Leak Secret Information Research Articles

Improved Hybrid Bagging Resampling Framework for Deep Learning-Based Side-Channel Analysis

As cryptographic implementations leak secret information through side-channel emissions, the Hamming weight (HW) leakage model is widely used in deep learning profiling side-channel analysis (SCA) attacks to expose the leaked model. However, imbalanced datasets often arise from the HW leakage model, increasing the attack complexity and limiting the performance of deep learning-based SCA attacks. Effective management of class imbalance is vital for training deep neural network models to achieve optimized and improved performance results. Recent works focus on either improved deep-learning methodologies or data augmentation techniques. In this work, we propose the hybrid bagging resampling framework, a two-pronged strategy for tackling class imbalance in side-channel datasets, consisting of data augmentation and ensemble learning. We show that adopting this framework can boost attack performance results in a practical setup. From our experimental results, the SMOTEENN ensemble achieved the best performance in the ASCAD dataset, and the basic ensemble performed the best in the CHES dataset, with both contributing over 70% practical improvements in performance compared to the original imbalanced dataset, and accelerating practical attack space in comparison to the classical setup of the attack.

SIHNet: A safe image hiding method with less information leaking

AbstractImage hiding is a task that hides secret images into cover images. The purposes of image hiding are to ensure the secret images are invisible to the human and the secret images can be recovered. The current state‐of‐the‐art steganography methods run the risk of secret information leakage. A safe image hiding network (SIHNet) is presented to reduce the leakage of secret information. Based on some phenomena of image hiding methods which use invertible neural network, a reversible secret image processing (SIP) module is proposed to make the secret images suitable for hiding and make the stego images leak less secret information. Besides, a reversible lost information hiding (LIH) module is used to hide the lost information into the cover images, thus the method can recover the secret images better than the method that uses random noise to replace the lost information. Experimental results show that SIHNet outperforms other state‐of‐the‐art methods on the PSNR and SSIM values of the recovered secret images and the stego images. Besides, residual images of other state‐of‐the‐art methods all contain information about secret images while residual images of SIHNet leak almost no secret information. Thus the method can prevent the listener of transmission channel from obtaining the information of the secret image through the residual image, which means SIHNet performs better in security than other state‐of‐the‐art methods.

Screen‐shooting resistant robust document watermarking in the Discrete Fourier Transform domain

AbstractMetaverse's augmented reality (AR) function allows virtual information to be seamlessly superimposed onto real scenes through the camera of a head‐mounted device. However, this raises concerns about privacy protection and copyright authentication when transmitting cross‐media information. Additionally, there is a risk of secret information leakage due to screen candid shooting in the real world. Ensuring information security and copyright authentication in case of unauthorized screen capturing is crucial. To prevent information loss and interference from cross‐media transfer between screens and cameras, we implement digital watermarking for copyright protection. We have proposed an innovative framework for automatic document watermarking that can resist screen‐shooting. Our approach involves embedding a ring watermark in the document underlay. On the extraction side, the watermark extraction process is divided into three key steps: automatic location, automatic correction, and automatic extraction. First, the document image is located in the covert photography. Then, perspective correction is performed based on the text line features of the document. Finally, the watermark information is extracted by combining the ring watermark features. Our method is capable of automatically extracting watermarks from covert photography while considering aspects such as concealment, robustness, and visual quality. The watermark is embedded in the document underlay, which ensures good visual quality and does not affect the normal reading and editing. We also propose various embedding strength schemes that can adapt to different usage scenarios, providing resistance to screen‐shooting or screenshot attacks, as well as various noise attacks. Through extensive experiments, we have demonstrated the feasibility of the proposed automated framework and the robustness of the watermarking algorithm, as well as the superiority and broad application prospects of our method.

