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2021-07-27
Bao, Zhida, Zhao, Haojun.  2020.  Evaluation of Adversarial Attacks Based on DL in Communication Networks. 2020 7th International Conference on Dependable Systems and Their Applications (DSA). :251–252.
Deep Neural Networks (DNN) have strong capabilities of memories, feature identifications and automatic analyses, solving various complex problems. However, DNN classifiers have obvious fragility that adding several unnoticeable perturbations to the original examples will lead to the errors in the classifier identification. In the field of communications, the adversarial examples will greatly reduce the accuracy of the signal identification, causing great information security risks. Considering the adversarial examples pose a serious threat to the security of the DNN models, studying their generation mechanisms and testing their attack effects are critical to ensuring the information security of the communication networks. This paper will study the generation of the adversarial examples and the influences of the adversarial examples on the accuracy of the DNN-based communication signal identification. Meanwhile, this paper will study the influences of the adversarial examples under the white-box models and black-box models, and explore the adversarial attack influences of the factors such as perturbation levels and iterative steps. The insights of this study would be helpful for ensuring the security of information networks and designing robust DNN communication networks.
2021-06-30
Asyaev, G. D., Antyasov, I. S..  2020.  Model for Providing Information Security of APCS Based on Predictive Maintenance Technology. 2020 Global Smart Industry Conference (GloSIC). :287—290.
In article the basic criteria of quality of work of the automated control system of technological process (APCS) are considered, the analysis of critical moments and level of information safety of APCS is spent. The model of maintenance of information safety of APCS on the basis of technology of predictive maintenance with application of intellectual methods of data processing is offered. The model allows to generate the list of actions at detection of new kinds of the threats connected with destructive influences on object, proceeding from acceptability of predicted consequences of work of APCS. In article with use of the system analysis the complex model of the technical object of automation is developed, allowing to estimate consequences from realization of threats of information safety at various system levels of APCS.
Maalla, Allam.  2020.  Research on Data Transmission Security Architecture Design and Process. 2020 IEEE International Conference on Information Technology,Big Data and Artificial Intelligence (ICIBA). 1:1195—1199.
With the development of business, management companies are currently facing a series of problems and challenges in terms of resource allocation and task management. In terms of the technical route, this research will use cloud services to implement the public honesty system, and carry out secondary development and interface development on this basis, the architecture design and the formulation of the process are realized for various types, relying on the support of the knowledge base and case library, through the system intelligent configuration corresponding work instructions, safety work instructions, case references and other reference information to the existing work plan to provide managers Reference; managers can configure and adjust the work content by themselves through specific requirements to efficiently and flexibly adapt to the work content.
2021-06-28
Sarabia-Lopez, Jaime, Nuñez-Ramirez, Diana, Mata-Mendoza, David, Fragoso-Navarro, Eduardo, Cedillo-Hernandez, Manuel, Nakano-Miyatake, Mariko.  2020.  Visible-Imperceptible Image Watermarking based on Reversible Data Hiding with Contrast Enhancement. 2020 International Conference on Mechatronics, Electronics and Automotive Engineering (ICMEAE). :29–34.
Currently the use and production of multimedia data such as digital images have increased due to its wide use within smart devices and open networks. Although this has some advantages, it has generated several issues related to the infraction of intellectual property. Digital image watermarking is a promissory solution to solve these issues. Considering the need to develop mechanisms to improve the information security as well as protect the intellectual property of the digital images, in this paper we propose a novel visible-imperceptible watermarking based on reversible data hiding with contrast enhancement. In this way, a watermark logo is embedded in the spatial domain of the original image imperceptibly, so that the logo is revealed applying reversible data hiding increasing the contrast of the watermarked image and the same time concealing a great amount of data bits, which are extracted and the watermarked image restored to its original conditions using the reversible functionality. Experimental results show the effectiveness of the proposed algorithm. A performance comparison with the current state-of-the-art is provided.
2021-06-01
Sharma, Rajesh Kumar, Pippal, Ravi Singh.  2020.  Malicious Attack and Intrusion Prevention in IoT Network using Blockchain based Security Analysis. 2020 12th International Conference on Computational Intelligence and Communication Networks (CICN). :380–385.
The Internet of Things (IoT) as a demanding technology require the best features of information security for effective development of the IoT based smart city and technological activity. There are huge number of recent security threats searching for some loopholes which are ready to exploit any network. Against the back-drop of recent rapidly growing technological advancement of IoT, security-threats have become a critical challenge which demand responsive and continuous action. As privacy and security exhibit an ever-present flourishing issue, so loopholes detection and analysis are indispensable process in the network. This paper presents Block chain based security analysis of data generated from IoT devices to prevent malicious attacks and intrusion in the IoT network.
2021-05-25
Zanin, M., Menasalvas, E., González, A. Rodriguez, Smrz, P..  2020.  An Analytics Toolbox for Cyber-Physical Systems Data Analysis: Requirements and Challenges. 2020 43rd International Convention on Information, Communication and Electronic Technology (MIPRO). :271–276.
The fast improvement in telecommunication technologies that has characterised the last decade is enabling a revolution centred on Cyber-Physical Systems (CPSs). Elements inside cities, from vehicles to cars, can now be connected and share data, describing both our environment and our behaviours. These data can also be used in an active way, by becoming the tenet of innovative services and products, i.e. of Cyber-Physical Products (CPPs). Still, having data is not tantamount to having knowledge, and an important overlooked topic is how should them be analysed. In this contribution we tackle the issue of the development of an analytics toolbox for processing CPS data. Specifically, we review and quantify the main requirements that should be fulfilled, both functional (e.g. flexibility or dependability) and technical (e.g. scalability, response time, etc.). We further propose an initial set of analysis that should in it be included. We finally review some challenges and open issues, including how security and privacy could be tackled by emerging new technologies.
Ajorlou, Amir, Abbasfar, Aliazam.  2020.  An Optimized Structure of State Channel Network to Improve Scalability of Blockchain Algorithms. 2020 17th International ISC Conference on Information Security and Cryptology (ISCISC). :73—76.
Nowadays, blockchain is very common and widely used in various fields. The properties of blockchain-based algorithms such as being decentralized and uncontrolled by institutions and governments, are the main reasons that has attracted many applications. The security and the scalability limitations are the main challenges for the development of these systems. Using second layer network is one of the various methods proposed to improve the scalability of these systems. This network can increase the total number of transactions per second by creating extra channels between the nodes that operate in a different layer not obligated to be on consensus ledger. In this paper, the optimal structure for the second layer network has been presented. In the proposed structure we try to distribute the parameters of the second layer network as symmetrically as possible. To prove the optimality of this structure we first introduce the maximum scalability bound, and then calculate it for the proposed structure. This paper will show how the second layer method can improve the scalability without any information about the rate of transactions between nodes.
ÇELİK, Mahmut, ALKAN, Mustafa, ALKAN, Abdulkerim Oğuzhan.  2020.  Protection of Personal Data Transmitted via Web Service Against Software Developers. 2020 International Conference on Information Security and Cryptology (ISCTURKEY). :88—92.
Through the widespread use of information technologies, institutions have started to offer most of their services electronically. The best example of this is e-government. Since institutions provide their services to the electronic environment, the quality of the services they provide increases and their access to services becomes easier. Since personal information can be verified with inter-agency information sharing systems, wrong or unfair transactions can be prevented. Since information sharing between institutions is generally done through web services, protection of personal data transmitted via web services is of great importance. There are comprehensive national and international regulations on the protection of personal data. According to these regulations, protection of personal data shared between institutions is a legal obligation; protection of personal data is an issue that needs to be handled comprehensively. This study, protection of personal data shared between institutions through web services against software developers is discussed. With a proposed application, it is aimed to take a new security measure for the protection of personal data. The proposed application consists of a web interface prepared using React and Java programming languages and rest services that provide anonymization of personal data.
AKCENGİZ, Ziya, Aslan, Melis, Karabayır, Özgür, Doğanaksoy, Ali, Uğuz, Muhiddin, Sulak, Fatih.  2020.  Statistical Randomness Tests of Long Sequences by Dynamic Partitioning. 2020 International Conference on Information Security and Cryptology (ISCTURKEY). :68—74.
Random numbers have a wide usage in the area of cryptography. In practice, pseudo random number generators are used in place of true random number generators, as regeneration of them may be required. Therefore because of generation methods of pseudo random number sequences, statistical randomness tests have a vital importance. In this paper, a randomness test suite is specified for long binary sequences. In literature, there are many randomness tests and test suites. However, in most of them, to apply randomness test, long sequences are partitioned into a certain fixed length and the collection of short sequences obtained is evaluated instead. In this paper, instead of partitioning a long sequence into fixed length subsequences, a concept of dynamic partitioning is introduced in accordance with the random variable in consideration. Then statistical methods are applied. The suggested suite, containing four statistical tests: Collision Tests, Weight Test, Linear Complexity Test and Index Coincidence Test, all of them work with the idea of dynamic partitioning. Besides the adaptation of this approach to randomness tests, the index coincidence test is another contribution of this work. The distribution function and the application of all tests are given in the paper.
Sabillon, Regner, Serra-Ruiz, Jordi, Cavaller, Victor, Cano, Jeimy.  2017.  A Comprehensive Cybersecurity Audit Model to Improve Cybersecurity Assurance: The CyberSecurity Audit Model (CSAM). 2017 International Conference on Information Systems and Computer Science (INCISCOS). :253—259.

