Due to the evolution in digital communications, sending a sheltered message, where interferers are prying for any useful piece of information, has become a rigid mission. In this paper, a multiple layer message security scheme is proposed, utilizing 3D images. The proposed scheme is robust against any means of eavesdropping or intruding as it is comprised of four layers of security as follows: encryption using AES–128, encoding using a repetition code, least significant bit (LSB) steganography and jamming through the addition of noise. The proposed scheme is compared with its counterparts from the literature and is shown to exhibit excellent traits, in terms of being reversible and its ability to carry out blind extraction of the data as well as withstanding geometrical attacks. Furthermore, the proposed scheme exhibits very good performance in terms of the mean squared error (MSE) and the peak signal to noise ratios (PSNR).

Secure Message Embedding in 3D Images

In this paper, we propose a steganalysis method based on the principle of additive operator, which chooses non-zero AC coefficients as carriers, with secret information independent of the carrier information flow. In the proposed method, AC coefficient statistical and energy features are initially extracted and used to construct a 3D feature vector. By employing the principle of Fisher linear discriminate analysis, a flexible discriminate classifier suitable for the extracted features is designed to improve detection performance. We infer and confirm theory of change in the statistical and energetic characteristics of the AC coefficient before and after additive steganography. The effectiveness of the proposed method is proven by the experiments. Moreover, the proposed method consistently outperforms related methods.

A steganalysis method in the DCT domain

Protocol reverse engineering is essential to information security of industrial control systems. In this paper, we propose a V-gram method, which takes variable gram as input of XGBoost. In view of the periodic and structurally fixed characteristics of industrial control protocol, progressive multi-sequence alignment algorithm is used to cluster initial message samples for traffic with the same payload length. V-gram is generated after the variable domain and fixed domain of message sequences are separated, and feature words are extracted by XGBoost model. The states of data packets are classified and tagged with XGBoost, so as to realize the construction of FSM model. Experimental results show that the proposed approach is effective in mining junior semantic information for industrial control protocols.

Reverse Engineering of Industrial Control Protocol By XGBoost with V-gram

licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Abstract: Supervisory control and data acquisition systems (SCADAs) play an important role in supervising and controlling industrial production with the help of programmable logic controllers (PLCs) in industrial control systems (ICSs). A PLC receives the control information or program from a SCADA to control the production equipment and feeds the production data back to the SCADA. Once a SCADA is controlled by an attacker, it may threaten the safety of industrial production. The lack of security protection, such as identity authentication and encryption for industrial control protocols, increases the potential security risks. In this paper, we propose a PLC protection system combined with a monitor between a SCADA and a PLC and a physically separated monitoring station. By using the PLC protection system, identity verification and command verification are separated, and both the identity of the operator and the corresponding commands are recorded. Experiments show that even if the SCADA is controlled by an attacker, our system could still protect the PLC in the field and record the identity of the key command operator, which facilitates the tracing and forensics of malicious activities.

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PLC Protection System Based on Verification Separation

Launch vehicle network as an extremely important national defense information system, is faced with the threat of information security because of the dynamic detection limitation of the traditional firewall, virus detection software and so on. In this paper, we choose evaluation index and establish the entropy weight combination model based on the exponentially weighted moving-average (EWMA) model and the echo state network (ESN) model, Finally, we select the actual traffic data of the network, verify the effectiveness of the sequential dynamic security detection model, and study the influence of different time window observation scale on anomaly detection.

Research on Abnormal Behavior Detection Technology of Launch Vehicle Controlled Network

Steganalysis is the opposite art to steganography, whose goal is to detect whether or not the seemly innocent objects like image hiding message. With the explosive growth of the Internet information. Making real time image steganalysis online to detect the malicious use of multimedia documents for covert communication has become more and more difficult. Traditional research on image steganalysis mainly focus on how to improve the accuracy of Steganalysis, few of them pay much attention on the efficiency of the Image Steganalysis technology and the architecture optimizing for Steganalysis service providing. Regarding this problem, this paper proposed a Image Steganalysis Technique Based on Cloud Computing and BP Neutral Network, the structure and workflow of the system is introduced in detail. The result of simulation experiment proves that the import of cloud computing architecture can apparently improve the efficiency of image Steganalysis in the environment of internet and the accuracy of Steganalysis algorithm is acceptable instead of being greatly affected by system load.

Peng Yong

Papers

Research on the Large Scale Image Steganalysis Technology Based on Cloud Computing and BP Neutral Network

Scenario fingerprint of an industrial control system and abnormally detection