An Automated Framework for Board-Level Trojan Benchmarking

Economic and operational advantages have led the supply chain of printed circuit boards (PCBs) to incorporate various untrusted entities. Any of the untrusted entities are capable of introducing malicious alterations to facilitate a functional failure or leakage of secret information during field operation. While researchers have been investigating the threat of malicious modification within the scale of individual microelectronic components, the possibility of a board-level malicious manipulation has essentially been unexplored. In the absence of standard benchmarking solutions, prospective countermeasures for PCB trust assurance are likely to utilize homegrown representation of the attacks that undermine their evaluation and do not provide scope for comparison with other techniques. In this article, we have developed a benchmarking solution to facilitate an unbiased and comparable evaluation of countermeasures applicable to PCB trust assurance. Based on a taxonomy tailored for PCB-level alterations, we have developed a toolflow for the automatic generation of Trojan benchmarks to facilitate a comprehensive evaluation against a large number of diverse Trojan implementations and application of data mining for trust verification. Using the toolflow, we have developed a suite of custom “Trojan benchmarks” (i.e., PCB designs with Trojans) containing representative examples of Trojans in the taxonomy inserted in different PCB designs of varying complexity and functionality. Finally, with experimental measurements from a fabricated PCB and structural analysis of netlist, we analyze the stealthiness of the Trojan designs and present the runtime of the tool for a large number of PCB designs.

BLAST: Belling the Black-Hat High-Level Synthesis Tool

A hardware Trojan (HT) is a malicious modification of the design done by a rogue employee or a malicious foundry to leak secret information, create a backdoor for attackers, alter functionality, degrade performance and even halt the system. In Black-hat high-level synthesis (HLS) (Pilato et al., 2019), the authors have introduced a possibility of HTs insertion in the register transfer level (RTL) design by the HLS tool itself. Specifically, degradation attack (DA), battery exhaustion (BE) attack, and downgrade attack (DG) have been proposed in that work. In this study, we show how all three HTs inserted by Pilato et al. (2019) can be detected using a C-to-RTL equivalence checking framework. We have assumed that both the input C code and the Trojan-infected RTL code are available for our analysis. Specifically, our framework extracts an RTL-level finite-state machine with datapaths (RTL-FSMDs) from the HLS-generated RTL. During finite-state machine with datapath (FSMD) construction, a BE attack can be identified. Our proposed method then compares the FSMD of the input C code with the RTL-FSMD to identify the DA and the DG. The experimental results confirm the detection of HTs of the black-hat HLS tool.

A Group Covert Communication Method of Digital Currency Based on Blockchain Technology

With the rapid development of the Internet, it has become a hot spot in protecting important information from illegal theft and destruction during network transmission. The characteristics of strong robustness, anonymity and distributed transmission in blockchain technology can precisely make up for the disadvantages faced by traditional covert communication in transmitting important data, such as poor robustness, easy exposure of participants and difficulty in achieving group covert transmission. Therefore, a group steganography method for digital currency based on blockchain technology is proposed in this paper. In this method, an index matrix of address interaction is designed for group covert communication, using the address interaction relationship and transaction amount to hide secret message alternately, the transaction hiding secret message is published on the blockchain. In different groups, the receivers use different keys to extract different secret message. The method proposed also introduces a fine-grained group division mechanism to control the spread of secret information and reduce the risk of secret information leakage. And the application scenarios of the method proposed are more universal, breaking the limitation of using a single digital currency for covert communication on the blockchain. In addition, the proposed method modulates the number of addresses reasonably by sensing the generation time of the block, enhancing the concealment of the method. Through practical tests on a variety of mainstream digital currencies, the experimental results show that digital currencies with smaller block generation times need to consume less embedding time.