Nowadays, private corporations and public institutions are dealing with constant and sophisticated cyberthreats and cyberattacks. As a general warning, organizations must build and develop a cybersecurity culture and awareness in order to defend against cybercriminals. Information Technology (IT) and Information Security (InfoSec) audits that were efficient in the past, are trying to converge into cybersecurity audits to address cyber threats, cyber risks and cyberattacks that evolve in an aggressive cyber landscape. However, the increase in number and complexity of cyberattacks and the convoluted cyberthreat landscape is challenging the running cybersecurity audit models and putting in evidence the critical need for a new cybersecurity audit model. This article reviews the best practices and methodologies of global leaders in the cybersecurity assurance and audit arena. By means of the analysis of the current approaches and theoretical background, their real scope, strengths and weaknesses are highlighted looking forward a most efficient and cohesive synthesis. As a resut, this article presents an original and comprehensive cybersecurity audit model as a proposal to be utilized for conducting cybersecurity audits in organizations and Nation States. The CyberSecurity Audit Model (CSAM) evaluates and validates audit, preventive, forensic and detective controls for all organizational functional areas. CSAM has been tested, implemented and validated along with the Cybersecurity Awareness TRAining Model (CATRAM) in a Canadian higher education institution. A research case study is being conducted to validate both models and the findings will be published accordingly.

