Biblio

In recent years, data security incidents caused by insider threats in distributed file systems have attracted the attention of academia and industry. The most common way to detect insider threats is based on user profiles. Through analysis, we realize that based on existing user profiles are not efficient enough, and there are many false positives when a stable user profile has not yet been formed. In this work, we propose personalized user profiles and design an insider threat detection framework, which can intelligently detect insider threats for securing distributed file systems in real-time. To generate personalized user profiles, we come up with a time window-based clustering algorithm and a weighted kernel density estimation algorithm. Compared with non-personalized user profiles, both the Recall and Precision of insider threat detection based on personalized user profiles have been improved, resulting in their harmonic mean F1 increased to 96.52%. Meanwhile, to reduce the false positives of insider threat detection, we put forward operation recommendations based on user similarity to predict new operations that users will produce in the future, which can reduce the false positive rate (FPR). The FPR is reduced to 1.54% and the false positive identification rate (FPIR) is as high as 92.62%. Furthermore, to mitigate the risks caused by inaccurate authorization for users, we present user tags based on operation content and permission. The experimental results show that our proposed framework can detect insider threats more effectively and precisely, with lower FPR and high FPIR.

Anonymous Communication (AC) hides traffic patterns and protects message metadata from being leaked during message transmission. Many practical AC systems have been proposed aiming to reduce communication latency and support a large number of users. However, how to design AC systems which possess strong security property and at the same time achieve optimal performance (i.e., the lowest latency or highest horizontal scalability) has been a challenging problem. In this paper, we propose an ObliComm framework, which consists of six modular AC subroutines. We also present a strong security definition for AC, named oblivious communication, encompassing confidentiality, unobservability, and a new requirement sending-and-receiving operation hiding. The AC subroutines in ObliComm allow for modular construction of oblivious communication systems in different network topologies. All constructed systems satisfy oblivious communication definition and can be provably secure in the universal composability (UC) framework. Additionally, we model the relationship between the network topology and communication measurements by queuing theory, which enables the system's efficiency can be optimized and estimated by quantitative analysis and calculation. Through theoretical analyses and empirical experiments, we demonstrate the efficiency of our scheme and soundness of the queuing model.

As an efficient deletion method, unlinking is widely used in cloud storage. While unlinking is a kind of incomplete deletion, `deleted data' remains on cloud and can be recovered. To make `deleted data' unrecoverable, overwriting is an effective method on cloud. Users lose control over their data on cloud once deleted, so it is difficult for them to confirm overwriting. In face of such a crucial problem, we propose a Provable and Traceable Assured Deletion (PTAD) scheme in cloud storage based on blockchain. PTAD scheme relies on overwriting to achieve assured deletion. We reference the idea of data integrity checking and design algorithms to verify if cloud overwrites original blocks properly as specific patterns. We utilize technique of smart contract in blockchain to automatically execute verification and keep transaction in ledger for tracking. The whole scheme can be divided into three stages-unlinking, overwriting and verification-and we design one specific algorithm for each stage. For evaluation, we implement PTAD scheme on cloud and construct a consortium chain with Hyperledger Fabric. The performance shows that PTAD scheme is effective and feasible.

In ciphertext policy attribute-based encryption scheme, access policies are associated with ciphertext and tied to it. It is necessary to hide the access policy in the most sensitive spots such as political, medical and economic fields, that is, receiver's anonymity. In this paper, we propose an efficient CP-ABE construction with hidden policy and prove it to be fully secure under static assumptions applying the dual system encryption methodology. Access structures in our construction are AND gates on positive, negative and wildcard attributes and the ciphertext size is short, which is only concerned with the number of wildcards.