Practical Security Research Articles

A Mutation-Based Data Enhancement Approach for Software Vulnerability Detection

Effective software vulnerability detection is paramount for ensuring the security of software systems. However, the presence of imbalanced data in extensive datasets often leads to overfitting on non-vulnerable code and suboptimal performance on vulnerable code. Traditional methods of collecting vulnerable data frequently fall short in capturing the complexities of real-world scenarios. This paper proposes a mutation-based data enhancement approach to tackle this challenge, with a focus on capturing essential traits of vulnerable source code. Our approach systematically extracts traits from extensive vulnerable source code and employs mutation operators to introduce high-level alterations. We evaluate the convergence of multiple mutation rounds using a diversity index to ensure consistent enhancements. By selecting the most effective mutation operators for subsequent model training, our approach achieves substantial accuracy improvements across diverse datasets and deep neural network models. This work represents the initial version of our approach, with continuous refinements underway to facilitate practical implementation and address real-world security challenges.

Shifting Security Left: A Guide to Cybersecurity Education for Children

This article investigates the effectiveness of tailored cybersecurity education frameworks for children and adolescents. It explores how structured learning approaches, gamified platforms, and family engagement strategies influence learning outcomes. The article, conducted over 18 months, analyzes educational progress across three age groups (7-10, 11-14, and 15-18 years), revealing significant variations in learning effectiveness and retention rates among different age cohorts. Through a systematic evaluation of multiple learning platforms and national initiatives, the research demonstrates that age-appropriate content delivery, gamified learning experiences, and consistent family involvement substantially improve cybersecurity awareness and behavioral outcomes. Key findings include notably high retention rates in elementary students when using visual and interactive content, significant improvements in practical security skills among middle school students, and advanced concept mastery in high school participants. The article also identifies critical challenges in implementation, including resource accessibility gaps, technical barriers, and varying levels of family engagement capability. These insights inform a comprehensive set of recommendations for educational framework improvements, enhanced monitoring strategies, and policy developments, providing a roadmap for advancing children's cybersecurity education. The findings contribute significantly to understanding how age-appropriate cybersecurity education can be effectively designed and implemented while highlighting the crucial role of family involvement and institutional support in developing secure digital behaviors among young users.

Practical Security of Continuous Variable Measurement- Device-Independent Quantum Key Distribution with Local Local Oscillator

Continuous-variable (CV) measurement-device-independent (MDI) quantum key distribution (QKD) can remove the feasible side-channel attacks on detectors based on the accurate Bell-state measurement (BSM), where an optical amplitude modulator (AM) plays a crucial role in managing the intensity of the transmitted light pulse. However, the AM-involved practical security has remained elusive as the operating frequency of the AM usually determines the actual secret key rate of the CV-MDI-QKD system. We find that an imperfect pulse generated from the AM at high speed can lead to a challenge to the practical security as a minor intensity change of the light pulse can bring about a potential information leakage. Taking advantage of this flaw, we suggest an attack strategy targeting the embedded AM in CV-MDI-QKD without sending the local oscillator (LO). This attack can damage the AM and thus decrease the estimated secret key rate of the system even when the orthogonal local LO (LLO) scheme is carried out. To assess the practical security risk resulting from the leaked information from the AM, we conduct numerical simulations to demonstrate the influence of the AM on the CVMDI-QKD system.

A new quantum solution to blind millionaires’ problem without an honest third party

The quantum blind millionaires’ (QBM) problem is an expanded version of the millionaires’ problem in a quantum environment. For any two sets with different members, the QBM problem represents the quantum solution of the private summation in each set and the private comparison of the results simultaneously. During it, the secrets of any participant should be protected. As a new topic in quantum secure multiparty computation (QSMC), current solutions to QBM problems usually require an honest third party to resist some potential attack strategies. However, the assumptions will affect their applicability in practical cooperative security systems. In this paper, we propose a new solution to the quantum blind millionaires’ (QBM) problem without the help of an honest third party for the first time. In our solution, the shift operations are applied to the d-dimensional 2-particle entangled states to encode the secrets of the participants. According to our analysis, the proposed solution can effectively resist typical internal and external attacks by applying the detection methods generated by the participants. We hope that the research will make positive developments for QSMC.

Towards practical quantum secure time transfer

Towards practical quantum secure time transfer

Side-channel free quantum digital signature with source monitoring

Abstract Quantum digital signature (QDS) can guarantee the information-theoretical security of a signature with the fundamental laws of quantum physics. However, most current QDS protocols do not take source security into account, leading to an overestimation of the signature rate. In this paper, we propose to utilize Hong-Ou-Mandel interference to characterize the upper-bound of the source imperfections, and further to quantify information leakage from potential side-channels. Additionally, we combine decoy-state methods and finite-size analysis in analyzing the signature rate. Simulation results demonstrate the performance and feasibility of our approach. Our current work can improve the practical security of QDS systems, thereby promoting their further networked applications.

