Zhaoquan Gu¹, Yu Su¹, Chenwei Liu¹, Yinyu Lyu¹, Yunxiang Jian¹, Hao Li², Zhen Cao³, Le Wang^{1, *}

CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1437-1452, 2020, DOI:10.32604/cmc.2020.011834 - 20 August 2020

Abstract The license plate recognition system (LPRS) has been widely adopted in daily life due to its efficiency and high accuracy. Deep neural networks are commonly used in the LPRS to improve the recognition accuracy. However, researchers have found that deep neural networks have their own security problems that may lead to unexpected results. Specifically, they can be easily attacked by the adversarial examples that are generated by adding small perturbations to the original images, resulting in incorrect license plate recognition. There are some classic methods to generate adversarial examples, but they cannot be adopted on More >

Zhaoquan Gu¹, Yinyin Cai¹, Sheng Wang¹, Mohan Li^{1, *}, Jing Qiu¹, Shen Su¹, Xiaojiang Du¹, Zhihong Tian¹

CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 1755-1770, 2020, DOI:10.32604/cmc.2020.010739 - 30 June 2020

Abstract Recommender systems are very useful for people to explore what they really need. Academic papers are important achievements for researchers and they often have a great deal of choice to submit their papers. In order to improve the efficiency of selecting the most suitable journals for publishing their works, journal recommender systems (JRS) can automatically provide a small number of candidate journals based on key information such as the title and the abstract. However, users or journal owners may attack the system for their own purposes. In this paper, we discuss about the adversarial attacks More >

Kyeonghwan Lim¹, Nak Young Kim¹, Younsik Jeong¹, Seong-je Cho¹, Sangchul Han², Minkyu Park²

Intelligent Automation & Soft Computing, Vol.25, No.1, pp. 143-153, 2019, DOI:10.31209/2018.100000051

Abstract The Android application package (APK) uses the DEX format as an executable file format. Since DEX files are in Java bytecode format, you can easily get Java source code using static reverse engineering tools. This feature makes it easy to steal Android applications. Tools such as ijiami, liapp, alibaba, etc. can be used to protect applications from static reverse engineering attacks. These tools typically save encrypted classes.dex in the APK file, and then decrypt and load dynamically when the application starts. However, these tools do not protect multidex Android applications. A multidex Android application is More >

Youngseok Park¹, Hyunsang Choi¹, Sanghyun Cho¹, Young-Gab Kim^2,*

CMC-Computers, Materials & Continua, Vol.61, No.3, pp. 1075-1090, 2019, DOI:10.32604/cmc.2019.08520

Abstract The speech recognition technology has been increasingly common in our lives. Recently, a number of commercial smart speakers containing the personal assistant system using speech recognition came out. While the smart speaker vendors have been concerned about the intelligence and the convenience of their assistants, but there have been little mentions of the smart speakers in security aspects. As the smart speakers are becoming the hub for home automation, its security vulnerabilities can cause critical problems. In this paper, we categorize attack vectors and classify them into hardware-based, network-based, and software-based. With the attack vectors, More >

Wen Tian¹, Xiaopeng Ji^1,*, Weiwei Liu¹, Guangjie Liu¹, Rong Lin^1,2, Jiangtao Zhai³, Yuewei Dai³

CMC-Computers, Materials & Continua, Vol.60, No.1, pp. 193-211, 2019, DOI:10.32604/cmc.2019.05290

Abstract Cyber-physical system (CPS) is an advanced system that integrats physical processes, computation and communication resources. The security of cyber-physical systems has become an active research area in recent years. In this paper, we focus on defensive strategies against network attacks in CPS. We introduce both low- and highinteraction honeypots into CPS as a security management tool deliberately designed to be probed, attacked and compromised. In addition, an analysis resource constraint is introduced for the purpose of optimizing defensive strategies against network attacks in CPS. We study the offensive and defensive interactions of CPS and model… More >

Mohan Li¹, Yanbin Sun^{1, *}, Shen Su¹, Zhihong Tian¹, Yuhang Wang^{1, *}, Xianzhi Wang²

CMC-Computers, Materials & Continua, Vol.59, No.1, pp. 331-344, 2019, DOI:10.32604/cmc.2019.05379

Abstract Maliciously manufactured user profiles are often generated in batch for shilling attacks. These profiles may bring in a lot of quality problems but not worthy to be repaired. Since repairing data always be expensive, we need to scrutinize the data and pick out the data that really deserves to be repaired. In this paper, we focus on how to distinguish the unintentional data quality problems from the batch generated fake users for shilling attacks. A two-steps framework named DPIF is proposed for the distinguishment. Based on the framework, the metrics of homology and suspicious degree More >

Yue Zhang¹, Dengpan Ye², Junjun Gan¹, Zhenyu Li³, Qingfeng Cheng^1,*

CMC-Computers, Materials & Continua, Vol.56, No.1, pp. 151-167, 2018, DOI:10.3970/cmc.2018.02464

Abstract In view of the fact that the current adaptive steganography algorithms are difficult to resist scaling attacks and that a method resisting scaling attack is only for the nearest neighbor interpolation method, this paper proposes an image steganography algorithm based on quantization index modulation resisting both scaling attacks and statistical detection. For the spatial image, this paper uses the watermarking algorithm based on quantization index modulation to extract the embedded domain. Then construct the embedding distortion function of the new embedded domain based on S-UNIWARD steganography, and use the minimum distortion coding to realize the… More >

Jieren Cheng^1,2, Ruomeng Xu^1,*, Xiangyan Tang¹, Victor S. Sheng³, Canting Cai¹

CMC-Computers, Materials & Continua, Vol.55, No.1, pp. 95-119, 2018, DOI:10.3970/cmc.2018.055.095

Abstract Distributed denial-of-service (DDoS) is a rapidly growing problem with the fast development of the Internet. There are multitude DDoS detection approaches, however, three major problems about DDoS attack detection appear in the big data environment. Firstly, to shorten the respond time of the DDoS attack detector; secondly, to reduce the required compute resources; lastly, to achieve a high detection rate with low false alarm rate. In the paper, we propose an abnormal network flow feature sequence prediction approach which could fit to be used as a DDoS attack detector in the big data environment and… More >