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2021-08-03
Jin, Ya, Chen, Yin Fang, Xu, Chang Da, Qi, Yi Chao, Chen, Shao Kang, Chen, Wei, Zhu, Ning Hua.  2020.  A hybrid optical frequency-hopping scheme based on OAM multiplexing for secure optical communications. 2020 Asia Communications and Photonics Conference (ACP) and International Conference on Information Photonics and Optical Communications (IPOC). :1—3.
In this paper, a hybrid optical frequency hopping system based on OAM multiplexing is proposed, which is mainly applied to the security of free space optical communication. In the proposed scheme, the segmented users' data goes through two stages of hopping successively to realize data hiding. And the security performance is also analyzed in this paper. © 2020 The Author(s).
2021-07-08
Li, Sichun, Jin, Xin, Yao, Sibing, Yang, Shuyu.  2020.  Underwater Small Target Recognition Based on Convolutional Neural Network. Global Oceans 2020: Singapore – U.S. Gulf Coast. :1—7.
With the increasingly extensive use of diver and unmanned underwater vehicle in military, it has posed a serious threat to the security of the national coastal area. In order to prevent the underwater diver's impact on the safety of water area, it is of great significance to identify underwater small targets in time to make early warning for it. In this paper, convolutional neural network is applied to underwater small target recognition. The recognition targets are diver, whale and dolphin. Due to the time-frequency spectrum can reflect the essential features of underwater target, convolutional neural network can learn a variety of features of the acoustic signal through the image processed by the time-frequency spectrum, time-frequency image is input to convolutional neural network to recognize the underwater small targets. According to the study of learning rate and pooling mode, the network parameters and structure suitable for underwater small target recognition in this paper are selected. The results of data processing show that the method can identify underwater small targets accurately.
2021-02-15
Myasnikova, N., Beresten, M. P., Myasnikova, M. G..  2020.  Development of Decomposition Methods for Empirical Modes Based on Extremal Filtration. 2020 Moscow Workshop on Electronic and Networking Technologies (MWENT). :1–4.
The method of extremal filtration implementing the decomposition of signals into alternating components is considered. The history of the method development is described, its mathematical substantiation is given. The method suggests signal decomposition based on the removal of known components locally determined by their extrema. The similarity of the method with empirical modes decomposition in terms of the result is shown, and their comparison is also carried out. The algorithm of extremal filtration has a simple mathematical basis that does not require the calculation of transcendental functions, which provides it with higher performance with comparable results. The advantages and disadvantages of the extremal filtration method are analyzed, and the possibility of its application for solving various technical problems is shown, i.e. the formation of diagnostic features, rapid analysis of signals, spectral and time-frequency analysis, etc. The methods for calculating spectral characteristics are described: by the parameters of the distinguished components, based on the approximation on the extrema by bell-shaped pulses. The method distribution in case of wavelet transform of signals is described. The method allows obtaining rapid evaluation of the frequencies and amplitudes (powers) of the components, which can be used as diagnostic features in solving problems of recognition, diagnosis and monitoring. The possibility of using extremal filtration in real-time systems is shown.
2020-12-11
Zhang, L., Shen, X., Zhang, F., Ren, M., Ge, B., Li, B..  2019.  Anomaly Detection for Power Grid Based on Time Series Model. 2019 IEEE International Conference on Computational Science and Engineering (CSE) and IEEE International Conference on Embedded and Ubiquitous Computing (EUC). :188—192.

In the process of informationization and networking of smart grids, the original physical isolation was broken, potential risks increased, and the increasingly serious cyber security situation was faced. Therefore, it is critical to develop accuracy and efficient anomaly detection methods to disclose various threats. However, in the industry, mainstream security devices such as firewalls are not able to detect and resist some advanced behavior attacks. In this paper, we propose a time series anomaly detection model, which is based on the periodic extraction method of discrete Fourier transform, and determines the sequence position of each element in the period by periodic overlapping mapping, thereby accurately describe the timing relationship between each network message. The experiments demonstrate that our model can detect cyber attacks such as man-in-the-middle, malicious injection, and Dos in a highly periodic network.

