Security Algorithms Research Articles

Full states pseudo-random projective synchronization of hyperchaotic system and corresponding secure communication algorithm

Full states pseudo-random projective synchronization of hyperchaotic system and corresponding secure communication algorithm

A Review: Machine Learning Approaches for Zero-Day Attacks Recognition

Advancements and rapid technological developments in information age promoted computerization of day to day activities in all walks of life. As technology is growing rapidly, the cybercrime rate also increases both in number and complexity. Since a variety of attacks evolves regularly with complex patterns and varied signatures the task of securing cyberspace becomes more and more difficult and challenging. To minimize the impact of cybercrime through early detection of intrusions, network activity in terms of network traffic, is monitored in real-time thus accumulating huge data which is sometimes erroneous. Therefore, synergizing the concepts of cybersecurity and data analytics is essential to develop effective security algorithms for attack detection. Existing security measures like firewalls are no longer sufficient to deal with these emerging attacks. Because the firewall only checks the header of the data packet, it doesn't go through the details of the packet. Intrusion Detection Systems (IDSs) are the systems introduced as a second line of security after firewalls to handle cyber intrusions more efficiently. IDSs play a key role in protecting cyberspace by examining the entire details of the traffic packets to detect intrusions.

Enhanced Adaptive Security Algorithm (EASA) for optimized performance in smart city networks

Enhanced Adaptive Security Algorithm (EASA) for optimized performance in smart city networks

Automatic Translation of English Terms for Computer Network Security Based on Deep Learning

Translation computer network security refers to the protection of sensitive information during the transmission of data across networks in different languages. With the increasing globalization of businesses and communications, the need for secure translation services has become paramount. Security measures such as encryption, authentication, and data integrity verification play a crucial role in safeguarding translations from unauthorized access, interception, or tampering. Additionally, the use of secure communication protocols and encryption algorithms ensures that data remains confidential and protected from cyber threats. This paper presents an automatic translation approach for English terms related to computer network security, leveraging deep learning techniques with Cryptographic Hashing Authentication Classification (CHAC). The proposed framework aims to enhance the accuracy and efficiency of translating security terms across different languages, facilitating effective communication and collaboration in cybersecurity contexts. Through simulated experiments and empirical validations, the effectiveness of the CHAC-enhanced deep learning model is evaluated, demonstrating significant improvements in translation accuracy and performance. For instance, the CHAC model achieved an average accuracy rate of 90% in translating security terms, outperforming traditional translation methods by 20%. Additionally, the framework reduced translation time by 30%, streamlining the process of generating multilingual security documentation and communications. These results underscore the potential of deep learning with CHAC in automating the translation of English terms for computer network security, enhancing global cybersecurity efforts and facilitating cross-cultural collaboration.

An Enhanced AES-ECC model with Key Dependent Dynamic S-Box for the Security of Mobile Applications using Cloud Computing

The spectacular growth of computational clouds has drawn attention and enabled intensive computing on client devices with constrained resources. Smart phones mostly use the data centre demand service model to provide data to computationally intensive applications. It is challenging to outsource sensitive and private information to distant data centres due to growing concerns about data privacy and security. Therefore, conventional security algorithms have to be upgraded to address the brand-new security concerns that have emerged in the cloud environment. The Advanced Encryption Standard (AES) algorithm encrypts and decrypts messages using the four steps, namely Sub-Bytes, Shift-Rows, Mix-Columns, and Add Round Key. It has been changed so that the Sub-byte transformation depends on the round key. Making the S box round key dependent is intended to make it such that even a little change in the key will have a big impact on the cipher text. The avalanche effect and execution time of the standard and modified AES algorithms are implemented and assessed. In order to suggest a safe and efficient solution, the study also aims to modify the shift rows and the mix column phases of AES. Using cryptographic techniques such as elliptic curve cryptography (ECC), several protocols and algorithms have been developed to guarantee the security and integrity of the data. The proposed solution combines the enhanced and updated The Advanced Encryption Standard (AES) technology with the ECC to guarantee data secrecy. The avalanche effect approach is used in this study to explore and analyze the strength and quality of the new s-box. The results demonstrated that each encryption operation generates a unique cipher text. A strong avalanche effect was also achieved with the redesigned dynamic s-box using irreducible polynomials, surpassing the strict avalanche criterion (SAC). The results show that the proposed method ECC-EAESKDS Elliptic Curve Cryptography-Enhanced AES with Key Dependent S box is efficient and yields better results than the alternatives. According to the suggested security architecture, cloud users may control data protection and integrity in a secure manner.

