Hybrid Security Research Articles

A Secure Hybrid Dynamic-State Estimation Approach for Power Systems Under False Data Injection Attacks

Dynamic-state estimation plays a critical role in achieving real-time wide-area monitoring of power systems. On the other hand, false data injection (FDI) attacks are substantial threats, which can undesirably ruin the state estimation results. To tackle this problem, an effective secure hybrid dynamic-state estimation approach that involves a dynamic model of the attack vector is proposed in this article. In the proposed method, an initial estimation of the system states is first obtained using a designed unknown input observer (UIO). Subsequently, based on the system, UIO models, and the initial estimations of the states, a dynamic model for the attack vector is extracted. Ultimately, the attack model is augmented with the main system model for coestimation of the attack and the system states using a Kalman filter. The onset of the FDI attack is rapidly detected by the accurate estimation of the attack vector. The effectiveness of the proposed approach is demonstrated under different FDI attack scenarios by a thorough theoretical analysis as well as simulations on IEEE 14-bus and 57-bus test systems. In order to show that the proposed method can keep up with typical scan rates of commercial phasor measurement units, a series of software-in-the-loop experiments are also conducted and the real-time feasibility of the proposed approach is guaranteed.

Hybrid Analog-Digital Precoder Design for Securing Cognitive Millimeter Wave Networks

Millimeter wave (mmWave) communications and cognitive radio technologies constitute key technologies of improving the spectral efficiency of communications. Hence, we conceive a hybrid secure precoder for enhancing the physical layer security of a cognitive mmWave wiretap channel, where a secondary transmitter broadcasts confidential information signals to multiple secondary users under the interference temperature constraint of the primary user (PU). The optimization problem is formulated as jointly optimizing the analog and digital precoder for maximizing the minimum secrecy rate of all the secondary users under practical constraints. In particular, our design satisfies the constraint on the maximum interference power received by multiple PUs, as well as the secondary users’ minimum quality-of-service (Qos), and the unit-modulus constraint on the analog precoder. Due to the non-convexity of the resultant objective function and owing to the coupling between the analog and digital precoder, the optimization problem formulated is nonconvex and nonlinear, hence it is very challenging to solve directly. Hence, we first transform it into a tractable form, and develop a penalty dual decomposition (PDD) based iterative algorithm to locate its Karush-Kuhn-Tucker (KKT) solution. Finally, we generalize the proposed PDD algorithm to a secure hybrid precoder design relying on practical finite-resolution phase shifters and show that the proposed PDD algorithm can be straightforwardly adapted to handle the scenario, where each PU is equipped with multiple antennas and the CSI of multiple eavesdroppers (Eves) is imperfectly known. Our simulation results validate the efficiency of the proposed iterative algorithm.

Precoding and Transmit Antenna Subarray Selection for Secure Hybrid Spatial Modulation

Spatial modulation (SM) is a particularly important form of multiple-input multiple-output (MIMO), which uses both modulation symbols and antenna indices to carry information. In this paper, to avoid the high cost and circuit complexity of SM, we consider the hybrid SM system with a hybrid precoding transmitter architecture, combining a digital precoder and an analog precoder. In such a system, we carried out secure hybrid precoding and transmit antenna subarray selection (TASS) methods. Two hybrid precoding methods, called maximizing approximate secrecy rate (SR) via gradient ascent (Max-ASR-GA) and maximizing approximate SR via alternating direction method of multipliers (Max-ASR-ADMM), are proposed to improve the SR performance. As for TASS, a high-performance method of maximizing the approximate SR (Max-ASR) is first presented. To reduce its high complexity, two low-complexity TASS methods, namely maximizing eigenvalue (Max-EV) and maximizing product of signal-to-interference-plus-noise ratio and artificial noise-to-signal-plus-noise ratio (Max-P-SINR-ANSNR), are proposed. Simulation results demonstrate that the proposed Max-ASR-GA and Max-ASR-ADMM hybrid precoders harvest substantial SR performance gains over existing method. For TASS, the proposed three methods Max-ASR, Max-EV, and Max-P-SINR-ANSNR perform better than existing leakage method. Particularly, the proposed Max-EV and Max-P-SINR-ANSNR are of low-complexity at the expense of a little performance loss compared with Max-ASR.