Huang, Y., Wang, Y..  2019.  Multi-format speech perception hashing based on time-frequency parameter fusion of energy zero ratio and frequency band variance. 2019 3rd International Conference on Electronic Information Technology and Computer Engineering (EITCE). :243—251.

In order to solve the problems of the existing speech content authentication algorithm, such as single format, ununiversal algorithm, low security, low accuracy of tamper detection and location in small-scale, a multi-format speech perception hashing based on time-frequency parameter fusion of energy zero ratio and frequency band bariance is proposed. Firstly, the algorithm preprocesses the processed speech signal and calculates the short-time logarithmic energy, zero-crossing rate and frequency band variance of each speech fragment. Then calculate the energy to zero ratio of each frame, perform time- frequency parameter fusion on time-frequency features by mean filtering, and the time-frequency parameters are constructed by difference hashing method. Finally, the hash sequence is scrambled with equal length by logistic chaotic map, so as to improve the security of the hash sequence in the transmission process. Experiments show that the proposed algorithm is robustness, discrimination and key dependent.

Hassan, S. U., Khan, M. Zeeshan, Khan, M. U. Ghani, Saleem, S..  2019.  Robust Sound Classification for Surveillance using Time Frequency Audio Features. 2019 International Conference on Communication Technologies (ComTech). :13—18.

Over the years, technology has reformed the perception of the world related to security concerns. To tackle security problems, we proposed a system capable of detecting security alerts. System encompass audio events that occur as an outlier against background of unusual activity. This ambiguous behaviour can be handled by auditory classification. In this paper, we have discussed two techniques of extracting features from sound data including: time-based and signal based features. In first technique, we preserve time-series nature of sound, while in other signal characteristics are focused. Convolution neural network is applied for categorization of sound. Major aim of research is security challenges, so we have generated data related to surveillance in addition to available datasets such as UrbanSound 8k and ESC-50 datasets. We have achieved 94.6% accuracy for proposed methodology based on self-generated dataset. Improved accuracy on locally prepared dataset demonstrates novelty in research.

Geng, J., Yu, B., Shen, C., Zhang, H., Liu, Z., Wan, P., Chen, Z..  2019.  Modeling Digital Low-Dropout Regulator with a Multiple Sampling Frequency Circuit Technology. 2019 IEEE 13th International Conference on Anti-counterfeiting, Security, and Identification (ASID). :207—210.

The digital low dropout regulators are widely used because it can operate at low supply voltage. In the digital low drop-out regulators, the high sampling frequency circuit has a short setup time, but it will produce overshoot, and then the output can be stabilized; although the low sampling frequency circuit output can be directly stabilized, the setup time is too long. This paper proposes a two sampling frequency circuit model, which aims to include the high and low sampling frequencies in the same circuit. By controlling the sampling frequency of the circuit under different conditions, this allows the circuit to combine the advantages of the circuit operating at different sampling frequencies. This shortens the circuit setup time and the stabilization time at the same time.

Fujiwara, N., Shimasaki, K., Jiang, M., Takaki, T., Ishii, I..  2019.  A Real-time Drone Surveillance System Using Pixel-level Short-time Fourier Transform. 2019 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR). :303—308.

In this study we propose a novel method for drone surveillance that can simultaneously analyze time-frequency responses in all pixels of a high-frame-rate video. The propellers of flying drones rotate at hundreds of Hz and their principal vibration frequency components are much higher than those of their background objects. To separate the pixels around a drone's propellers from its background, we utilize these time-series features for vibration source localization with pixel-level short-time Fourier transform (STFT). We verify the relationship between the number of taps in the STFT computation and the performance of our algorithm, including the execution time and the localization accuracy, by conducting experiments under various conditions, such as degraded appearance, weather, and defocused blur. The robustness of the proposed algorithm is also verified by localizing a flying multi-copter in real-time in an outdoor scenario.

Kousri, M. R., Deniau, V., Gransart, C., Villain, J..  2019.  Optimized Time-Frequency Processing Dedicated to the Detection of Jamming Attacks on Wi-Fi Communications. 2019 URSI Asia-Pacific Radio Science Conference (AP-RASC). :1—4.

