefore, this paper will dive deep into website security through the use of public key infrastructure and its core components; certificates, certificate authorities, and their relationship with web browsers.
The collection of high frequency metering data in the emerging smart grid gives rise to the concern of consumer privacy. Anonymization of metering data is one of the proposed approaches in the literature, which enables transmission of unmasked data while preserving the privacy of the sender. Distributed anonymization methods can reduce the dependency on service providers, thus promising more privacy for the consumers. However, the distributed communication among the end-users introduces overhead and requires methods to prevent external attacks. In this paper, we propose four variants of a distributed anonymization method for smart metering data privacy, referred to as the Collaborative Anonymity Set Formation (CASF) method. The performance overhead analysis and security analysis of the variants are done using NS-3 simulator and the Scyther tool, respectively. It is shown that the proposed scheme enhances the privacy preservation functionality of an existing anonymization scheme, while being robust against external attacks.
Bitcoin is a decentralized digital currency, widely used for its perceived anonymity property, and has surged in popularity in recent years. Bitcoin publishes the complete transaction history in a public ledger, under pseudonyms of users. This is an alternative way to prevent double-spending attack instead of central authority. Therefore, if pseudonyms of users are attached to their identities in real world, the anonymity of Bitcoin will be a serious vulnerability. It is necessary to enhance anonymity of Bitcoin by a coin mixing service or other modifications in Bitcoin protocol. But in a coin mixing service, the relationship among input and output addresses is not hidden from the mixing service provider. So the mixing server still has the ability to track the transaction records of Bitcoin users. To solve this problem, We present a new coin mixing scheme to ensure that the relationship between input and output addresses of any users is invisible for the mixing server. We make use of a ring signature algorithm to ensure that the mixing server can't distinguish specific transaction from all these addresses. The ring signature ensures that a signature is signed by one of its users in the ring and doesn't leak any information about who signed it. Furthermore, the scheme is fully compatible with existing Bitcoin protocol and easily to scale for large amount of users.
The ubiquity of the Internet and email, have provided a mostly insecure communication medium for the consumer. During the last few decades, we have seen the development of several ways to secure email messages. However, these solutions are inflexible and difficult to use for encrypting email messages to protect security and privacy while communicating or collaborating via email. Under the current paradigm, the arduous process of setting up email encryption is non-intuitive for the average user. The complexity of the current practices has also yielded to incorrect developers' interpretation of architecture which has resulted in interoperability issues. As a result, the lack of simple and easy-to-use infrastructure in current practices means that the consumers still use plain text emails over insecure networks. In this paper, we introduce and describe a novel, holistic model with new techniques for protecting email messages. The architecture of our innovative model is simpler and easier to use than those currently employed. We use the simplified trust model, which can relieve users from having to perform many complex steps to achieve email security. Utilizing the new techniques presented in this paper can safeguard users' email from unauthorized access and protect their privacy. In addition, a simplified infrastructure enables developers to understand the architecture more readily eliminating interoperability.
Universally Composable (UC) framework provides the strongest security notion for designing fully trusted cryptographic protocols, and it is very challenging on applying UC security in the design of RFID mutual authentication protocols. In this paper, we formulate the necessary conditions for achieving UC secure RFID mutual authentication protocols which can be fully trusted in arbitrary environment, and indicate the inadequacy of some existing schemes under the UC framework. We define the ideal functionality for RFID mutual authentication and propose the first UC secure RFID mutual authentication protocol based on public key encryption and certain trusted third parties which can be modeled as functionalities. We prove the security of our protocol under the strongest adversary model assuming both the tags' and readers' corruptions. We also present two (public) key update protocols for the cases of multiple readers: one uses Message Authentication Code (MAC) and the other uses trusted certificates in Public Key Infrastructure (PKI). Furthermore, we address the relations between our UC framework and the zero-knowledge privacy model proposed by Deng et al. [1].
Recently perceived vulnerabilities in public key infrastructures (PKI) demand that a semantic or cognitive definition of trust is essential for augmenting the security through trust formulations. In this paper, we examine the meaning of trust in PKIs. Properly categorized trust can help in developing intelligent algorithms that can adapt to the security and privacy requirements of the clients. We delineate the different types of trust in a generic PKI model.
