Biblio

Artificial intelligence is a subfield of computer science that refers to the intelligence displayed by machines or software. The research has influenced the rapid development of smart devices that have a significant impact on our daily lives. Science, engineering, business, and medicine have all improved their prediction powers in order to make our lives easier in our daily tasks. The quality and efficiency of regions that use artificial intelligence has improved, as shown in this study. It successfully handles data organisation and environment difficulties, allowing for the development of a more solid and rigorous model. The pace of life is quickening in the digital age, and the PC Internet falls well short of meeting people’s needs. Users want to be able to get convenient network information services at any time and from any location

The past decade has shown us the power of cyber space and we getting dependent on the same. The exponential evolution in the domain has attracted attackers and defenders of technology equally. This inevitable domain has led to the increase in average human awareness and knowledge too. As we see the attack sophistication grow the protectors have always been a step ahead mitigating the attacks. A study of the various Threat Detection, Protection and Mitigation Systems revealed to us a common similarity wherein users have been totally ignored or the systems rely heavily on the user inputs for its correct functioning. Compiling the above we designed a study wherein user inputs were taken in addition to independent Detection and Prevention systems to identify and mitigate the risks. This approach led us to a conclusion that involvement of users exponentially enhances machine learning and segments the data sets faster for a more reliable output.

This paper proposes a lightweight digital signing scheme for supporting document signing on mobile devices connected to cloud computing. We employ elliptic curve (ECC) digital signature algorithm (ECDSA) for key pair generation done at mobile device and introduce outsourced proxy (OSP) to decrypt the encrypted file and compute hash value of the files stored in the cloud system. In our model, a mobile client invokes fixed-sized message digests to be signed with a private key stored in the device and produces the digital signature. Then, the signature is returned to the proxy for embedding it onto the original file. To this end, the trust between proxy and mobile devices is guaranteed by PKI technique. Based on the lightweight property of ECC and the modular design of our OSP, our scheme delivers the practical solution that allows mobile users to create their own digital signatures onto documents in a secure and efficient way. We also present the implementation details including system development and experimental evaluation to demonstrate the efficiency of our proposed system.

Nowadays the use of Wi-Fi has been widely used in public places, such as in restaurants. The use of Wi-Fi in public places has a very large security vulnerability because it is used by a wide variety of visitors. Therefore, this study was conducted to evaluate the security of the WLAN network in restaurants. The methods used are Vulnerability Assessment and Penetration Testing. Penetration Testing is done by conducting several attack tests such as Deauthentication Attack, Evil Twin Attack with Captive Portal, Evil Twin Attack with Sniffing and SSL stripping, and Unauthorized Access.

Due to the difficulty of obtaining a database of original images that are required in the classification process to detect tampering, this paper presents a technique for detecting image tampering such as image steganography in the spatial domain. The system depends on deriving the auto-correlation function of the image histogram, then applying a high-pass filter with a threshold. This technique can be used to decide which image is cover or a stego image, without adopting the original image. The results have eventually revealed the validity of this system. Although this study has focused on least-significant-bit (LSB) steganography, we expect that it could be extended to other types of image tapering.

This paper proposes 2 multiple layer message security schemes. Information security is carried out through the implementation of cryptography, steganography and image processing techniques. In both schemes, the sensitive data is first encrypted by employing a chaotic function. In the first proposed scheme, LSB steganography is then applied to 2D slices of a 3D image. In the second proposed scheme, a corner detection filter is first applied to the 2D slices of a 3D image, then LSB embedding is carried out in those corner-detected pixels. The number of neighboring pixels used for corner detection is varied and its effect is noted. Performance of the proposed schemes is numerically evaluated using a number of metrics, including the mean squared error (MSE), the peak signal to noise ratio (PSNR), the structure similarity index measure (SSIM), the normalized cross-correlation (NCC), the image fidelity (IF), as well as the image difference (ID). The proposed schemes exhibit superior payload capacity and security in comparison to their counterparts from the literature.