Fuzzy logic Based Seagull Optimization Algorithm for Efficiency and Security in Wireless Sensor Networks

Wireless sensor networks (WSN) find applications in diverse fields such as environmental monitoring, healthcare, and industrial control systems. The pivotal components of these networks are the sensor nodes, which, unfortunately, consume a substantial amount of energy when transmitting information directly to the base station (BS). To mitigate energy consumption associated with direct transmission, this paper proposes a two-phase approach utilizing hybrid clustering and routing algorithms. The proposed approach incorporates fuzzy and seagull techniques for clustering and adopts optimal CH (cluster head) selection, CBRP (Cluster-Based Routing Protocol), and AES (Advanced Encryption Standard) for secure routing. The system employs rule-based fuzzy logic to correlate input values in both clustering and routing algorithms. Decision-making is based on factors such as the residual energy of sensor nodes, distance from the BS, and the number of nodes within the communication range. Input variables' crisp values are transformed into diverse fuzzy values, and the fuzzy output values are converted back to crisp values using the centroid defuzzification method. Selection of cluster heads and routers is determined by the output values, with sensor nodes being allocated to respective cluster heads based on their load-handling capacity. The routing path is then generated considering the capacity of routers. Simulations are conducted to evaluate energy consumption, active sensor nodes per round, and the sustainability period of the network. This proposed hybrid clustering and routing system aim to enhance the overall efficiency of wireless sensor networks by optimizing energy consumption and ensuring secure data transmission. The optimization model identifies the most suitable nodes in the routing cycle, starting with chosen cluster heads. The overarching goal is to enhance network indicators, including network lifespan, power consumption per node, and packet delivery percentage. The proposed solution achieved a network lifetime of 100 hours and a data delivery rate of 98%. additionally, it consumed the least amount of energy, measuring at 95,000 joules.

A Torpor-based Enhanced Security Model for CSMA/CA Protocol in Wireless Networks

Mobile wireless networks enable the connection of devices to a network with minimal or no infrastructure. This comes with the advantages of ease and cost-effectiveness, thus largely popularizing the network. Notwithstanding these merits, the open physical media, infrastructural-less attributes, and pervasive deployment of wireless networks make the channel of communication (media access) vulnerable to attacks such as traffic analysis, monitoring, and jamming. This study designed a virtual local area network (VLAN) model to circumvent virtual jamming attacks and other intrusions at the Media Access Control (MAC) layer of the Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) protocol. A Torpor VLAN (TVLAN) Data Frame Encapsulation and the algorithm for T-VLAN security in CSMA/CA were formulated and presented. A simulation experiment was conducted on the model using OMNeT++ software. The performance metrics used to evaluate the model were packet delivery ratio, network throughput, end-to-end channel delay, and channel load. The simulation results show that the TVLAN defence mechanism did not increase the channel load arbitrarily during TVLAN defence. similarly, the system throughput was shown to be 82% during TVLAN defence. Nevertheless, the network delay of the system during TVLAN defence was significantly high but the channel load was 297 when the TVLAN security mechanism was launched. These results demonstrate the model’s ability to provide a survivability mechanism for critical systems when under attack and add a security layer to the CSMA/CA protocol in wireless networks. Such a remarkable performance is required of a CSMA/CA infrastructure for improving the cybersecurity posture of a wireless network.

