Information Security Techniques Research Articles

A robust audio steganography technique based on image encryption using different chaotic maps

The development of innovative methods for concealing critical data in multimedia files has exploded in information security in recent years. Cryptography and steganography cannot be used alone to protect data; rather, they can be combined and used in a single system. Audio steganography is among the most important information security techniques. It involves the concealment of information within audio signals to achieve covert communication. This paper introduces a comprehensive technique that integrates chaos Henon, Baker, and Arnold maps for image encryption with audio steganography to create a robust and secure audio steganography technique. First, the target image is encrypted using chaotic maps. Then, it is embeded within the high frequencies of the cover audio signal based on the Inverse Short Time Fourier Transform (ISTFT) to be transmitted to the destination through the channel. By integrating both encryption and concealment techniques, the cover audio signal quality can be preserved. Moreover, the hidden image security and robustness are improved, making the technique resistant to many types of attacks. The simulation results confirm that the suggested technique is robust in the presence of attacks. It achieves a distinct perceptual quality with an appreciated peak signal-to-noise ratio (PSNR) of 91.2 dB and a Mean Square Error (MSE) of 7.5 × 10–10. The randomness of the resulting encrypted image has successfully passed the National Institute of Standards and Technology (NIST) statistical test suite.

Disguising Text Using Caesar Cipher, Reverse Cipher and Least Significant Bit (LSB) Algorithms in Video

In communication, there is a process of transferring information from the sender to the recipient. The information sent must be the same as the information received. If there are differences, it means that there has been a data change process carried out by irresponsible parties. One technique for changing the content of information is man in the middle. The data changer will receive information from the sender, then change it and forward it to the recipient, so that the changed information appears to have come from the sender.To protect information, this can be done by utilizing the science of cryptography and steganography which aims to protect information by changing it to another form or by inserting the information into other media. In this research, to protect information the Caesar Cipher Algorithm is used, this algorithm will change the letters in plaintext to another letter (ciphertext) by using an alphabetical shift according to the number in the form of the key used, namely > 1 and < 26, then the Reverse Cipher algorithm is carried out, namely changing the position of the letters of the plaintext from the first order to the last order and so on. The encrypted information will then be inserted into a video using the Steganography Algorithm, namely Least Significant Bit (LSB). Before being inserted, the video will first be converted into several image frames, then in one frame the information will be inserted. This can be done because the frame is a collection of RGB arrays which have values 0-255 or 0 and 1. So the insertion is done in bit form. Frames containing information will then be converted back into a video.On the receiving side, the video will be converted into a frame, next is the process of retrieving the information that was previously inserted. The information that has been taken is then reversed in order and then shifted using the Caesar chipper algorithm according to the key used by the sender, then the first letter of each word is changed to capital, so that the information sent is the same as that received. The implication of this research is that it is a way to combine cryptography with steganography as an information security technique.

The Effectiveness of Deploying Machine Learning Techniques in Information Security to Detect Nine Attacks: UNSW-NB15 Dataset as a Case Study

The Effectiveness of Deploying Machine Learning Techniques in Information Security to Detect Nine Attacks: UNSW-NB15 Dataset as a Case Study

Evaluating Encryption Algorithm Method Based on Software Encryption Tools for Information Security

Information security is the combination of policies, rules and practices to prevent any unauthorized access or attacks that causes corruption to data, information, and computing services. Information security techniques and programs are built around the core objective to secure data and information by adapting encryption algorithms methods. Encryption algorithm methods impeded in the information security programs or encryption software tools enforce more security by encrypting and decrypting data and information. Encryption algorithm methods are based on algorithms that scramble data and information by converting them into unreadable text. There are various encryption methods used in various encryption software tools. The more encryption algorithm methods used within the encryption software tool, the more security provided on data and information effective data and information security. In this paper, the most used encryption algorithm methods are analyzed and evaluated based on their usage in encryption software tools to determine the most encryption algorithm method that is used ensure more security on data and information.