Steganography security is the main concern in today’s informative world. The fact is that communication takes place to hide information secretly. Steganography is the technique of hiding secret data within an ordinary, non-secret, file, text message and images. This technique avoids detection of the secret data then extracted at its destination. The main reason for using steganography is, we can hide any secret message behind its ordinary file. This work presents a unique technique for image steganography based on a 512-bit algorithm. The secure stego image is a very challenging task to give protection. Therefore we used the least significant bit (LSB) techniques for implementing stego and cover image. However, data encryption and decryption are used to embedded text and replace data into the least significant bit (LSB) for better approaches. Android-based interface used in encryption-decryption techniques that evaluated in this process.Contribution—this research work with 512-bit data simultaneously in a block cipher to reduce the time complexity of a system, android platform used for data encryption decryption process. Steganography model works with stego image that interacts with LSB techniques for data hiding.

Image steganography is a technique of hiding confidential data in the images. We do this by incorporating the LSB(Least Significant Bit) of the image pixels. LSB steganography has been there for a while, and much progress has been made in it. In this paper, we try to increase the security of the LSB steganography process by incorporating a random data distribution method which we call pixel locator sequence (PLS). This method scatters the data to be infused into the image by randomly picking up the pixels and changing their LSB value accordingly. This random distribution makes it difficult for unknowns to look for the data. This PLS file is also encrypted using AES and is key for the data encryption/decryption process between the two parties. This technique is not very space-efficient and involves sending meta-data (PLS), but that trade-off was necessary for the additional security. We evaluated the proposed approach using two criteria: change in image dynamics and robustness against steganalysis attacks. To assess change in image dynamics, we measured the MSE and PSNR values. To find the robustness of the proposed method, we used the tool StegExpose which uses the stego image produced from the proposed algorithm and analyzes them using the major steganalysis attacks such as Primary Sets, Chi-Square, Sample Pairs, and RS Analysis. Finally, we show that this method has good security metrics for best known LSB steganography detection tools and techniques.

We propose a voting ensemble of models trained by using block-wise transformed images with secret keys against black-box attacks. Although key-based adversarial defenses were effective against gradient-based (white-box) attacks, they cannot defend against gradient-free (black-box) attacks without requiring any secret keys. In the proposed ensemble, a number of models are trained by using images transformed with different keys and block sizes, and then a voting ensemble is applied to the models. Experimental results show that the proposed defense achieves a clean accuracy of 95.56 % and an attack success rate of less than 9 % under attacks with a noise distance of 8/255 on the CIFAR-10 dataset.

In this paper we tackle the open paradoxical challenge of FPGA-accelerated cloud computing: On one hand, clients aim to secure their Intellectual Property (IP) by encrypting their configuration bitstreams prior to uploading them to the cloud. On the other hand, cloud service providers disallow the use of encrypted bitstreams to mitigate rogue configurations from damaging or disabling the FPGA. Instead, cloud providers require a verifiable check on the hardware design that is intended to run on a cloud FPGA at the netlist-level before generating the bitstream and loading it onto the FPGA, therefore, contradicting the IP protection requirement of clients. Currently, there exist no practical solution that can adequately address this challenge.We present the first practical solution that, under reasonable trust assumptions, satisfies the IP protection requirement of the client and provides a bitstream sanity check to the cloud provider. Our proof-of-concept implementation uses existing tools and commodity hardware. It is based on a trusted FPGA shell that utilizes less than 1% of the FPGA resources on a Xilinx VCU118 evaluation board, and an Intel SGX machine running the design checks on the client bitstream.

In this paper, two of the main Blockchain development platforms, Ethereum and EOS.IO are compared. The objective is to help developers select the most appropriate platform as the back-end Blockchain for their apps. A decentralized application was implemented on each of the platforms triggering basic operations and timing them. The simulations were performed on Microsoft’s Azure cloud, running up to 150 Blockchain nodes while recording the user response time, the CPU utilization, and the totally used memory in Mbytes. The results in this study show that although recognized as a major competitor to Ethereum, EOS.IO fails to outperform the Ethereum platform in this experiment, recording a very high response time in comparison to Ethereum.

