Route Optimization Algorithm Based on Game Theory for Tourism Routes at Pseudo-Imperial Palace

( Guangjie Liu ),( Jinlong Zhu ),( Qiucheng Sun ),( Jiaze Hu ),( Hao Yu ) 한국정보처리학회 2021 Journal of information processing systems Vol.17 No.5

With improvements in living conditions, an increasing number of people are choosing to spend their time traveling. Comfortable tour routes are affected by the season, time, and other local factors. In this paper, the influencing factors and principles of scenic spots are analyzed, a model used to find the available routes is built, and a multi-route choice model based on a game theory utilizing a path recommendation weight is developed. A Monte Carlo analysis of a tourist route subjected to fixed access point conditions is applied to account for uncertainties such as the season, start time, end time, stay time, number of scenic spots, destination, and start point. We use the Dijkstra method to obtain multiple path plans and calculate the path evaluation score using the Monte Carlo method. Finally, according to the user preference in the input path, game theory generates path ordering for user choice. The proposed approach achieves a state-of-the-art performance at the pseudo-imperial palace. Compared with other methods, the proposed method can avoid congestion and reduce the time cost.

Designing Rich-Secure Network Covert Timing Channels Based on Nested Lattices

( Weiwei Liu ),( Guangjie Liu ),( Xiaopeng Ji ),( Jiangtao Zhai ),( Yuewei Dai ) 한국인터넷정보학회 2019 KSII Transactions on Internet and Information Syst Vol.13 No.4

As the youngest branch of information hiding, network covert timing channels conceal the existence of secret messages by manipulating the timing information of the overt traffic. The popular model-based framework for constructing covert timing channels always utilizes cumulative distribution function (CDF) of the inter-packet delays (IPDs) to modulate secret messages, whereas discards high-order statistics of the IPDs completely. The consequence is the vulnerability to high-order statistical tests, e.g., entropy test. In this study, a rich security model of covert timing channels is established based on IPD chains, which can be used to measure the distortion of multi-order timing statistics of a covert timing channel. To achieve rich security, we propose two types of covert timing channels based on nested lattices. The CDF of the IPDs is used to construct dot-lattice and interval-lattice for quantization, which can ensure the cell density of the lattice consistent with the joint distribution of the IPDs. Furthermore, compensative quantization and guard band strategy are employed to eliminate the regularity and enhance the robustness, respectively. Experimental results on real traffic show that the proposed schemes are rich-secure, and robust to channel interference, whereas some state-of-the-art covert timing channels cannot evade detection under the rich security model.

Refined identification of hybrid traffic in DNS tunnels based on regression analysis

Bai, Huiwen,Liu, Guangjie,Zhai, Jiangtao,Liu, Weiwei,Ji, Xiaopeng,Yang, Luhui,Dai, Yuewei Electronics and Telecommunications Research Instit 2021 ETRI Journal Vol.43 No.1

DNS (Domain Name System) tunnels almost obscure the true network activities of users, which makes it challenging for the gateway or censorship equipment to identify malicious or unpermitted network behaviors. An efficient way to address this problem is to conduct a temporal-spatial analysis on the tunnel traffic. Nevertheless, current studies on this topic limit the DNS tunnel to those with a single protocol, whereas more than one protocol may be used simultaneously. In this paper, we concentrate on the refined identification of two protocols mixed in a DNS tunnel. A feature set is first derived from DNS query and response flows, which is incorporated with deep neural networks to construct a regression model. We benchmark the proposed method with captured DNS tunnel traffic, the experimental results show that the proposed scheme can achieve identification accuracy of more than 90%. To the best of our knowledge, the proposed scheme is the first to estimate the ratios of two mixed protocols in DNS tunnels.

Detection and Parameter Estimation for Jitterbug Covert Channel Based on Coefficient of Variation

( Hao Wang ),( Guangjie Liu ),( Jiangtao Zhai ),( Yuewei Dai ) 한국인터넷정보학회 2016 KSII Transactions on Internet and Information Syst Vol.10 No.4

Jitterbug is a passive network covert timing channel supplying reliable stealthy transmission. It is also the basic manner of some improved covert timing channels designed for higher undetectability. The existing entropy-based detection scheme based on training sample binning may suffer from model mismatching, which results in detection performance deterioration. In this paper, a new detection method based on the feature of Jitterbug covert channel traffic is proposed. A fixed binning strategy without training samples is used to obtain bins distribution feature. Coefficient of variation (CV) is calculated for several sets of selected bins and the weighted mean is used to calculate the final CV value to distinguish Jitterbug from normal traffic. Furthermore, the timing window parameter of Jitterbug is estimated based on the detected traffic. Experimental results show that the proposed detection method can achieve high detection performance even with interference of network jitter, and the parameter estimation method can provide accurate values after accumulating plenty of detected samples.

Classroom Roll-Call System Based on ResNet Networks

Jinlong Zhu,Fanhua Yu,Guangjie Liu,Mingyu Sun,Dong Zhao,Qingtian Geng,Jinbo Su 한국정보처리학회 2020 Journal of information processing systems Vol.16 No.5

A convolution neural networks (CNNs) has demonstrated outstanding performance compared to otheralgorithms in the field of face recognition. Regarding the over-fitting problem of CNN, researchers haveproposed a residual network to ease the training for recognition accuracy improvement. In this study, a novelface recognition model based on game theory for call-over in the classroom was proposed. In the proposedscheme, an image with multiple faces was used as input, and the residual network identified each face with aconfidence score to form a list of student identities. Face tracking of the same identity or low confidence weredetermined to be the optimisation objective, with the game participants set formed from the student identitylist. Game theory optimises the authentication strategy according to the confidence value and identity set toimprove recognition accuracy. We observed that there exists an optimal mapping relation between face andidentity to avoid multiple faces associated with one identity in the proposed scheme and that the proposedgame-based scheme can reduce the error rate, as compared to the existing schemes with deeper neural network.