Hybridization of OFDMand Physical Layer Techniques for Information Security in Wireless System

Due to quest for high data rate, reliable and secure communication, this has motivated both wired and wireless network access service providers to deploy a next-generation network with ability to meet the required need. The use orthogonal frequency division multiplexing(OFDM) enables reliable transmission of various data traffic by optimizing subcarrier, power, and allocation of bits among different users. Traditionally, securing data in wireless system is always at the upper layer of open system interconnection(OSI) Model by using data encryption techniques. However, such techniques may not be acceptable for future decentralized networks due to their high complexity in implementation and computation. In this work, an OFDM IEEE 802.11a wireless system is used and physical layer encryption (PLE) schemes are implemented in securing the information transfer between two legitimate parties. In the simulation, the source data are encrypted by obfuscation with dummy data in between the encrypted data of which 52 subcarriers were considered of which 25 subcarriers are reserved for dummy data and 27 were for data. The simulation was conducted for four different modulation techniques i.e., BPSK, QPSK, 16 QAM, and 64 QAM. The result obtained shown that for all the modulation schemes, the key rate increases with an increase in the reserved subcarrier bits. Also ,the security level increased when substantial percentages of the subcarriers are reserved for dummy data

Upconversion/Downshifting Multimode Luminescence of Lanthanide-doped Nanocrystals for Multidimensional Information Encoding Security.

Information encoding security has always been a research hotspot in the optical field. Although many studies focused on luminescent materials and techniques for information security, the optical information encoding is limited by low information capacity and security. Herein, we present new core-shell-shell (CSS) lanthanide-doped nanocrystals which display multi-stimuli-responsive and multimode emission. In the designed CSS nanostructure, the Stokes and anti-Stokes processes can be both achieved in the same nanocrystals under the excitation of 1532, 980, and 254 nm via self-excited Er3+ and Ce3+ -sensitized mechanisms. Subsequently, a group of unique multimode emission CSS nanocrystals were designed as optical modules and successfully utilized in multidimensional information encoding, which demonstrates high-level information encoding capability and security. This work brings a powerful idea for information encoding security designs based on multimode luminesce materials.

A Study of Z-Transform Based Encryption Algorithm

It has become increasingly important to ensure the protection of information, especially data in transit. Therefore, it is the primary goal of any encryption algorithm to safeguard the protection of information against security attacks. It is equally important to design high-performance solutions with affordable cost of implementation. Encryption algorithms are used to transform plain text to the ciphertext in order to protect privacy, prevent data fraud, and prevent unauthorized access of data in daily transactions. There are multiple types of encryption algorithms, each with its niche tactics to enhance security. For instance, different kinds of algorithms include but are not limited to the following: Blowfish, RSA, AES, DES, Triple DES. This paper contributes an efficient and secure encryption algorithm technique for information security based on Z transformation and XOR function known as the Z Transformation Encryption (ZTE) technique. To elaborate, this technique implements concepts of Z transformation and XOR operations at the source. The reverse process is applied at the receiving end of the transaction wherein the inverse of Z transformation and XOR is applied to reveal the original plain text message. The simulation of the proposed algorithm is conducted using the R language. The results show a promising performance comparing to other symmetric algorithms.

Vision: An empirical framework for examiners to accessing password-protected resources for on-the-scene digital investigations

It is increasingly becoming difficult to acquire meaningful information in the field of digital forensics through the traditional approach owing to advances in information security and anti-forensics techniques. To counteract anonymous services such as data in remote areas without authentication information, data encryption, device locks, and cryptocurrencies, it is important to acquire key information through live forensics at search and seizure sites. Thus, it is necessary to establish a response system that explores and processes credential information on site and extracts meaningful information based on the processed information. To this end, this study proposes a new digital forensics framework for application at search and seizure sites. The proposed framework is designed to allow expansion in the form of additional functions on account of a module type development for the system even when new services and digital devices appear in the future. We then explain its applicability through case studies of actual digital investigations.