Energy Proficient Hybrid Secure Scheme for Wireless Sensor Networks

One way hash chain with a new key indicating the performance of the node as well to isolate malicious nodes from the network. Public key cryptography is derived using elliptical curve cryptography (ECC) have couple of key for decryption and encryption. Public key cryptography provides protection and verification using numerous algorithms. In addition secret session key is generated for secured data transmission and improve energy efficiency in WSN. Advanced encryption standard (AES) is applied for message cipher text once the key validation process gets finished. Energy proficient hybrid secure scheme (EPHSS) is proposed to provide secured and energy efficient data transmissions in WSN. To utilise the node energy in a proper way node clustering process is carried out. Clustering process efficiently reduces unnecessary energy wastage during node communication. Graded co-prime keys are generated for public and private keys, also encrypting functions are performed for providing security mechanisms. This mechanism improves security measures and simultaneously reduces energy consumption among nodes. The route should be undetectable by malicious nodes and the data should not be lacerate by the opponent node even it gets to know the public key. Identifying private key component [B, n] is difficult for malevolent; thus building it computationally infeasible for discovering decryption type at receiver side. Simulation presentations of the networks are analysed by network simulator tool. Efficiency of the proposed scheme is computed by taking delivery rates of packets which results in 18% better than the conventional ECCSAS scheme.

Deep Hashing for Secure Multimodal Biometrics

When compared to unimodal systems, multimodal biometric systems have several advantages, including lower error rate, higher accuracy, and larger population coverage. However, multimodal systems have an increased demand for integrity and privacy because they must store multiple biometric traits associated with each user. In this paper, we present a deep learning framework for feature-level fusion that generates a secure multimodal template from each user's face and iris biometrics. We integrate a deep hashing (binarization) technique into the fusion architecture to generate a robust binary multimodal shared latent representation. Further, we employ a hybrid secure architecture by combining cancelable biometrics with secure sketch techniques and integrate it with a deep hashing framework, which makes it computationally prohibitive to forge a combination of multiple biometrics that pass the authentication. The efficacy of the proposed approach is shown using a multimodal database of face and iris and it is observed that the matching performance is improved due to the fusion of multiple biometrics. Furthermore, the proposed approach also provides cancelability and unlinkability of the templates along with improved privacy of the biometric data. Additionally, we also test the proposed hashing function for an image retrieval application using a benchmark dataset. The main goal of this paper is to develop a method for integrating multimodal fusion, deep hashing, and biometric security, with an emphasis on structural data from modalities like face and iris. The proposed approach is in no way a general biometric security framework that can be applied to all biometric modalities, as further research is needed to extend the proposed framework to other unconstrained biometric modalities.

Lattice based access control for protecting user data in cloud environments with hybrid security

Cloud computing is an aspired reverie of computing that provides a huge capacity of storage. The users of the cloud, store large volumes of their private data, where sometimes they have to suffer vulnerabilities and attacks on it. Since there is only partial control over the stored data, the users require strong and significant protection techniques to guard their data. The protection of data storage is a challenging and formidable task and so the user data should be protected against security threats. There is a great deal of uncertainty on how to provide security for the user data also. Thus, encrypting the data before storage might be the most promising approach. In this paper, a hybrid layered approach is proposed to protect the user's data along with the association of lattice-based security technique. In this proposed model, a new approach has been incorporated for checking roles and responsibilities using lattice model. For this implementation text-based Patient Health care Records (PHR) are taken and significance of the proposed method is tested. Advanced Encryption Standard and Rivest-Shamir-Adleman are employed in this approach to provide further and better security to the sensitive data. The proposed model uses a CloudSim simulator in which virtual machine has been created with balanced configuration and it is implemented as well as tested. Compared to the existing methods, the proposed scheme is more secure and we offers easy interface to the patients for uploading and downloading their records. We have tested the differed parameters of proposed method with state of art approaches. The experimentation results show that the proposed scheme is more efficient.

Secure hybrid pulse compression as a technique against jamming in radar systems

In this paper, we propose a secure hybrid pulse compression method for radar waveform design. This method uses a confidential code as the phase-code for the binary-shift keying modulation. We also use another confidential code for the frequency-code. This code is replaced in the frequency control register of a direct digital synthesizer to perform the narrow-band frequency-shift keying. We exploit the output of an encryption algorithm, e.g. a block cipher, as the binary code, which fulfills security and confidentiality requirements of electronic warfare scenarios. In contrast to other proposals that use only confidential phase-codes, we propose a method that considers both the frequency and phase codes to be confidential. We evaluate the proposed method’s performance in the presence of a jammer for three cases: where the jammer has access only to the phase-code, only the frequency code, and has access to neither. Our method effectively decreases the probability of false alarms, while improving detection probability.

