Searchable encryption allows users to perform search operations on encrypted data before decrypting it first. Secret sharing is one of the most important cryptographic primitives used to design an information theoretic scheme. Nowadays cryptosys-tem designers are providing a facility to adjust the security parameters in real time to circumvent AI-enabled cyber security threats. For long term security of data which is used by various applications, proactive secret sharing allows the shares of the original secret to be dynamically adjusted during a specific interval of time. In proactive secret sharing, the updation of shares at regular intervals of time is done by the servers (participants) and not by the dealer. In this paper, we propose a novel proactive secret sharing scheme where the shares stored at servers are updated using preshared pairwise keys between servers at regular intervals of time. The direct search of words over sentences using the conjunctive search function without the generation of any index is possible using the underlying querying method.

This article proposes a technique that establishes the procedure for evaluating the level of efficiency of the information security department (an employee performing information security functions). The technique uses performance evaluation criteria based on the apparatus of fuzzy logic, the composition of fuzzy relations. The technique describes the procedure for evaluating the effectiveness of the information security department (information security officer) during audits in the area of "Organization and state of work on information protection", self-assessment of the effectiveness of work. The method of assessing the level of efficiency consists in presenting with the help of a set of measurements (both at the quantitative and qualitative level) the features collected to build a classification of the effectiveness of the information security department (information security officer). Based on a set of measurements of signs, the decision-maker must determine (classify) the effectiveness of work using the criteria for assessing the quality of their work. In the future, the methodology can be expanded for additional purposes of predicting the level of security of informatization objects.

Questions of video information resource security assessment are considered in case of the video conferencing organization in systems of public administration. Is shown that for an assessment of information security it is necessary to make the analysis of potential security risks, to construct model of threats and to execute an assessment for specific conditions of functioning of a video conferencing. The most significant security risks are defined.

In response to the advent of software defined world, this Fast Abstract introduces a new notion, information gravitation, with an attempt to unify and expand two related ones, information mass (related to the supposed fifth force) and data gravitation. This is motivated by the following question: is there a new kind of (gravitational) force between any two distinct pieces of information conveying messages. A possibly affirmative answer to this question of information gravitation, which is supposed to explore the theoretically and/or experimentally justified interplay between information and gravitation, might make significant sense for the software defined world being augmented with artificial intelligence and virtual reality in the age of information. Information induces gravitation. Information gravitation should be related to Newton s law of universal gravitation and Einstein s general theory of relativity, and even to gravitational waves and the unified theory of everything.

Chaotic cryptography is structurally related to the concepts of confusion and diffusion in traditional cryptography theory. Chaotic cryptography is formed by the inevitable connection between chaos theory and pure cryptography. In order to solve the shortcomings of the existing research on information encryption security system, this paper discusses the realization technology of information security, the design principles of encryption system and three kinds of chaotic mapping systems, and discusses the selection of development tools and programmable devices. And the information encryption security system based on chaos algorithm is designed and discussed, and the randomness test of three groups of encrypted files is carried out by the proposed algorithm and the AES (Advanced Encryption Standard) algorithm. Experimental data show that the uniformity of P-value value of chaos algorithm is 0.714 on average. Therefore, it is verified that the information encryption security system using chaos algorithm has high security.

The role of information security in network accounting is very important, but there is a problem of inaccurate outcome evaluation. The one-way hash encryption algorithm cannot solve the information security problem in network accounting, and the evaluation is unreasonable. Therefore, this paper proposes an AES algorithm for network accounting information security analysis. First, the business operation theory is used to integrate the data, and the indicators are divided according to the information security requirements to reduce network accounting information s security in the interfering factor. Then, the business operation theory is used to form a network accounting scheme and synthesize the AES algorithm analysis results. MBAZ shows that under certain evaluation criteria, the AES algorithm is safe for the accounting information of network accounting the accuracy and time are better than the one-way hash encryption algorithm.

To date, there are a lot of research works related to the application of game theory to model the interaction between a cyber attacker and defender. At the same time there are some challenges that prevent development and practical application of such approaches. One of the challenges is that at each point in time, the cyber attacker and the defender do not have accurate information about the adversary’s strategy, which results in an uncertainty in choosing their own strategy. The paper considers the application of hypergame theory to process this uncertainty. The authors use the attack graph is used to determine the possible strategies of the cyber attacker, while the graph of dependencies between the assets of the information system is used to determine the gain when applying a particular strategy. Thus, the result of the research is a proposed approach to security analysis and decision support for security incidents response based on the hypergame theory.

With the help of a well-thought-out information security threat model, you can develop a protection plan that will be based on current threats. The task of creating the most effective system for assessing the state of asset protection of an enterprise is one of the main goals of modeling. They imply the universality of information security concepts. You should use various methodologies of this process with the necessary perspective and sufficient level of detail to describe the threat models. An approach using all possible threat implementations is constructed in the form of trees or attack graphs (GAT) with verification of their properties. The set of threats, connections and their parameters are determined by asset owners and information security specialists. The elimination of shortcomings in the security model with complete overlap became possible thanks to the use of such a data set and the described structure. In this article, we describe the creation of a software application for automating and formalizing the process of assessing the information security of information system assets and localization of information system security bottlenecks. A distinctive feature of the application is the use of the threat database of the FSTEC of Russia to simulate an attack tree. FSTEC of Russia is the state regulator in the field of information security. The developed software application saves time by simplifying the process of assessing the security of information systems, and also makes the process of threat modeling visual.