2021-05-18
Zhang, Chi, Chen, Jinfu, Cai, Saihua, Liu, Bo, Wu, Yiming, Geng, Ye.  2020.  iTES: Integrated Testing and Evaluation System for Software Vulnerability Detection Methods. 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom). :1455–1460.
To find software vulnerabilities using software vulnerability detection technology is an important way to ensure the system security. Existing software vulnerability detection methods have some limitations as they can only play a certain role in some specific situations. To accurately analyze and evaluate the existing vulnerability detection methods, an integrated testing and evaluation system (iTES) is designed and implemented in this paper. The main functions of the iTES are:(1) Vulnerability cases with source codes covering common vulnerability types are collected automatically to form a vulnerability cases library; (2) Fourteen methods including static and dynamic vulnerability detection are evaluated in iTES, involving the Windows and Linux platforms; (3) Furthermore, a set of evaluation metrics is designed, including accuracy, false positive rate, utilization efficiency, time cost and resource cost. The final evaluation and test results of iTES have a good guiding significance for the selection of appropriate software vulnerability detection methods or tools according to the actual situation in practice.
2021-05-13
Susukailo, Vitalii, Opirskyy, Ivan, Vasylyshyn, Sviatoslav.  2020.  Analysis of the attack vectors used by threat actors during the pandemic. 2020 IEEE 15th International Conference on Computer Sciences and Information Technologies (CSIT). 2:261—264.

