Minimal Information Leakage Research Articles

Secrecy Enhancement of relay cooperative NOMA network based on user behavior

From the perspective of information security, relays exhibit varying levels of trustworthiness when forwarding information. For screening and eliminating the malicious users of cooperative NOMA relay networks, a reputation-based algorithm is proposed, in which the user relays (URs) are categorized into three types based on their behaviors—malicious users, speculative users, and honest users. Meanwhile, in order to minimize information leakage at the relay, cooperative interference signals are transmitted by far user (FU) and near user (NU) via the uplink while the base station (BS) is also transmitting signals to the relay. This approach increases inter-user interference (IUI) to confuse the eavesdropping capability of the relay. To verify the superiority of the proposed scheme, an asymptotic lower bound expression for the ergodic secrecy rate (ESR) of the downlink is derived to characterize the secrecy performance of the proposed scheme. Furthermore, in the case of limited system power, a joint power allocation algorithm based on the golden section method is also proposed to further enhance the security performances of the system. The simulation results validate the accuracy of the derived analysis results and demonstrate that the proposed scheme has a significant improvement in the ESR compared with the traditional scheme.

Why Privacy-Preserving Protocols Are Sometimes Not Enough: A Case Study of the Brisbane Toll Collection Infrastructure

The use of Electronic Toll Collection (ETC) systems is on the rise, as these systems have a significant impact on reducing operational costs. Toll service providers (TSPs) access various information, including drivers' IDs and monthly toll fees, to bill drivers. While this is legitimate, such information could be misused for other purposes violating drivers' privacy, most prominent, to infer drivers' movement patterns. To this end, privacy-preserving ETC (PPETC) schemes have been designed to minimize the amount of information leaked while still allowing drivers to be charged. We demonstrate that merely applying such PPETC schemes to current ETC infrastructures may not ensure privacy. This is due to the (inevitable) minimal information leakage, such as monthly toll fees, which can potentially result in a privacy breach when combined with additional background information, such as road maps and statistical data. To show this, we provide a counterexample using the case study of Brisbane's ETC system. We present two attacks: the first, being a variant of the presence disclosure attack, tries to disclose the toll stations visited by a driver during a billing period as well as the frequency of visits. The second, being a stronger attack, aims to discover cycles of toll stations (e.g., the ones passed during a commute from home to work and back) and their frequencies. We evaluate the success rates of our attacks using real parameters and statistics from Brisbane's ETC system. In one scenario, the success rate of our toll station disclosure attack can be as high as 94%. This scenario affects about 61% of drivers. In the same scenario, our cycle disclosure attack can achieve a success rate of 51%. It is remarkable that these high success rates can be achieved by only using minimal information as input, which is, e.g., available to a driver's payment service provider or bank, and by following very simple attack strategies without exploiting optimizations. As a further contribution, we analyze how the choice of various parameters, such as the set of toll rates, the number of toll stations, and the billing period length, impact a driver's privacy level regarding our attacks.

A generalized approach to estimation of memoryless covert channel information leakage capacity

Estimating the amount of information that is leaked by covert channels is a necessity to comprehend and mitigate the severity of attacks exploiting these channels. Having such an estimation in design-state provides an opportunity for designers to adjust their systems to minimize information leakage. In this paper, we propose a methodology to estimate the worst-case information leakage (or capacity for the information leakage) through various memoryless covert channels – both analog and digital ones – exhibiting on–off keying structure. In that respect, we first model the communication channel as a deletion–insertion channel to account for the information losses due to software activities. Then, we derive the effective noise in covert channels as the combination of jitter noise caused by signaling time variation and Additive White Gaussian Noise (AWGN). Considering this effective noise, we propose a communication model which can be generalized for various covert channels and takes insertions, deletions, and asynchronous nature of covert channels into account. By leveraging the link between this communication model and information theory literature, we obtain the information leakage capacity that reveals the leakage limit for the worst-case scenarios. Finally, we provide experimental results to demonstrate that the proposed model is an effective and a generalized methodology to score the resilience of a given system to covert channel attacks.