Intensity correlations in measurement-device-independent quantum key distribution.

The intensity correlations due to imperfect modulation during the quantum-state preparation in a measurement-device-independent quantum key distribution (MDI QKD) system compromise its security performance. Therefore, it is crucial to assess the impact of intensity correlations on the practical security of MDI QKD systems. In this work, we propose a theoretical model that quantitatively analyzes the secure key rate of MDI QKD systems under intensity correlations. Furthermore, we apply the theoretical model to a practical MDI QKD system with measured intensity correlations, which shows that the system struggles to generate keys efficiently under this model. We also explore the boundary conditions of intensity correlations to generate secret keys. This study extends the security analysis of intensity correlations to MDI QKD protocols, providing a methodology to evaluate the practical security of MDI QKD systems.

Amplitude-boosting attack against practical discrete-modulated continuous-variable quantum key distribution

Discrete-modulated continuous-variable quantum key distribution offers significant practical deployment advantages due to its straightforward state preparation and high compatibility with coherent optical communication systems. However, security analysis and parameter estimation of discrete-modulated protocol are different with Gaussian-modulated protocols, which could cause different practical security problems. Herein, we investigate the amplitude-boosting attack against discrete-modulated continuous-variable quantum key distribution systems and assess its impact on system performance. Our findings reveal that this attack could cause overestimation of secret key rate perceived by Alice and Bob, thereby opening a security loophole, and the vulnerability could be severer than Gaussian modulation. Additionally, we summarize defensive countermeasures, marking a crucial step towards enhancing the practical security of discrete-modulated continuous-variable quantum key distribution.

Light-injection attack against practical continuous-variable measurement-device-independent quantum key distribution systems.

Continuous-variable measurement-device-independent quantum key distribution (CV-MDI QKD) can defend all detection-side attacks effectively. Therefore, the source side is the final battlefield for performing quantum hacking attacks. This paper investigates the practical security of a CV-MDI QKD system under a light-injection attack. Here, we first describe two different light-injection attacks, i.e., the induced-photorefractive attack and the strong-power injection attack. Then, we consider three attack cases where Eve only attacks one of the parties or both parties of the CV-MDI QKD system. Based on the analysis of the parameter estimation, we find that the legitimate communication parties will overestimate the secret key rate of the system under the effect of a light-injection attack. This opens a security loophole for Eve to successfully obtain secret key information in a practical CV-MDI QKD system. In particular, compared to the laser-damage attack, the above attacks use a lower power of injected light and have a more serious effect on the security of the system. To eliminate the above effects, we can enhance the practical security of the system by doping the lithium niobate material with various impurities or by using protective devices, such as optical isolators, circulators, optical power limiters, and narrow-band filters. Apart from these, we can also use an intensity monitor or a photodetector to detect the light-injection attack.

A Practical Security Assessment Methodology for Power System Operations Considering Uncertainty

A Practical Security Assessment Methodology for Power System Operations Considering Uncertainty

Hybrid algorithm GA-PSO-BP in secure localization technology for wireless sensor networks

ABSTRACT Wireless sensors face problems such as poor positioning accuracy in their applications. A hybrid indoor space safety positioning technology is proposed for this purpose. This technology uses genetic models and particle swarm optimization models to optimize the parameters of neural networks. Considering the vulnerability of wireless sensors to Sybil attacks during the positioning process, communication encryption and location awareness are used for optimization. In the positioning experiment, the proposed method had maximum positioning errors of 0.23 m and 0.43 m on the first and second floors, respectively, which were superior to other methods. In the positioning security experiment, the positioning errors of the first and second floors after being attacked by Sybil were 4 m and 5 m respectively, while the proposed security positioning technology had an error range of 1 m. In terms of security comparison, when there are 31–35 attack samples, the proposed method has a maximum root mean square error and average absolute error of 0.72 m and 0.79 m, respectively, which is superior to other models. It can be seen that the proposed technology has excellent positioning effect and stability. The research content will provide important technical support for the practical deployment and security management of wireless sensor networks.

