Biblio

To protect data in cloud servers, fully homomorphic encryption (FHE) is an effective solution. In addition to encrypting data, FHE allows a third party to evaluate arithmetic circuits (i.e., computations) over encrypted data without decrypting it, guaranteeing protection even during the calculation. However, FHE supports only addition and multiplication. Functions that cannot be directly represented by additions or multiplications cannot be evaluated with FHE. A naïve implementation of such arithmetic operations with FHE is a bit-wise operation that encrypts numerical data as a binary string. This incurs huge computation time and storage costs, however. To overcome this limitation, we propose an efficient protocol to evaluate multi-input functions with FHE using a lookup table. We extend our previous work, which evaluates a single-integer input function, such as f(x). Our extended protocol can handle multi-input functions, such as f(x,y). Thus, we propose a new method of constructing lookup tables that can evaluate multi-input functions to handle general functions. We adopt integer encoding rather than bit-wise encoding to speed up the evaluations. By adopting both permutation operations and a private information retrieval scheme, we guarantee that no information from the underlying plaintext is leaked between two parties: a cloud computation server and a decryptor. Our experimental results show that the runtime of our protocol for a two-input function is approximately 13 minutes, when there are 8,192 input elements in the lookup table. By adopting a multi-threading technique, the runtime can be further reduced to approximately three minutes with eight threads. Our work is more practical than a previously proposed bit-wise implementation, which requires 60 minutes to evaluate a single-input function.

Due to users' network flow requirement and usage amount nowadays, TCP/IP networks may face various problems. For one, users of video services may access simultaneously the same content, which leads to the host incurring extra costs. Second, although nearby nodes may have the file that a user wants to access, the user cannot directly verify the file itself. This issue will lead the user to connect to a remote host rather than the nearby nodes and causes the network traffic to greatly increase. Therefore, the named data network (NDN), which is based on data itself, was brought about to deal with the aforementioned problems. In NDN, all users can access a file from the nearby nodes, and they can directly verify the file themselves rather than the specific host who holds the file. However, NDN still has no complete standard and secure file transfer protocol to support the ciphertext transmission and the problem of the unknown potential receivers. The straightforward solution is that a sender uses the receiver's public key to encrypt a file before she/he sends the file to NDN nodes. However, it will limit the behavior of users and incur significant storage costs of NDN nodes. This paper presents a complete secure file transfer protocol, which combines the data re-encryption, satisfies the requirement of secure ciphertext transmission, solves the problem of the unknown potential receivers, and saves the significant storage costs of NDN nodes. The proposed protocol is the first one that achieves data confidentiality and solves the problem of the unknown potential receivers in NDN. Finally, we also provide formal security models and proofs for the proposed FTP-NDN.

The network attack graph is a powerful tool for analyzing network security, but the generation of a large-scale graph is non-trivial. The main challenge is from the explosion of network state space, which greatly increases time and storage costs. In this paper, three parallel algorithms are proposed to generate scalable attack graphs. An OpenMP-based programming implementation is used to test their performance. Compared with the serial algorithm, the best performance from the proposed algorithms provides a 10X speedup.