Zero knowledge proof for secure two-party computation with malicious adversaries in distributed networks

The rapid development of big data has brought more problems in network information security and privacy protection. This paper will study the specific network information security and privacy protection technologies in this context. The first part of this paper firstly discusses the connotation and characteristics of big data, and then puts forward the information security and privacy protection problems in the era of big data. The last part deeply studies how to solve the solutions corresponding to these problems.

RFID in the Information Security and Privacy is hidden in a crisis. RFID Information Security and Privacy Protection using hardware ways to achieve the target is the best way, however, it is subject to the problem of Tag costs and capacity and is currently still unresolved issues. This study focus on the Information Security and Privacy Protection and put forth a EPC specifications to use the model of XOR logic operation with the method of CRC examining the computing, and simulating the shopping mall system which provides a Information Security and Privacy Protection system. We got the data after simulations to show that XOR computing to actual test of 8 bytes, the required time is 17.29 Ticks in average, the spend time is rather short. Follow-up our simulations to the test data of DES encryption methods, an average time of 8,039.41 Ticks is required, the two time required considerable differences. It was informed that this study through practical shows that we could provide a match hardware encryption methods of the specific solutions to achieve their personal privacy protection, confidentiality, confirmed, and the fulfillment of the Information Security and Privacy Protection.

Due to various reasons, only few researchers focused their investigations on the current status of information security and privacy protection of e-Government services in Africa. This paper attempts to partially fill the gap by reporting on the compliance evaluation of privacy protection in e-Government systems in the countries of Anglophone West Africa, namely in Ghana, Nigeria, Liberia, Sierra Leone and Gambia. In the countries, e-Government services have become one of the most important and efficient means by which government interacts with citizens. The ways to facilitate information privacy protection in e-Government systems of a given country include enactment of a comprehensive information privacy regulation. The regulation serves as a legal framework that considers internationally accepted privacy protection principles, such as those of the ISO/IEC 29100:2011, and applicable guidelines of the U.S. NIST SP 800–53 Rev.4. In this paper, the privacy principles of the ISO/IEC 29100:2011 serve as a baseline for evaluation of the content of privacy protection regulations of the Anglophone West African countries. The paper also reports results of a passive security reconnaissance performed on selected e-Government websites. While the paper acknowledges recent progresses made in the area of privacy protection in the countries of Anglophone West Africa, recommendations are provided to mitigate the identified gaps.

Oblivious transfer (OT) is a significant primitive with wide use in secure two-party computation, private set intersection private and other cryptographic schemes. In the past ten years, different variants of OT primitive like cut-and-choose OT (CCOT) and outsourced OT (OOT), have been proposed so as to satisfy various emerging models. In this paper, we firstly propose and formalize a new primitive called permutable cut-and-choose OT (PCCOT) which generalizes the original CCOT functionality. Furthermore, we construct an efficient PCCOT protocol in the presence of malicious adversaries using the Decisional Diffie-Hellman (DDH) hard assumption. It is worth mentioning that we apply the PCCOT primitive to the efficient construction of secure wildcard pattern matching (WPM) protocol. The WPM functionality allows a party to determine the locations of its pattern with wildcard characters occurs in a long text of another party while revealing nothing to either party in addition to the length of their own inputs. Our proposed secure WPM protocol via PCCOT is secure against semi-honest adversary with 2 rounds and has identical communication cost as the the state-of-the-art scheme.

Secure two-party computation provides a way for two parties to compute a function, that depends on the two parties’ inputs, while keeping them private. Known since the 1980s, Yao’s garbled circuits appear to be a general solution to this problem, in the semi-honest model. Decades of optimizations have made this tool a very practical solution. However, it is well known that a malicious adversary could modify a garbled circuit before submitting it. Many protocols, mostly based on cut-&-choose, have been proposed to secure Yao’s garbled circuits in the presence of malicious adversaries. Nevertheless, how much an adversary can modify a circuit and make it still executable has not been studied yet. The main contribution of this paper is to prove that any modification made by an adversary is equivalent to adding/removing NOT gates arbitrarily in the original circuit, otherwise the adversary can get caught. Thereafter, we study some evaluation functions for which, even without using cut-&-choose, no adversary can gain more information about the inputs by modifying the circuit. We also give an improvement over most recent cut-&-choose solutions by requiring that different circuits of the same function are used instead of just one.

Web search has become an integral part of our lives and we use it daily for business and pleasure. Unfortunately, however, we unwittingly reveal a huge amount of private information about ourselves when we search the web. A look at a user's search terms over a period of a few months paints a frighteningly clear and detailed picture about the user's life. In this paper, we build on previous work by Castella-Roca et al. (Computer Communications 2009) and show how to achieve privacy in web searches efficiently and practically without resorting to full-blown anonymous routing. In contrast to previous work, our protocol is secure in the presence of malicious adversaries.