Nowadays, biometric is a most technique to authenticate /identify human been, because its resistance against theft, loss or forgetfulness. However, biometric is subject to different transmission attacks. Today, the protection of the sensitive biometric information is a big challenge, especially in current wireless networks such as internet of things where the transmitted data is easy to sniffer. For that, this paper proposes an Eigens-Fingerprint-based biometric cryptosystem, where the biometric feature vectors are extracted by the Principal Component Analysis technique with an appropriate quantification. The key-binding principle incorporated with bit-wise and byte-wise correcting code is used for encrypting data and sharing key. Several recognition rates and computation time are used to evaluate the proposed system. The findings show that the proposed cryptosystem achieves a high security without decreasing the accuracy.

Nowadays, biometric-based authentication systems are widely used. This fact has led to increased attacks on biometric data of users. Therefore, biometric template protection is sure to keep the attention of researchers for the security of the authentication systems. Many previous works proposed the biometric template protection schemes by transforming the original biometric data into a secure domain, or establishing a cryptographic key with the use of biometric data. The main purpose was that fulfill the all three requirements: cancelability, security, and performance as many as possible. In this paper, using random projection merged with fuzzy commitment, we will introduce a hybrid scheme of biometric template protection. We try to limit their own drawbacks and take full advantages of these techniques at the same time. In addition, an analysis of non-invertibility property will be exercised with regards to the use of random projection aiming at enhancing the security of the system while preserving the discriminability of the original biometric template.

Physical unclonable functions (PUFs) are used to create unique device identifiers from their inherent fabrication variability. Unstable readings and variation of the PUF response over time are key issues that limit the applicability of PUFs in real-world systems. In this project, we developed a fuzzy extractor (FE) to generate robust cryptographic keys from ReRAM-based PUFs. We tested the efficiency of the proposed FE using BCH and Polar error correction codes. We use ReRAM-based PUFs operating in pre-forming range to generate binary cryptographic keys at ultra-low power with an objective of tamper sensitivity. We investigate the performance of the proposed FE with real data using the reading of the resistance of pre-formed ReRAM cells under various noise conditions. The results show a bit error rate (BER) in the range of 10−5 for the Polar-codes based method when 10% of the ReRAM cell array is erroneous at Signal to Noise Ratio (SNR) of 20dB.This error rate is achieved by using helper data length of 512 bits for a 256 bit cryptographic key. Our method uses a 2:1 ratio for helper data and key, much lower than the majority of previously reported methods. This property makes our method more robust against helper data attacks.

Proofs in simulation-based frameworks have the greatest rigor when they are machine checked. But the level of details in these proofs surpasses what the formal-methods community can handle with existing tools. Existing formal results consider streamlined versions of simulation-based frameworks to cope with this complexity. Hence, a central question is how to abstract details from composability results and enable their formal verification.In this paper, we focus on the modeling of system communication in composable security statements. Existing formal models consider fixed communication patterns to reduce the complexity of their proofs. However, as we will show, this can affect the reusability of security statements. We propose an abstract approach to modeling system communication in Constructive Cryptography that avoids this problem. Our approach is suitable for mechanized verification and we use CryptHOL, a framework for developing mechanized cryptography proofs, to implement it in the Isabelle/HOL theorem prover. As a case study, we formalize the construction of a secure channel using Diffie-Hellman key exchange and a one-time-pad.

Smart grids can be exposed to relay attacks (or wormhole attacks) resulting from weaknesses in cryptographic operations such as authentication and key derivation associated with process automation protocols. Relay attacks refer to attacks in which authentication is evaded without needing to attack the smart grid itself. By using a universal composability model that provides a strong security notion for designing cryptographic operations, we formulate the necessary relay resilience settings for strengthening authentication and key derivation and enhancing relay security in process automation protocols in this paper. We introduce R-Chain, a universally composable relay resilience framework that prevents bypass of cryptographic operations. Our framework provides an ideal chaining functionality that integrates all cryptographic operations such that all outputs from a preceding operation are used as input to the subsequent operation to support relay resilience. We apply R-Chain to provide relay resilience in a practical smart grid process automation protocol, namely WirelessHART.