Abstract IA20: California Teachers Study (CTS) Data Management Platform: A model for a repeatable turnkey, end-to-end, cloud-based data management and analytics solution for epidemiology cohorts

Abstract The Health Cyberinfrastructure (CI) Division at the San Diego Supercomputer Center (SDSC) has been deploying secure, compliant, end-to-end solutions to support critical applications including, but not limited to, biomedical research, detecting and preventing medical fraud, enterprise risk management, and medical device data management. These applications have relied on technologies ranging from the traditional data warehouse to the more recent big data platforms leveraging Hadoop, Software as a Service (SaaS) capability leveraging container technology, business intelligence and analytics solutions, and IOT/streaming solutions. Operating these applications and the underlying platforms requires organizations to be agile and visionary in this arena to grow with the ever-changing technological, regulatory, and unique customer requirements, while simultaneously ensuring data security and privacy. To that end, the SDSC Health CI Division is participating in a multi-institution project with City of Hope, a National Cancer Institute (NCI)-designated Comprehensive Cancer Center, and other universities and health organizations to create a research cyberinfrastructure that includes a secure, cloud-based data management platform. The data management platform consolidates all CTS data, including datasets, codes, and accompanying documentation, and operates within Sherlock Cloud, a secure hybrid cloud platform. The innovative platform allows every member of the CTS team to securely access and use all CTS data and information in real time in a consolidated, integrated, and secure manner. Researchers have access to a data warehouse, domain-specific data marts, and analytics platform built on secure cloud technology that greatly enhances the reliability and accuracy of the data collected, and has a more seamless mechanism to access, annotate, input, and transmit data, thereby heightening accuracy and the quality of collaborative analysis performed. This approach not only transforms how CTS data is collected, stored, and shared for high-impact research, but also has the potential to reduce associated costs of ongoing research while increasing efficiency and security. SDSC Health CI Division’s work in building innovative data management and compute solutions for health care researchers over the last decade, and its collaboration with the CTS researchers more recently, has demonstrated a clear need for a unique type of managed services capability that serves the biomedical community. Specifically, the epidemiology cohorts have practiced a more traditional approach consisting of decentralized data management and computing. Even though this approach has served the community well in the past, as we look into the future, it has obvious shortcomings in terms of supporting enterprise-level data management, scale, interoperability, and provenance. SDSC Health CI Division takes a modern approach to information lifecycle management through its Sherlock Cloud platform. Sherlock Cloud Data Management framework captures users’ evolving requirements, and provides centralized, secure cloud-based managed services capability that supports end-to-end data lifecycle management including data integration capabilities, allowing data to be captured, rationalized, homogenized, and managed using best practices and standards. This includes dynamic mappings, transformations, and master data-management techniques utilizing established governance methodologies, with specific focus on data quality, metadata management, and governance. The CTS data management and analytics platform implementation can serve as a model for other epidemiology cohorts and studies. SDSC Health CI Division plans to achieve this by leveraging the existing investment NCI and CTS has already made in building the cloud-based, secure CTS data management platform. Using container technology, Sherlock will package the various components of the data management framework and analytical tools, creating a turnkey offering that can be deployed for other similar studies. This cloud platform agnostic, open-source, turnkey solution provides other cohorts a template they can build on top of, and leverage all the work CTS has performed to develop the core, domain-specific data management and analytics capability, and all that will remain is study specific customizations that cohorts will need to perform. Additionally, APIs built on top of the in-built data model will provide seamless integration with external NCI- and NIH-established Commons. The epidemiology community has a way to go before it is on par with communities in other verticals in their adoption of cutting-edge, enterprise platforms and tools for data management and analytics, but initiatives like CTS can demonstrate that, once designed and developed, these capabilities can be easily packaged and deployed for other studies, providing a framework that a larger research community can leverage. Citation Format: Sandeep Chandra. California Teachers Study (CTS) Data Management Platform: A model for a repeatable turnkey, end-to-end, cloud-based data management and analytics solution for epidemiology cohorts [abstract]. In: Proceedings of the AACR Special Conference on Modernizing Population Sciences in the Digital Age; 2019 Feb 19-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(9 Suppl):Abstract nr IA20.