This article describes attacks methods, vectors and technics used by threat actors during pandemic situations in the world. Identifies common targets of threat actors and cyber-attack tactics. The article analyzes cybersecurity challenges and specifies possible solutions and improvements in cybersecurity. Defines cybersecurity controls, which should be taken against analyzed attack vectors.

Hu, Xiaoyi, Wang, Ke.  2020.  Bank Financial Innovation and Computer Information Security Management Based on Artificial Intelligence. 2020 2nd International Conference on Machine Learning, Big Data and Business Intelligence (MLBDBI). :572—575.
In recent years, with the continuous development of various new Internet technologies, big data, cloud computing and other technologies have been widely used in work and life. The further improvement of data scale and computing capability has promoted the breakthrough development of artificial intelligence technology. The generalization and classification of financial science and technology not only have a certain impact on the traditional financial business, but also put forward higher requirements for commercial banks to operate financial science and technology business. Artificial intelligence brings fresh experience to financial services and is conducive to increasing customer stickiness. Artificial intelligence technology helps the standardization, modeling and intelligence of banking business, and helps credit decision-making, risk early warning and supervision. This paper first discusses the influence of artificial intelligence on financial innovation, and on this basis puts forward measures for the innovation and development of bank financial science and technology. Finally, it discusses the problem of computer information security management in bank financial innovation in the era of artificial intelligence.
Nakhushev, Rakhim S., Sukhanova, Natalia V..  2020.  Application of the Neural Networks for Cryptographic Information Security. 2020 International Conference Quality Management, Transport and Information Security, Information Technologies (IT QM IS). :421–423.
The object of research is information security. The tools used for research are artificial neural networks. The goal is to increase the cryptography security. The problems are: the big volume of information, the expenses for neural networks design and training. It is offered to use the neural network for the cryptographic transformation of information.
Zhang, Yunxiang, Rao, Zhuyi.  2020.  Research on Information Security Evaluation Based on Artificial Neural Network. 2020 3rd International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE). :424–428.

In order to improve the information security ability of the network information platform, the information security evaluation method is proposed based on artificial neural network. Based on the comprehensive analysis of the security events in the construction of the network information platform, the risk assessment model of the network information platform is constructed based on the artificial neural network theory. The weight calculation algorithm of artificial neural network and the minimum artificial neural network pruning algorithm are also given, which can realize the quantitative evaluation of network information security. The fuzzy neural network weighted control method is used to control the information security, and the non-recursive traversal method is adopted to realize the adaptive training of information security assessment process. The adaptive learning of the artificial neural network is carried out according to the conditions, and the ability of information encryption and transmission is improved. The information security assessment is realized. The simulation results show that the method is accurate and ensures the information security.

2021-05-03
Kolomoitcev, V. S..  2020.  Effectiveness of Options for Designing a Pattern of Secure Access ‘Connecting Node’. 2020 Wave Electronics and its Application in Information and Telecommunication Systems (WECONF). :1–5.
The purpose of the work was to study the fault- tolerant pattern of secure access of computer system nodes to external network resources - the pattern of secure access `Connecting node'. The pattern of secure access `Connecting node' includes a group/cluster (or several groups) of routers, a computing node that includes hardware and software for information protection and communication channels that connect it to the end nodes of the computing system and the external network (network resources that are not controlled by the information protection system). The efficiency assessment and comparative analysis of options for designing a pattern of secure access `Connecting node' according to various efficiency criteria were carried out. In this work, an assessment of the individual and comprehensive efficiency index was carried out. It was assumed that the system is recoverable. The effectiveness of using some options of designing a pattern of secure access in terms of the operational availability factor, as well as a group of parameters - the operational availability factor, service delays of information protection system and the grade of information protection.
2021-04-29
Belim, S. V., Belim, S. Y..  2020.  The Security Policies Optimization Problem for Composite Information Systems. 2020 International Multi-Conference on Industrial Engineering and Modern Technologies (FarEastCon). :1—4.