A Sponge-Based Key Expansion Scheme for Modern Block Ciphers

Many systems in use today require strong cryptographic primitives to ensure confidentiality and integrity of data. This is especially true for energy systems, such as smart grids, as their proper operation is crucial for the existence of a functioning society. Because of this, we observe new developments in the field of cryptography every year. Among the developed primitives, one of the most important and widely used are iterated block ciphers. From AES (Advanced Encryption Standard) to LEA (Lightweight Encryption Algorithm), these ciphers are omnipresent in our world. While security of the encryption process of these ciphers is often meticulously tested and verified, an important part of them is neglected—the key expansion. Many modern ciphers use key expansion algorithms which produce reversible sub-key sequences. This means that, if the attacker finds out a large-enough part of this sequence, he/she will be able to either calculate the rest of the sequence, or even the original key. This could completely compromise the cipher. This is especially concerning due to research done into side-channel attacks, which attempt to leak secret information from memory. In this paper, we propose a novel scheme which can be used to create key expansion algorithms for modern ciphers. We define two important properties that a sequence produced by such algorithm should have and ensure that our construction fulfills them, based on the research on hashing functions. In order to explain the scheme, we describe an example algorithm constructed this way, as well as a cipher called IJON which utilizes it. In addition to this, we provide results of statistical tests which show the unpredictability of the sub-key sequence produced this way. The tests were performed using a test suite standardized by NIST (National Institute for Standards and Technology). The methodology of our tests is also explained. Finally, the reference implementation of the IJON cipher is published, ready to be used in software. Based on the results of tests, we conclude that, while more research and more testing of the algorithm is advised, the proposed key expansion scheme provides a very good generation of unpredictable bits and could possibly be used in practice.

Selective Noise Based Power-Efficient and Effective Countermeasure against Thermal Covert Channel Attacks in Multi-Core Systems

With increasing interest in multi-core systems, such as any communication systems, infra-structures can become targets for information leakages via covert channel communication. Covert channel attacks lead to leaking secret information and data. To design countermeasures against these threats, we need to have good knowledge about classes of covert channel attacks along with their properties. Temperature–based covert communication channel, known as Thermal Covert Channel (TCC), can pose a threat to the security of critical information and data. In this paper, we present a novel scheme against such TCC attacks. The scheme adds selective noise to the thermal signal so that any possible TCC attack can be wiped out. The noise addition only happens at instances when there are chances of correct information exchange to increase the bit error rate (BER) and keep the power consumption low. Our experiments have illustrated that the BER of a TCC attack can increase to 94% while having similar power consumption as that of state-of-the-art.

Исследование методов защиты конфиденциальных данных

The article analyzes the main methods of protecting confidential information. Organizational and technical measures to protect it are considered. Criteria for an adequate assessment of methods for protecting confidential data are highlighted. Within the framework of experimental studies, the best method of protecting confidential data has been identified. Currently, much attention is paid to the protection of confidential information - that is, information that a limited number of people have the right to access. This may be personal data of citizens or secrets of commercial activity of firms, official and state secrets, or materials of legal proceedings. As a result of the leakage of secret information, there is a loss of customers, a decrease in income, etc. Attackers can seize valuable information, damage the reputation of citizens, gain access to bank accounts, private and state secret documents. To ensure the protection of confidential information, not only the development of separate mechanisms and methods of protection is required, but a whole systematic approach is needed - a set of measures, such as the use of software and hardware, engineering and cryptographic tools; legal and organizational measures. The complex nature of protection arises from the complex actions of intruders who seek to obtain important information for them by any means. Among the methods of preserving confidential data, the most common are: data certification, licensing, categorization, certification. Disclosure of confidential information is one of the main security threats. The implementation of threats is the result of one of the actions and events: disclosure of confidential information, leakage of confidential information and unauthorized access to protected information. In case of disclosure or leakage, the confidentiality of restricted access information is violated.

Deep Multi-Image Steganography with Private Keys

In this paper, we propose deep multi-image steganography with private keys. Recently, several deep CNN-based algorithms have been proposed to hide multiple secret images in a single cover image. However, conventional methods are prone to the leakage of secret information because they do not provide access to an individual secret image and often decrypt the entire hidden information all at once. To tackle the problem, we introduce the concept of private keys for secret images. Our method conceals multiple secret images in a single cover image and generates a visually similar container image containing encrypted secret information inside. In addition, private keys corresponding to each secret image are generated simultaneously. Each private key provides access to only a single secret image while keeping the other hidden images and private keys unrevealed. In specific, our model consists of deep hiding and revealing networks. The hiding network takes a cover image and secret images as inputs and extracts high-level features of the cover image and generates private keys. After that, the extracted features and private keys are concatenated and used to generate a container image. On the other hand, the revealing network extracts high-level features of the container image and decrypts a secret image using the extracted feature and a corresponding private key. Experimental results demonstrate that the proposed algorithm effectively hides and reveals multiple secret images while achieving high security.