Attacks by Jamming on wireless communication network can provoke Denial of Services. According to the communication system which is affected, the consequences can be more or less critical. In this paper, we propose to develop an algorithm which could be implemented at the reception stage of a communication terminal in order to detect the presence of jamming signals. The work is performed on Wi-Fi communication signals and demonstrates the necessity to have a specific signal processing at the reception stage to be able to detect the presence of jamming signals.

Li, J., Liu, H., Wu, J., Zhu, J., Huifeng, Y., Rui, X..  2019.  Research on Nonlinear Frequency Hopping Communication Under Big Data. 2019 International Conference on Computer Network, Electronic and Automation (ICCNEA). :349—354.

Aiming at the problems of poor stability and low accuracy of current communication data informatization processing methods, this paper proposes a research on nonlinear frequency hopping communication data informatization under the framework of big data security evaluation. By adding a frequency hopping mediation module to the frequency hopping communication safety evaluation framework, the communication interference information is discretely processed, and the data parameters of the nonlinear frequency hopping communication data are corrected and converted by combining a fast clustering analysis algorithm, so that the informatization processing of the nonlinear frequency hopping communication data under the big data safety evaluation framework is completed. Finally, experiments prove that the research on data informatization of nonlinear frequency hopping communication under the framework of big data security evaluation could effectively improve the accuracy and stability.

Ma, X., Sun, X., Cheng, L., Guo, X., Liu, X., Wang, Z..  2019.  Parameter Setting of New Energy Sources Generator Rapid Frequency Response in Northwest Power Grid Based on Multi-Frequency Regulation Resources Coordinated Controlling. 2019 IEEE 8th International Conference on Advanced Power System Automation and Protection (APAP). :218—222.
Since 2016, the northwest power grid has organized new energy sources to participate in the rapid frequency regulation research and carried out pilot test work at the sending end large power grid. The experimental results show that new energy generator has the ability to participate in the grid's rapid frequency regulation, and its performance is better than that of conventional power supply units. This paper analyses the requirements for fast frequency control of the sending end large power grid in northwest China, and proposes the segmented participation indexes of photovoltaic and wind power in the frequency regulation of power grids. In accordance with the idea of "clear responsibilities, various types of unit coordination", the parameter setting of new energy sources rapid frequency regulation is completed based on the coordinated control based on multi-frequency regulation resources in northwest power grid. The new energy fast frequency regulation model was established, through the PSASP power grid stability simulation program and the large-scale power grid stability simulation analysis was completed. The simulation results show that the wind power and photovoltaic adopting differential rapid frequency regulation parameters can better utilize the rapid frequency regulation capability of various types of power sources, realize the coordinated rapid frequency regulation of all types of units, and effectively improve the frequency security prevention and control level of the sending end large power grid.
Abratkiewicz, K., Gromek, D., Samczynski, P..  2019.  Chirp Rate Estimation and micro-Doppler Signatures for Pedestrian Security Radar Systems. 2019 Signal Processing Symposium (SPSympo). :212—215.

A new approach to micro-Doppler signal analysis is presented in this article. Novel chirp rate estimators in the time-frequency domain were used for this purpose, which provided the chirp rate of micro-Doppler signatures, allowing the classification of objects in the urban environment. As an example verifying the method, a signal from a high-resolution radar with a linear frequency modulated continuous wave (FMCW) recording an echo reflected from a pedestrian was used to validate the proposed algorithms for chirp rate estimation. The obtained results are plotted on saturated accelerograms, giving an additional parameter dedicated for target classification in security systems utilizing radar sensors for target detection.