Federated Learning Security and Privacy-Preserving Algorithm and Experiments Research Under Internet of Things Critical Infrastructure

Federated Learning Security and Privacy-Preserving Algorithm and Experiments Research Under Internet of Things Critical Infrastructure

Review on Symmetric and Asymmetric Cryptography

Abstract: As the technology is progressing, internet is growing day by day and it has became more vulnerable than ever. To prevent data from being tampered or viewed by third parties, cryptography is used. Cryptography has it’s roots from ancient egypt, where secret writings are developed to transfer messages. Now, modern cryptography is used to secure data over the network, which are classified into symmetric and asymmetric cryptography. Both cryptographic methods has it’s own limitations and advantages, which are further used to develop algorithms for better security. More and more efficient algorithms are developed which are discussed in this paper

A Lightweight Image Cryptosystem for Cloud-Assisted Internet of Things

Cloud computing and the increasing popularity of 5G have greatly increased the application of images on Internet of Things (IoT) devices. The storage of images on an untrusted cloud has high security and privacy risks. Several lightweight cryptosystems have been proposed in the literature as appropriate for resource-constrained IoT devices. These existing lightweight cryptosystems are, however, not only at the risk of compromising the integrity and security of the data but also, due to the use of substitution boxes (S-boxes), require more memory space for their implementation. In this paper, a secure lightweight cryptography algorithm, that eliminates the use of an S-box, has been proposed. An algorithm termed Enc, that accepts a block of size n divides the block into L n R bits of equal length and outputs the encrypted block as follows: E=L⨂R⨁R, where ⨂ and ⨁ are exclusive-or and concatenation operators, respectively, was created. A hash result, hasR=SHA256P⨁K, was obtained, where SHA256, P, and K are the Secure Hash Algorithm (SHA−256), the encryption key, and plain image, respectively. A seed, S, generated from enchash=Enchashenc,K, where hashenc is the first n bits of hasR, was used to generate a random image, Rim. An intermediate image, intimage=Rim⨂P, and cipher image, C=Encintimage,K, were obtained. The proposed scheme was evaluated for encryption quality, decryption quality, system sensitivity, and statistical analyses using various security metrics. The results of the evaluation showed that the proposed scheme has excellent encryption and decryption qualities that are very sensitive to changes in both key and plain images, and resistance to various statistical attacks alongside other security attacks. Based on the result of the security evaluation of the proposed cryptosystem termed Hash XOR Permutation (HXP), the study concluded that the security of the cryptography algorithm can still be maintained without the use of a substitution box.

A Secure Image Cryptographic Algorithm Based on Triple Incorporated Ciphering Stages

Lately, image encryption has stand out as a highly urgent demand to provide high security for digital images against use and unauthorized distribution. A lot of existing researches use chaotic systems, symmetric or asymmetric schemes for image encryption, but cryptosystem based on one encryption technique only, faces many challenges like weak security and low complexity. Therefore, incorporating two or more different ciphering methods yields a secure and efficient algorithm to protect image information. In this work, a new image cryptosystem is suggested by joining zigzag scan technique, RSA algorithm and chaotic systems. These three security factors introduce Triple Incorporated Ciphering stages system (TIC). Initially, the plaintext image is divided into $8\times 8$ non-overlapping blocks, then the odd blocks are isolated from the even blocks. After that, a new modified zigzag scan in two different directions is adopted for shuffling pixels in the odd and even blocks. This operation effectively enhances the shuffling degree. Next, the RSA algorithm is utilized after combining the scrambled blocks in one matrix. Finally, chaotic systems are implemented on the resultant encrypted matrix to complete the ciphering process. The chaos is implemented in two steps; confusion and diffusion. Duffing map is exploited in the confusion stage, whereas L"u system is adopted on the shuffled matrix in the diffusion stage. The simulation results show the superiority of TIC in both security and attacks robustness compared to other cryptographic algorithms. Therefore, TIC can be exploited in real-time communication systems for secure image transmission.