Modulation leakage vulnerability in continuous-variable quantum key distribution

Flaws in the process of modulation, or encoding of key bits in the quadratures of the electromagnetic light field, can make continuous-variable quantum key distribution systems susceptible to leakage of secret information. Here, we report such a modulation leakage vulnerability in a system that uses an optical in-phase and quadrature modulator to implement a single sideband encoding scheme. The leakage arises from the limited suppression of a quantum-information-carrying sideband during modulation. Based on the results from a proof-of-concept experiment, we theoretically analyze the impact of this vulnerability and show that the leakage reduces the range over which secret key can be obtained, and can even lead to a security breach, if disregarded. We also study the efficacy of additional trusted noise to counter this vulnerability.

A Refinement of Key Mismatch Attack on NewHope

Abstract NewHope cryptosystem is one of the second-round submissions of the National Institute of Standards and Technology post-quantum cryptography standardization process, which is a suite of two key encapsulation mechanisms based on the ring-learning with errors (LWE) problem. It has received much attention from the research community due to its small key size and high efficiency. Recently, three key mismatch attacks are proposed against NewHope under the condition of key reuse. They do not solve the ring-LWE instance directly but exploit the leakage of secret information. As far as we know, the best result is given by Okada et al. ((2020) Improving Key Mismatch Attack on NewHope with Fewer Queries. In Proc. of the 25th Australasian Conf. on Information Security and Privacy, Perth, WA, Australia, November 30–December 2, pp. 505–524. Springer Cham, Switzerland), which recovers the whole secret with a success probability of $97\%$ and $233,803$ average queries. In this paper, we further improve the key mismatch attack of NewHope by reducing the average queries to $106,577$ and raising the success probability to $100\%$. Moreover, we analyze the key mismatch attack without key reuse for the first time and we propose a combinatorial attack against NewHope1024. The total complexity of the combinatorial attack is $2^{253}$, which is lower than the complexity of primal attack and the claimed security strength of NewHope1024.

MADP-IIME: malware attack detection protocol in IoT-enabled industrial multimedia environment using machine learning approach

Internet of Things (IoT) is one of the fastest-growing technologies. With the deployment of massive and faster mobile networks, almost every daily-use item is connected to the Internet. IoT-enabled industrial multimedia environment is used for the collection and analysis of different types of multimedia data (i.e., images, videos, audios, etc.). This multimedia data is generated by various types of smart devices like drones, robots, smart controller, smart surveillance system which are deployed for the industrial monitoring and control. The multimedia data is generated in the enormous amount which can be considered as the big data. This data is further utilized in various types of business needs for example, chances of fire accidents in the industrial plant, overall machine health, etc., which can be predicted through the application of big data analytics. Therefore, IoT-enabled industrial multimedia environment is very helpful to the concerned authorities as they come to know the important information in advance. However, all the smart devices are connected and controlled through the Internet. It further causes severe threats to the communication happens in an IoT-enabled industrial multimedia environment. It is vulnerable to various types of attacks such as replay, man-in-the-middle, impersonation, secret information leakage, sensitive information modification, and malware injection (i.e., mirai). Therefore, it is important to prevent the communication of such an environment against the different types of possible attacks. These days, the attacks performed by botnets (i.e., malware attacks such as mirai and reaper) have drawn attention to the researchers. Under the influence of such attacks, the communication of IoT-enabled industrial multimedia environment is disrupted. Moreover, the attackers may also control the smart devices remotely and can change their functionalities. Hence, we need some robust mechanism to detect the presence of the malware attacks in such an environment. In this paper, we propose a malware detection mechanism in IoT-enabled industrial multimedia environment with the help of machine-learning approach, which is named as MADP-IIME. MADP-IIME uses four different types of machine learning methods (i.e., naive bayes, logistic regression, artificial neural networks (ANN) and random forest) to detect the presence of malware attacks successfully. Furthermore, MADP-IIME performs better than other related existing schemes and achieves $$99.5 \%$$ detection and $$0.5 \%$$ false positive rate. In addition, the conducted security analysis proves the resilience of the proposed MADP-IIME against different types of malware attacks.