A novel secure chaos-based pseudo random number generator based on ANN-based chaotic and ring oscillator: design and its FPGA implementation

This paper presents a novel, real time, high speed and robust chaos-based pseudo random number generator (PRNG) design using the structures of artificial neural network (ANN)-based 2D chaotic oscillator and ring oscillator. In this study, four different robust PRNGs have been implemented using four different approaches (TS-55, Elliott-93, Elliott-2, Cordic-LUT) of TanSig activation functions (TSAF) that have been used in the design of ANN-based 2D chaotic oscillators. The designs have been coded in VHDL using IEEE-754–1985 number standard. The PRNGs have been synthesized for Virtex-6 FPGA chip using Xilinx ISE Design Tools. After Place&Route operation, FPGA chip statistics and maximum operating frequencies have been presented. The maximum operating frequencies of the proposed PRNGs range between 184 and 241 MHz. The 1 Mbit of bit streams generated by PRNGs have been subjected to NIST-800–22 randomness tests. Among 4 different proposed PRNGs, the proposed PRNGs that designed using the Elliott-93 and Cordic-LUT approaches have successfully passed all NIST-800–22 tests and have a bit production rate of 241 Mbps. The proposed secure hybrid chaos-based PRNG structures were compared with similar studies conducted in the literature in recent years. According to the results, the proposed FPGA-based secure new chaotic PRNG structures are useful in cryptographic applications.

NVM-Shelf: Secure Hybrid Encryption with Less Flip for Non-Volatile Memory

The Non-Volatile Memory (NVM), such as PRAM or STT-MRAM, is often adopted as the main memory in portable embedded systems. The non-volatility triggers a security issue against physical attacks, which is a vulnerability caused by memory extraction and snapshots. However, simply encrypting the NVM degrades the performance of the memory (high energy consumption, short lifetime), since typical encryption causes an avalanche effect while most NVMs suffer from the memory-write operation. In this paper, we propose NVM-shelf: Secure Hybrid Encryption with Less Flip (shelf) for Non-Volatile Memory (NVM), which is hybrid encryption to reduce the flip penalty. The main idea is that a stream cipher, such as block cipher CTR mode, is flip-tolerant when the keystream is reused. By modifying the CTR mode in AES block cipher, we let the keystream updated in a short period and reuse the keystream to achieve flip reduction while maintaining security against physical attacks. Since the CTR mode requires additional storage for the nonce, we classify write-intensive cache blocks and apply our CTR mode to the write-intensive blocks and apply the ECB mode for the rest of the blocks. To extend the cache-based NVM-shelf implementation toward SPM-based systems, we also propose an efficient compiler for SA-SPM: Security-Aware Scratch Pad Memory, which ensures the security of main memories in SPM-based embedded systems. Our compiler is the first approach to support full encryption of memory regions (i.e., stack, heap, code, and static variables) in an SPM-based system. By integrating the NVM-shelf framework to the SA-SPM compiler, we obtain the NVM-shelf implementation for both cache-based and SPM-based systems. The cache-based experiment shows that the NVM-shelf achieves encryption flip penalty less than 3%, and the SPM-based experiment shows that the NVM-shelf reduces the flip penalty by 31.8% compared to the whole encryption.

Improved Hybrid Precoder Design for Secure mmWave MIMO Communications

Key challenges of emerging mobile communication systems are to provide higher data rates, diverse device connectivity, low latency, higher system capacity, and low energy consumption. The communication systems exploiting the millimeter-wave (mmWave) band are realized to resolve thereof inevitable issues. However, security is considered as one of the challenging issues in mmWave communication in addition to unavoidable problems (e.g., propagation loss, penetration loss, and fading). This study aims to construct efficient secure hybrid precoder with low-resolution phase shifters that can protect legitimate information from eavesdropping by employing coordinated analog precoder and combiner algorithms and improve the secrecy rate. Moreover, in order to further enhance the secrecy rate, hybrid precoder are obtained using an efficient channel. This work compares its results with the recent approach reported in the literature, which indicates that our proposed model outperforms at high signal-to-noise ratio (SNR) values, while our model provides similar performance at low SNR values. Simulation studies also confirm the effectiveness of the proposed hybrid precoder to achieve maximum secrecy rate.

A hybrid-security model for privacy-enhanced distributed data mining

This study encompasses the proposal of a novel hybrid-security model that incorporates the benefits of both the centralised data mining system as well the distributed data mining system. The hybrid model provides two levels of security. The first security level perturbs the individual datasets by transforming it into a non-understandable form using the four-dimensional rotation transformation, and the second security level helps in performing secure distributed data mining using the ratio of secure summation protocol. The trivial data mining techniques, such as k-means clustering technique and naïve Bayes classification technique, verifies the efficiency and accuracy of the hybrid security model. The hybrid security model provides security to sensitive data without compromising the quality of the data. The accuracy obtained in classification task and clustering task using naïve Bayes and k-means technique is high when different datasets in a privacy-enhanced distributed data mining environment verify the working of the hybrid security model.