Different organizations or countries maybe adopt different PKI trust model in real applications. On a large scale, all certification authorities (CA) and end entities construct a huge mesh network. PKI trust model exhibits unstructured mesh network as a whole. However, mesh trust model worsens computational complexity in certification path processing when the number of PKI domains increases. This paper proposes an enhanced mesh trust model for PKI. Keys generation and signature are fulfilled in Trusted Platform Module (TPM) for higher security level. An algorithm is suggested to improve the performance of certification path processing in this model. This trust model is less complex but more efficient and robust than the existing PKI trust models.
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.
Cloud storage can provide outsourcing data services for both organizations and individuals. However, cloud storage still faces many challenges, e.g., public integrity auditing, the support of dynamic data, and low computational audit cost. To solve the problems, a number of techniques have been proposed. Recently, Tian et al. proposed a novel public auditing scheme for secure cloud storage based on a new data structure DHT. The authors claimed that their scheme was proven to be secure. Unfortunately, through our security analysis, we find that the scheme suffers from one attack and one security shortage. The attack is that an adversary can forge the data to destroy the correctness of files without being detected. The shortage of the scheme is that the updating operations for data blocks is vulnerable and easy to be modified. Finally, we give our countermeasures to remedy the security problems.
For over two decades the OpenPGP format has provided the mainstay of email confidentiality and authenticity, and is currently being relied upon to provide authenticated package distributions in open source Unix systems. In this work, we provide the first language theoretical analysis of the OpenPGP format, classifying it as a deterministic context free language and establishing that an automatically generated parser can in principle be defined. However, we show that the number of rules required to describe it with a deterministic context free grammar is prohibitively high, and we identify security vulnerabilities in the OpenPGP format specification. We identify possible attacks aimed at tampering with messages and certificates while retaining their syntactical and semantical validity. We evaluate the effectiveness of these attacks against the two OpenPGP implementations covering the overwhelming majority of uses, i.e., the GNU Privacy Guard (GPG) and Symantec PGP. The results of the evaluation show that both implementations turn out not to be vulnerable due to conser- vative choices in dealing with malicious input data. Finally, we provide guidelines to improve the OpenPGP specification
as data size is growing up, cloud storage is becoming more familiar to store a significant amount of private information. Government and private organizations require transferring plenty of business files from one end to another. However, we will lose privacy if we exchange information without data encryption and communication mechanism security. To protect data from hacking, we can use Asymmetric encryption technique, but it has a key exchange problem. Although Asymmetric key encryption deals with the limitations of Symmetric key encryption it can only encrypt limited size of data which is not feasible for a large amount of data files. In this paper, we propose a probabilistic approach to Pretty Good Privacy technique for encrypting large-size data, named as ``BigCrypt'' where both Symmetric and Asymmetric key encryption are used. Our goal is to achieve zero tolerance security on a significant amount of data encryption. We have experimentally evaluated our technique under three different platforms.
Internet of Thing (IoT) provide services by linking the different platform devices. They have the limitation in providing intelligent service. The IoT devices are heterogeneous which includes wireless sensors to less resource constrained devices. These devices are prone to hardware/software and network attacks. If not properly secured, it may lead to security issues like privacy and confidentiality. To resolve the above problem, an Intelligent Security Framework for IoT Devices is proposed in this paper. The proposed method is made up of (1) the light weight Asymmetric cryptography for securing the End-To-End devices which protects the IoT service gateway and the low power sensor nodes and (2) implements Lattice-based cryptography for securing the Broker devices/Gateway and the cloud services. The proposed architecture implements Asymmetric Key Encryption to share session key between the nodes and then uses this session key for message transfer This protects the system from Distributed Denial of Service Attacks, eavesdropping and Quantum algorithm attacks. The proposed protocol uses the unique Device ID of the sensors to generate key pair to establish mutual authentication between Devices and Services. Finally, the Mutual authentication mechanism is implemented in the gateway.