The problem of optimizing the security policy for the composite information system is formulated. Subject-object model for information system is used. Combining different types of security policies is formalized. The target function for the optimization task is recorded. The optimization problem for combining two discretionary security policies is solved. The case of combining two mandatory security policies is studied. The main problems of optimization the composite security policy are formulated. +50 CHMBOJIOB‼!

2021-04-27
Damis, H. A., Shehada, D., Fachkha, C., Gawanmeh, A., Al-Karaki, J. N..  2020.  A Microservices Architecture for ADS-B Data Security Using Blockchain. 2020 3rd International Conference on Signal Processing and Information Security (ICSPIS). :1—4.

The use of Automatic Dependent Surveillance - Broadcast (ADS-B) for aircraft tracking and flight management operations is widely used today. However, ADS-B is prone to several cyber-security threats due to the lack of data authentication and encryption. Recently, Blockchain has emerged as new paradigm that can provide promising solutions in decentralized systems. Furthermore, software containers and Microservices facilitate the scaling of Blockchain implementations within cloud computing environment. When fused together, these technologies could help improve Air Traffic Control (ATC) processing of ADS-B data. In this paper, a Blockchain implementation within a Microservices framework for ADS-B data verification is proposed. The aim of this work is to enable data feeds coming from third-party receivers to be processed and correlated with that of the ATC ground station receivers. The proposed framework could mitigate ADS- B security issues of message spoofing and anomalous traffic data. and hence minimize the cost of ATC infrastructure by throughout third-party support.

Putz, B., Pernul, G..  2020.  Detecting Blockchain Security Threats. 2020 IEEE International Conference on Blockchain (Blockchain). :313—320.
In many organizations, permissioned blockchain networks are currently transitioning from a proof-of-concept stage to production use. A crucial part of this transition is ensuring awareness of potential threats to network operations. Due to the plethora of software components involved in distributed ledgers, threats may be difficult or impossible to detect without a structured monitoring approach. To this end, we conduct a survey of attacks on permissioned blockchains and develop a set of threat indicators. To gather these indicators, a data processing pipeline is proposed to aggregate log information from relevant blockchain components, enriched with data from external sources. To evaluate the feasibility of monitoring current blockchain frameworks, we determine relevant data sources in Hyperledger Fabric. Our results show that the required data is mostly available, but also highlight significant improvement potential with regard to threat intelligence, chaincode scanners and built-in metrics.
Korać, D., Damjanović, B., Simić, D..  2020.  Information Security in M-learning Systems: Challenges and Threats of Using Cookies. 2020 19th International Symposium INFOTEH-JAHORINA (INFOTEH). :1—6.
The trend of rapid development of mobile technologies has highlighted new challenges and threats regarding the information security by the using cookies in mobile learning (m-learning) systems. In order to overcome these challenges and threats, this paper has identified two main objectives. First, to give a review of most common types to cookies and second, to consider the challenges and threats regarding cookies with aspects that are directly related to issues of security and privacy. With these objectives is possible to bridge security gaps in m-learning systems. Moreover, the identified potential challenges and threats are discussed with the given proposals of pragmatic solutions for their mitigating or reducing. The findings of this research may help students to rise security awareness and security behavior in m-learning systems, and to better understand on-going security challenges and threats in m-learning systems.
Yermalovich, P., Mejri, M..  2020.  Information security risk assessment based on decomposition probability via Bayesian Network. 2020 International Symposium on Networks, Computers and Communications (ISNCC). :1–8.
Well-known approaches to risk analysis suggest considering the level of an information system risk as one frame in a film. This means that we only can perform a risk assessment for the current point in time. This article explores the idea of risk assessment in a future period, as a prediction of what we will see in the film later. In other words, the article presents an approach to predicting a potential future risk and suggests the idea of relying on forecasting the likelihood of an attack on information system assets. To establish the risk level at a selected time interval in the future, one has to perform a mathematical decomposition. To do this, we need to select the required information system parameters for the predictions and their statistical data for risk assessment. This method can be used to ensure more detailed budget planning when ensuring the protection of the information system. It can be also applied in case of a change of the information protection configuration to satisfy the accepted level of risk associated with projected threats and vulnerabilities.
2021-04-09
Mir, N., Khan, M. A. U..  2020.  Copyright Protection for Online Text Information : Using Watermarking and Cryptography. 2020 3rd International Conference on Computer Applications Information Security (ICCAIS). :1—4.
Information and security are interdependent elements. Information security has evolved to be a matter of global interest and to achieve this; it requires tools, policies and assurance of technologies against any relevant security risks. Internet influx while providing a flexible means of sharing the online information economically has rapidly attracted countless writers. Text being an important constituent of online information sharing, creates a huge demand of intellectual copyright protection of text and web itself. Various visible watermarking techniques have been studied for text documents but few for web-based text. In this paper, web page watermarking and cryptography for online content copyrights protection is proposed utilizing the semantic and syntactic rules using HTML (Hypertext Markup Language) and is tested for English and Arabic languages.
Lyshevski, S. E., Aved, A., Morrone, P..  2020.  Information-Centric Cyberattack Analysis and Spatiotemporal Networks Applied to Cyber-Physical Systems. 2020 IEEE Microwave Theory and Techniques in Wireless Communications (MTTW). 1:172—177.