Security for whom? Analysing hybrid security governance in Africa's extractive sectors

Abstract In this article, we analyse the factors underpinning the shift towards hybrid security governance in Africa. Extant scholarship largely attributes this shift to broader global processes, such as histories of colonialism, neoliberalism and transformations in global governance, which have served to legitimize the role of private authority in security provision around sites of resource extraction. Our analysis seeks to understand the relative and relational influence of power and rules in international politics by offering empirical insights about what hybrid security arrangements look like ‘on the ground’. Drawing upon recently conducted fieldwork in Kenya, Uganda and Ghana, we examine how hybrid security arrangements affect the lives of those living near sites of natural resource extraction. Our analyses suggest that although hybrid security has emerged as the leading approach to security governance, this approach to security does not uniformly involve or serve the interests of all stakeholders. Rather, we find that hybrid security arrangements aid the security of extractive operations—securing investments in both physical and human capital—while sometimes undermining the security of nearby communities.

Enhancement of Security and QoS in Wireless Medical Sensor Networks

Wireless medical sensor networks (WMSN) collect the data of a patient’s vital body parameters using wearable or nonwearable biosensors. Since WMSN is wireless in nature there occur numerous issues like a false alarm, lack of robustness, and low processor speed, which reduce the system’s effectiveness. One of the major issues is the security and privacy protection of the collected data and providing a greater Quality of Service (QoS) for the network in terms of energy efficiency, standardization, etc. Targeting these problems, we introduced a hybrid secure and fuzzy fusion system to achieve efficient secure transmission and data fusion in WMSN. The basic idea of the proposed method is to generate a private key from specific features of the digital color image; the generated key is encrypted by the Advanced Encryption Standards (AES) mechanism. The proposed system handles the vague and imprecise data to reduce energy consumption and increases the network lifetime. The inference results verify the efficiency of the proposed method in terms of security and energy consumption of the network.

An Improved Cybersecurity Model using Cryptography and Steganography with NTRU-LSB Algorithm

Data and information has become one of the prime targets of hackers due to the sensitive nature of patients’ information. Some methods such as DES, 3DES, Blue fish and AES were used but found to be inefficient. This research aims to reduce the vulnerability of threats and increase the user satisfaction based on Embedding Capacity (EC), Mean Square Error (MSE) and Peak Signal to Noise Ratio (PSNR) on patient’s information since healthcare systems are getting very common within the society. Nth Degree Polynomial Ring Unit and Least Significant Bits were used to encrypt a text message into audio file. The research, therefore, developed a hybrid security system that can hide compressed information in audio using NTRU and LSB. The concept of cryptography and steganography was introduced to encrypt the original data by using symmetric key cryptography and to hide that data into an audio file. The proposed model was developed using MATLAB R2018(a) software. The results revealed that the proposed model is more secured in comparison to the existing model. The MSE for the proposed system is 2.4320e-06 as against 2.5321e-06 for the existing model with the peak signal to noise ratio of 156.1154 and 161.0154 for the proposed system. The proposed system has embedding capacity of 0.020 bps, while the existing system is having 2.75 bps. From the result analysis, the proposed system has performed significantly better than the existing system in terms of MSE, PSNR and embedded capacity.

Secure Hybrid Crypto-system AES/RSA on FPGA for Data Communication

With the development of information technologies, our environment is surrounded by digital data that transit via networks. When data are important, they become vulnerable to external attacks which can be avoided by using cryptography which provides confidentiality, integrity and availability required to secure digital data transactions such as e- commerce, mobile telephony and Internet. This paper deals with securing data transmitted over a network composed by a server and several clients, where a security platform has been integrated into the server and embedded on an FPGA circuit. The protection of data transfer between clients is provided by hybrid cryptography combining symmetric and asymmetric cryptographies. The security of client-server communication is ensured by the AES protocol and the Diffie-Hellman key exchange protocol. To offer a good management of keys and their sharing, a dedicated system for generating keys is designed to fit with public key infrastructures. This system is a part of the server and has been implemented using JAVA language and executed on a computer. This communication system provides a Graphical User Interface (GUI) offering to clients ease and flexibility in transferring their data.

