Searchable atribute-based mechanism with efficiient data sharing for secure cloud storage

To date, the growth of electronic personal data leads to a trend that data owners prefer to remotely outsource their data to clouds for the enjoyment of the high-quality retrieval and storage service without worrying the burden of local data management and maintenance. However, secure share and search for the outsourced data is a formidable task, which may easily incur the leakage of sensitive personal information. Efficient data sharing and searching with security is of critical importance. This paper, for the first time, proposes a searchable attribute-based proxy re-encryption system. When compared to existing systems only supporting either searchable attribute-based functionality or attribute-based proxy re-encryption, our new primitive supports both abilities and provides flexible keyword update service. Specifically, the system enables a data owner to efficiently share his data to a specified group of users matching a sharing policy and meanwhile, the data will maintain its searchable property but also the corresponding search keyword(s) can be updated after the data sharing. The new mechanism is applicable to many real-world applications, such as electronic health record systems. It is also proved chosen ciphertext secure in the random oracle model

Explanation of the Model Checker Verification Results

Immer wenn neue Anforderungen an ein System gestellt werden, müssen die Korrektheit und Konsistenz der Systemspezifikation überprüft werden, was in der Praxis in der Regel manuell erfolgt. Eine mögliche Option, um die Nachteile dieser manuellen Analyse zu überwinden, ist das sogenannte Contract-Based Design. Dieser Entwurfsansatz kann den Verifikationsprozess zur Überprüfung, ob die Anforderungen auf oberster Ebene konsistent verfeinert wurden, automatisieren. Die Verifikation kann somit iterativ durchgeführt werden, um die Korrektheit und Konsistenz des Systems angesichts jeglicher Änderung der Spezifikationen sicherzustellen. Allerdings ist es aufgrund der mangelnden Benutzerfreundlichkeit und der Schwierigkeiten bei der Interpretation von Verifizierungsergebnissen immer noch eine Herausforderung, formale Ansätze in der Industrie einzusetzen. Stellt beispielsweise der Model Checker bei der Verifikation eine Inkonsistenz fest, generiert er ein Gegenbeispiel (Counterexample) und weist gleichzeitig darauf hin, dass die gegebenen Eingabespezifikationen inkonsistent sind. Hier besteht die gewaltige Herausforderung darin, das generierte Gegenbeispiel zu verstehen, das oft sehr lang, kryptisch und komplex ist. Darüber hinaus liegt es in der Verantwortung der Ingenieurin bzw. des Ingenieurs, die inkonsistente Spezifikation in einer potenziell großen Menge von Spezifikationen zu identifizieren. Diese Arbeit schlägt einen Ansatz zur Erklärung von Gegenbeispielen (Counterexample Explanation Approach) vor, der die Verwendung von formalen Methoden vereinfacht und fördert, indem benutzerfreundliche Erklärungen der Verifikationsergebnisse der Ingenieurin bzw. dem Ingenieur präsentiert werden. Der Ansatz zur Erklärung von Gegenbeispielen wird mittels zweier Methoden evaluiert: (1) Evaluation anhand verschiedener Anwendungsbeispiele und (2) eine Benutzerstudie in Form eines One-Group Pretest-Posttest Experiments.Whenever new requirements are introduced for a system, the correctness and consistency of the system specification must be verified, which is often done manually in industrial settings. One viable option to traverse disadvantages of this manual analysis is to employ the contract-based design, which can automate the verification process to determine whether the refinements of top-level requirements are consistent. Thus, verification can be performed iteratively to ensure the system’s correctness and consistency in the face of any change in specifications. Having said that, it is still challenging to deploy formal approaches in industries due to their lack of usability and their difficulties in interpreting verification results. For instance, if the model checker identifies inconsistency during the verification, it generates a counterexample while also indicating that the given input specifications are inconsistent. Here, the formidable challenge is to comprehend the generated counterexample, which is often lengthy, cryptic, and complex. Furthermore, it is the engineer’s responsibility to identify the inconsistent specification among a potentially huge set of specifications. This PhD thesis proposes a counterexample explanation approach for formal methods that simplifies and encourages their use by presenting user-friendly explanations of the verification results. The proposed counterexample explanation approach identifies and explains relevant information from the verification result in what seems like a natural language statement. The counterexample explanation approach extracts relevant information by identifying inconsistent specifications from among the set of specifications, as well as erroneous states and variables from the counterexample. The counterexample explanation approach is evaluated using two methods: (1) evaluation with different application examples, and (2) a user-study known as one-group pretest and posttest experiment