Cyber-physical systems (CPS) depend on cybersecurity to ensure functionality, data quality, cyberattack resilience, etc. There are known and unknown cyber threats and attacks that pose significant risks. Information assurance and information security are critical. Many systems are vulnerable to intelligence exploitation and cyberattacks. By investigating cybersecurity risks and formal representation of CPS using spatiotemporal dynamic graphs and networks, this paper investigates topics and solutions aimed to examine and empower: (1) Cybersecurity capabilities; (2) Information assurance and system vulnerabilities; (3) Detection of cyber threat and attacks; (4) Situational awareness; etc. We introduce statistically-characterized dynamic graphs, novel entropy-centric algorithms and calculi which promise to ensure near-real-time capabilities.

2021-04-08
Guerrini, F., Dalai, M., Leonardi, R..  2020.  Minimal Information Exchange for Secure Image Hash-Based Geometric Transformations Estimation. IEEE Transactions on Information Forensics and Security. 15:3482—3496.
Signal processing applications dealing with secure transmission are enjoying increasing attention lately. This paper provides some theoretical insights as well as a practical solution for transmitting a hash of an image to a central server to be compared with a reference image. The proposed solution employs a rigid image registration technique viewed in a distributed source coding perspective. In essence, it embodies a phase encoding framework to let the decoder estimate the transformation parameters using a very modest amount of information about the original image. The problem is first cast in an ideal setting and then it is solved in a realistic scenario, giving more prominence to low computational complexity in both the transmitter and receiver, minimal hash size, and hash security. Satisfactory experimental results are reported on a standard images set.
Zhang, H., Ma, J., Wang, Y., Pei, Q..  2009.  An Active Defense Model and Framework of Insider Threats Detection and Sense. 2009 Fifth International Conference on Information Assurance and Security. 1:258—261.
Insider attacks is a well-known problem acknowledged as a threat as early as 1980s. The threat is attributed to legitimate users who take advantage of familiarity with the computational environment and abuse their privileges, can easily cause significant damage or losses. In this paper, we present an active defense model and framework of insider threat detection and sense. Firstly, we describe the hierarchical framework which deal with insider threat from several aspects, and subsequently, show a hierarchy-mapping based insider threats model, the kernel of the threats detection, sense and prediction. The experiments show that the model and framework could sense the insider threat in real-time effectively.