Evolutionary computation (EC) is a kind of advanced computational intelligence (CI) algorithm and advanced artificial intelligence (AI) algorithm. EC algorithms have been widely studied for solving optimization and scheduling problems in various real-world applications, which act as one of the Big Three in CI and AI, together with fuzzy systems and neural networks. Even though EC has been fast developed in recent years, there is an assumption that the algorithm designer can obtain the objective function of the optimization problem so that they can calculate the fitness values of the individuals to follow the “survival of the fittest” principle in natural selection. However, in a real-world application scenario, there is a kind of problem that the objective function is privacy so that the algorithm designer can not obtain the fitness values of the individuals directly. This is the privacy-preserving optimization problem (PPOP) where the assumption of available objective function does not check out. How to solve the PPOP is a new emerging frontier with seldom study but is also a challenging research topic in the EC community. This paper proposes a rank-based cryptographic function (RCF) to protect the fitness value information. Especially, the RCF is adopted by the algorithm user to encrypt the fitness values of all the individuals as rank so that the algorithm designer does not know the exact fitness information but only the rank information. Nevertheless, the RCF can protect the privacy of the algorithm user but still can provide sufficient information to the algorithm designer to drive the EC algorithm. We have applied the RCF privacy-preserving method to two typical EC algorithms including particle swarm optimization (PSO) and differential evolution (DE). Experimental results show that the RCF-based privacy-preserving PSO and DE can solve the PPOP without performance loss.

Trusted Platform Modules (TPM) have grown to be crucial safeguards from the number of software-based strikes. By giving a restricted range of cryptographic providers by way of a well-defined user interface, divided as a result of the program itself, TPM and Infrastructure as a service (IaaS) can function as a root of loyalty so when a foundation aimed at advanced equal protection methods. This information studies the works aimed at uses on TPM within the cloud computing atmosphere, by journal times composed somewhere among 2013 as well as 2020. It identifies the present fashion as well as goals from these technologies within the cloud, as well as the kind of risks that it mitigates. The primary investigation is being focused on the TPM's association to the IaaS security based on the authorization and the enabling schema for integrity. Since integrity measurement is among the key uses of TPM and IaaS, particular focus is given towards the evaluation of operating period phases as well as S/W levels it's put on to. Finally, the deep survey on recent schemes can be applied on Cloud Environment.

Application of cryptography and how various encryption algorithms methods are used to encrypt and decrypt data that traverse the network is relevant in securing information flows. Implementing cryptography in a secure network environment requires the application of secret keys, public keys, and hash functions to ensure data confidentiality, integrity, authentication, and non-repudiation. However, providing secure communications to prevent interception, interruption, modification, and fabrication on network systems has been challenging. Cyberattacks are deploying various methods and techniques to break into network systems to exploit digital signatures, VPNs, and others. Thus, it has become imperative to consider applying techniques to provide secure and trustworthy communication and computing using cryptography methods. The paper explores applied cryptography concepts in information and network systems security to prevent cyberattacks and improve secure communications. The contribution of the paper is threefold: First, we consider the various cyberattacks on the different cryptography algorithms in symmetric, asymmetric, and hashing functions. Secondly, we apply the various RSA methods on a network system environment to determine how the cyberattack could intercept, interrupt, modify, and fabricate information. Finally, we discuss the secure implementations methods and recommendations to improve security controls. Our results show that we could apply cryptography methods to identify vulnerabilities in the RSA algorithm in secure computing and communications networks.

Mobile security remains a concern for multiple stakeholders. Safe user behavior is crucial key to avoid and mitigate mobile threats. The research used a survey design to capture key constructs of mobile user threat avoidance behavior. Analysis revealed that there is no significant difference between the two key drivers of secure behavior, threat appraisal and coping appraisal, for Android and iOS users. However, statistically significant differences in avoidance motivation and avoidance behavior of users of the two operating systems were displayed. This indicates that existing threat avoidance models may be insufficient to comprehensively deal with factors that affect mobile user behavior. A newly introduced variable, perceived security, shows a difference in the perceptions of their level of protection among the users of the two operating systems, providing a new direction for research into mobile security.

