Information Forensics - Frame deletion forensics has been a major area of video forensics in recent years. The detection effect of current deep neural network-based methods outperforms previous traditional detection methods. Recently, researchers have used residual features as input to the network to detect frame deletion and have achieved promising results. We propose an IReF (Improved Residual Feature) by analyzing the effect of residual features on frame deletion traces. IReF preserves the main motion features and edge information by denoising and enhancing the residual features, making it easier for the network to identify the tampered features. And the sparse noise reduction reduces the storage requirement. Experiments show that under the 2D convolutional neural network, the accuracy of IReF compared with residual features is increased by 3.81 \%, and the storage space requirement is reduced by 78\%. In the 3D convolutional neural network with video clips as feature input, the accuracy of IReF features is increased by 5.63\%, and the inference efficiency is increased by 18\%.

Information Forensics - There are a large number of illegal websites on the Internet, such as pornographic websites, gambling websites, online fraud websites, online pyramid selling websites, etc. This paper studies the use of crawler technology for digital forensics on illegal websites. First, a crawler based illegal website forensics program is designed and developed, which can detect the peripheral information of illegal websites, such as domain name, IP address, network topology, and crawl key information such as website text, pictures, and scripts. Then, through comprehensive analysis such as word cloud analysis, word frequency analysis and statistics on the obtained data, it can help judge whether a website is illegal.

Information Forensics - WhatsApp is one of the rare applications that has managed to become one of the most popular instant messaging applications all over the world. While inherently designed for simple and fast communication, privacy features such as end-to-end encryption have made confidential communication easy for criminals aiming to commit illegal acts. However, as it meets many daily communication and communication needs, it has a great potential to be digital evidence in interpersonal disputes. In this study, in parallel with the potential of WhatsApp application to contain digital evidence, the abuse of this situation and the manipulation method of multimedia files, which may cause wrong decisions by the judicial authorities, are discussed. The dangerous side of this method, which makes the analysis difficult, is that it can be applied by anyone without the need for high-level root authority or any other application on these devices. In addition, it is difficult to detect as no changes can be made in the database during the analysis phase. In this study, a controlled experimental environment was prepared on the example scenario, the manipulation was carried out and the prepared system analysis was included. The results obtained showed that the evidence at the forensic analysis stage is open to misinterpretation.

Information Forensics - As an important branch of computer forensics, network forensics technology, whether abroad or at home, is in its infancy. It mainly focuses on the research on the framework of some forensics systems or some local problems, and has not formed a systematic theory, method and system. In order to improve the network forensics sys-tem, have a relatively stable and correct model for refer-ence, ensure the authenticity and credibility of network fo-rensics from the forensics steps, provide professional and non professional personnel with a standard to measure the availability of computer network crime investigation, guide the current network forensics process, and promote the gradual maturity of network forensics theories and methods, This paper presents a fuzzy decision tree reason-ing method for network forensics analysis.

Information Forensics - With the advent of information and communication technology, the digital space is becoming a playing ground for criminal activities. Criminals typically prefer darkness or a hidden place to perform their illegal activities in a real-world while sometimes covering their face to avoid being exposed and getting caught. The same applies in a digital world where criminals prefer features which provide anonymity or hidden features to perform illegal activities. It is from this spirit the Darkweb is attracting all kinds of criminal activities conducted over the Internet such as selling drugs, illegal weapons, child pornography, assassination for hire, hackers for hire, and selling of malicious exploits, to mention a few. Although the anonymity offered by Darkweb can be exploited as a tool to arrest criminals involved in cybercrime, an in-depth research is needed to advance criminal investigation on Darkweb. Analysis of illegal activities conducted in Darkweb is in its infancy and faces several challenges like lack of standard operating procedures. This study proposes progressive standard operating procedures (SOPs) for Darkweb forensics investigation. We provide the four stages of SOP for Darkweb investigation. The proposed SOP consists of the following stages; identification and profiling, discovery, acquisition and preservation, and the last stage is analysis and reporting. In each stage, we consider the objectives, tools and expected results of that particular stage. Careful consideration of this SOP revealed promising results in the Darkweb investigation.

Information Theoretic Security - From an information-theoretic standpoint, the intrusion detection process can be examined. Given the IDS output(alarm data), we should have less uncertainty regarding the input (event data). We propose the Capability of Intrusion Detection (CID) measure, which is simply the ratio of mutual information between IDS input and output, and the input of entropy. CID has the desirable properties of (1) naturally accounting for all important aspects of detection capability, such as true positive rate, false positive rate, positive predictive value, negative predictive value, and base rate, (2) objectively providing an intrinsic measure of intrusion detection capability, and (3) being sensitive to IDS operation parameters. When finetuning an IDS, we believe that CID is the best performance metric to use. In terms of the IDS’ inherent ability to classify input data, the so obtained operation point is the best that it can achieve.