A survey on lattice‐based security and authentication schemes for smart‐grid networks in the post‐quantum era

SummaryThe present scenario witnesses “the second quantum revolution,” which has enabled the development of revolutionary novel quantum tools. Quantum computing endeavors to establish higher computing standards that can potentially solve complex structures. Post‐quantum cryptography (PQC) has emerged as one of the new domains of cryptography, which is resilient to quantum attacks owing to the revolution in quantum computing. To ensure quantum security, the lattice‐based cryptosystem (LB‐cryptosystem) is one of the promising tools of PQC to address quantum‐based threats. The traditional security algorithms, such as RSA and Diffie–Hellman (DH), are strong enough to resist present security threats. However, it has been predicted that quantum technologies have the capability to break the security of most traditional algorithms whose security is based on prime factorization and DH‐type hard problems. Therefore, research is currently focused on addressing the security and privacy threats by using LB‐cryptosystems to secure various applications, organizations' data, and information infrastructure in the quantum era. The purpose of this article is to investigate recent advances in LB‐cryptosystems that may allow the design of secure models for smart‐grid networks (SGNs) against existing and future quantum attacks. SGNs have been explored as the bi‐directional assimilation of communication in terms of electricity generation, transmission, allocation, and utilization. This survey provides a comprehensive overview of LB‐cryptosystems, as well as their potential applications in securing SGNs. Lastly, the article summarizes the various PQC primitives, NIST selected algorithms, open‐source tools along with their packages, and various PQC industrial initiatives, and also compares traditional cryptographic schemes with other PQC.

Online Voting System

Having a democratic voting system in place is crucial for any nation due to the general distrust of the conventional voting system. Individuals have seen the infringement of their basic rights. Lack of transparency has been a problem with several electronic voting methods. The government has a hard time winning the confidence of its citizens since most voting processes aren't transparent enough. It is easy to abuse, which is why both the old and new digital voting systems have failed. Finding solutions to issues with both the paper and electronic voting systems, such as voting-related injustices and accidents, is the main goal. A fair election with less injustice is possible with the use of blockchain technology integrated into the voting process. Both digital and physical voting methods have their limitations, making them unsuitable for widespread use. This evaluates the importance of finding a way to protect people's democratic rights. To foster confidence between voters and election officials, this article introduces a platform built on blockchain technology, which maximises system stability and transparency. Without the need for traditional polling places, the proposed technology lays the groundwork for digital voting using blockchain. A scalable blockchain may be supported by our suggested architecture via the use of adaptable consensus algorithms. The voting process is made more secure with the use of the Chain Security algorithm. When conducting a chain transaction, smart contracts provide a safe channel of communication between the user and the network. There has also been talk of the voting system's security being based on blockchain technology.

Secure and Fast Image Encryption Algorithm Based on Modified Logistic Map

In the past few decades, the transmission of data over an unsecure channel has resulted in an increased rate of hacking. The requirement to make multimedia data more secure is increasing day by day. Numerous algorithms have been developed to improve efficiency and robustness in the encryption process. In this article, a novel and secure image encryption algorithm is presented. It is based on a modified chaotic logistic map (CLM) that provides the advantage of taking less computational time to encrypt an input image. The encryption algorithm is based on Shannon’s idea of using a substitution–permutation and one-time pad network to achieve ideal secrecy. The CLM is used for substitution and permutation to improve randomness and increase dependency on the encryption key. Various statistical tests are conducted, such as keyspace analysis, complexity analysis, sensitivity analysis, strict avalanche criteria (SAC), histogram analysis, entropy analysis, mean of absolute deviation (MAD) analysis, correlation analysis, contrast analysis and homogeneity, to give a comparative analysis of the proposed algorithm and verify its security. As a result of various statistical tests, it is evident that the proposed algorithm is more efficient and robust as compared to previous ones.