METHOD OF CONSTRUCTION MATRIX CARDANO’S GRIDS FOR COMPRESSION OF INFORMATION

Due to the rapid development of computer technology and the information field, issues related to information security are becoming increasingly important. Knowledge of information security tools is required for the effective organization of the process of transmission and storage of classified information. The main means of information protection such as encryption, compression and covert transmission of information are present in the article . Information security techniques, including cryptographic data protection systems, play an important role in today’s information-filled world. The means of cryptographic data protection, in particular encryption using the Cardano’s encryption grid are list and analyze in the article. Existing mechanisms for reliable storage and transmission of information today do not provide adequate protection. The problem of lack of effective means of information protection is explained by rapid and systematic changes in information technology. The article is devoted to the method of constructing Cardano matrix gratings for compression and hidden data transmission. The developed method is based on the integrated use of existing approaches and methods of information protection. In particular, on the classic cipher of the route permutation – Cardano’s encryption grid. Cardano matrix lattice is based on frequency analysis of English text. The algorithm of frequency analysis of the text and its results are presented in the article. As a result of performing operations of matrix cryptographic transformation of numbers – the rules of distribution of symbols on a lattice are received. In the future, the proposed method will build new algorithms for encrypting information by analogy with the encryption lattice. Also, the created algorithmic models are the basis for building a method of compression and covert data transmission. The methods of information protection considered in the article – encryption, compression and covert transmission, allow us to draw the general conclusion that only their integrated use will ensure an adequate level of protection.

Metaheuristics with Machine Learning Enabled Information Security on燙loud Environment

The increasing quantity of sensitive and personal data being gathered by data controllers has raised the security needs in the cloud environment. Cloud computing (CC) is used for storing as well as processing data. Therefore, security becomes important as the CC handles massive quantity of outsourced, and unprotected sensitive data for public access. This study introduces a novel chaotic chimp optimization with machine learning enabled information security (CCOML-IS) technique on cloud environment. The proposed CCOML-IS technique aims to accomplish maximum security in the CC environment by the identification of intrusions or anomalies in the network. The proposed CCOML-IS technique primarily normalizes the networking data by the use of data conversion and min-max normalization. Followed by, the CCOML-IS technique derives a feature selection technique using chaotic chimp optimization algorithm (CCOA). In addition, kernel ridge regression (KRR) classifier is used for the detection of security issues in the network. The design of CCOA technique assists in choosing optimal features and thereby boost the classification performance. A wide set of experimentations were carried out on benchmark datasets and the results are assessed under several measures. The comparison study reported the enhanced outcomes of the CCOML-IS technique over the recent approaches interms of several measures.

Comprehensive DDoS Attack Classification Using Machine Learning Algorithms

The fast development of Internet technologies ignited the growth of techniques for information security that protect data, networks, systems, and applications from various threats. There are many types of threats. The dedicated denial of service attack (DDoS) is one of the most serious and widespread attacks on Internet resources. This attack is intended to paralyze the victim's system and cause the service to fail. This work is devoted to the classification of DDoS attacks in the special network environment called Software-Defined Networking (SDN) using machine learning algorithms. The analyzed dataset included instances of two classes: benign and malicious. As the dataset contained twenty-two features, the feature selection techniques were required for dimensionality reduction. In these experiments, the Information gain, the Chi-square, and the F-test were applied to decrease the number of features to ten. The classes were also not completely balanced, so undersampling, oversampling, and synthetic minority oversampling (SMOTE) techniques were used to balance classes equally. The previous research works observed the classification of DDoS attacks applying various feature selection techniques and one or more machine learning algorithms. Still, they did not pay much attention to classifying the combinations of feature selection and balancing methods with different machine learning algorithms. This work is devoted to the classification of datasets with eight machine learning algorithms: naïve Bayes, logistic regression, support vector machine, k-nearest neighbors, decision tree, random forest, XGBoost, and CatBoost. In the experimental results, the Information gain and F-test feature selection methods achieved better performance with all eight ML algorithms than with the Chi-square technique. Furthermore, the accuracy values of the oversampled and SMOTE datasets were higher than that of the undersampled and imbalanced datasets. Among machine learning algorithms, the accuracy of support vector machine, logistic regression, and naïve Bayes fluctuates between 0.59 and 0.75, while decision tree, random forest, XGBoost, and CatBoost allowed achieving values around 0.99 and 1.00 with all feature selection and class balancing techniques among all the algorithms.