2020-08-03
Liu, Fuxiang, Jiang, Qi.  2019.  Research on Recognition of Criminal Suspects Based on Foot Sounds. 2019 IEEE 3rd Information Technology, Networking, Electronic and Automation Control Conference (ITNEC). :1347–1351.
There are two main contributions in this paper: Firstly, by analyzing the frequency domain features and Mel domain features, we can identify footstep events and non-footstep events. Secondly, we compared the two footstep sound signals of the same person in frequency domain under different experimental conditions, finding that almost all of their peak frequencies and trough frequencies in the main frequency band are respectively corresponding one-to-one. However for the two different people, even under the same experimental conditions, it is difficult to have the same peak frequencies and trough frequencies in the main frequency band of their footstep sound signals. Therefore, this feature of footstep sound signals can be used to identify different people.
Zarazaga, Pablo Pérez, B¨ackström, Tom, Sigg, Stephan.  2019.  Robust and Responsive Acoustic Pairing of Devices Using Decorrelating Time-Frequency Modelling. 2019 27th European Signal Processing Conference (EUSIPCO). :1–5.
Voice user interfaces have increased in popularity, as they enable natural interaction with different applications using one's voice. To improve their usability and audio quality, several devices could interact to provide a unified voice user interface. However, with devices cooperating and sharing voice-related information, user privacy may be at risk. Therefore, access management rules that preserve user privacy are important. State-of-the-art methods for acoustic pairing of devices provide fingerprinting based on the time-frequency representation of the acoustic signal and error-correction. We propose to use such acoustic fingerprinting to authorise devices which are acoustically close. We aim to obtain fingerprints of ambient audio adapted to the requirements of voice user interfaces. Our experiments show that the responsiveness and robustness is improved by combining overlapping windows and decorrelating transforms.
2020-06-29
Tran, Thang M., Nguyen, Khanh-Van.  2019.  Fast Detection and Mitigation to DDoS Web Attack Based on Access Frequency. 2019 IEEE-RIVF International Conference on Computing and Communication Technologies (RIVF). :1–6.

We have been investigating methods for establishing an effective, immediate defense mechanism against the DDoS attacks on Web applications via hacker botnets, in which this defense mechanism can be immediately active without preparation time, e.g. for training data, usually asked for in existing proposals. In this study, we propose a new mechanism, including new data structures and algorithms, that allow the detection and filtering of large amounts of attack packets (Web request) based on monitoring and capturing the suspect groups of source IPs that can be sending packets at similar patterns, i.e. with very high and similar frequencies. The proposed algorithm places great emphasis on reducing storage space and processing time so it is promising to be effective in real-time attack response.

2020-05-29
Yao, Lin, Jiang, Binyao, Deng, Jing, Obaidat, Mohammad S..  2019.  LSTM-Based Detection for Timing Attacks in Named Data Network. 2019 IEEE Global Communications Conference (GLOBECOM). :1—6.

Named Data Network (NDN) is an alternative to host-centric networking exemplified by today's Internet. One key feature of NDN is in-network caching that reduces access delay and query overhead by caching popular contents at the source as well as at a few other nodes. Unfortunately, in-network caching suffers various privacy risks by different attacks, one of which is termed timing attack. This is an attack to infer whether a consumer has recently requested certain contents based on the time difference between the delivery time of those contents that are currently cached and those that are not cached. In order to prevent the privacy leakage and resist such kind of attacks, we propose a detection scheme by adopting Long Short-term Memory (LSTM) model. Based on the four input features of LSTM, cache hit ratio, average request interval, request frequency, and types of requested contents, we timely capture more important eigenvalues by dividing a constant time window size into a few small slices in order to detect timing attacks accurately. We have performed extensive simulations to compare our scheme with several other state-of-the-art schemes in classification accuracy, detection ratio, false alarm ratio, and F-measure. It has been shown that our scheme possesses a better performance in all cases studied.