Chapter 10 - Techniques for Privacy Preserving Data Publication in the Cloud for Smart City Applications

In this paper, a new notion which we call private data deduplication protocol, a deduplication technique for private data storage is introduced and formalized. Intuitively, a private data deduplication protocol allows a client who holds a private data proves to a server who holds a summary string of the data that he/she is the owner of that data without revealing further information to the server. Our notion can be viewed as a complement of the state-of-the-art public data deduplication protocols of Halevi et al [7]. The security of private data deduplication protocols is formalized in the simulation-based framework in the context of two-party computations. A construction of private deduplication protocols based on the standard cryptographic assumptions is then presented and analyzed. We show that the proposed private data deduplication protocol is provably secure assuming that the underlying hash function is collision-resilient, the discrete logarithm is hard and the erasure coding algorithm can erasure up to α-fraction of the bits in the presence of malicious adversaries in the presence of malicious adversaries. To the best our knowledge this is the first deduplication protocol for private data storage.

Recently, there has been huge progress in the field of concretely efficient secure computation, even while providing security in the presence of malicious adversaries. This is especially the case in the two-party setting, where constant-round protocols exist that remain fast even over slow networks. However, in the multi-party setting, all concretely efficient fully-secure protocols, such as SPDZ, require many rounds of communication.

Recently, there has been huge progress in the field of concretely efficient secure computation, even while providing security in the presence of malicious adversaries. This is especially the case in the two-party setting, where constant-round protocols exist that remain fast even over slow networks. However, in the multi-party setting, all concretely efficient fully-secure protocols, such as SPDZ, require many rounds of communication.

With the rapid advancement of deepfake technology, its application in multimodal content such as video and audio has posed severe threats to digital information security and privacy protection. Although existing deepfake detection methods have made significant progress, three critical challenges remain: efficient fusion of cross-modal information, precise extraction of fine-grained visual features, and effective discrimination between the distributions of authentic and forged samples. To address these challenges, this paper innovatively proposes FUME, a crossmodal deepfake detection framework integrating facial UV maps with momentum contrastive learning. Specifically, the method introduces a Texture-Aware Video Transformer (TAViT) to achieve deep fusion of facial UV maps and spatiotemporal video features, while employing an Audio Spectrogram Transformer (AST) for multi-scale feature modeling of speech signals. Additionally, we design a momentum contrastive learning based cross-modal alignment mechanism, which achieves semantic-level matching of audiovisual representations through dynamic construction of positive and negative sample pairs, while incorporating a OneClass softmax loss function to enhance generalization capability against unseen deepfake generation techniques. Extensive experiments on datasets including DeepfakeTIMIT, DFDC, and KoDF validate our method’s superiority. Notably, on the KoDF dataset, our approach achieves $97.59 \%$ accuracy and $98.23 \%$ AUC, surpassing the current audio-visual state-of-the-art by 1.91 % and $2.99 \%$.

Tracked Changes. Information security, cybersecurity and privacy protection. Privacy information management systems. Requirements and guidance

Telematics technology development offers vehicles a range of intelligent and convenient functions, including navigation and mapping services, intelligent driving assistance, and intelligent traffic management. However, since these functions deal with sensitive information like vehicle location and driving habits, it is crucial to address concerns regarding information security and privacy protection. Federated learning (FL) is highly suitable for addressing such problems due to its characteristics, in which a client does not need to share private data and upload model parameters to a parameter server via the network. This results in the establishment of a federated vehicle network (FVN). As a distributed paradigm, the efficiency of communication is crucial in federated learning as it impacts all aspects of the FVN. This paper introduces a parameter freezing algorithm based on historical information to reduce the data transferred between the client and the parameter server in each round of communication, thus minimizing the communication overhead of federated learning. Additionally, we propose using a particle swarm algorithm to allocate network bandwidth to each vehicle based on the packet sizes sent by each vehicle (i.e., the non-freezing parameters) to minimize the communication latency in each FL round. Furthermore, due to the high time complexity of the particle swarm algorithm, we employ it to generate training data for training a transformer model with fast response and sufficient accuracy, thereby accelerating the bandwidth allocation process. Through extensive experiments, we prove the feasibility of our approach and its efficiency in improving communication in federated learning.

As risk managers and IT auditors, we are confronted with too many standards and types of certificates for information security and privacy protection (IS&PP). In the scope of Knowledge Management and Enrichment, a critical review has been performed revealing that any and all standards and certifications use a common approach and their assessments generally lead to a similar set of security measures. In this paper, we derive the basics of some of these standards and revive the underlying scientific models. We explain the principles of IT risk management and the selection of an appropriate set of IS&PP measures with a single Cube, assisting risk managers and IT auditors in standardizing their work.

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