Information Leakage Research Articles

Decency or devilment: the impact of blockchain technology on product line design

ABSTRACT Blockchain is a secure database shared across a network of all participants, characterised by immutability, openness, transparency, and traceability. Therefore, blockchain technology is widely used in supply chain management, which can increase consumers' understanding of product information when goods arrive at the consumer end and increase the risk of consumer privacy information leakage. Considering a supply chain system that consists of a manufacturer and a platform, this paper studies the strategic interactions between the platform's adoption of blockchain technology and the manufacturer's product line design based on blockchain's positive and negative impacts on consumers. We examine the driving factors of the platform's use of blockchain technology, which are related to the effect of information transparency and privacy concerns caused by blockchain and the marginal production cost coefficient. In particular, a higher marginal production cost coefficient could make the platform more likely to use blockchain technology. We also find that the practice of blockchain technology may incentivize a manufacturer to extend its product line.

The dynamics of informed trading around corporate bankruptcies

We investigate the dynamics of informed trading both before and after corporate bankruptcy announcements using high frequency data. Our findings reveal that pre-announcement informed selling attenuates subsequent announcement returns, with this effect being weaker for firms receiving extensive pre-announcement media coverage or adverse news sentiment. We also find that post-announcement informed trading can serve as a predictor of subsequent bankruptcy outcomes. Overall, results are consistent with there being material information leakage, warranting policy efforts to better safeguard less informed investors.

Optimization of Network Security Intelligent Early Warning System Based on Image Matching Technology of Partial Differential Equation

In order to effectively avoid network information leakage and computer network paralysis, and improve the ability of computer network security early warning, it is necessary to design a computer network security intelligent early warning system based on network behavior. Security warning is considered as the second defense mechanism behind the firewall. It can monitor and warn the network without affecting the network performance, so as to provide real-time protection for external attacks, internal attacks and misoperations, and improve the network security. This paper designs an intelligent early warning system for network security based on partial differential equation image matching technology. The system adopts B/S development mode, and the server and browser are located in the campus network. Data fusion technology is used to assess network security, predict potential threats, and add new intrusion features to the feature database for subsequent use. In this paper, a target matching algorithm based on partial differential equation is proposed by using partial differential equation. The algorithm calculates the phase difference through the algebraic combination of orthogonal filter outputs. For scenes with continuous disparity changes, the error matching rate of this algorithm is lower than that of Michael Bleyer algorithm and vertical constraint algorithm. In general, the disparity map generated by this algorithm has high matching accuracy. The results show that the distribution of alarm information is reasonable and in line with the actual situation.

NotaryVault: Secure Document Authentication on Blockchain

The Notarial Office(NO), working on providing various essential certificates, still relies on manual handling and requires paper materials from other government departments. That brings lots of inconvenience. The Notarial Office rejects non-local paper materials for their lower credibility in the local place and then cannot provide cross-border services. It also easily causes sensitive information leakage as copies of paper materials have been stored. In this case, a blockchain-based system is suitable to address challenges in this scenario because of its advantages (e.g, decentralized, immutability, transparency, auditability). We implemented this system on top of the Hyperledger Fabric. Moreover, we replace manual operations with smart contracts, set extra ledgers to off-load different types of transactions and provide encryption for private information when needed. In the end, we get the expected result. That is, the modification outperformed the unmodified network in experiments.