StoreSim: Optimizing Information Leakage in Multi-Cloud Storage Services

Abstract: Many schemes have been recently advanced for storing data on multiple clouds. Distributing data over different cloud storage providers (CSPs) automatically provides users with a certain degree of information leakage control, as no single point of attack can leak all a user’s information. However, unplanned distribution of data chunks can lead to high information disclosure even while using multiple clouds. In this paper, to address this problem, we present Store-Sim, an information leakage-aware storage system in multi cloud. Store-Sim aims to store syntactically similar data on the same cloud, thus minimizing the user’s information leakage across multiple clouds. We design an approximate algorithm to efficiently generate similarity- preserving signatures for data chunks based on Min-Hash and Bloom filters, and design a function to compute the information leakage based on these signatures. Next, we present an effective storage plan generation algorithm based on clustering for distributing data chunks with minimal information leakage across multiple clouds. Finally, we evaluated our scheme using two real datasets from Wikipedia and GitHub. We show that our scheme can reduce information leakage by up to 60-70 Percent. Keywords: Min-Hash, Bloom-Filter, Multi-Cloud, StoreSim, Data Leakage.

A Secure Searchable Encryption Framework for Privacy-Critical Cloud Storage Services

Searchable encryption has received a significant attention from the research community with various constructions being proposed, each achieving asymptotically optimal complexity for specific metrics (e.g., search, update). Despite their elegance, the recent attacks and deployment efforts have shown that the optimal asymptotic complexity might not always imply practical performance, especially if the application demands a high privacy. In this article, we introduce a novel Dynamic Searchable Symmetric Encryption (DSSE) framework called Incidence Matrix (IM)-DSSE, which achieves a high level of privacy, efficient search/update, and low client storage with actual deployments on real cloud settings. We harness an incidence matrix along with two hash tables to create an encrypted index, on which both search and update operations can be performed effectively with minimal information leakage. This simple set of data structures surprisingly offers a high level of DSSE security while achieving practical performance. Specifically, IM-DSSE achieves forward-privacy, backward-privacy and size-obliviousness simultaneously. We also create several DSSE variants, each offering different trade-offs that are suitable for different cloud applications and infrastructures. We fully implemented our framework and evaluated its performance on a real cloud system (Amazon EC2). We have released IM-DSSE as an open-source library for wide development and adaptation.

A Survey on Statistical, Information, and Estimation—Theoretic Views on Privacy

Privacy has become an emerging challenge in both information theory and computer science due to massive (centralized) collection of user data. In this article, we overview privacy-preserving mechanisms and metrics from the lenses of information theory, and unify different privacy metrics, including f-divergences, Rényi divergences, and differential privacy (DP), in terms of the probability likelihood ratio (and its logarithm). We review recent progress on the design of privacy-preserving mechanisms according to the privacy metrics in computer science, where DP is the standard privacy notion which controls the output shift given small input perturbation, and information theory, where the privacy is guaranteed by minimizing information leakage. In particular, for DP, we include its important variants (e.g., Rényi DP, Pufferfish privacy) and properties, discuss its connections with information-theoretic quantities, and provide the operational interpretations of its additive noise mechanisms. For information-theoretic privacy, we cover notable frameworks, including the privacy funnel, originated from rate-distortion theory and information bottleneck, to privacy guarantee against statistical inference/guessing, and information obfuscation on samples and features. Finally, we discuss the implementations of these privacy-preserving mechanisms in current data-driven machine learning scenarios, including deep learning, information obfuscation, federated learning, and dataset sharing.

Privacy considerations for sharing genomics data.

An increasing amount of attention has been geared towards understanding the privacy risks that arise from sharing genomic data of human origin. Most of these efforts have focused on issues in the context of genomic sequence data, but the popularity of techniques for collecting other types of genome-related data has prompted researchers to investigate privacy concerns in a broader genomic context. In this review, we give an overview of different types of genome-associated data, their individual ways of revealing sensitive information, the motivation to share them as well as established and upcoming methods to minimize information leakage. We further discuss the concise threats that are being posed, who is at risk, and how the risk level compares to potential benefits, all while addressing the topic in the context of modern technology, methodology, and information sharing culture. Additionally, we will discuss the current legal situation regarding the sharing of genomic data in a selection of countries, evaluating the scope of their applicability as well as their limitations. We will finalize this review by evaluating the development that is required in the scientific field in the near future in order to improve and develop privacy-preserving data sharing techniques for the genomic context.

Optimizing Information Leakage in Multicloud Storage Services

Many schemes have been recently advanced for storing data on multiple clouds. Distributing data over different cloud storage providers (CSPs) automatically provides users with a certain degree of information leakage control, for no single point of attack can leak all the information. However, unplanned distribution of data chunks can lead to high information disclosure even while using multiple clouds. In this paper, we study an important information leakage problem caused by unplanned data distribution in multicloud storage services. Then, we present StoreSim , an information leakage aware storage system in multicloud. StoreSim aims to store syntactically similar data on the same cloud, thus minimizing the user's information leakage across multiple clouds. We design an approximate algorithm to efficiently generate similarity-preserving signatures for data chunks based on MinHash and Bloom filter, and also design a function to compute the information leakage based on these signatures. Next, we present an effective storage plan generation algorithm based on clustering for distributing data chunks with minimal information leakage across multiple clouds. Finally, we evaluate our scheme using two real datasets from Wikipedia and GitHub . We show that our scheme can reduce the information leakage by up to 60 percent compared to unplanned placement. Furthermore, our analysis on system attackability demonstrates that our scheme makes attacks on information more complex.