Quantum Secret Sharing Based on Continuous-Variable GHZ States

Based on the continuous-variable GHZ states, an efficient (n, n) quantum secret sharing protocol is designed, where the Dealer can distribute the various shares to different participants at one time. Likewise, every participant can transfer the same message (share) to other participants simultaneously in the secret recovery process. In this way, the cost of time and quantum photons sharply decreases. What’s more, the proposed QSS is proved to be feasible in the terrible quantum channel with low transmission efficiency and be secure without any secret information leakage under the participant attack.

On the feasibility of using evolvable hardware for hardware Trojan detection and prevention

Evolvable hardware (EH) architectures are capable of changing their configuration and behavior dynamically based on inputs from the environment. In this paper, we investigate the feasibility of using EH to prevent Hardware Trojan Horses (HTHs) from being inserted, activated, or propagated in a digital electronic chip. HTHs are malicious hardware components that intend to leak secret information or cause malfunctioning at run-time in the chip in which they are integrated. We hypothesize that EH can detect internal circuit errors at run-time and reconfigure to a state in which the errors are no longer present. We implement a Virtual Reconfigurable Circuit (VRC) on a Field-Programmable Gate Array (FPGA) that autonomously and periodically reconfigures itself based on an Evolutionary Algorithm (EA). New VRC configurations are generated with an on-chip EA engine.We show that the presented approach is applicable in a scenario in which (1) the HTH-critical areas in the circuit are known in advance, and (2) the VRC is a purely combinatorial circuit, as opposed to the on-chip memory holding the golden reference, which requires one or more cycles to be read/written. We compare two different approaches for protecting the system against HTHs: Genetic Programming (GP) and Cartesian Genetic Programming (CGP). The paper reports on experiments on four benchmark circuits and gives an overview of both the limitations and the added value of the presented approaches.

A Novel Grayscale Image Steganography Scheme Based on Chaos Encryption and Generative Adversarial Networks

This article proposes a novel grayscale image steganography scheme that is capable of hiding an encrypted secret image into a cover image of the same size. The secret image is encrypted using the chaos encryption technology before being hidden. The encrypted image and cover image are then transformed into the steg image by a convolutional neural network (CNN). Also, a generative adversarial network (GAN) is adopted to produce a more realistic steg image, whose appearance is difficult to distinguish from the cover image. The steganography scheme is composed of three CNNs which are regarded as hiding network, discriminative network, and extracting network, respectively. Additionally, a new weight allocation mechanism is introduced to ensure the balanced training procedure of hiding-extracting networks. The obtained experimental results show that the proposed scheme not only solved the problems of secret information leakage and color distortion of the current mainstream methods but also maintain high embedding capacity. Compared with other methods, the average values of the PSNR and SSIM of our steg images can reach 0.987 and 42.3, respectively. And the quality of the reconstructed secret images is also advantageous.