Information Theoretic Security - Artificial Intelligence (AI) technology is developing rapidly, permeating every aspect of human life. Although the integration between AI and communication contributes to the flourishing development of wireless communication, it induces severer security problems. As a supplement to the upper-layer cryptography protocol, physical layer security has become an intriguing technology to ensure the security of wireless communication systems. However, most of the current physical layer security research does not consider the intelligence and mobility of collusive eavesdroppers. In this paper, we consider a MIMO system model with a friendly intelligent jammer against multiple collusive intelligent eavesdroppers, and zero-sum game is exploited to formulate the confrontation of them. The Nash equilibrium is derived by convex optimization and alternative optimization in the free-space scenario of a single user system. We propose a zero-sum game deep learning algorithm (ZGDL) for general situations to solve non-convex game problems. In terms of the effectiveness, simulations are conducted to confirm that the proposed algorithm can obtain the Nash equilibrium.

This paper assesses the impact on the performance that information-theoretic physical layer security (IT-PLS) introduces when integrated into a 5G New Radio (NR) system. For this, we implement a wiretap code for IT-PLS based on a modular coding scheme that uses a universal-hash function in its security layer. The main advantage of this approach lies in its flexible integration into the lower layers of the 5G NR protocol stack without affecting the communication s reliability. Specifically, we use IT-PLS to secure the transmission of downlink control information by integrating an extra pre-coding security layer as part of the physical downlink control channel (PDCCH) procedures, thus not requiring any change of the 3GPP 38 series standard. We conduct experiments using a real-time open-source 5G NR standalone implementation and use software-defined radios for over-the-air transmissions in a controlled laboratory environment. The overhead added by IT-PLS is determined in terms of the latency introduced into the system, which is measured at the physical layer for an end-to-end (E2E) connection between the gNB and the user equipment.

Information Theoretic Security - Geospatial fog computing system offers various benefits as a platform for geospatial computing services closer to the end users, including very low latency, good mobility, precise position awareness, and widespread distribution. In recent years, it has grown quickly. Fog nodes security is susceptible to a number of assaults, including denial of service and resource abuse, because to their widespread distribution, complex network environments, and restricted resource availability. This paper proposes a Quantum Key Distribution (QKD)-based geospatial quantum fog computing environment that offers a symmetric secret key negotiation protocol that can preserve information-theoretic security. In QKD, after being negotiated between any two fog nodes, the secret keys can be given to several users in various locations to maintain forward secrecy and long-term protection. The new geospatial quantum fog computing environment proposed in this work is able to successfully withstand a variety of fog computing assaults and enhances information security.

Information Theoretic Security - Physical layer (PHY) security in decode-and-forward (DF) relay systems is discussed. Based on the types of wiretap links, the secrecy performance of three typical secure DF relay models is analyzed. Different from conventional works in this field, rigorous derivations of the secrecy channel capacity are provided from an information-theoretic perspective. Meanwhile, closed-form expressions are derived to characterize the secrecy outage probability (SOP). For the sake of unveiling more system insights, asymptotic analyses are performed on the SOP for a sufficiently large signal-to-noise ratio (SNR). The analytical results are validated by computer simulations and are in excellent agreement.

Information Theoretic Security - Measuring the information leakage is critical for evaluating the practical security of cryptographic devices against side-channel analysis. Information-theoretic measures can be used (along with Fano’s inequality) to derive upper bounds on the success rate of any possible attack in terms of the number of side-channel measurements. Equivalently, this gives lower bounds on the number of queries for a given success probability of attack. In this paper, we consider cryptographic implementations protected by (first-order) masking schemes, and derive several information-theoretic bounds on the efficiency of any (second-order) attack. The obtained bounds are generic in that they do not depend on a specific attack but only on the leakage and masking models, through the mutual information between side-channel measurements and the secret key. Numerical evaluations confirm that our bounds reflect the practical performance of optimal maximum likelihood attacks.

Information Theoretic Security - A multi-designated receiver authentication code (MDRA-code) with information-theoretic security is proposed as an extension of the traditional multi-receiver authentication code. The purpose of the MDRA-code is to securely transmit a message via a broadcast channel from a single sender to an arbitrary subset of multiple receivers that have been designated by the sender, and only the receivers in the subset (i.e., not all receivers) should accept the message if an adversary is absent. This paper proposes a model and security formalization of MDRA-codes, and provides constructions of MDRA-codes.