Practically secure linear-map vector commitment and its applications

The primitive of vector commitment scheme allows a user to commit to an ordered sequence of messages (i.e., a vector) and later open the commitment at any position subset of the vector. The most important and desirable feature of vector commitment schemes is that the size of the opening proof is sublinear in the length of the committed vector. The original vector commitment scheme has now been extended to support several new functionalities like aggregation, updatability and homomorphism, and has applications ranging from verifiable data streaming to stateless cryptocurrency. Among these extensions, the linear-map vector commitment (LVC) scheme enables a user to open a general linear map evaluated on the committed vector, rather than those messages of the committed vector as in the original vector commitment scheme. However, the existing LVC schemes are only proved to be secure under the idealized assumptions, i.e., using the algebraic group model, which might be unpractical in the real world. To this end, we eliminate the use of algebraic group model, and propose a practically secure LVC construction. Our construction achieves practical security by additionally generating degree proofs for polynomials that enable a verifier to check the degree of polynomials publicly. We prove the security of the proposed LVC construction in the standard model under a q-type complexity assumption over bilinear groups. Moreover, we demonstrate how to use the proposed LVC scheme to construct maintainable vector commitments and verifiable data streaming protocols. The theoretical comparison and experimental results indicate that our proposal provides stronger security guarantee, while being competitive in terms of efficiency.

Controllable multi-soliton spectral tunneling by airy pulses in photonic crystal fiber

A straightforward method to induce tunable multi-soliton spectral tunneling (SST) using a finite energy Airy pulse in a photonic crystal fiber (PCF) featuring three zero-dispersion wavelengths is proposed numerically in the paper. The study reveals that the distinctive multi-envelope structure of the Airy pulse enables the control of tunneling distances, properties, and soliton numbers through modulation of its attenuation factor and peak intensity. Notably, the SST process involving the Airy pulse generates multiple blue-shifted and red-shifted dispersion waves, along with associated trapping waves, contributing to the formation of an ultra-flat and ultra-wide supercontinuum. Furthermore, the velocity and efficiency of multi-SST can be manipulated to enhance the overall tunability of the phenomenon. The findings underscore the potential application of Airy pulse-driven SST in secure multi-frequency signal transmission and controlled supercontinuum generation, with the tunability of these processes being governed by the specific attenuation factor and peak power settings of the input Airy pulse. This work advances the understanding of multi-SST dynamics in PCFs and provides a theoretical framework for exploiting these dynamics in practical information security and optical spectrum management contexts.

Space Division and WGAN-GP Based Fast Generation Method of Practical Dynamic Security Region Boundary

Fast and accurate transient stability analysis is crucial to power system operation. With high penetration level of wind power resources, practical dynamic security region (PDSR) with hyper plane expression has outstanding advantages in situational awareness and series of optimization problems. The precondition of obtaining accurate PDSR boundary is to locate sufficient points around the boundary (critical points). Therefore, this paper proposes a space division and Wasserstein generative adversarial network with gradient penalty (WGAN-GP) based fast generation method of PDSR boundary. First, the typical differential topological characterizations of dynamic security region (DSR) provide strong theoretical foundation that the interior of DSR is hole-free and the boundaries of DSR are tight and knot-free. Then, the space division method is proposed to calculate critical operation area where the PDSR boundary is located, tremendously compressing the search space to locate critical points and improving the confidence level of boundary fitting result. Furthermore, the WGAN-GP model is utilized to fast obtain large number of critical points based on learning the data distribution of the small training set aforementioned. Finally, the PDSR boundary with hyperplanes is fitted by the least square method. The case study is tested on the Institute of Electrical and Electronics Engineers (IEEE) 39-bus system and the results verify the accuracy and efficiency of the proposed method.

A Survey on Network Security Traffic Analysis and Anomaly Detection Techniques

With the increasingly severe network security situation, advanced network traffic anomaly detection techniques are urgently needed. This paper provides a comprehensive survey of the research status and latest progress in the field of network anomaly detection. Firstly, we introduce the basic concepts, common methods, and challenges of network traffic analysis, which lays the foundation for anomaly detection. Then, we systematically summarize the mainstream techniques in the anomaly detection field, including statistical methods, machine learning methods, deep learning methods, and behavior analysis methods, analyzing their basic principles, representative works, advantages and disadvantages, and applicable scenarios. Next, we focus on discussing the hybrid methods in the anomaly detection field, elaborating on the motivations, common strategies, and representative works of hybrid methods, and pointing out that hybrid methods are an important development direction for anomaly detection. In addition, the paper also summarizes the application effects of several types of methods in practical network security tasks and makes a quantitative comparison in tabular form. Finally, we prospect the future development trends of network anomaly detection techniques, proposing goals such as intelligentization, automation, federalization, and interpretability, while analyzing the challenges faced by anomaly detection, including data heterogeneity, complexity of security threats, model robustness, privacy protection, and interpretability. We argue that network anomaly detection requires interdisciplinary integration, strengthening of security big data governance, and a shift from passive defense to active immunity. As the strategic position of cyberspace security becomes increasingly prominent, driven by disruptive technologies such as big data, artificial intelligence, and blockchain, network anomaly detection will surely usher in new development opportunities and challenges.

