Visible to the public Biblio

Filters: Author is Liu, Yulin  [Clear All Filters]
2022-10-03
Liu, Yulin, Han, Guangjie, Wang, Hao, Jiang, Jinfang.  2021.  FPTSA-SLP: A Fake Packet Time Slot Assignment-based Source Location Privacy Protection Scheme in Underwater Acoustic Sensor Networks. 2021 Computing, Communications and IoT Applications (ComComAp). :307–311.
Nowadays, source location privacy in underwater acoustic sensor networks (UASNs) has gained a lot of attention. The aim of source location privacy is to use specific technologies to protect the location of the source from being compromised. Among the many technologies available are fake packet technology, multi-path routing technology and so on. The fake packet technology uses a certain amount of fake packets to mask the transmission of the source packet, affecting the adversary's efficiency of hop-by-hop backtracking to the source. However, during the operation of the fake packet technology, the fake packet, and the source packet may interfere with each other. Focus on this, a fake packet time slot assignment-based source location privacy protection (FPTSA-SLP) scheme. The time slot assignment is adopted to avoid interference with the source packet. Also, a relay node selection method based on the handshake is further proposed to increase the diversity of the routing path to confuse the adversary. Compared with the comparison algorithm, the simulation results demonstrate that the proposed scheme has a better performance in safety time.
2021-08-11
He, Guorong, Dong, Chen, Liu, Yulin, Fan, Xinwen.  2020.  IPlock: An Effective Hybrid Encryption for Neuromorphic Systems IP Core Protection. 2020 IEEE 4th Information Technology, Networking, Electronic and Automation Control Conference (ITNEC). 1:612—616.
Recent advances in resistive synaptic devices have enabled the emergence of brain-inspired smart chips. These chips can execute complex cognitive tasks in digital signal processing precisely and efficiently using an efficient neuromorphic system. The neuromorphic synapses used in such chips, however, are different from the traditional integrated circuit architectures, thereby weakening their resistance to malicious transformation and intellectual property (IP) counterfeiting. Accordingly, in this paper, we propose an effective hybrid encryption methodology for IP core protection in neuromorphic computing systems, in-corporating elliptic curve cryptography and SM4 simultaneously. Experimental results confirm that the proposed method can implement real-time encryption of any number of crossbar arrays in neuromorphic systems accurately, while reducing the time overhead by 14.40%-26.08%.