Features of liability for cyber-attacks in EU countries

The article is devoted to the peculiarities of responsibility for cyber-attacks in the countries of the European Union. It is noted that cyber-attacks on state bodies can be a component of cyber war or hybrid war and at the same time pose a threat to national and global security, as they can lead to the leakage of important information, disrupt the operation of state systems and lead to various negative consequences. So, for example, in Europe, the main goals of hackers from 2022, in addition to Ukraine, became Poland, the Baltic countries, Northern Europe and Germany. The share of cyberattacks on European Union (EU) countries increased from about 10% in the first quarter of 2022 to almost 50% in 2023. In total, 162 cyber-attacks were carried out on Ukraine in 2022; to Poland – 114; Estonia, Lithuania and Latvia – 157; Sweden, Norway, Denmark and Finland – 95, Germany – 57.
 An increase in the activity of cyber-attacks on the networks of the energy sector, the diplomatic corps, law enforcement agencies, the defense complex, state enterprises and media companies has been established. The main goal of these attacks is to damage the country’s critical infrastructure. Globally, there has been a steady trend towards an increase in the number of targeted cyber-attacks on critical infrastructure facilities in recent years. And therefore, in connection with the possible negative consequences in the case of the implementation of cyber-attacks, it is important to note that ensuring the effective functioning of the country’s cyber defense system remains a high-priority task. Each year underscores the urgency of this challenge as threats in cyberspace continue to grow and become more highly specialized.
 It was concluded that their public attribution will be important for determining possible responsibility in the countries of the European Union for a cyber-attack, which will include the identification and public announcement of who is behind a specific cyber-attack that affects state, commercial or other objects.

LPG CYLINDER AUTO FILLING AND GAS LEAKAGE DETECTION

The project "LPG Cylinder Auto Filling and Gas Leakage Detection" integrates IoT technology for automating the LPG cylinder filling process and detecting gas leakages. The system utilizes a Load Cell connected to a Node MCU to measure the weight of the cylinder. Concurrently, a gas sensor interfaced with an Arduino board detects any gas leakages. Through serial communication between the Node MCU and Arduino, the weight data from the Load Cell is transmitted to the Arduino, which then displays both the weight information and gas leakage status on an LCD display. Additionally, a Python installed PC is employed to facilitate email notifications. Upon detecting a gas leak or a decrease in weight, the Arduino sends this information to the Python PC via serial communication. Subsequently, email alerts are generated and sent to the designated recipients, notifying them of the detected gas leakage and the need for refilling the cylinder. Moreover, in case of a gas leak, the system activates a pump to initiate the refilling process. Through this integrated approach, the project aims to enhance safety and efficiency in LPG cylinder management. Keywords : Node MCU, Arduino UNO, Gas sensor, Load cell, Python installed PC, Buzzer, Relay, DC Motor.

Contesting American hegemony: attacks to US scientific initiatives in Cold War Europe (and means to secretly defy these challenges)

ABSTRACT This article focuses on the French communist scientists’ attack, executed in 1953, on US initiatives for the promotion of science in Europe. Collated in the anonymous booklet Un plan U.S.A. de mainmise sur la science, these accusations caused a sensation in the already tense political climate of the early 1950s by alleging that American initiatives offered cover to intelligence operations, and a chokehold on the development of European science. While US government agencies never offered an official comment on these indictments, in great secrecy their officials sought to find out about the booklet’s authors, identify potential leaks of restricted information that might have informed its completion, and reorient science initiatives in Europe because of what the communist propaganda exposed. This essay thus argues that US efforts to reduce the impact that the publication had in France (and Western Europe more generally) played a role in shaping American hegemony, since finding ways to deflate the influence of dissenting voices in European science, at times stealthily, was as decisive as consensus building through the strengthening of transatlantic scientific relations.

PowerScout: Security-Oriented Power Delivery Network Modeling for Side-Channel Vulnerability Analysis

The growing complexity of modern electronic systems leads to the design of more sophisticated power delivery networks (PDNs). Similar to other system-level shared hardware resources, the on-board PDN unintentionally introduces side channels across design layers and voltage domains which are not explicitly specified in the functional specification. Recent works have demonstrated that the exploitation of the side channel can compromise the system security such as information leakage and fault injection. In this work, we systematically investigate the PDN-based side channel as well as potential countermeasures. To facilitate this goal, we develop PowerScout, a security-oriented PDN simulation framework that unifies the modeling of different PDN-based side-channel attacks. PowerScout performs a fast nodal analysis of complex PDNs at the system level to quantitatively evaluate the severity of side-channel vulnerabilities. With the support of PowerScout, for the first time, we validate PDN side-channel attacks in the literature via simulation. Furthermore, we are able to quantitatively measure the security impact of PDN parameters and configurations. For example, towards information leakage, removing near-chip capacitors can increase intra-chip information leakage by a maximum of 23.23 dB at mid-frequency range and inter-chip leakage by an average of 31.68 dB at mid- and high-frequency range. Similarly, the optimal toggling frequency and duty cycle are derived to achieve fault injection attacks with higher success rate and more precise control. In addition, the vulnerabilities are evaluated when hiding-based countermeasures are implemented. Based on the evaluation, we can understand the optimal defense configuration and explore the trade-off between information leakage mitigation and power supply stability.