Design of a Cloud-Blockchain-based Secure Internet of Things Architecture

The growing number of Internet of Things (IoT) objects and the operational and security challenges in IoT systems are encouraging researchers to design suitable IoT architecture. Enormous data generated in the IoT environment face several kinds of security and privacy challenges. IoT system generally suffers from several issues like data storage, safety, privacy, integrity, transparency, trust, and single point of failure. IoT environment is emerging with several solutions to resolve these problems. The main objective of this paper is to design a cloud-blockchain-based secure IoT architecture that provides advanced and efficient storage and security solutions to IoT ecosystem. Blockchain technology appears to be a decent choice to resolve such kinds of problems. Blockchain technology uses a hash-based cryptographic technique for information security and integrity. Cloud computing provides advanced storage solutions with several remote services to store, compute and analyze the data. The proposed IoT architecture is based on the integration of cloud and blockchain services, which aim to provide transparent, decentralized, and trustworthy and secure storage solutions. In addition to the standard layers (perception layer, network layer, processing layer, and application layer) the proposed IoT architecture in the present paper includes a service layer, a security layer, and a parallel management and control layer, which focus on the security and management of the entire IoT infrastructure.

Enhanced Security: Implementation of Hybrid Image Steganography Technique using Low-Contrast LSB and AES-CBC Cryptography

Now-a-days, sensitive and confidential information needs to be exchanged over open, public, and not secure networks such as the Internet. For this purpose, some information security techniques combine cryptographic and steganographic algorithms and image processing techniques to exchange information securely. Therefore, this research presents the implementation of an algorithm that combines the AES-CBC cryptographic technique with the LSB steganographic technique, which is statistically enhanced by image processing by looking for low-contrast areas where the encrypted information will be stored. This hybrid algorithm was developed to send a plaintext file hidden in an image in BMP format, so the changes in the image are invisible to the human eye and undetectable in possible steganographic analysis. The implementation was performed using Python and its libraries PyCryptodome for encryption and CV2 for image processing. As a result, it was found that the hybrid algorithm implemented has three layers of security over a plaintext encrypted and hidden in a digital image, which makes it difficult to break the secrecy of the information exchanged in a stego-image file. Additionally, the execution times of the hybrid algorithm were evaluated for different sizes of plaintext and digital image files.

Systematic Literature Review of the Role of Fuzzy Logic in the Development of Cryptographic and Steganographic Techniques

The rapid technological revolution had an impact on a variety of information security techniques. This will be important because information can be confidential to some entities that communicate with each other. Internet in intelligent technology will be a loophole for cryptanalysts to look for information vulnerabilities. Cryptography is a method of securing data and information which is currently still supported by the development of the method. However, the data and information that are secured will still have vulnerabilities in their delivery. The combination of fuzzy logic techniques with cryptographic techniques has been applied to support the improvement of information security. This study applies a systematic literature review method, to find articles that combine the two fields. The purpose of this study is to see the development of information security techniques with a fuzzy logic approach. As a result, it is found that the development of cryptographic and steganographic techniques that utilize fuzzy logic to help improve information security. In addition, the use of fuzzy logic is also not limited to increasing security. Fuzzy logic also plays a role in selecting the best key and password and issuing random numbers from a Pseudo-Random Number Generator (PRNG).