Secure and efficient federated learning via novel multi-party computation and compressed sensing

Federated learning (FL) enables the full utilization of decentralized training without raw data. However, various attacks still threaten the training process of FL. To address these concerns, differential privacy (DP) and secure multi-party computation (SMC) are applied, but these methods may result in low accuracy and heavy training load. Moreover, the high communication consumption of FL in resource-constrained devices is also a challenging problem. In this paper, we propose a novel SMC algorithm for the FL (FL-IPFE) to protect the local gradients. It does not require a trusted third party (TTP) and is more suitable for FL. Furthermore, we propose a secure and efficient FL algorithm (SEFL), which applies compressed sensing (CS) and all-or-nothing transform (AONT) to minimize the number of transmitted and encrypted model updates. Additionally, our FL-IPFE is used to encrypt the last element of the preprocessed parameters for guaranteeing the security of the entire local model updates. Meanwhile, the issue of participant dropouts is also taken into account. Theoretical analyses demonstrate that our proposed algorithms can aggregate model updates with high security. Finally, experimental evaluation reveals that our SEFL possesses higher efficiency compared to other state-of-the-art works, while providing comparable model accuracy and strong privacy guarantees.

Combination of AES (Advanced Encryption Standard) and SHA256 Algorithms for Data Security in Bill Payment Applications

In the era of information technology development, digital payments and e-payments are becoming a dominant trend, supported by the crucial role of payment gateways such as Midtrans. Midtrans uses APIs to facilitate various online transactions, including debit cards. In this research, two cryptographic algorithms will be combined, namely Advance Encryption Standard (AES) with 256 bits and Secure Hash Algorithm (SHA) with 256 bits. The importance of data security in e-payments is recognized, with the application of cryptographic algorithms to protect sensitive transaction information. Yayasan Antero Prosesi Edukasi (YAPE) as an educational marketing consultant faced the challenge of time-consuming and inefficient manual payments. In an effort towards efficiency and security, YAPE plans to develop an online payment application with Midtrans Payment Gateway and the use of AES-256 and SHA-256 cryptographic algorithms. This step is expected to help the foundation keep up with technological developments, provide ease of payment, and achieve computerized efficiency. The results showed that the use of a combination of AES 256 bit and SHA256 encryption significantly increased security, making hacking attempts ineffective because encrypted data could not be accessed, with quite complicated calculation stages.

A Review of Encryption Algorithms for Enhancing Data Security in Cloud Computing

Cloud computing is one of the most rapidly evolving technologies today; it provides numerous advantages that increase its affordability and dependability for use in the company. This paper goes over the concepts of cloud computing, such as its characteristics, deployment model, and service model, discusses the various benefits of cloud computing, and highlights the most pressing issues and security concerns in cloud storage. As a consequence, that leads to a review of distinctive cryptography algorithms that meet the security requirements (CIA: confidentiality, integrity, and availability) that are used to secure communications in cloud computing situations. It also displays many algorithms depending on the previous studies, such as Blowfish, RSA, DES, AES, MD5, Feistel, SP, HIGHT, LED, Cybpher, PRESENT, RC6, Diamond2, mCrypton, SLIM, Klein, PUFFIN-2, SEA, CLEFIA, LBlock, TWINE, 2, ANU, ANU-II, NLBSIT, Piccolo, BORON, RECTANGLE, LICI, QTL, LOGIC, TRIVIUM, Fruit-v2, Fruit-80, A4, the Enocoro family, and Grain family, to make a comparison among them using many measurements. It found that modern and lightweight algorithms are more suitable for use in this field. Furthermore, the purpose of this paper is to make some suggestions for improving the safety and security of cloud computing technologies.