Defining and Controlling Information Leakage in US Equities Trading

We present a new framework for defining information leakage in the setting of US equities trading, and construct methods for deriving trading schedules that stay within specified information leakage bounds. Our approach treats the stock market as an interactive protocol performed in the presence of an adversary, and draws inspiration from the related disciplines of differential privacy as well as quantitative information flow. We apply a linear programming solver using examples from historical trade and quote (TAQ) data for US equities and describe how this framework can inform actual algorithmic trading strategies.

Causality between streaks and bursts in wall-bounded turbulence

We use an information-theoretic method, referred to as information flux, to quantify the causal relationships between streaks and bursts in a non-intrusive manner. Within this framework, causality is quantified as the flux of Shannon information from the present of the quantities of interest to their future. We also use the so-called information leak to measure the information that is not accounted for due to unobserved variables. We investigate data from a direct numerical simulation of turbulent channel flow at the friction Reynolds number Re τ ≈ 180. The spatial distribution of causality is investigated as two time scales based on 50% value of the information leak and maximum of the normalized cross-induced information flux. It is found that the most causal spatial configuration for streaks and bursts is always streamwise-aligned. Furthermore, four dominant causal spatial configurations between streaks and bursts are identified. At the short time scale around 10 viscous units (when information flux is 50%), streaks and bursts have comparable causality to one another. At the longer time scale (corresponding to the maximum cross-induced causality), there is greater causality from streaks to bursts.

PSYCHOLOGICAL CULTURE OF MODERN YOUTH: THREATS AND PROBLEMS OF VIRTUAL SOCIAL SPACE

The essence of such concepts as "information culture", "information literacy" and "information worldview" is considered. The conclusion is made about the high level of penetration of information technologies into the lives of modern youth, but the insufficient level of information literacy and information worldview among young people. Based on a quantitative sociological study, the key threats to modern youth arising in the information space are identified. Among the most acute problems for modern youth, we have attributed: Internet addiction of young people, the rupture of real social ties and their substitution with virtual connections, loss of personal freedom, leakage of personal information, involvement in criminal and destructive groups through the Internet. It was noted that the more actively virtual space replaces real social connections, the newer threats are recorded in the Internet space. It has been established that criminal work on the Internet is especially active against teenagers. It is determined that the level of information culture among young people is correlated with age. The younger the respondents, the lower their level of information culture. It is concluded that social norms in the virtual space lag behind specific practices. Thus, modern society needs to more actively develop rules and norms of behavior in a new environment for it -the virtual space. The recommendation is given to develop the norms of information culture and cultural competencies among young people more actively. Educational programs should include issues of information literacy, including information security. All organizations working with young people need to step up their efforts toraise awareness of personal information security issues, especially among young people.

SoK: Secure Human-centered Wireless Sensing

Human-centered wireless sensing (HCWS) aims to understand the fine-grained environment and activities of a human using the diverse wireless signals around him/her. While the sensed information about a human can be used for many good purposes such as enhancing life quality, an adversary can also abuse it to steal private information about the human (e.g., location and person's identity). However, the literature lacks a systematic understanding of the privacy vulnerabilities of wireless sensing and the defenses against them, resulting in the privacy-compromising HCWS design. In this work, we aim to bridge this gap to achieve the vision of secure human-centered wireless sensing. First, we propose a signal processing pipeline to identify private information leakage and further understand the benefits and tradeoffs of wireless sensing-based inference attacks and defenses. Based on this framework, we present the taxonomy of existing inference attacks and defenses. As a result, we can identify the open challenges and gaps in achieving privacy-preserving human-centered wireless sensing in the era of machine learning and further propose directions for future research in this field.

