Secret key agreement with large antenna arrays under the pilot contamination attack

We present a secret key agreement (SKA) protocol for a multi-user time-division duplex system where a base-station (BS) with a large antenna array (LAA) shares secret keys with users in the presence of non-colluding eavesdroppers. In the system, when the BS transmits random sequences to legitimate users for sharing common randomness, the eavesdroppers can attempt the pilot contamination attack (PCA) in which each of eavesdroppers transmits its target user's training sequence in hopes of acquiring possible information leak by steering beam towards the eavesdropper. We show that there exists a crucial complementary relation between the received signal strengths at the eavesdropper and its target user. This relation tells us that the eavesdropper inevitably leaves a trace that enables us to devise a way of measuring the amount of information leakage to the eavesdropper even if PCA parameters are unknown. To this end, we derive an estimator for the channel gain from the BS to the eavesdropper and propose a rate-adaptation scheme for adjusting the length of secret key under the PCA. Extensive analysis and evaluations are carried out under various setups, which show that the proposed scheme adequately takes advantage of the LAA to establish the secret keys under the PCA.Comment: 15 pages, 5 figures, and the paper is under minor revision for the publication in IEEE transactions on wireless communication

Hierarchical Text Classification as Sub-hierarchy Sequence Generation

Hierarchical text classification (HTC) is essential for various real applications. However, HTC models are challenging to develop because they often require processing a large volume of documents and labels with hierarchical taxonomy. Recent HTC models based on deep learning have attempted to incorporate hierarchy information into a model structure. Consequently, these models are challenging to implement when the model parameters increase for a large-scale hierarchy because the model structure depends on the hierarchy size. To solve this problem, we formulate HTC as a sub-hierarchy sequence generation to incorporate hierarchy information into a target label sequence instead of the model structure. Subsequently, we propose the Hierarchy DECoder (HiDEC), which decodes a text sequence into a sub-hierarchy sequence using recursive hierarchy decoding, classifying all parents at the same level into children at once. In addition, HiDEC is trained to use hierarchical path information from a root to each leaf in a sub-hierarchy composed of the labels of a target document via an attention mechanism and hierarchy-aware masking. HiDEC achieved state-of-the-art performance with significantly fewer model parameters than existing models on benchmark datasets, such as RCV1-v2, NYT, and EURLEX57K

Implications of cation-disordered grain boundaries on the electrochemical performance of the LiNi0.5Co0.2Mn0.3O2 cathode material for lithium ion batteries

Although lithium-mixed transition metal oxides (LiTM) have promising properties suitable for practical applications, unavoidable cation disorder in their structure during their synthesis or their operation leads to complex effects on their electrochemical performance. The microscopic mechanism of the cation disorder remains elusive owing to the lack of information on the atomic structures with specific chemical identities. In this study, the Li-content-dependent cation disorder phenomenon near the grain boundary of LiNi0.5Co0.2Mn0.3O2 particles is uncovered using atom-resolved chemical and valence mapping techniques. LiTM with 1% excess Li (LiTM101) shows outstanding electrical conductivity at the grain boundary, whereas no enhancement in the electrical conductivity is manifested in LiTM with 7% excess Li. Remarkably, this superior property of LiTM101 is coupled to the combined cation disorder of Ni and Co in the Li layer with their increased valences, while the Mn ions in both samples are not labile to migrate. This work highlights the hitherto hidden role of highly oxidized Co ions in the Li layer as a key agent for enhancing the electrochemical performance, together with Ni ions acting as pillars to stabilize the layered structure, thus providing a new insight for engineering stable and durable cathode materials with high performance. © The Royal Society of Chemistry 201