2020-05-11
Yu, Dunyi.  2018.  Research on Anomaly Intrusion Detection Technology in Wireless Network. 2018 International Conference on Virtual Reality and Intelligent Systems (ICVRIS). :540–543.
In order to improve the security of wireless network, an anomaly intrusion detection algorithm based on adaptive time-frequency feature decomposition is proposed. This paper analyzes the types and detection principles of wireless network intrusion detection, it adopts the information statistical analysis method to detect the network intrusion, constructs the traffic statistical analysis model of the network abnormal intrusion, and establishes the network intrusion signal model by combining the signal fitting method. The correlation matching filter is used to filter the network intrusion signal to improve the output signal-to-noise ratio (SNR), the time-frequency analysis method is used to extract the characteristic quantity of the network abnormal intrusion, and the adaptive correlation spectrum analysis method is used to realize the intrusion detection. The simulation results show that this method has high accuracy and strong anti-interference ability, and it can effectively guarantee the network security.
2019-09-09
Wang, S., Zhou, Y., Guo, R., Du, J., Du, J..  2018.  A Novel Route Randomization Approach for Moving Target Defense. 2018 IEEE 18th International Conference on Communication Technology (ICCT). :11–15.
Route randomization is an important research focus for moving target defense which seeks to proactively and dynamically change the forwarding routes in the network. In this paper, the difficulties of implementing route randomization in traditional networks are analyzed. To solve these difficulties and achieve effective route randomization, a novel route randomization approach is proposed, which is implemented by adding a mapping layer between routers' physical interfaces and their corresponding logical addresses. The design ideas and the details of proposed approach are presented. The effectiveness and performance of proposed approach are verified and evaluated by corresponding experiments.
2019-03-15
Kostyria, O., Storozhenko, V., Naumenko, V., Romanov, Y..  2018.  Mathematical Models of Blocks for Compensation Multipath Distortion in Spatially Separated Passive Time-Frequency Synchronization Radio System. 2018 International Scientific-Practical Conference Problems of Infocommunications. Science and Technology (PIC S T). :104-108.

Multipath propagation of radio waves negatively affects to the performance of telecommunications and radio navigation systems. When performing time and frequency synchronization tasks of spatially separated standards, the multipath signal propagation aggravates the probability of a correct synchronization and introduces an error. The presence of a multipath signal reduces the signal-to-noise ratio in the received signal, which in turn causes an increase in the synchronization error. If the time delay of the additional beam (s) is less than the useful signal duration, the reception of the useful signal is further complicated by the presence of a partially correlated interference, the level and correlation degree of which increases with decreasing time delay of the interference signals. The article considers with the method of multi-path interference compensation in a multi-position (telecommunication or radio navigation system) or a time and frequency synchronization system for the case if at least one of the receiving positions has no noise signal or does not exceed the permissible level. The essence of the method is that the interference-free useful signal is transmitted to other points in order to pick out the interference component from the signal / noise mix. As a result, an interference-free signal is used for further processing. The mathematical models of multipath interference suppressors in the temporal and in the frequency domain are presented in the article. Compared to time processing, processing in the frequency domain reduces computational costs. The operation of the suppressor in the time domain has been verified experimentally.

2018-04-11
Huang, Kaiyu, Qu, Y., Zhang, Z., Chakravarthy, V., Zhang, Lin, Wu, Z..  2017.  Software Defined Radio Based Mixed Signal Detection in Spectrally Congested and Spectrally Contested Environment. 2017 Cognitive Communications for Aerospace Applications Workshop (CCAA). :1–6.

In a spectrally congested environment or a spectrally contested environment which often occurs in cyber security applications, multiple signals are often mixed together with significant overlap in spectrum. This makes the signal detection and parameter estimation task very challenging. In our previous work, we have demonstrated the feasibility of using a second order spectrum correlation function (SCF) cyclostationary feature to perform mixed signal detection and parameter estimation. In this paper, we present our recent work on software defined radio (SDR) based implementation and demonstration of such mixed signal detection algorithms. Specifically, we have developed a software defined radio based mixed RF signal generator to generate mixed RF signals in real time. A graphical user interface (GUI) has been developed to allow users to conveniently adjust the number of mixed RF signal components, the amplitude, initial time delay, initial phase offset, carrier frequency, symbol rate, modulation type, and pulse shaping filter of each RF signal component. This SDR based mixed RF signal generator is used to transmit desirable mixed RF signals to test the effectiveness of our developed algorithms. Next, we have developed a software defined radio based mixed RF signal detector to perform the mixed RF signal detection. Similarly, a GUI has been developed to allow users to easily adjust the center frequency and bandwidth of band of interest, perform time domain analysis, frequency domain analysis, and cyclostationary domain analysis.