Information Theoretic Security - All-or-nothing transforms (AONT) were proposed by Rivest as a message preprocessing technique for encrypting data to protect against brute-force attacks, and have many applications in cryptography and information security. Later the unconditionally secure AONT and their combinatorial characterization were introduced by Stinson. Informally, a combinatorial AONT is an array with the unbiased requirements and its security properties in general depend on the prior probability distribution on the inputs s-tuples. Recently, it was shown by Esfahani and Stinson that a combinatorial AONT has perfect security provided that all the inputs s-tuples are equiprobable, and has weak security provided that all the inputs s-tuples are with non-zero probability. This paper aims to explore on the gap between perfect security and weak security for combinatorial (t, s, v)-AONTs. Concretely, we consider the typical scenario that all the s inputs take values independently (but not necessarily identically) and quantify the amount of information H(\mathcalX\mid \mathcalY) about any t inputs \mathcalX that is not revealed by any s−t outputs \mathcalY. In particular, we establish the general lower and upper bounds on H(\mathcalX\mid \mathcalY) for combinatorial AONTs using information-theoretic techniques, and also show that the derived bounds can be attained in certain cases.

Information Theoretic Security - Building occupancy data helps increase energy management systems’ performance, enabling lower energy use while preserving occupant comfort. The focus of this study is employing environmental data (e.g., including but not limited to temperature, humidity, carbon dioxide (CO2), etc.) to infer occupancy information. This will be achieved by exploring the application of information theory metrics with machine learning (ML) approaches to classify occupancy levels for a given dataset. Three datasets and six distinct ML algorithms were used in a comparative study to determine the best strategy for identifying occupancy patterns. It was determined that both k-nearest neighbors (kNN) and random forest (RF) identify occupancy labels with the highest overall level of accuracy, reaching 97.99\% and 98.56\%, respectively.

Information Theoretic Security - The problem of information security of critical information infrastructure objects in the conditions of openness is formulated. The concept of information infrastructure openness is analyzed. An approach to assessing the openness of an information system is presented. A set-theoretic model of information resources openness was developed. The formulation of the control problem over the degree of openness with restrictions on risk was carried out. An example of solving the problem of finding the coefficient of openness is presented.

Industrial Control Systems - The power industrial control system is an important part of the national critical Information infrastructure. Its security is related to the national strategic security and has become an important target of cyber attacks. In order to solve the problem that the vulnerability detection technology of power industrial control system cannot meet the requirement of non-destructive, this paper proposes an industrial control vulnerability analysis technology combined with dynamic and static analysis technology. On this basis, an industrial control non-destructive vulnerability detection system is designed, and a simulation verification platform is built to verify the effectiveness of the industrial control non-destructive vulnerability detection system. These provide technical support for the safety protection research of the power industrial control system.

Industrial Control Systems - Machine tool is known as the mother of industry. CNC machine tool is the embodiment of modern automatic control productivity. In the context of the rapid development of the industrial Internet, a large number of equipment and systems are interconnected through the industrial Internet, realizing the flexible adaptation from the supply side to the demand side. As the a typical core system of industrial Internet, CNC system is facing the threat of industrial virus and network attack. The problem of information security is becoming more and more prominent. This paper analyzes the security risks of the existing CNC system from the aspects of terminal security, data security and network security. By comprehensively using the technologies of data encryption, identity authentication, digital signature, access control, secure communication and key management, this paper puts forward a targeted security protection and management scheme, which effectively strengthens the overall security protection ability.

Industrial Control Systems - Currently, risk assessment of industrial control systems is static and performed manually. With the increased convergence of operational technology and information technology, risk assessment has to incorporate a combined safety and security analysis along with their interdependency. This paper investigates the data inputs required for safety and security assessments, also if the collection and utilisation of such data can be automated. A particular focus is put on integrated assessment methods which have the potential for automation. In case the overall process to identify potential hazards and threats and analyze what could happen if they occur can be automated, manual efforts and cost of operation can be reduced, thus also increasing the overall performance of risk assessment.

Industrial Control Systems - With the introduction of the national “carbon peaking and carbon neutrality” strategic goals and the accelerated construction of the new generation of power systems, cloud applications built on advanced IT technologies play an increasingly important role in meeting the needs of digital power business. In view of the characteristics of the current power industrial control system operation support cloud platform with wide coverage, large amount of log data, and low analysis intelligence, this paper proposes a cloud platform network security behavior audit method based on FP-Growth association rule algorithm, aiming at the uniqueness of the operating data of the cloud platform that directly interacts with the isolated system environment of power industrial control system. By using the association rule algorithm to associate and classify user behaviors, our scheme formulates abnormal behavior judgment standards, establishes an automated audit strategy knowledge base, and improves the security audit efficiency of power industrial control system operation support cloud platform. The intelligent level of log data analysis enables effective discovery, traceability and management of internal personnel operational risks.