A Comprehensive Bibliometric Analysis on Social Network Anonymization: Current Approaches and Future Directions

In recent decades, social network anonymization has become a crucial research field due to its pivotal role in preserving users' privacy. However, the high diversity of approaches introduced in relevant studies poses a challenge to gaining a profound understanding of the field. In response to this, the current study presents an exhaustive and well-structured bibliometric analysis of the social network anonymization field. To begin our research, related studies from the period of 2007-2022 were collected from the Scopus Database then pre-processed. Following this, the VOSviewer was used to visualize the network of authors' keywords. Subsequently, extensive statistical and network analyses were performed to identify the most prominent keywords and trending topics. Additionally, the application of co-word analysis through SciMAT and the Alluvial diagram allowed us to explore the themes of social network anonymization and scrutinize their evolution over time. These analyses culminated in an innovative taxonomy of the existing approaches and anticipation of potential trends in this domain. To the best of our knowledge, this is the first bibliometric analysis in the social network anonymization field, which offers a deeper understanding of the current state and an insightful roadmap for future research in this domain.Comment: 73 pages, 28 figure

Raptor: A Practical Lattice-Based (Linkable) Ring Signature

We present Raptor, the first practical lattice-based (linkable) ring signature scheme with implementation. Raptor is as fast as classical solutions; while the size of the signature is roughly $1.3$ KB per user. Prior to our work, all existing lattice-based solutions are analogues of their discrete-log or pairing-based counterparts. We develop a generic construction of (linkable) ring signatures based on the well-known generic construction from Rivest et al., which is not fully compatible with lattices. We show that our generic construction is provably secure in random oracle model. We also give instantiations from both standard lattice, as a proof of concept, and NTRU lattice, as an efficient instantiation. We showed that the latter construction, called Raptor, is almost as efficient as the classical RST ring signatures and thus may be of practical interest

RingCT 2.0: A Compact Accumulator-Based (Linkable Ring Signature) Protocol for Blockchain Cryptocurrency Monero

In this work, we initially study the necessary properties and security requirements of Ring Confidential Transaction (RingCT) protocol deployed in the popular anonymous cryptocurrency Monero. Firstly, we formalize the syntax of RingCT protocol and present several formal security definitions according to its application in Monero. Based on our observations on the underlying (linkable) ring signature and commitment schemes, we then put forward a new efficient RingCT protocol (RingCT 2.0), which is built upon the well-known Pedersen commitment, accumulator with one-way domain and signature of knowledge (which altogether perform the functions of a linkable ring signature). Besides, we show that it satisfies the security requirements if the underlying building blocks are secure in the random oracle model. In comparison with the original RingCT protocol, our RingCT 2.0 protocol presents a significant space saving, namely, the transaction size is independent of the number of groups of input accounts included in the generalized ring while the original RingCT suffers a linear growth with the number of groups, which would allow each block to process more transactions

Privacy-Preserving Credentials Upon Trusted Computing Augmented Servers

Abstract. Credentials are an indispensable means for service access control in electronic commerce. However, regular credentials such as X.509 certificates and SPKI/SDSI certificates do not address user pri-vacy at all, while anonymous credentials that protect user privacy are complex and have compatibility problems with existing PKIs. In this pa-per we propose privacy-preserving credentials, a concept between regular credentials and anonymous credentials. The privacy-preserving creden-tials enjoy the advantageous features of both regular credentials and anonymous credentials, and strike a balance between user anonymity and system complexity. We achieve this by employing computer servers equipped with TPMs (Trusted Platform Modules). We present a detailed construction for ElGamal encryption credentials. We also present XML-based specification for the privacy-preserving credentials.