The Overhead from Combating Side-Channels in Cloud Systems Using VM-Scheduling

Recent work suggests that scheduling, with security as a consideration, can be effective in minimizing information leakage, via side-channels, that can exist when virtual machines (VMs) co-reside in clouds. We analyze the overhead that is incurred by such an approach. We first pose and answer a fundamental question: is the problem tractable? We show that the seemingly simpler sub-cases of initial placement and migration across only two equal-capacity servers are both intractable ( $\mathbf {NP}\text{-hard}$ NP -hard ). However, a decision version of the general problem to which the optimization version is related polynomially is in $\mathbf {NP}$ NP . With these results as the basis, we make several other contributions. We revisit recent work that proposes a greedy algorithm for this problem, called Nomad. We establish that if $\mathbf {P} \not= \mathbf {NP}$ P ≠ NP , then there exist infinitely many classes of input, each with an infinite number of inputs, for which a decrease in information leakage is possible, but Nomad provides none, let alone minimize it. We establish also that a mapping to Integer Linear Programming (ILP) in prior work is deficient in that the mapping can be inefficient (exponential-time), and therefore does not accurately convey the overhead of such an approach that, unlike Nomad, actually decreases information leakage. We present our efficient reductions to ILP and boolean satisfiability in conjunctive normal form (CNF-SAT). We have implemented these approaches and conducted an empirical assessment using the same ILP solver as prior work, and a SAT solver. Our analytical and empirical results more accurately convey the overhead that is incurred by an approach that actually provides security (decrease in information leakage).

Boolean Searchable Symmetric Encryption with Filters on Trusted Hardware

The prevalence and availability of cloud infrastructures has made them the de facto solution for storing and archiving data, both for organizations and individual users. Nonetheless, the cloud's wide spread adoption is still hindered by dependability and security concerns, particularly in applications with large data collections where efficient search and retrieval services are also major requirements. This leads to an increased tension between security, efficiency, and search expressiveness. In this paper we tackle this tension by proposing BISEN, a new provably-secure boolean searchable symmetric encryption scheme that improves these three complementary dimensions by exploring the design space of isolation guarantees offered by novel commodity hardware such as Intel SGX, abstracted as Isolated Execution Environments (IEEs). BISEN is the first scheme to support multiple users and enable highly expressive and arbitrarily complex boolean queries, with minimal information leakage regarding performed queries and accessed data, and verifiability regarding fully malicious adversaries. Furthermore, BISEN extends the traditional SSE model to support filter functions on search results based on generic metadata created by the users. Experimental validation and comparison with the state of art shows that BISEN provides better performance with enriched search semantics and security properties.

Secrecy Enhancement of Cooperative NOMA Networks With Two-Way Untrusted Relaying

The two-way relaying (TWR) technique has been confirmed to achieve higher spectral efficiency and average sum rate compared with the one-way relaying (OWR) technique in ultra-dense next generation networks with limited spectal resources. In this paper, an enhanced secrecy cooperative TWR scheme for cooperative non-orthogonal multiple access (NOMA) networks against untrusted relaying is highlighted. Specifically, with the application of NOMA principle, a base station (Bs) communicates with two trusted users, i.e., namely a near and a far users, where the communication with the far user takes place only via an untrusted relay (UR) employing both TWR and analog network coding (ANC) mechanisms. To minimize information leakage at the UR, the far user transmits its uplink signal simultaneously with Bs's downlink signal to confuse the eavesdropping capability of the UR by increasing inter-user interference (IUI). To investigate the benefits of the proposed scheme, asymptotic lower bound expressions of the ergodic secrecy sum rate (ESSR) of uplink/downlink rates and their scaling law are derived to characterize the secrecy performance. The system parameters have been carefully studied to maitain the desired ESSR performance where we obtain an optimal value for the uplink power sharing coefficient with an arbitrary known value of the downlink one. Analytical and simulation results show that the proposed scheme can achieve scaling gain of 1/8 ln ρ of positive ESSR over the untrusted OWR scheme with adaptive uplink/downlink jamming and a significant gain over the other conventional NOMA uplink/downlink schemes in two time slots of communication.

