Information Leakage Rate Research Articles

Secureimagesec: A privacy-preserving framework for outsourced picture representation with content-based image retrieval

Content-Based Image Retrieval (CBIR) uses complicated algorithms to analyze visual attributes and retrieve relevant photos from large databases. CBIR is essential to a privacy-preserving feature extraction and protection method for outsourced picture representation. SecureImageSec combines essential methods with the system’s key entities to ensure secure, private and protected image feature processing during outsourcing. For a system to be implemented effectively, these techniques must be seamlessly integrated across critical entities, such as the client, the cloud server that is being outsourced, the component that protects secure features, the component that maintains privacy in communication, access control, and authorization, and the integration and system evaluation. The client entity initiates outsourcing using advanced encryption techniques to protect privacy. SecureImageSec protects outsourced data by using cutting-edge technologies like Fully Homomorphic Encryption (FHE) and Secure Multi-Party Computation (SMPC). Cloud servers hold secure feature protection entities and protect outsourced features’ privacy and security. SecureImageSec uses AES and FPE to protect data format. SecureImageSec’s cloud-outsourced privacy-preserving communication uses SSL/TLS and QKD to protect data transmission. Attribute-Based Encryption (ABE) and Functional Encryption (FE) in SecureImageSec limit access to outsourced features based on user attributes and allow fine-grained access control over decrypted data. SecureImageSec’s Information Leakage Rate (ILR) of 0.02 for a 1000-feature dataset shows its efficacy. SecureImageSec also achieves 4.5 bits of entropy, ensuring the encrypted feature set’s muscular cryptographic strength and randomness. Finally, SecureImageSec provides secure and private feature extraction and protection, including CBIR capabilities, for picture representation outsourcing.

Joint Optimization for Secure and Reliable Communications in Finite Blocklength Regime

To realize ultra-reliable low latency communications with high spectral efficiency and security, we investigate a joint optimization problem for downlink communications with multiple users and eavesdroppers in the finite blocklength (FBL) regime. We formulate a multi-objective optimization problem to maximize a sum secrecy rate by developing a secure precoder and to minimize a maximum error probability and information leakage rate. The main challenges arise from the complicated multi-objective problem, non-tractable back-off factors from the FBL assumption, non-convexity and non-smoothness of the secrecy rate, and the intertwined optimization variables. To address these challenges, we adopt an alternating optimization approach by decomposing the problem into two phases: secure precoding design, and maximum error probability and information leakage rate minimization. In the first phase, we obtain a lower bound of the secrecy rate and derive a first-order Karush–Kuhn–Tucker (KKT) condition to identify local optimal solutions with respect to the precoders. Interpreting the condition as a generalized eigenvalue problem, we solve the problem by using a power iteration-based method. In the second phase, we adopt a weighted-sum approach and derive KKT conditions in terms of the error probabilities and leakage rates for given precoders. Simulations validate the proposed algorithm.

Secure Vehicular Communications With Varying QoS and Environments: A Unified Cross-Layer Policy-Adaptation Approach

With the ubiquitous connectivity in internet of vehicles, secure transmission is of vital importance for intelligent vehicle-to-everything (V2X) communications. However, in order to effectively guarantee the secrecy performance, once the short-term statistics of channel quality are low, which frequently happens because of the high mobility of vehicles, the throughput performance can be weakened by using the existing either cryptography techniques or physical-layer security (PLS) technique. To improve the throughput of secure data transmission, we propose the concept of statistical security, which utilizes the time-sensitive characteristics of information, such as the position of mobile vehicles, in V2X communications. Specifically, the time-sensitive information has its own outdated rate. As long as the information leakage rate is less than the information outdated rate, the eavesdropper still cannot obtain any useful information. Then, we use a queue system to characterize the eavesdropping process, where the queue-length violation probability indicates the level of secure transmission. Under this statistical security model, we investigate the throughput maximization problem and give the optimal power allocation scheme for the legitimate vehicular users. Furthermore, since the service’s security QoS requirements and wireless environments are both varying in V2X communications, we propose a unified cross-layer policy-adaption approach to guarantee the varying security QoS requirements meanwhile improving the throughput. Simulation results verify that our proposed approach significantly outperforms the existing baseline schemes.

Information Leakage Rate of Optical Code Division Multiple Access Network Using Wiretap Code.

