Hierarchical and dynamic threshold Paillier cryptosystem without trusted dealer

We propose the first hierarchical and dynamic threshold Paillier cryptosystem without trusted dealer and prove its security in the malicious adversary model. The new cryptosystem is fully distributed, i. e., public and private key generation is performed without a trusted dealer. The private key is shared with a hierarchical and dynamic secret sharing scheme over the integers. In such a scheme not only the amount of shareholders, but also their levels in the hierarchy decide whether or not they can reconstruct the secret and new shareholders can be added or removed without reconstruction of the secret

Trustworthy Federated Learning: A Survey

Federated Learning (FL) has emerged as a significant advancement in the field of Artificial Intelligence (AI), enabling collaborative model training across distributed devices while maintaining data privacy. As the importance of FL increases, addressing trustworthiness issues in its various aspects becomes crucial. In this survey, we provide an extensive overview of the current state of Trustworthy FL, exploring existing solutions and well-defined pillars relevant to Trustworthy . Despite the growth in literature on trustworthy centralized Machine Learning (ML)/Deep Learning (DL), further efforts are necessary to identify trustworthiness pillars and evaluation metrics specific to FL models, as well as to develop solutions for computing trustworthiness levels. We propose a taxonomy that encompasses three main pillars: Interpretability, Fairness, and Security & Privacy. Each pillar represents a dimension of trust, further broken down into different notions. Our survey covers trustworthiness challenges at every level in FL settings. We present a comprehensive architecture of Trustworthy FL, addressing the fundamental principles underlying the concept, and offer an in-depth analysis of trust assessment mechanisms. In conclusion, we identify key research challenges related to every aspect of Trustworthy FL and suggest future research directions. This comprehensive survey serves as a valuable resource for researchers and practitioners working on the development and implementation of Trustworthy FL systems, contributing to a more secure and reliable AI landscape.Comment: 45 Pages, 8 Figures, 9 Table

Society-oriented cryptographic techniques for information protection

Groups play an important role in our modern world. They are more reliable and more trustworthy than individuals. This is the reason why, in an organisation, crucial decisions are left to a group of people rather than to an individual. Cryptography supports group activity by offering a wide range of cryptographic operations which can only be successfully executed if a well-defined group of people agrees to co-operate. This thesis looks at two fundamental cryptographic tools that are useful for the management of secret information. The first part looks in detail at secret sharing schemes. The second part focuses on society-oriented cryptographic systems, which are the application of secret sharing schemes in cryptography. The outline of thesis is as follows

Development of Visual Cryptography Technique for Authentication Using Facial Images

Security in the real world is an important issue to be taken care and to be encountered with various aspects and preventive measures. In the present era, whole major security concerns is the protection of this multimedia web is coming closer from text data to multimedia data, one of the data. Image, which covers the highest percentage of the multimedia data, its protection is very important. These might include Military Secrets, Commercial Secrets and Information of individuals. This can be achieved by visual Cryptography. It is one kind of image encryption. Incurrent technology, most of visual cryptography areembedded a secret using multiple shares. Visual is secret sharing technique used in visual cryptography which divides the secret image into multiple shares and by superimposing those shares the original secret image is going to be revealed, but it create a threat when an intruder get shares with which the image is going to be decrypted easily. However in these project work, an extremely useful bitwise operation is perform on every pixel with the help of key. The key is provided by new concept of sterilization algorithm. Initially Red, Green and Blue channels get separated from image and are going to be encrypted on multiple levels using multiple shares, convert an image into unreadable format and by combining all the shares in proper sequence the original secret image revealed

Privacy-preserving scoring of tree ensembles : a novel framework for AI in healthcare