Towards trustworthy and privacy-preserving decentralized auctions

Blockchain smart-contracts can be used as service mappers, connecting a contractor with the service provider best fitting desired service requirements (e.g., price or quality of service). The allocation consists of comparing competitive bids using a smart-contract. However, in competitive environments, service providers may be reluctant to share sensitive information offers with the blockchain as it makes any transaction implicitly public. To reconcile data privacy imperatives with the benefits of blockchain, we propose to leverage fully homomorphic encryption (FHE) for blockchain-based sealed-bid auctions. More precisely (i) FHE enables the processing of bids without decrypting them, (ii) smart-contracts gather and orchestrate bids comparison, and (iii) a computation oracle carries on comparisons over ciphered data. Collusion attempts may occur between bidders and the computation oracle. To prevent this, we combine FHE with hybrid RSA/AES encryption to preserve the privacy of the onchain bid contents. Hence, our protocol prevents information leakage onchain and on the service providers’ side during bids comparison. We validate this approach through an implemented prototype.

Unanticipated Political Events and Their Effect on the Nepalese Insurance Sector and Stock Market

This study analyzes the relationship between unanticipated political events and their profound impact on both the insurance sector and the Nepalese stock market (NEPSE). Utilizing comprehensive analysis, the research spans 200 days before to 10 days after the political event’s announcement. Employing Levene’s test, dummy variable regression, and estimated average abnormal return, the study reveals significant effects of political events on the insurance index and NEPSE indices. The pre-event period is particularly significant, indicating potential information leakage. Window Frame 1 (-10, -1) stands out as the most profoundly impacted period, with Window Frame 2 (0, +10) witnessing moderate impact during the announcement and Window Frame 3 (+2, +10) experiencing a comparatively lesser post-event effect. Nepali Congress Wins Election (Event 1) and End of Nepal Blockade (Event 3) were identified as the most significant events for the Insurance and NEPSE indexes. Dummy variable regression emphasizes the significance (P < 0.05) of multiple window frames (mostly 1, 5, & 6) in the NEPSE index, suggesting early information leakage adjustments. The insurance sector also demonstrates a highly significant (P < 0.05) impact of unanticipated political events across various data points, with the post-event period (Windows 2 and 3) as the sole exception. Cumulative abnormal return analysis demonstrates that the Nepalese stock market is moderately inefficient, as it reinforces the market’s attempt to incorporate political influences within three to five days of the announcement date. These findings bear implications for investors, policymakers, and regulatory authorities seeking to understand the dynamics of the Nepalese stock market, enabling informed decision-making during times of political transitions and uncertainty.

A novel quantum dialogue without information leakage based on single photons in both polarization and spatial-mode degrees of freedom

This paper puts forward a novel quantum dialogue (QD) protocol without information leakage based on single photons in both polarization and spatial-mode degrees of freedom. In this protocol, the receiver sends his private message to the sender in the way of quantum secure direct communication; and the receiver decodes out the private message of the sender with the help of auxiliary single photons in two degrees of freedom, double controlled-not (CNOT) operations and an auxiliary classical bit sequence sent from the sender. As a result, no information leakage takes place. Moreover, this protocol is proven to defeat the intercept-resend attack, the measure-resend attack, the entangle-measure attack and the Trojan horse attack from an outside eavesdropper. This protocol only employs single photons in two degrees of freedom as quantum resource and needs single-photon measurements. The qubit efficiency of this protocol is as high as 66.7%.

Research on Blockchain Transaction Privacy Protection Methods Based on Deep Learning

To address the challenge of balancing privacy protection with regulatory oversight in blockchain transactions, we propose a regulatable privacy protection scheme for blockchain transactions. Our scheme utilizes probabilistic public-key encryption to obscure the true identities of blockchain transaction participants. By integrating commitment schemes and zero-knowledge proof techniques with deep learning graph neural network technology, it provides privacy protection and regulatory analysis of blockchain transaction data. This approach not only prevents the leakage of sensitive transaction information, but also achieves regulatory capabilities at both macro and micro levels, ensuring the verification of the legality of transactions. By adopting an identity-based encryption system, regulatory bodies can conduct personalized supervision of blockchain transactions without storing users’ actual identities and key data, significantly reducing storage computation and key management burdens. Our scheme is independent of any particular consensus mechanism and can be applied to current blockchain technologies. Simulation experiments and complexity analysis demonstrate the practicality of the scheme.