Degenerate Curve Attacks

Invalid curve attacks are a well-known class of attacks against implementations of elliptic curve cryptosystems, in which an adversary tricks the cryptographic device into carrying out scalar multiplication not on the expected secure curve, but on some other, weaker elliptic curve of his choosing. In their original form, however, these attacks only affect elliptic curve implementations using addition and doubling formulas that are independent of at least one of the curve parameters. This property is typically satisfied for elliptic curves in Weierstrass form but not for newer models that have gained increasing popularity in recent years, like Edwards and twisted Edwards curves. It has therefore been suggested (e.g. in the original paper on invalid curve attacks) that such alternate models could protect against those attacks. In this paper, we dispel that belief and present the first attack of this nature against (twisted) Edwards curves, Jacobi quartics, Jacobi intersections and more. Our attack differs from invalid curve attacks proper in that the cryptographic device is tricked into carrying out a computation not on another elliptic curve, but on a group isomorphic to the multiplicative group of the underlying base field. This often makes it easy to recover the secret scalar with a single invalid computation. We also show how our result can be used constructively, especially on curves over random base fields, as a fault attack countermeasure similar to Shamir\u27s trick

Machine Learning Applications for Load Predictions in Electrical Energy Network

In this work collected operational data of typical urban and rural energy network are analysed for predictions of energy consumption, as well as for selected region of Nordpool electricity markets. The regression techniques are systematically investigated for electrical energy prediction and correlating other impacting parameters. The k-Nearest Neighbour (kNN), Random Forest (RF) and Linear Regression (LR) are analysed and evaluated both by using continuous and vertical time approach. It is observed that for 30 minutes predictions the RF Regression has the best results, shown by a mean absolute percentage error (MAPE) in the range of 1-2 %. kNN show best results for the day-ahead forecasting with MAPE of 2.61 %. The presented vertical time approach outperforms the continuous time approach. To enhance pre-processing stage, refined techniques from the domain of statistics and time series are adopted in the modelling. Reducing the dimensionality through principal components analysis improves the predictive performance of Recurrent Neural Networks (RNN). In the case of Gated Recurrent Units (GRU) networks, the results for all the seasons are improved through principal components analysis (PCA). This work also considers abnormal operation due to various instances (e.g. random effect, intrusion, abnormal operation of smart devices, cyber-threats, etc.). In the results of kNN, iforest and Local Outlier Factor (LOF) on urban area data and from rural region data, it is observed that the anomaly detection for the scenarios are different. For the rural region, most of the anomalies are observed in the latter timeline of the data concentrated in the last year of the collected data. For the urban area data, the anomalies are spread out over the entire timeline. The frequency of detected anomalies where considerably higher for the rural area load demand than for the urban area load demand. Observing from considered case scenarios, the incidents of detected anomalies are more data driven, than exceptions in the algorithms. It is observed that from the domain knowledge of smart energy systems the LOF is able to detect observations that could not have detected by visual inspection alone, in contrast to kNN and iforest. Whereas kNN and iforest excludes an upper and lower bound, the LOF is density based and separates out anomalies amidst in the data. The capability that LOF has to identify anomalies amidst the data together with the deep domain knowledge is an advantage, when detecting anomalies in smart meter data. This work has shown that the instance based models can compete with models of higher complexity, yet some methods in preprocessing (such as circular coding) does not function for an instance based learner such as k-Nearest Neighbor, and hence kNN can not option for this kind of complexity even in the feature engineering of the model. It will be interesting for the future work of electrical load forecasting to develop solution that combines a high complexity in the feature engineering and have the explainability of instance based models.publishedVersio