Machine Learning (ML) techniques now impact a wide variety of domains. Highly regulated industries such as healthcare and finance have stringent compliance and data governance policies around data sharing. Advances in secure multiparty computation (SMC) for privacy-preserving machine learning (PPML) can help transform these regulated industries by allowing ML computations over encrypted data with personally identifiable information (PII). Yet very little of SMC-based PPML has been put into practice so far. In this paper we present the very first framework for privacy-preserving classification of tree ensembles with application in healthcare. We first describe the underlying cryptographic protocols that enable a healthcare organization to send encrypted data securely to a ML scoring service and obtain encrypted class labels without the scoring service actually seeing that input in the clear. We then describe the deployment challenges we solved to integrate these protocols in a cloud based scalable risk-prediction platform with multiple ML models for healthcare AI. Included are system internals, and evaluations of our deployment for supporting physicians to drive better clinical outcomes in an accurate, scalable, and provably secure manner. To the best of our knowledge, this is the first such applied framework with SMC-based privacy-preserving machine learning for healthcare

Unified architecture of mobile ad hoc network security (MANS) system

In this dissertation, a unified architecture of Mobile Ad-hoc Network Security (MANS) system is proposed, under which IDS agent, authentication, recovery policy and other policies can be defined formally and explicitly, and are enforced by a uniform architecture. A new authentication model for high-value transactions in cluster-based MANET is also designed in MANS system. This model is motivated by previous works but try to use their beauties and avoid their shortcomings, by using threshold sharing of the certificate signing key within each cluster to distribute the certificate services, and using certificate chain and certificate repository to achieve better scalability, less overhead and better security performance. An Intrusion Detection System is installed in every node, which is responsible for colleting local data from its host node and neighbor nodes within its communication range, pro-processing raw data and periodically broadcasting to its neighborhood, classifying normal or abnormal based on pro-processed data from its host node and neighbor nodes. Security recovery policy in ad hoc networks is the procedure of making a global decision according to messages received from distributed IDS and restore to operational health the whole system if any user or host that conducts the inappropriate, incorrect, or anomalous activities that threaten the connectivity or reliability of the networks and the authenticity of the data traffic in the networks. Finally, quantitative risk assessment model is proposed to numerically evaluate MANS security

Long-Term Confidential Secret Sharing-Based Distributed Storage Systems

Secret sharing-based distributed storage systems can provide long-term protection of confidentiality and integrity of stored data. This is achieved by periodically refreshing the stored shares and by checking the validity of the generated shares through additional audit data. However, in most real-life environments (e.g. companies), this type of solution is not optimal for three main reasons. Firstly, the access rules of state of the art secret sharing-based distributed storage systems do not match the hierarchical organization in place in these environments. Secondly, data owners are not supported in selecting the most suitable storage servers while first setting up the system nor in maintaining it secure in the long term. Thirdly, state of the art approaches require computationally demanding and unpractical and expensive building blocks that do not scale well. In this thesis, we mitigate the above mentioned issues and contribute to the transition from theory to more practical secret sharing-based long-term secure distributed storage systems. Firstly, we show that distributed storage systems can be based on hierarchical secret sharing schemes by providing efficient and secure algorithms, whose access rules can be adapted to the hierarchical organization of a company and its future modifications. Secondly, we introduce a decision support system that helps data owners to set up and maintain a distributed storage system. More precisely, on the one hand, we support data owners in selecting the storage servers making up the distributed storage system. We do this by providing them with scores that reflect their actual performances, here used in a broad sense and not tied to a specific metric. These are the output of a novel performance scoring mechanism based on the behavioral model of rational agents as opposed to the classical good/bad model. On the other hand, we support data owners in choosing the right secret sharing scheme parameters given the performance figures of the storage servers and guide them in updating them accordingly with the updated performance figures so as to maintain the system secure in the long term. Thirdly, we introduce efficient and affordable distributed storage systems based on a trusted execution environment that correctly outsources the data and periodically computes valid shares. This way, less information-theoretically secure channels have to be established for confidentiality guarantees and more efficient primitives are used for the integrity safeguard of the data. We present a third-party privacy-preserving mechanism that protects the integrity of data by checking the validity of the shares