A Configurable CRYSTALS-Kyber Hardware Implementation with Side-Channel Protection

In this work, we present a configurable and side channel resistant implementation of the post-quantum key-exchange algorithm CRYSTALS-Kyber . The implemented design can be configured for different performance and area requirements leading to different trade-offs for different applications. A low area implementation can be achieved in 5,269 LUTs and 2,422 FFs, whereas a high performance implementation required 7,151 LUTs and 3,730 FFs. Due to a deeply pipelined architecture, a high operating speed of more than 250 MHz could be achieved on 28nm Xilinx FPGAs. The side channel resistance is implemented using a carefully chosen set of novel and known techniques such as Fault Detection Hashes, Instruction Randomization, FSM Protection and so on. resulting in a low overhead of less than 5% while being highly configurable. To the best of our knowledge, this work presents the first side-channel and fault attack protected configurable accelerator for CRYSTALS-Kyber . Using TVLA (test vector leakage assessment), we validate the implemented protection techniques and demonstrate that the design does not leak information even after 200 K traces. Furthermore, one of the configuration choices results in the smallest hardware implementation of CRYSTALS-Kyber known in the literature.

Optical phase-truncation-based double-image encryption using equal modulus decomposition and random masks

This work reports an optical double-image crosstalk free encryption scheme that employs equal modulus decomposition and random masks. For the encryption, two plaintexts by a random amplitude mask and a random phase mask have been encrypted into a single ciphertext mask and two private key masks. Owing to the two random masks introduced, the functional relation between the plaintext pair and the ciphertext indirectly cause the paucity of constraints employed for the specific attack. Unlike the traditional phase-truncation-based techniques, this scheme is immune to the information leakage and different types of attacks. Furthermore, the three different diffraction distances and the illuminating wavelength also function as four additional keys to significantly reinforce the security. Simulation results demonstrate the feasibility and validity of the proposal.

Optimizing Online Business Security with Blockchain Technology

This research discusses the implementation of blockchain technology to improve online business security. The main problem facing online businesses today is their vulnerability to security attacks such as data theft and information leaks. The aim of this research is to optimize online business security by utilizing the advantages of blockchain technology in providing data security, integrity, and transparency. This research method includes a literature review to understand existing online business security frameworks and analysis of possible weaknesses. Next, we designed and implemented a blockchain-based solution to mitigate the identified security risks. Data collection is carried out through security attack simulations and reliability testing of the proposed system. The research results show that the application of blockchain technology significantly increases the security of online businesses, reduces the risk of data theft, and provides a high level of transparency. The conclusions of this research support the view that blockchain can be an effective solution to overcome security problems in the context of online business. This research makes a significant contribution to understanding and applying blockchain technology as an innovative security solution in the context of online business.

LPP-BPSI: A location privacy-preserving scheme using blockchain and Private Set Intersection in spatial crowdsourcing

Leakage of location information can lead to malicious attacks on workers in spatial crowdsourcing (SC) and loss of security. In response, a location privacy preserving scheme based on blockchain and Private Set Intersection were proposed, which reduced the computational overhead of workers by using a cloud service provider for outsourcing secure computation while ensuring their location privacy. First, three smart contracts based on blockchain were designed that could eliminate the control of traditional spatial crowdsourcing servers on the task allocation process. Second, differential privacy of the location method was proposed to construct the privacy location, and the cloud service provider used the privacy location to perform the location matching calculation. Third, an improved variant of the Private Set Intersection algorithm was constructed for the case of matching multiple workers for a single task in spatial crowdsourcing, which could efficiently perform location matching while protecting location privacy. To further reduce the computational overhead, Bloom filters were utilized to filter out a large number of free workers with zero location relevance before location matching. The experimental results showed that the scheme was robust and practical in the case of a large number of workers and concurrent task requests.