Privacy-preserving aggregation protocol is an essential building block in privacy-enhanced federated learning (FL), which enables the server to obtain the sum of users’ locally trained models while keeping local training data private. However, most of the work on privacy-preserving aggregation provides privacy guarantees for only one communication round in FL. In fact, as FL usually involves long-term training, i.e., multiple rounds, it may lead to more information leakages due to the dynamic user participation over rounds. In this connection, we propose a long-term privacy-preserving aggregation (LTPA) protocol providing both single-round and multi-round privacy guarantees. Specifically, we first introduce our batch-partitioning-dropping-updating (BPDU) strategy that enables any user-dynamic FL system to provide multi-round privacy guarantees. Then we present our LTPA construction which integrates our proposed BPDU strategy with the state-of-the-art privacy-preserving aggregation protocol. Furthermore, we investigate the impact of LTPA parameter settings on the trade-off between privacy guarantee, protocol efficiency, and FL convergence performance from both theoretical and experimental perspectives. Experimental results show that LTPA provides similar complexity to that of the state-of-the-art, i.e., an additional cost of around only 1.04X for a 100,000-user FL system, with an additional long-term privacy guarantee.

In the application of cloud storage, a user no longer possesses his files in his local depository. Thus, he is concerned about the security of the stored files. Data confidentiality and data robustness are the main security issues. For data confidentiality, the user can first encrypt files and then store the encrypted files in a cloud storage. For data robustness, there are two concerns: service failure, and service corruption. We are concerned about data robustness in cloud storage services. Lin and Tzeng proposed a secure erasure code-based storage system with multiple key servers recently. Their system supports a repair mechanism, where a new storage server can compute a new ciphertext from the ciphertexts obtained from the remaining storage servers. Their system considers data confidentiality in the cloud, and data robustness against storage server failure. In this paper, we propose an integrity check scheme for their system to enhance data robustness against storage server corruption, which returns tampered ciphertexts. With our integrity check scheme, their storage system can deal with not only the problem of storage server failure, but also the problem of storage server corruption. The challenging part of our work is to have homomorphic integrity tags. New integrity tags can be computed from old integrity tags by storage servers without involvement of the user's secret key or backup servers. We prove the security of our integrity check scheme formally, and establish the parameters for achieving an overwhelming probability of a successful data retrieval.

With the increasing popularity of cloud computing, Hadoop has become a widely used open source cloud computing framework for large scale data processing. However, few studies have been done to enhance data confidentiality of Hadoop against storage servers. In this paper, we address the data confidentiality issue by integrating hybrid encryption schemes and the Hadoop distributed file system (HDFS). We propose and implement two integrations, HDFS-RSA and HDFS-Pairing, as extensions of HDFS. Experiments are conducted to demonstrate the performance overhead of HDFS-RSA and HDFS-Pairing. Our integrations provide alternatives toward achieving data confidentiality for Hadoop.

A cloud storage system, consisting of a collection of storage servers, provides long-term storage services over the Internet. Storing data in a third party's cloud system causes serious concern over data confidentiality. General encryption schemes protect data confidentiality, but also limit the functionality of the storage system because a few operations are supported over encrypted data. Constructing a secure storage system that supports multiple functions is challenging when the storage system is distributed and has no central authority. We propose a threshold proxy re-encryption scheme and integrate it with a decentralized erasure code such that a secure distributed storage system is formulated. The distributed storage system not only supports secure and robust data storage and retrieval, but also lets a user forward his data in the storage servers to another user without retrieving the data back. The main technical contribution is that the proxy re-encryption scheme supports encoding operations over encrypted messages as well as forwarding operations over encoded and encrypted messages. Our method fully integrates encrypting, encoding, and forwarding. We analyze and suggest suitable parameters for the number of copies of a message dispatched to storage servers and the number of storage servers queried by a key server. These parameters allow more flexible adjustment between the number of storage servers and robustness.

Erasure code based distributed storage systems provide data robustness by storing encoded-fragments over servers. To maintain data robustness, a repair mechanism recovers a storage system from server failures by repairing encoded-fragments. For decentralized erasure code based storage systems, we propose a decentralized repair mechanism. Our mechanism has the following features. Firstly, an encoded- fragment is replenished by a combination of a number u of encoded-fragments that are randomly chosen. Secondly, the number u depends on the number of the available encoded- fragments and is independent of the pattern of missing encoded-fragments. Thirdly, multiple encoded-fragments are simultaneously replenished in parallel. We measure the communication cost in terms of the number u of required network connections for replenishing an encoded-fragment. We then conducted a numerical analysis by using traces of real systems. We find that our requirement on u is smaller than that from existing methods. Both theoretical and numerical results show that our decentralized repair mechanism outperforms existing ones in terms of the communication cost under the same consideration of efficiency cost for storage.

Distributed networked storage systems provide the storage service on the Internet. We address the privacy issue of the distributed networked storage system. It is desired that data stored in the system remain private even if all storage servers in the system are compromised. The major challenge of designing these distributed networked storage systems is to provide a better privacy guarantee while maintaining the distributed structure. To achieve this goal, we introduce secure decentralized erasure code, which combines a threshold public key encryption scheme and a variant of the decentralized erasure code. Our secure distributed networked storage system constructed by the secure decentralized erasure code is decentralized, robust, private, and with low storage cost.