A Study of Z-Transform Based Encryption Algorithm

It has become increasingly important to ensure the protection of information, especially data in transit. Therefore, it is the primary goal of any encryption algorithm to safeguard the protection of information against security attacks. It is equally important to design high-performance solutions with affordable cost of implementation. Encryption algorithms are used to transform plain text to the ciphertext in order to protect privacy, prevent data fraud, and prevent unauthorized access of data in daily transactions. There are multiple types of encryption algorithms, each with its niche tactics to enhance security. For instance, different kinds of algorithms include but are not limited to the following: Blowfish, RSA, AES, DES, Triple DES. This paper contributes an efficient and secure encryption algorithm technique for information security based on Z transformation and XOR function known as the Z Transformation Encryption (ZTE) technique. To elaborate, this technique implements concepts of Z transformation and XOR operations at the source. The reverse process is applied at the receiving end of the transaction wherein the inverse of Z transformation and XOR is applied to reveal the original plain text message. The simulation of the proposed algorithm is conducted using the R language. The results show a promising performance comparing to other symmetric algorithms.

Electrically Tunable All-Dielectric Metasurfaces Integrated With Nematic Liquid Crystals for Information Encryption

As artificially designed two-dimensional (2D) arrays of subwavelength nanostructures, metasurfaces provide a new avenuefor the design of static planar optics. However, one would prefer a dynamic modulation of the metasurface in the event of practical applications. As a potentially important technique for information security, meta-holographic encryption has the characteristics of subwavelength pixels, precise control, and high safety factor. In this paper, by integrating birefringent liquid crystals (LCs) with all-dielectric metasurfaces in combination with visual cryptography (VC), we demonstrate a tunable metasurface with an information encryption function in the visible range. In the encryption process, the secret image is hidden in a set of unidentifiable and orthogonal arranged phase-only meta-holograms with high security of concealment. In the decryption process, the generated meta-hologram is illuminated by a plane wave and an electric field across the LC layer is applied to superimpose the reconstructed holographic patterns, thus we could acquire the secret image. Therefore, the decryption method can be flexibly and sufficiently adjusted with applied field under monitorable condition. For this reason, it is useful in enhancing the diversity of information hiding methods and improving the security of information. Our method can be extended to other similar applications.

Improving DFT-Based Image Watermarking Using Particle Swarm Optimization Algorithm

Robust digital image watermarking is an information security technique that has been widely used to solve several issues related mainly with copyright protection as well as ownership authentication. In general terms, robust watermarking conceals a small signal called a “watermark” in a host image in a form imperceptible to human vision. The efficiency of conventional robust watermarking based on frequency domain depend directly on the results of performance in terms of robustness and imperceptibility. According to the application scenario and the image dataset, it is common practice to adjust the key parameters used by robust watermarking methods in an experimental form; however, this manual adjustment may involve exhaustive tasks and at the same time be a drawback in practical scenarios. In recent years, several optimization techniques have been adopted by robust watermarking to allowing adjusting in an automatic form its key operation parameters, improving thus its performance. In this context, this paper proposes an improved robust watermarking algorithm in discrete Fourier transform via spread spectrum, optimizing the key operation parameters, particularly the amounts of bands and coefficients of frequency as well as the watermark strength factor using particle swarm optimization in conjunction with visual information fidelity and bit correct rate criteria. Experimental results obtained in this research show improved robustness against common signal processing and geometric distortions, preserving a high visual quality in color images. Performance comparison with conventional discrete Fourier transform proposal is provided, as well as with the current state-of-the-art of particle swarm optimization applied to image watermarking.

A Comprehensive Review on Medical Image Steganography Based on LSB Technique and Potential Challenges

The rapid development of telemedicine services and the requirements for exchanging medical information between physicians, consultants, and health institutions have made the protection of patients’ information an important priority for any future e-health system. The protection of medical information, including the cover (i.e. medical image), has a specificity that slightly differs from the requirements for protecting other information. It is necessary to preserve the cover greatly due to its importance on the reception side as medical staff use this information to provide a diagnosis to save a patient's life. If the cover is tampered with, this leads to failure in achieving the goal of telemedicine. Therefore, this work provides an investigation of information security techniques in medical imaging, focusing on security goals. Encrypting a message before hiding them gives an extra layer of security, and thus, will provide an excellent solution to protect the sensitive information of patients during the sharing of medical information. Medical image steganography is a special case of image steganography, while Digital Imaging and Communications in Medicine (DICOM) is the backbone of all medical imaging divisions, whereby it is most broadly used to store and transmit medical images. The main objective of this study is to provide a general idea of what Least Significant Bit-based (LSB) steganography techniques have achieved in medical images.