Industrial Control Systems - The Industrial Internet expands the attack surface of industrial control systems(ICS), bringing cybersecurity threats to industrial controllers located in operation technology(OT) networks. Honeypot technology is an important means to detect network attacks. However, the existing honeypot system cannot simulate business logic and is difficult to resist highly concealed APT attacks. This paper proposes a high-simulation ICS security defense framework based on virtualization technology. The framework utilizes virtualization technology to build twins for protected control systems. The architecture can infer the execution results of control instructions in advance based on actual production data, so as to discover hidden attack behaviors in time. This paper designs and implements a prototype system and demonstrates the effectiveness and potential of this architecture for ICS security.

Industrial Control Systems - With the wide application of Internet technology in the industrial control field, industrial control networks are getting larger and larger, and the industrial data generated by industrial control systems are increasing dramatically, and the performance requirements of the acquisition and storage systems are getting higher and higher. The collection and analysis of industrial equipment work logs and industrial timing data can realize comprehensive management and continuous monitoring of industrial control system work status, as well as intrusion detection and energy efficiency analysis in terms of traffic and data. In the face of increasingly large realtime industrial data, existing log collection systems and timing data gateways, such as packet loss and other phenomena [1], can not be more complete preservation of industrial control network thermal data. The emergence of software-defined networking provides a new solution to realize massive thermal data collection in industrial control networks. This paper proposes a 10-gigabit industrial thermal data acquisition and storage scheme based on software-defined networking, which uses software-defined networking technology to solve the problem of insufficient performance of existing gateways.

With the development of industrial informatization, information security in the power production industry is becoming more and more important. In the power production industry, as the critical information egress of the industrial control system, the information security of the Networked Control System is particularly important. This paper proposes a construction method for an information security platform of Networked Control System, which is used for research, testing and training of Networked Control System information security.

Industrial Control Systems - The new paradigm of industrial development, called Industry 4.0, faces the problems of Cybersecurity, and as it has already manifested itself in Information Systems, focuses on the use of Artificial Intelligence tools. The authors of this article build on their experience with the use of the above mentioned tools to increase the resilience of Information Systems against Cyber threats, approached to the choice of an effective structure of Cyber-protection of Industrial Systems, primarily analyzing the objective differences between them and Information Systems. A number of analyzes show increased resilience of the decentralized architecture in the management of large-scale industrial processes to the centralized management architecture. These considerations provide sufficient grounds for the team of the project to give preference to the decentralized structure with flock behavior for further research and experiments. The challenges are to determine the indicators which serve to assess and compare the impacts on the controlled elements.

Industrial Control Systems - The industrial Internet platform has been applied to various fields of industrial production, effectively improving the data flow of all elements in the production process, improving production efficiency, reducing production costs, and ensuring the market competitiveness of enterprises. The premise of the effective application of the industrial Internet platform is the interconnection of industrial equipment. In the industrial Internet platform, industrial robot is a very common industrial control device. These industrial robots are connected to the control network of the industrial Internet platform, which will have obvious advantages in production efficiency and equipment maintenance, but at the same time will cause more serious network security problems. The industrial robot system based on the industrial Internet platform not only increases the possibility of industrial robots being attacked, but also aggravates the loss and harm caused by industrial robots being attacked. At the same time, this paper illustrates the effects and scenarios of industrial robot attacks based on industrial interconnection platforms from four different scenarios of industrial robots being attacked. Availability and integrity are related to the security of the environment.

Industrial Control Systems - The fourth industrial revolution has led to the rapid development of industrial control systems. While the large number of industrial system devices connected to the Internet provides convenience for production management, it also exposes industrial control systems to more attack surfaces. Under the influence of multiple attack surfaces, sensitive data leakage has a more serious and time-spanning negative impact on industrial production systems. How to quickly locate the source of information leakage plays a crucial role in reducing the loss from the attack, so there are new requirements for tracing sensitive data in industrial control information systems. In this paper, we propose a digital watermarking traceability scheme for sensitive data in industrial control systems to address the above problems. In this scheme, we enhance the granularity of traceability by classifying sensitive data types of industrial control systems into text, image and video data with differentiated processing, and achieve accurate positioning of data sources by combining technologies such as national secret asymmetric encryption and hash message authentication codes, and mitigate the impact of mainstream watermarking technologies such as obfuscation attacks and copy attacks on sensitive data. It also mitigates the attacks against the watermarking traceability such as obfuscation attacks and copy attacks. At the same time, this scheme designs a data flow watermark monitoring module on the post-node of the data source to monitor the unauthorized sensitive data access behavior caused by other attacks.