Performance Test of WAP Gateway Over Web Server Using OPNET

The Security for the portable devices such as mobile phones,iPad and laptops becoming extremely important day by day.The intermediates such as gateway are the main source for communication through wireless media. In today's era, maintaining the transport level security amongst cellular devices like mobile phones and PDA(Personal Digital Assistant) become the most burning issue.During communications of smart phones with the web server through broadband method pass communication through the gateway known as Wireless Applications Protocol. The main purpose of WAP gateway is to transfer all the protocol used in WAP to the protocols used on the internet server. The WAP proxy server uses marshalling and unmarshalling methodology for the content to reduce the size of the data that has been sent through the wireless link. Further, the communication between the mobile phones and wireless application protocol is secured by using the security protocol called WTLS. The communication between the WAP gateway and web server is secured through the TLS/SSL security protocols. This paper simulates an assessment of wireless and wired networks using OPNET simulation tools. This paper simulated 2 different scenarios comparing wireless mobile client communication using WTLS gateway MD5_RSA encryption and Firewall gateway TLS encryption using MD5_RSA.The investigation results shows how the end to end security takes place between wireless clients to web servers using hybrid security protocol.

A Novel Hybrid Secure Image Encryption Based on the Shuffle Algorithm and the Hidden Attractor Chaos System.

Aiming at the problems of small key space, low security of encryption structure, and easy to crack existing image encryption algorithms combining chaotic system and DNA sequence, this paper proposes an image encryption algorithm based on a hidden attractor chaotic system and shuffling algorithm. Firstly, the chaotic sequence generated by the hidden attractor chaotic system is used to encrypt the image. The shuffling algorithm is used to scramble the image, and finally, the DNA sequence operation is used to diffuse the pixel value of the image. Experimental results show that the key space of the scheme reaches 2327 and is very sensitive to keys. The histogram of encrypted images is evenly distributed. The correlation coefficient of adjacent pixels is close to 0. The entropy values of encrypted images are all close to eight and the unified average change intensity (UACI) value and number of pixel changing rate (NPCR) value are close to ideal values. All-white and all-black image experiments meet the requirements. Experimental results show that the encryption scheme in this paper can effectively resist exhaustive attacks, statistical attacks, differential cryptanalysis, known plaintext and selected plaintext attacks, and noise attacks. The above research results show that the system has better encryption performance, and the proposed scheme is useful and practical in communication and can be applied to the field of image encryption.

Secure clustering-based energy efficient protocol using hybrid soft computing

A hybrid protocol is proposed which utilizes secure clustering and hybrid soft computing to improve the network lifetime. Ant colony optimization (ACO) and Particle swam optimization (PSO) with crossover operator are used to design a hybrid soft computing-based inter-cluster data aggregation. Initially, cluster heads are selected based upon adaptive threshold function. Recommendation-based signatures are then assigned to every aggregated data. Then, tree-based data aggregation comes in action and collects sensing information directly from cluster heads by utilizing short distance obtained from the hybrid soft computing. The use of compressive sensing reduces the packet size which is going to be transmitted in the sensor network. Extensive analysis shows that the hybrid protocol considerably enhances network lifetime by conserving the energy in more efficient manner than other protocols at present deployed for sensor networks.

A Novel Hybrid Secure Method Based on DNA Encoding Encryption and Spiral Scrambling in Chaotic OFDM-PON

This paper proposes a novel hybrid secure method based on improved deoxyribonucleic acid (DNA) encoding encryption and spiral scrambling in chaotic OFDM-PON for enhancing the physical-layer security. In the improved DNA encoding encryption, the odd-even cross-bit DNA encoding, base scrambling and base-level substitution are determined by chaotic sequences. For each binary and base, the selected encoding rules and base scrambling methods are dynamically changing, which enhances the robustness against malicious attacks by attackers. In the spiral scrambling process, the QAM symbol matrix is divided into several blocks, and these blocks are scrambled. In the scrambling of the plural matrix, the position where the spiral starts and the orientation and direction of the traversal are also controlled by the chaotic sequences. By employing DNA encoding encryption and spiral scrambling, a key space of $\sim \!{10^{135}}$ can be achieved in the multi-fold encryption of the proposed scheme, which can improve the physical-layer security. The encrypted 16-QAM OFDM data are successfully transmitted over a 60-km SSMF in OFDM-PON. The simulation results demonstrate that it has better BER performance at the BER of ${10^{ - 3}}$ than other schemes. The proposed encryption method can effectively protect data from attacks by eavesdroppers or illegal users.