An innovative image encryption algorithm enhanced with the Pan-Tompkins Algorithm for optimal security

This study introduces a cutting-edge image encryption algorithm aimed at elevating security standards. The Pan-Tompkins Algorithm (PTA) for key generation is proposed for the first time in this study. Additionally, employing steganography through the Least Significant Bit (LSB) method for embedding keys within the encrypted image enhances secure key distribution, thereby fortifying the encryption process. On the other hand, the integration of advanced algorithms, such as Zigzag scanning, the Affine Image Encryption Algorithm (AA), and the Vigenere Image Encryption Algorithm (VA), constitutes the fundamental innovation of the proposed image encryption algorithm. The proposed algorithm is named PanAAVA:Affine Algorithm and Vigenere Algorithm Encryption with PTA-Based Key Generation. The PanAAVA algorithm ensures unparalleled security by encrypting the positions and values of pixels using AA and VA. Notably, using PTA for key generation marks a distinctive and new key generation method feature of the algorithm. To assess the effectiveness of the PanAAVA, a comprehensive comparative analysis is conducted against well-established encryption methodologies, including Lena, Baboon, Airplane, and Pepper.The PanAAVA demonstrates exceptional proficiency in histogram analysis. The PanAAVA demonstrates a Unified Average Changing Intensity (UACI) of 33.4044%. Additionally, the Number of Pixels Change Rate (NPCR) is measured at 99.7442%, showcasing the algorithm’s effectiveness in inducing significant pixel changes. The proposed algorithm’s Mean Square Error (MSE) is calculated at 3.20679E5%. The proposed algorithm’s Peak Signal to Noise Ratio (PSNR) is recorded at 9.512475. The Key Space Size of the proposed algorithm is measured at 2209. Regarding correlation analysis, the PanAAVA achieves a high correlation score of 7.9996. The proposed algorithm successfully passes the National Institute of Standards and Technology (NIST) analysis, demonstrating a remarkably strong correlation close to 0 and a Structural Similarity Index Measure (SSIM) of 0.9977. Furthermore, regarding quantum communication, the proposed algorithm maintains stable key rates of 47.5 ± 0.8 kHz during the day and 50.9 ± 0.7 kHz at night. Additionally, PanAAVA achieves low Quantum Bit Error Rate (QBER) values of 4.77 ± 0.02, ensuring reliable and secure communication. The PanAAVA also demonstrates robust asymmetries at 49.81 ± 0.02 and 50.14 ± 0.03 for a crystal length of 20 mm. highlighting PanAAVA’s adaptability and effectiveness in different scenarios. PanAAVA outperforms other encryption algorithms concerning performance measurements and comparisons. In conclusion, the PanAAVA emerges as a beacon of superior security capabilities and innovation in image encryption, showcasing the potential to redefine standards in the field.

Consensus algorithms based on collusion resistant publicly verifiable random number seeds

Publicly verifiable random number seeds are widely used in distributed systems and applications, especially in consensus algorithms. The purpose was to distribute the tasks and benefits among the participants fairly. A secure and efficient consensus algorithm is the foundation and guarantee of blockchain. We have been working on more concise, fair, and secure blockchain consensus algorithms. In this paper, we propose a new, more concise, efficient, and publicly verifiable random number seed generation scheme based on the existing secret sharing scheme and one-way function. We combined it with two blockchain consensus algorithms to improve the security and efficiency of the original scheme.

A Blockchain-based carbon emission security accounting scheme

To solve the problem of climate warming, countries around the world have paid special attention to the construction of carbon governance. Carbon emission accounting is an important policy tool to control the vented CO2. But at present, there are third-party agencies in carbon emission accounting that cannot ensure the fairness and impartiality of accounting, and there may be risks such as illegal use and leakage of sensitive information in the process of carbon emission data transmission. Therefore, We design the blockchain-based carbon emission security accounting scheme (BCESAS) and propose cross-chain verification contract to ensure the efficiency of cross-chain information accounting. In addition, bilinear pairing is used to ensure data integrity, and we encrypt private data using an improved and more secure homomorphic encryption algorithm to ensure that privacy is not leaked during the transfer of carbon emission data, which is more efficient than other homomorphic encryption algorithms. We also use reputation mechanism to regulate the behavior of carbon emission auditors. The theoretical and experimental analysis demonstrates that BCESAS can verify the integrity, correctness and privacy of cross-chain data calculation result effectively, realizing secure and reliable expansion of blockchain.