Cloud computing emerged in the last years to handle systems with large-scale services sharing between vast numbers of users. It provides enormous storage for data and computing power to users over the Internet. There are many issues with the high growth of data. Data security is one of the most important issues in cloud computing. There are many algorithms and implementation for data security. These algorithms provided various encryption methods. In this work, We present a comprehensive study between Symmetric key and Asymmetric key encryption algorithms that enhanced data security in cloud computing system. We discuss AES, DES, 3DES and Blowfish for symmetric encryption algorithms, and RSA, DSA, Diffie-Hellman and Elliptic Curve, for asymmetric encryption algorithms.
Trust Management (TM) systems for authentication are vital to the security of online interactions, which are ubiquitous in our everyday lives. Various systems, like the Web PKI (X.509) and PGP's Web of Trust are used to manage trust in this setting. In recent years, blockchain technology has been introduced as a panacea to our security problems, including that of authentication, without sufficient reasoning, as to its merits.In this work, we investigate the merits of using open distributed ledgers (ODLs), such as the one implemented by blockchain technology, for securing TM systems for authentication. We formally model such systems, and explore how blockchain can help mitigate attacks against them. After formal argumentation, we conclude that in the context of Trust Management for authentication, blockchain technology, and ODLs in general, can offer considerable advantages compared to previous approaches. Our analysis is, to the best of our knowledge, the first to formally model and argue about the security of TM systems for authentication, based on blockchain technology. To achieve this result, we first provide an abstract model for TM systems for authentication. Then, we show how this model can be conceptually encoded in a blockchain, by expressing it as a series of state transitions. As a next step, we examine five prevalent attacks on TM systems, and provide evidence that blockchain-based solutions can be beneficial to the security of such systems, by mitigating, or completely negating such attacks.
Cooperative spectrum sensing is often necessary in cognitive radios systems to localize a transmitter by fusing the measurements from multiple sensing radios. However, revealing spectrum sensing information also generally leaks information about the location of the radio that made those measurements. We propose a protocol for performing cooperative spectrum sensing while preserving the privacy of the sensing radios. In this protocol, radios fuse sensing information through a distributed particle filter based on a tree structure. All sensing information is encrypted using public-key cryptography, and one of the radios serves as an anonymizer, whose role is to break the connection between the sensing radios and the public keys they use. We consider a semi-honest (honest-but-curious) adversary model in which there is at most a single adversary that is internal to the sensing network and complies with the specified protocol but wishes to determine information about the other participants. Under this scenario, an adversary may learn the sensing information of some of the radios, but it does not have any way to tie that information to a particular radio's identity. We test the performance of our proposed distributed, tree-based particle filter using physical measurements of FM broadcast stations.
Data Deduplication provides lots of benefits to security and privacy issues which can arise as user's sensitive data at risk of within and out of doors attacks. Traditional secret writing that provides knowledge confidentiality is incompatible with knowledge deduplication. Ancient secret writing wants completely different users to encode their knowledge with their own keys. Thus, identical knowledge copies of completely different various users can result in different ciphertexts that makes Deduplication not possible. Convergent secret writing has been planned to enforce knowledge confidentiality whereas creating Deduplication possible. It encrypts/decrypts a knowledge copy with a confluent key, that is obtained by computing the cryptographical hash price of the content of the information copy. Once generation of key and encryption, the user can retain the keys and send ciphertext to cloud.
Bitcoin, a peer-to-peer payment system and digital currency, is often involved in illicit activities such as scamming, ransomware attacks, illegal goods trading, and thievery. At the time of writing, the Bitcoin ecosystem has not yet been mapped and as such there is no estimate of the share of illicit activities. This paper provides the first estimation of the portion of cyber-criminal entities in the Bitcoin ecosystem. Our dataset consists of 854 observations categorised into 12 classes (out of which 5 are cybercrime-related) and a total of 100,000 uncategorised observations. The dataset was obtained from the data provider who applied three types of clustering of Bitcoin transactions to categorise entities: co-spend, intelligence-based, and behaviour-based. Thirteen supervised learning classifiers were then tested, of which four prevailed with a cross-validation accuracy of 77.38%, 76.47%, 78.46%, 80.76% respectively. From the top four classifiers, Bagging and Gradient Boosting classifiers were selected based on their weighted average and per class precision on the cybercrime-related categories. Both models were used to classify 100,000 uncategorised entities, showing that the share of cybercrime-related is 29.81% according to Bagging, and 10.95% according to Gradient Boosting with number of entities as the metric. With regard to the number of addresses and current coins held by this type of entities, the results are: 5.79% and 10.02% according to Bagging; and 3.16% and 1.45% according to Gradient Boosting.