Artificial Intelligence Techniques for Information Security in 5G IoT Environments

The development of the telecommunication networks observed in present and future time is impressive. Today we witness rapid implementation of 5G networks. We can say that this actually is the moment when (artificial intelligence) AI enters at small door but in the beyond 5G world it is expected to have the prime role in smart operation, management and maintenance of non-software defined networking (SDN), network function virtualization (NFV) and especially at SDN and NFV aware networks. Number of standardization body’s and work groups are focused in a way to create a framework that will define the future use of AI and security standards necessary to exist in order to create health environment for the next generation telecommunication infrastructure. In the wireless world AI/Machine learning (ML) has great potential to shake the way we operate and to become foundation of the transformation that leads to the next industrial revolution. Network virtualization gives flexibility and freedom of the telco operators to choose the hardware and network topology they need for AI/ML platforms and big data sets. 5G and IoT create positive environment for AI and ML development and usage. As the network requirements are developed and the number of the users raises, gains are expected to grow with the number of variables and the interactions among them so it becomes impossible to relay on humans to control the network for increased number of variables and this is why AI with ML and automation become beneficial and necessity to run the future networks. AI generally is defined as capacity of mind or ability to acquire and apply knowledge and skills while ML is defined as learning that does not require explicit programming. Combined usage of AI and ML can optimize almost any component of the wireless network, this does not mean that it should be used everywhere mainly because at the end of the day the cost benefit analysis of its usage must be positive. Smart operation, management and infrastructure maintenance (SOMM) networks are defined as: Intelligent, data driven, integrated and agile. Today AI is introduced but in future it will represent the network engine. It is interesting to mention that network security must be upgraded because the network will provide services for massive number of IoT devices that will have variety of functions and requests. AI/ML can improve the security services and to be used in order to elevate them at advanced level. In this text we focus our attention at AI/ML and security scenarios defined for IoT in 5G environment.

Artificial Intelligence Techniques for Information Security in 5G IoT Environments

The development of the telecommunication networks observed in present and future time is impressive. Today we witness rapid implementation of 5G networks. We can say that this actually is the moment when (artificial intelligence) AI enters at small door but in the beyond 5G world it is expected to have the prime role in smart operation, management and maintenance of non-software defined networking (SDN), network function virtualization (NFV) and especially at SDN and NFV aware networks. Number of standardization body’s and work groups are focused in a way to create a framework that will define the future use of AI and security standards necessary to exist in order to create health environment for the next generation telecommunication infrastructure. In the wireless world AI/Machine learning (ML) has great potential to shake the way we operate and to become foundation of the transformation that leads to the next industrial revolution. Network virtualization gives flexibility and freedom of the telco operators to choose the hardware and network topology they need for AI/ML platforms and big data sets. 5G and IoT create positive environment for AI and ML development and usage. As the network requirements are developed and the number of the users raises, gains are expected to grow with the number of variables and the interactions among them so it becomes impossible to relay on humans to control the network for increased number of variables and this is why AI with ML and automation become beneficial and necessity to run the future networks. AI generally is defined as capacity of mind or ability to acquire and apply knowledge and skills while ML is defined as learning that does not require explicit programming. Combined usage of AI and ML can optimize almost any component of the wireless network, this does not mean that it should be used everywhere mainly because at the end of the day the cost benefit analysis of its usage must be positive. Smart operation, management and infrastructure maintenance (SOMM) networks are defined as: Intelligent, data driven, integrated and agile. Today AI is introduced but in future it will represent the network engine. It is interesting to mention that network security must be upgraded because the network will provide services for massive number of IoT devices that will have variety of functions and requests. AI/ML can improve the security services and to be used in order to elevate them at advanced level. In this text we focus our attention at AI/ML and security scenarios defined for IoT in 5G environment.