Attack detection scheme for continuous variable quantum key distribution based on a graph neural network

The practical security of a continuous-variable quantum key distribution (CV-QKD) system is vulnerable to various attack strategies due to the significant difference between the idealized theoretical model and the practical physical system. The existing countermeasures against these attacks involve exploiting different real-time monitoring modules, which presents a challenge in effectively classifying attacks. We investigate a graph neural network (GNN)-based attack detection scheme for CV-QKD, which models data as a graph structure using three different methods for various conditions. Particularly, one of the proposed methods requires no additional devices and can detect attacks with over 99% accuracy. The algorithm can be expanded to different scenarios without additional training and can achieve a detection efficiency of more than 95%. Furthermore, our proposed scheme incorporates anomaly detection algorithms into the detection module, enabling 85% effective detection of partially unknown attacks with minimal security data.

Network security AIOps for online stream data monitoring

In cybersecurity, live production data for predictive analysis pose a significant challenge due to the inherently secure nature of the domain. Although there are publicly available, synthesized, and artificially generated datasets, authentic scenarios are rarely encountered. For anomaly-based detection, the dynamic definition of thresholds has gained importance and attention in detecting abnormalities and preventing malicious activities. Unlike conventional threshold-based methods, deep learning data modeling provides a more nuanced perspective on network monitoring. This enables security systems to continually refine and adapt to the evolving situation in streaming data online, which is also our goal. Furthermore, our work in this paper contributes significantly to AIOps research, particularly through the deployment of our intelligent module that cooperates within a monitoring system in production. Our work addresses a crucial gap in the security research landscape toward more practical and effective secure strategies.

Polar code-based secure transmission with higher message rate combining channel entropy and computational entropy

The existing physical layer security schemes, which are based on the key generation model and the wire-tap channel model, achieve security by utilizing channel reciprocity entropy and noise entropy, respectively. In contrast, we propose a novel secure transmission framework that combines noise entropy with reciprocity entropy, achieved by inserting reciprocity entropy into the frozen bits of polar codes. Note that in real-world scenarios, when eavesdroppers employ polynomial-time attacks, the bit error rate (BER) increases due to the introduction of computational entropy. To achieve indistinguishability security, we convert the practical physical layer security metric, BER, into the average min-entropy, a widely accepted concept in cryptography. The simulation results demonstrate that the eavesdropper’s BER can be significantly increased without compromising the communication performance of the legitimate receiver. Under concrete parameters we selected, when compared to the joint scheme of physical layer key generation and one time pad, the modular semantically-secure scheme based on the wire-tap channel model, and the simple channel entropy combination scheme, our scheme achieves a message rate approximately 1.2 times, 3.8 times, and 1.4 times better, respectively. Experimental testing validates the feasibility of our scheme.

HARNESSING AI FOR CYBER SECURITY CHALLENGES

Although human beings possess intelligence but still lack the capabilities to understand the problem and in finding solutions to them. However, when it comes to mitigating errors in operational tasks and finding deviations, artificial intelligence is leading human ability and is competing in every domain. Artificial intelligence is contributing in assessing errors that human beings are making vulnerably. It can help to protect organizations from Internet threats, identify types of malware, ensure practical security standards and help create better prevention and recovery strategies as a solution to cyber security. In this research paper, it is highlighted on how AI technologies and applications can contribute to cyber security, the opportunities provided by AI to different people and organisations and the potential challenges faced while relying completely on AI. The recommendations while implementing AI solutions are discussed followed by conclusion in the end.

Highly stable power control for chip-based continuous-variable quantum key distribution system.

Quantum key distribution allows secret key generation with information theoretical security. It can be realized with photonic integrated circuits to benefit the tiny footprints and the large-scale manufacturing capacity. Continuous-variable quantum key distribution is suitable for chip-based integration due to its compatibility with mature optical communication devices. However, the quantum signal power control compatible with the mature photonic integration process faces difficulties on stability, which limits the system performance and causes the overestimation of a secret key rate that opens practical security loopholes. Here, a highly stable chip-based quantum signal power control scheme based on a biased Mach-Zehnder interferometer structure is proposed, theoretically analyzed, and experimentally implemented with standard silicon photonic techniques. Simulations and experimental results show that the proposed scheme significantly improves the system stability, where the standard deviation of the secret key rate is suppressed by an order of magnitude compared with the system using traditional designs, showing a promising and practicable way to realize a highly stable continuous-variable quantum key distribution system on chip.