In this paper, a practical quantum public-key encryption model is proposed by studying the recent quantum public-key encryption. This proposed model makes explicit stipulations on the generation, distribution, authentication, and usage of the secret keys, thus forms a black-box operation. Meanwhile, this proposed model encapsulates the process of encryption and decryption for the users, and forms a blackbox client-side. In our models, each module is independent and can be replaced arbitrarily without affecting the proposed model. Therefore, this model has a good guiding significance for the design and development of the quantum public key encryption schemes.
We use symbolic formal models to study the composition of public key-based protocols with public key infrastructures (PKIs). We put forth a minimal set of requirements which a PKI should satisfy and then identify several reasons why composition may fail. Our main results are positive and offer various trade-offs which align the guarantees provided by the PKI with those required by the analysis of protocol with which they are composed. We consider both the case of ideally distributed keys but also the case of more realistic PKIs.,,Our theorems are broadly applicable. Protocols are not limited to specific primitives and compositionality asks only for minimal requirements on shared ones. Secure composition holds with respect to arbitrary trace properties that can be specified within a reasonably powerful logic. For instance, secrecy and various forms of authentication can be expressed in this logic. Finally, our results alleviate the common yet demanding assumption that protocols are fully tagged.
In this paper, we propose a lightweight multi-receiver encryption scheme for the device to device communications on Internet of Things (IoT) applications. In order for the individual user to control the disclosure range of his/her own data directly and to prevent sensitive personal data disclosure to the trusted third party, the proposed scheme uses device-generated public keys. For mutual authentication, third party generates Schnorr-like lightweight identity-based partial private keys for users. The proposed scheme provides source authentication, message integrity, replay-attack prevention and implicit user authentication. In addition to more security properties, computation expensive pairing operations are eliminated to achieve less time usage for both sender and receiver, which is favourable property for IoT applications. In this paper, we showed a proof of security of our scheme, computational cost comparison and experimental performance evaluations. We implemented our proposed scheme on real embedded Android devices and confirmed that it achieves less time cost for both encryption and decryption comparing with the existing most efficient certificate-based multi-receiver encryption scheme and certificateless multi-receiver encryption scheme.
Bitcoin is the most famous cryptocurrency currently operating with a total marketcap of almost 7 billion USD. This innovation stands strong on the feature of pseudo anonymity and strives on its innovative de-centralized architecture based on the Blockchain. The Blockchain is a distributed ledger that keeps a public record of all the transactions processed on the bitcoin protocol network in full transparency without revealing the identity of the sender and the receiver. Over the course of 2016, cryptocurrencies have shown some instances of abuse by criminals in their activities due to its interesting nature. Darknet marketplaces are increasing the volume of their businesses in illicit and illegal trades but also cryptocurrencies have been used in cases of extortion, ransom and as part of sophisticated malware modus operandi. We tackle these challenges by developing an analytical capability that allows us to map relationships on the blockchain and filter crime instances in order to investigate the abuse in law enforcement local environment. We propose a practical bitcoin analytical process and an analyzing system that stands alone and manages all data on the blockchain in real-time with tracing and visualizing techniques rendering transactions decipherable and useful for law enforcement investigation and training. Our system adopts combination of analyzing methods that provides statistics of address, graphical transaction relation, discovery of paths and clustering of already known addresses. We evaluated our system in the three criminal cases includes marketplace, ransomware and DDoS extortion. These are practical training in law enforcement, then we determined whether our system could help investigation process and training.