2018-02-27
Sulavko, A. E., Eremenko, A. V., Fedotov, A. A..  2017.  Users' Identification through Keystroke Dynamics Based on Vibration Parameters and Keyboard Pressure. 2017 Dynamics of Systems, Mechanisms and Machines (Dynamics). :1–7.

The paper considers an issues of protecting data from unauthorized access by users' authentication through keystroke dynamics. It proposes to use keyboard pressure parameters in combination with time characteristics of keystrokes to identify a user. The authors designed a keyboard with special sensors that allow recording complementary parameters. The paper presents an estimation of the information value for these new characteristics and error probabilities of users' identification based on the perceptron algorithms, Bayes' rule and quadratic form networks. The best result is the following: 20 users are identified and the error rate is 0.6%.

2017-11-13
Park, B., DeMarco, C. L..  2016.  Optimal control via waveform relaxation for power systems cyber-security applications. 2016 IEEE Power and Energy Society General Meeting (PESGM). :1–5.

This paper formulates a power system related optimal control problem, motivated by potential cyber-attacks on grid control systems, and ensuing defensive response to such attacks. The problem is formulated as a standard nonlinear program in the GAMS optimization environment, with system dynamics discretized over a short time horizon providing constraint equations, which are then treated via waveform relaxation. Selection of objective function and additional decision variables is explored first for identifying grid vulnerability to cyber-attacks that act by modifying feedback control system parameters. The resulting decisions for the attacker are then fixed, and the optimization problem is modified with a new objective function and decision variables, to explore a defender's possible response to such attacks.

2017-03-07
Senejohnny, D., Tesi, P., Persis, C. De.  2015.  Self-triggered coordination over a shared network under Denial-of-Service. 2015 54th IEEE Conference on Decision and Control (CDC). :3469–3474.

The issue of security has become ever more prevalent in the analysis and design of cyber-physical systems. In this paper, we analyze a consensus network in the presence of Denial-of-Service (DoS) attacks, namely attacks that prevent communication among the network agents. By introducing a notion of Persistency-of-Communication (PoC), we provide a characterization of DoS frequency and duration such that consensus is not destroyed. An example is given to substantiate the analysis.

2017-02-21
L. Thiele, M. Kurras, S. Jaeckel, S. Fähse, W. Zirwas.  2015.  "Interference-floor shaping for liquid coverage zones in coordinated 5G networks". 2015 49th Asilomar Conference on Signals, Systems and Computers. :1102-1106.

Joint transmission coordinated multi-point (CoMP) is a combination of constructive and destructive superposition of several to potentially many signal components, with the goal to maximize the desired receive-signal and at the same time to minimize mutual interference. Especially the destructive superposition requires accurate alignment of phases and amplitudes. Therefore, a 5G clean slate approach needs to incorporate the following enablers to overcome the challenging limitation for JT CoMP: accurate channel estimation of all relevant channel components, channel prediction for time-aligned precoder design, proper setup of cooperation areas corresponding to user grouping and to limit feedback overhead especially in FDD as well as treatment of out-of-cluster interference (interference floor shaping).

2015-05-05
Jian Wu, Yongmei Jiang, Gangyao Kuang, Jun Lu, Zhiyong Li.  2014.  Parameter estimation for SAR moving target detection using Fractional Fourier Transform. Geoscience and Remote Sensing Symposium (IGARSS), 2014 IEEE International. :596-599.

This paper proposes an algorithm for multi-channel SAR ground moving target detection and estimation using the Fractional Fourier Transform(FrFT). To detect the moving target with low speed, the clutter is first suppressed by Displace Phase Center Antenna(DPCA), then the signal-to-clutter can be enhanced. Have suppressed the clutter, the echo of moving target remains and can be regarded as a chirp signal whose parameters can be estimated by FrFT. FrFT, one of the most widely used tools to time-frequency analysis, is utilized to estimate the Doppler parameters, from which the moving parameters, including the velocity and the acceleration can be obtained. The effectiveness of the proposed method is validated by the simulation.