Secrecy-Enhancing Design for Cooperative Downlink and Uplink NOMA With an Untrusted Relay

We investigate a secrecy-enhancing design for cooperative downlink and uplink non-orthogonal multiple access (NOMA) transmissions with an untrusted relay. A source uses the NOMA principle to have downlink and uplink transmissions with a near user and a far user, and the communications between the source and the far user are aided by an untrusted relay. To minimize information leakage at the untrusted relay and achieve secure NOMA communications, adaptive downlink and uplink cooperative jamming schemes are proposed, where the far user in downlink and the near user in uplink adaptively emit a jamming signal to the untrusted relay to impair its eavesdropping capability. Both downlink and uplink jamming power are optimized to fully exploit the benefits of the proposed schemes for security enhancement. Then, for each scheme, we quantify the secrecy performance by deriving the ergodic secrecy sum rate lower bound and its scaling law. Finally, computer simulation is used to demonstrate the effectiveness of the proposed adaptive downlink and uplink cooperative jamming schemes and verify the accuracy of the derived analytical results.

A novel out-of-band biometrics authentication scheme for wearable devices

ABSTRACT Wearable Technology (WT) devices are growing at a rapid rate for their convenience and capabilities, especially in healthcare and fitness area. As the adoption of WT accelerates and a new level of functionality is introduced, it could potentially open the door to new threats to sensitive information and activities. The study shows that both passive attacks (eavesdropping on the wireless communication) and active attacks (man-in-the-middle attack and replay attack) can be successfully launched by exploiting the security vulnerability of the wearable such as lack of user authentication. Hence, a strong user authentication is required to create trust relationships between users and services and protect users’ data. In this research, a novel authentication protocol using enhanced out-of-band (e-OOBA) two-factor biometric authentication for wearable devices is introduced. The new authentication scheme is known as out-of-band biometrics authentication (OOB-BA) is capable to provide better security and minimize information leakage. The security measurements on this scheme are evaluated and benchmarked. One main finding from security analysis demonstrate that OOB-BA is able to mitigate the security risks such as impersonation attacks leading to stand as an alternative authentication model to be used in future WT adoption.

INFLUENCE OF CORRUPTION ON THE ECONOMIC DEVELOPMENT OF UKRAINE IN TERMS OF REFORMATION: A RETROSPECTIVE ANALYSIS

The subject of the study is to investigate the causes of the influence of corruption on the economic development of Ukraine in the context of reform. Corruption occurs at all levels of society and in some way interferes in all elements of society, and thus negatively affects democracy and economic development of the country. The research methodology involves a retrospective analysis of the problem of inveteracy of corruption associated with the study of its impact on the economy. It is precisely endemic corruption that threatens the formation of Ukraine’s stability and its transition to a market economy. Corruption as one of the most ancient phenomena in society exists in every modern country. The general understanding of corruption is that corruption is detrimental to economic growth. There are also many causes of corruption, namely, a cultural factor, a psychological factor and, therefore, factors associated with the system can cause corruption in every society. The methodological basis for the research was the works of Tylchyk O.V., Bilous V.T., Subbot A.I., Lytvynenko V.I., Hvozdetskyi V.D., Popovych V.M., Bodnarchuk O.H. in the field of administrative law and issues of counteracting and combating corruption, which indicate that there are some factors, such as monopoly power, discretionary power, and low civil servants’ liability, that may provide opportunities for the development of corruption. The purpose of the article was to analyse the causes of the impact of corruption on the country’s economic and political development. Today, corruption has a wide range of activities that undermine the country’s development. Researchers argue that corruption affects the country’s economic growth. However, contradictory evidence was found that corruption can have a positive effect on the country’s economic development or have no significant impact on economic performance. On the basis of analysis of these works, it was established that corruption is the result of institutional weakness, with a potential adverse effect on the country’s economic efficiency. Corruption negatively affects the efficiency of public spending, reduces budget revenues and increases its deficit, impedes foreign direct investment, reduces the effectiveness of international assistance, and hinders economic development. As a result of the analysis, ways to reduce corruption are identified, which suggest a policy of reducing corruption in Ukraine. The result of the study was conclusions on the need to develop and form a coherent system of scientific and legal views on identifying effective anticorruption measures, optimizing and improving the effectiveness of anticorruption activities, with the involvement of international experience in coordinating and minimizing information leakage and engaging civic initiatives among the non-public sector.