LiKe: Lightweight Certificateless Key Agreement for Secure IoT Communications

Certificateless public-key cryptography (CL-PKC) schemes are particularly robust against the leakage of secret information stored on a trusted third party (TTP). These security features are particularly relevant for Internet of Things (IoT) domains, where the devices are typically preconfigured with secret keys, usually stored locally on the TTP for following maintenance tasks. Despite some contributions already proposed for the adoption of CL-PKC schemes in constrained IoT devices, current solutions generally require high message overhead, are computationally demanding, and place a high toll on the energy budget. To close this gap, we propose LiKe, a lightweight pairing-free certificateless key agreement protocol suitable for integration in the latest ZigBee 3.0 protocol stack and constrained IoT devices. LiKe is an authenticated key agreement protocol characterized by: 1) ephemeral cryptographic materials; 2) support for intermittent connectivity with the TTP; 3) lightweight rekeying operations; and 4) robustness against impersonation attacks, even when information stored on the TTP is leaked. LiKe has been thoroughly described, and its security properties have been proved via formal tools. Moreover, we have implemented and tested it on real IoT devices, in networks with up to 11 nodes-the source code has been released as an open source. Results are striking: on the OpenMote-b hardware platform, LiKe requires a total time of 3.259 s to establish session keys on each participating device, and at most 0.258% of the overall battery capacity, emerging as a lightweight and energy-friendly solution. Finally, comparisons with competing solutions do show the superior quality and viability of our proposal.

CA-Based Detection of Coherence Exploiting Hardware Trojans

Nowadays, Hardware Trojan threats have become inevitable due to the growing complexities of Integrated Circuits (ICs) as well as the current trend of Intellectual Property (IP)-based hardware designs. An adversary can insert a Hardware Trojan during any of its life cycle phases — the design, fabrication or even at manufacturing phase. Once a Trojan is inserted into a system, it can cause an unwanted modification to system functionality which may degrade system performance or sometimes Trojans are implanted with the target to leak secret information. Once Trojans are implanted, they are hard to detect and impossible to remove from the system as they are already fabricated into the chip. In this paper, we propose three stealthy Trojan models which affect the coherence mechanism of Chip Multiprocessors’ (CMPs) cache system by arbitrarily modifying the cache block state which in turn may leave the cache line states as incoherent. We have evaluated the payload of such modeled Trojans and proposed a cellular automaton (CA)-based solution for detection of such Trojans.

A Hybrid-Based Verifiable Secret Sharing Scheme Using Chinese Remainder Theorem

It is not always in the best interests to rely on an individual to have control of entire sensitive information. This has led to the need for secret sharing schemes, which divide secret (key) among many participants or shareholders. To avoid any cheating by any of the shareholders, the need for verifiable secret sharing (VSS) has emerged. In this context, a hybrid approach for VSS scheme is suggested in this paper. The proposed algorithm shares multiple secrets among shareholders, where shareholders are also divided/classified into different levels. Hence, it includes multiple as well as multilevel secret sharing. Secrets can be recovered at intra- or inter-level, where shareholders of higher level can contribute their shares to lower levels. To reduce the complexity, the one-way hash function is used instead of the hard number-theoretic problems. The proposed scheme stands against the dishonest dealer and shareholders. To rule out a typical dishonest strategy of leaking secret information in the valid shares, the concept of dealer leakage resilience is used by reducing the dealer’s powers of selecting random values on his own. The execution is also done using cryptographic libraries. Finally, it is demonstrated that the scheme satisfies the security requirements of VSS.

Portable and writable photoluminescent chalk for on-site information protection on arbitrary substrates

Information protection is particularly important for secure communication between parties, avoiding the leakage of secret information to unknown parties. Among various strategies used for information protection in the previous reports in the literature, security inks made from photoluminescent materials are the most widely investigated. The security inks suffer from the drawbacks such as lack of universality on various substrates. In this work, we provide a promising new complement to the security ink-based protection techniques. We report a kind of portable photoluminescent chalk made from lanthanide-doped ultralong hydroxyapatite nanowires, which can directly write the covert information at anytime and anyplace on arbitrary surfaces and substrates including paper sheets, metals, fabrics, plastics, woods, walls, foams, leaves, and even human body. The as-written original information cannot be recognized under the ambient light, but it is readable upon exposure to the ultraviolet light. In this work, the dual and triple encryption strategies are also provided for the high-level information protection. It is expected that the versatile, convenient, and user-friendly strategy demonstrated herein is promising for the on-site secret information protection.