In this paper, we propose a scheme that supports statistic query and authorized access control on an Encrypted Electronic Medical Records Databases(EMDB). Different from other schemes, it is based on Differential-Privacy(DP), which can protect the privacy of patients. By deploying an improved Multi-Authority Attribute-Based Encryption(MA-ABE) scheme, all authorities can distribute their search capability to clients under different authorities without additional negotiations. To our best knowledge, there are few studies on statistical queries on encrypted data. In this work, we consider that support differentially-private statistical queries. To improve search efficiency, we leverage the Bloom Filter(BF) to judge whether the keywords queried by users exists. Finally, we use experiments to verify and evaluate the feasibility of our proposed scheme.

WebAssembly is an Increasingly popular lightweight binary instruction format, which can be efficiently embedded and sandboxed. Languages like C, C++, Rust, Go, and many others can be compiled into WebAssembly. This paper describes Twine, a WebAssembly trusted runtime designed to execute unmodified, language-independent applications. We leverage Intel SGX to build the runtime environment without dealing with language-specific, complex APIs. While SGX hardware provides secure execution within the processor, Twine provides a secure, sandboxed software runtime nested within an SGX enclave, featuring a WebAssembly system interface (WASI) for compatibility with unmodified WebAssembly applications. We evaluate Twine with a large set of general-purpose benchmarks and real-world applications. In particular, we used Twine to implement a secure, trusted version of SQLite, a well-known full-fledged embeddable database. We believe that such a trusted database would be a reasonable component to build many larger application services. Our evaluation shows that SQLite can be fully executed inside an SGX enclave via WebAssembly and existing system interface, with similar average performance overheads. We estimate that the performance penalties measured are largely compensated by the additional security guarantees and its full compatibility with standard WebAssembly. An indepth analysis of our results indicates that performance can be greatly improved by modifying some of the underlying libraries. We describe and implement one such modification in the paper, showing up to 4.1 × speedup. Twine is open-source, available at GitHub along with instructions to reproduce our experiments.

This article describes the process of synchronizing the generation of random sequences by a quantum random number generator (QRNG) that can be used as secret keys for known cryptographic transformations. The subject of the research is a method for synchronizing the generation of random QRNG sequences based on L1 (C/A) signals of the global positioning system (GPS) using control correcting information received from control correcting stations.

In recent years, many modifications have been done to combat the weaknesses of the Vigenère Cipher Algorithm. Several studies have been carried out to rectify the flaw of the algorithm’s repeating key nature by increasing the key length equal to that of the plain text. However, some characters cannot be encrypted due to the limited set of characters in the key. This paper modified the algorithm’s key generation process using a Pseudo-Random Number Generator to improve the algorithm’s security and expanded the table of characters to up to 190 characters. The results show that based on Monobit examination and frequency analysis, the repeating nature of the key is non-existent, and the generated key can be used to encrypt a larger set of characters. The ciphertext has a low IC value of 0.030, which is similar to a random string and polyalphabetic cipher with an IC value of 0.038 but not equal to a monoalphabetic cipher with an IC value of 0.065. Results show that the modified version of the algorithm performs better than some of the recent studies conducted on it

Crypto-ransomware is a malware that uses the system’s cryptography functions to encrypt user data. The irreversible effect of crypto-ransomware makes it challenging to survive the attack compared to other malware categories. When a crypto-ransomware attack encrypts user files, it becomes difficult to access these files without having the decryption key. Due to the availability of ransomware development tool kits like Ransomware as a Service (RaaS), many ransomware variants are being developed. This contributes to the rise of ransomware attacks witnessed nowadays. However, the conventional approaches employed by malware detection solutions are not suitable to detect ransomware. This is because ransomware needs to be detected as early as before the encryption takes place. These attacks can effectively be handled only if detected during the pre-encryption phase. Early detection of ransomware attacks is challenging due to the limited amount of data available before encryption. An adaptive pre-encryption model is proposed in this paper which is expected to deal with the population concept drift of crypto-ransomware given the limited amount of data collected during the pre-encryption phase of the attack lifecycle. With such adaptability, the model can maintain up-to-date knowledge about the attack behavior and identify the polymorphic ransomware that continuously changes its behavior.