Thread scheduling using ant colony optimization: An intelligent scheduling approach towards minimal information leakage

In multithreaded programs, scheduler controls the execution of threads. As a result, the scheduler may arrange the execution sequence of threads in such a way that multithreaded programs may violate the non-interference confidentiality policy. Due to a violation of non-interference, multithreaded programs may leak security sensitive information. In the proposed work, Ant Colony Optimization (ACO) based intelligent scheduling policy has been proposed in the form of algorithms to schedule threads in multithreading environment in such a way that the execution sequence leads to minimal information leakage. In the present work, the proposed scheduler also deals with conflicting scheduling parameters and provides the algorithmic solution which can handle all conflicting entities of scheduling like throughput, delay, security-privacy and fairness. In this work, dynamic creation and deletion of threads are also handled during the scheduling. Although the focus of this work is on the scheduling of threads, the proposed policy can be used as a general purpose scheduling policy in many computing fields.

Fundamental Limits of Caching With Secure Delivery

Caching is emerging as a vital tool for alleviating the severe capacity crunch in modern content-centric wireless networks. The main idea behind caching is to store parts of popular content in end-users' memory and leverage the locally stored content to reduce peak data rates. By jointly designing content placement and delivery mechanisms, recent works have shown order-wise reduction in transmission rates in contrast to traditional methods. In this work, we consider the secure caching problem with the additional goal of minimizing information leakage to an external wiretapper. The fundamental cache memory vs. transmission rate trade-off for the secure caching problem is characterized. Rather surprisingly, these results show that security can be introduced at a negligible cost, particularly for large number of files and users. It is also shown that the rate achieved by the proposed caching scheme with secure delivery is within a constant multiplicative factor from the information-theoretic optimal rate for almost all parameter values of practical interest.

Smart Meter Privacy for Multiple Users in the Presence of an Alternative Energy Source

Smart meters (SMs) measure and report users’ energy consumption to the utility provider (UP) in almost real-time, providing a much more detailed depiction of the consumer’s energy consumption compared to their analog counterparts. This increased rate of information flow to the UP, together with its many potential benefits, raise important concerns regarding user privacy. This paper investigates, from an information theoretic perspective, the privacy that can be achieved in a multiuser SM system in the presence of an alternative energy source (AES). To measure privacy, we use the mutual information rate between the users’ real energy consumption profile and SM readings that are available to the UP. The objective is to characterize the privacy-power function, defined as the minimal information leakage rate that can be obtained with an average power-limited AES. We characterize the privacy-power function in a single letter form when the users’ energy demands are assumed to be independent and identically distributed over time. Moreover, for binary and exponentially distributed energy demands, we provide an explicit characterization of the privacy-power function. For any discrete energy demands, we demonstrate that the privacy-power function can always be efficiently evaluated numerically. Finally, for continuous energy demands, we derive an explicit lower bound on the privacy-power function, which is tight for exponentially distributed loads.

Alpha Decay

Stocks purchased by institutional investors earn significant positive alpha that declines gradually over twelve months. Using a comprehensive new dataset of daily trades, we find that purchases predict alpha even after controlling for stock characteristics. Observed trading behaviour suggests that fund managers act strategically to minimize information leakage, consistent with Kyle-type models — managers build positions in small increments proportional to remaining alpha, trade more aggressively when the number of competitors and/or correlation among information signals is high, and do not increase trade size after unexpected capital flows. Alpha is negatively related to competition/correlation, also consistent with the strategic trading hypothesis.

Privacy and Recovery in Composite Web Service Transactions

Today’s numerous online transactions are implemented as composite web services in various domains including business, healthcare, government and education. This paper addresses privacy and recovery issues in composite web service transactions. In particular, we propose an intelligent semiautomated privacy-aware approach to efficiently building an appropriate composite web service along with a recovery mechanism to provide protection against privacy and service execution failures in the transactions. Our proposed approach aims to satisfy service I/O requirements using a minimum number of services with minimal information leakage and maximal compliance with a customer’s privacy preferences and trust (in service providers when available). The paper describes details of the proposed approach and illustrates its use that exploits generic knowledge about types and sensitivity levels of information, together with specific knowledge about customer privacy preferences and trusts on certain providers. By using privacy-aware contingency and various types of compensation, the recovery mechanism provides potentials to maximize forward recovery from failed transaction services.

Minimizing information leakage in the DNS

The domain name system is the global lookup service for network resources. To protect DNS information, the DNS security extensions have been developed and deployed on branches of the DNS to provide authentication and integrity protection using digital signatures. However, signed DNS nodes were found to have an unfortunate side effect: an attacker can query them as reconnaissance before attacking hosts on a particular network. There are different ways a zone administrator can minimize information leakage and still take advantage of DNSSEC for integrity and source authentication. This article describes the risk and examines the protocol and operational options and looks at their advantages and drawbacks.