Exploiting Correlation Characteristics to Detect Covert digital communication

( Shuhua Huang ),( Weiwei Liu ),( Guangjie Liu ),( Yuewei Dai ),( Wen Tian ) 한국인터넷정보학회 2020 KSII Transactions on Internet and Information Syst Vol.14 No.8

As a widely used way to exfiltrate information, wireless covert channel (WCC) brings a serious threat to communication security, which enables the wireless communication process to bypass the authorized access control mechanism to disclose information. Unlike the covert channel on the network layer, wireless covert channels on the physical layer (WCC-P) is a new covert communication mode to implement and improve covert wireless communication. Existing WCC-P scheme modulates the secret message bits into the Gaussian noise, which is also called covert digital communication system based on the joint normal distribution (CJND). Finding the existence of this type of covert channel remains a challenging work due to its high undetectability. In this paper, we exploit the square autocorrelation coefficient (SAC) characteristic of the CJND signal to distinguish the covert communication from legitimate communication. We study the sharp increase of the SAC value when the offset is equal to the symbol length, which is caused by embedding secret information. Then, the SAC value of the measured sample is compared with the threshold value to determine whether the measured sample is CJND sample. When the signal-to-noise ratio reaches 20db, the detection accuracy can reach more than 90%.

Honeypot game‐theoretical model for defending against APT attacks with limited resources in cyber‐physical systems

Wen Tian,Xiaopeng Ji,Weiwei Liu,Jiangztao Zhai,Guangjie Liu,Yauwei Dai,Shuhua Huang 한국전자통신연구원 2019 ETRI Journal Vol.41 No.5

A cyber‐physical system (CPS) is a new mechanism controlled or monitored by computer algorithms that intertwine physical and software components. Advanced persistent threats (APTs) represent stealthy, powerful, and well‐funded attacks against CPSs; they integrate physical processes and have recently become an active research area. Existing offensive and defensive processes for APTs in CPSs are usually modeled by incomplete information game theory. However, honeypots, which are effective security vulnerability defense mechanisms, have not been widely adopted or modeled for defense against APT attacks in CPSs. In this study, a honeypot game‐theoretical model considering both low‐ and high‐interaction modes is used to investigate the offensive and defensive interactions, so that defensive strategies against APTs can be optimized. In this model, human analysis and honeypot allocation costs are introduced as limited resources. We prove the existence of Bayesian Nash equilibrium strategies and obtain the optimal defensive strategy under limited resources. Finally, numerical simulations demonstrate that the proposed method is effective in obtaining the optimal defensive effect.

Directional crossover slime mould algorithm with adaptive Lévy diversity for the optimal design of real-world problems

Qi Ailiang,Zhao Dong,Yu Fanhua,Liu Guangjie,Heidari Ali Asghar,Chen Huiling,Algarni Abeer D.,Elmannai Hela,Gui Wenyong 한국CDE학회 2022 Journal of computational design and engineering Vol.9 No.6

The slime mould algorithm (SMA) has become a classical algorithm applied in many fields since it was presented. Nevertheless, when faced with complex tasks, the algorithm converges slowly and tends to fall into the local optimum. So, there is still room for improvement in the performance of SMA. This work proposes a novel SMA variant (SDSMA), combining the adaptive Lévy diversity mechanism and directional crossover mechanism. Firstly, the adaptive Lévy diversity mechanism can improve population diversity. Then, the directional crossover mechanism can enhance the balance of exploration and exploitation, thus helping SDSMA to increase the convergence speed and accuracy. SDSMA is compared with SMA variants, original algorithms, improved algorithms, improved-SMAs, and others on the benchmark function set to verify its performance. Meanwhile, the Wilcoxon signed-rank test, the Friedman test, and other analytical methods are considered to analyze the experimental results. The analysis results show that SDSMA with two strategies significantly improves the performance of SMA. Meanwhile, the computational cost of SDSMA is smaller than that of SMA on benchmark function. Finally, the proposed algorithm is applied to three real-world engineering design problems. The experiments prove that SDSMA is an effective aid tool for computationally complex practical tasks.

Morphology Controlled Synthesis of Octahedral Covalent Imine Frameworks Through Acid Modulated Aldehyde-Amine Polycondensation

Lili Pan,Zihua Chen,Wenxiu De,Guangjie Yang,Xikui Liu 한국고분자학회 2016 Macromolecular Research Vol.24 No.4

The past decades have witnessed significant advance in the synthesis of covalent organic frameworks (COFs), however, their formation and morphology revolution mechanism have been rarely reported. Here, through an acid modulated dynamic covalent chemistry approach, pure and uniform micro-octahedral covalent imine frameworks were obtained for the first time. Formation mechanism based on the stacking of initially formed two-dimensional nanoplates followed by surface smoothing enabled by the dynamic nature of imine bonding was proposed. Furthermore, we revealed for the first time that nonstoichiometric method can be applied to the synthesis of covalent organic frameworks. Thus we provide novel strategy for the morphology control COFs which will surely facilitate their application in energy-related area.