Visible to the public Biblio

Filters: Author is Gao, J.  [Clear All Filters]
2018
Gao, J., Lanchantin, J., Soffa, M. L., Qi, Y..  2018.  Black-Box Generation of Adversarial Text Sequences to Evade Deep Learning Classifiers. 2018 IEEE Security and Privacy Workshops (SPW). :50–56.

Although various techniques have been proposed to generate adversarial samples for white-box attacks on text, little attention has been paid to a black-box attack, which is a more realistic scenario. In this paper, we present a novel algorithm, DeepWordBug, to effectively generate small text perturbations in a black-box setting that forces a deep-learning classifier to misclassify a text input. We develop novel scoring strategies to find the most important words to modify such that the deep classifier makes a wrong prediction. Simple character-level transformations are applied to the highest-ranked words in order to minimize the edit distance of the perturbation. We evaluated DeepWordBug on two real-world text datasets: Enron spam emails and IMDB movie reviews. Our experimental results indicate that DeepWordBug can reduce the classification accuracy from 99% to 40% on Enron and from 87% to 26% on IMDB. Our results strongly demonstrate that the generated adversarial sequences from a deep-learning model can similarly evade other deep models.

2019
Wang, L., Wang, D., Gao, J., Huo, C., Bai, H., Yuan, J..  2019.  Research on Multi-Source Data Security Protection of Smart Grid Based on Quantum Key Combination. 2019 IEEE 4th International Conference on Cloud Computing and Big Data Analysis (ICCCBDA). :449–453.

Power communication network is an important infrastructure of power system. For a large number of widely distributed business terminals and communication terminals. The data protection is related to the safe and stable operation of the whole power grid. How to solve the problem that lots of nodes need a large number of keys and avoid the situation that these nodes cannot exchange information safely because of the lack of keys. In order to solve the problem, this paper proposed a segmentation and combination technology based on quantum key to extend the limited key. The basic idea was to obtain a division scheme according to different conditions, and divide a key into several different sub-keys, and then combine these key segments to generate new keys and distribute them to different terminals in the system. Sufficient keys were beneficial to key updating, and could effectively enhance the ability of communication system to resist damage and intrusion. Through the analysis and calculation, the validity of this method in the use of limited quantum keys to achieve the business data secure transmission of a large number of terminal was further verified.

Gao, J., Wang, J., Zhang, L., Yu, Q., Huang, Y., Shen, Y..  2019.  Magnetic Signature Analysis for Smart Security System Based on TMR Magnetic Sensor Array. IEEE Sensors Journal. :1–1.

This paper presents a novel low power security system based on magnetic anomaly detection by using Tunneling Magnetoresistance (TMR) magnetic sensors. In this work, a smart light has been developed, which consists of TMR sensors array, detection circuits, a micro-controller and a battery. Taking the advantage of low power consumption of TMR magnetic sensors, the smart light powered by Li-ion battery can work for several months. Power Spectrum Density of the obtained signal was analyzed to reject background noise and improve the signal to noise ratio effectively by 1.3 dB, which represented a 30% detection range improvement. Also, by sending the signals to PC, the magnetic fingerprints of the objects have been configured clearly. In addition, the quick scan measurement has been also performed to demonstrate that the system can discriminate the multiple objects with 30 cm separation. Since the whole system was compact and portable, it can be used for security check at office, meeting room or other private places without attracting any attention. Moreover, it is promising to integrate multiply such systems together to achieve a wireless security network in large-scale monitoring.