Information security construction is a social issue, and the most urgent task is to do an excellent job in information risk assessment. The bayesian neural network currently plays a vital role in enterprise information security risk assessment, which overcomes the subjective defects of traditional assessment results and operates efficiently. The risk quantification method based on fuzzy theory and Bayesian regularization BP neural network mainly uses fuzzy theory to process the original data and uses the processed data as the input value of the neural network, which can effectively reduce the ambiguity of language description. At the same time, special neural network training is carried out for the confusion that the neural network is easy to fall into the optimal local problem. Finally, the risk is verified and quantified through experimental simulation. This paper mainly discusses the problem of enterprise information security risk assessment based on a Bayesian neural network, hoping to provide strong technical support for enterprises and organizations to carry out risk rectification plans. Therefore, the above method provides a new information security risk assessment idea.

In today s society, with the continuous development of artificial intelligence, artificial intelligence technology plays an increasingly important role in social and economic development, and hass become the fastest growing, most widely used and most influential high-tech in the world today one. However, at the same time, information technology has also brought threats to network security to the entire network world, which makes information systems also face huge and severe challenges, which will affect the stability and development of society to a certain extent. Therefore, comprehensive analysis and research on information system security is a very necessary and urgent task. Through the security assessment of the information system, we can discover the key hidden dangers and loopholes that are hidden in the information source or potentially threaten user data and confidential files, so as to effectively prevent these risks from occurring and provide effective solutions; at the same time To a certain extent, prevent virus invasion, malicious program attacks and network hackers intrusive behaviors. This article adopts the experimental analysis method to explore how to apply the most practical, advanced and efficient artificial intelligence theory to the information system security assessment management, so as to further realize the optimal design of the information system security assessment management system, which will protect our country the information security has very important meaning and practical value. According to the research results, the function of the experimental test system is complete and available, and the security is good, which can meet the requirements of multi-user operation for security evaluation of the information system.

As technology has progressed, people have begun to perform various daily tasks by using different online applications and services, which has led to a large number of incidents of identity theft. These unpleasant events incur expensive costs for individuals, companies, and authorities, and as a result, identity theft concerns them greatly. Although scholars of information security have devoted their efforts to developing technology to prevent identity theft, it is not clear what factors influence an individual’s security protection motivation. Few empirical and behavioral studies on this topic have been conducted. To fill this gap, this study extends the protection motivation theory with anxiety, elucidating the influences of a future negative event (identity theft) on an individual’s current emotion, which in turn determines protection motivation. This study proposes a research model that explores the influences of threat appraisal (perceived severity and perceived susceptibility) and coping appraisal (response efficacy and self-efficacy) on anxiety, which affects protection motivation. The results in this study provide a more holistic comprehension of identity theft and protection motivation, and can be referred to when developing efficient security guidance and practices.

In a one-way secret key agreement (OW-SKA) protocol in source model, Alice and Bob have private samples of two correlated variables X and Y that are partially leaked to Eve through the variable Z, and use a single message from Alice to Bob to obtain a shared secret key. We propose an efficient secure OW-SKA when the sent message over the public channel can be tampered with by an active adversary. Our construction uses a specially designed hash function that is used for reconciliation, as well as detection of tampering. In detection of tampering the function is a Message Authentication Code (MAC) that maintains its security when the key is partially leaked. We prove the secrecy of the established key and robustness of the protocol, and discuss our results.

In wireless security, cognitive adversaries are known to inject jamming energy on the victim’s frequency band and monitor the same band for countermeasures thereby trapping the victim. Under the class of cognitive adversaries, we propose a new threat model wherein the adversary, upon executing the jamming attack, measures the long-term statistic of Kullback-Leibler Divergence (KLD) between its observations over each of the network frequencies before and after the jamming attack. To mitigate this adversary, we propose a new cooperative strategy wherein the victim takes the assistance for a helper node in the network to reliably communicate its message to the destination. The underlying idea is to appropriately split their energy and time resources such that their messages are reliably communicated without disturbing the statistical distribution of the samples in the network. We present rigorous analyses on the reliability and the covertness metrics at the destination and the adversary, respectively, and then synthesize tractable algorithms to obtain near-optimal division of resources between the victim and the helper. Finally, we show that the obtained near-optimal division of energy facilitates in deceiving the adversary with a KLD estimator.

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.

Intrusion Detection Systems (IDSs) are crucial security mechanisms widely deployed for critical network protection. However, conventional IDSs become incompetent due to the rapid growth in network size and the sophistication of large scale attacks. To mitigate this problem, Collaborative IDSs (CIDSs) have been proposed in literature. In CIDSs, a number of IDSs exchange their intrusion alerts and other relevant data so as to achieve better intrusion detection performance. Nevertheless, the required information exchange may result in privacy leakage, especially when these IDSs belong to different self-interested organizations. In order to obtain a quantitative understanding of the fundamental tradeoff between the intrusion detection accuracy and the organizations' privacy, a repeated two-layer single-leader multi-follower game is proposed in this work. Based on our game-theoretic analysis, we are able to derive the expected behaviors of both the attacker and the IDSs and obtain the utility-privacy tradeoff curve. In addition, the existence of Nash equilibrium (NE) is proved and an asynchronous dynamic update algorithm is proposed to compute the optimal collaboration strategies of IDSs. Finally, simulation results are shown to validate the analysis.