Secrecy capacity is usually employed as the performance metric of the physical layer security in fiber-optic wiretap channels. However, secrecy capacity can only qualitatively evaluate the physical layer security, and it cannot quantitatively evaluate the physical layer security of an imperfect security system. Furthermore, secrecy capacity cannot quantitatively evaluate the amount of information leakage to the eavesdropper. Based on the channel model of an optical CDMA network using wiretap code, the information leakage rate is analyzed to evaluate the physical layer security. The numerical results show that the information leakage rate can quantitatively evaluate the physical layer security of an optical CDMA wiretap channel, and it is related to transmission distance, eavesdropping position, confidential information rate and optical code.

PERFORMANCE ANALYSIS OF A POINT-TOPOINT SYSTEM UNDER ACTIVE ATTACK

—In wireless communications, security issues have become difficult due to unchangeable and unpredictable nature of the wireless medium. There are many traditional cryptographic techniques which were used previously. The physical layer security used for ensuring secure wireless communications apart from the cryptographic techniques, which is achieved after proper understanding of the nature wireless channels. Classical information theoretic secrecy is one of the metrics followed, in which, we assume that there is no(zero) leaked information at the eavesdropper which means the information decoding probability at the eavesdropper is '0'. But, practically achieving classical information theoretic secrecy is not possible. So, this project deals with partial secrecy. The partial secrecy of a system is measured in terms of equivocation, which gives the information of the level at which the eavesdropper (active) is confused. It means that in partial secrecy, there is information leakage but the eavesdropper cannot exactly decode the original message. The new secrecy metrics used GSOP (generalized secrecy outage probability), AFE (average fractional equivocation) and AILR (average information leakage rate) altogether provides more comprehensive and in-depth understanding of the secrecy performance over the fading channels.

Web Site Fingerprint Attack Generation Technology Combined with Genetic Algorithm

An anonymous network can be used to protect privacy and conceal the identities of both communication parties. A website fingerprinting attack identifies the target website for the data access by matching the pattern of the monitored data traffic, rendering the anonymous network ineffective. To defend against fingerprint attacks on anonymous networks, we propose a novel adversarial sample generation method based on genetic algorithms. We can generate effective adversarial samples with minimal cost by constructing an appropriate fitness function to select samples, allowing us to defend against several mainstream attack methods. The technique reduces the accuracy of a cutting-edge attack hardened with adversarial training from 90% to 20–30%. It also outperforms other defense methods of the same type in terms of information leakage rate.

Information Leakage in Index Coding With Sensitive and Nonsensitive Messages

Index coding can be viewed as a compression problem with multiple decoders with side information. In such a setup, an encoder compresses a number of messages into a common codeword such that every decoder can decode its requested messages with the help of knowing some other messages as side information. In this paper, we study how much information is leaked to a guessing adversary observing the codeword in index coding, where some messages in the system are sensitive and others are not. The non-sensitive messages can be used by the encoder in a manner similar to secret keys to mitigate leakage of the sensitive messages to the adversary. We first characterize the optimal information leakage rate of a given index coding problem by the optimal compression rate of a related problem, which is constructed by adding an extra decoder with certain parameters to the original problem. Both the achievability and converse of the characterization are derived from a graph-theoretic perspective based on confusion graphs (Alon et al. 2008). In particular, the achievable coding scheme is a randomized mapping exploiting certain symmetrical properties of the confusion graph. Our second main result is a practical deterministic linear coding scheme, developed from the rank minimization method based on fitting matrices (Bar-Yossef et al. 2011). The linear scheme leads to an upper bound on the optimal leakage rate, which is proved to be tight over all deterministic scalar linear codes. While it is shown through an example that simultaneously achieving optimal compression and leakage rates is not always possible, time-sharing between different schemes could be used to balance the compression and leakage rates. Finally, we show how our results can be applied to different variants of index coding.

Security in Diffusive Molecular Timing Channels: An Amount of Confusion Level Perspective

Secure transmission of information to a desired receiver is an important attribute of any molecular communication system. This paper analyzes the secrecy performance for a multi-particle diffusive molecular timing channel. We first obtain the fractional equivocation and then employ three standard secrecy performance metrics, namely, generalized secrecy outage probability, average fractional equivocation, and average information leakage rate to evaluate the secrecy performance of the channel in the presence of an eavesdropping user. We then propose a new secrecy performance metric, the amount of confusion level, which quantifies the severity of the confusion level at the eavesdropping user. Compared to the aforementioned metrics which are mainly based on the first-order statistics, the amount of confusion level is a second order measure that characterizes the eavesdropping effect in a better way, especially in environments with very small value of the Lévy noise parameter. The dependence of various secrecy metrics on various physical parameters, especially the Lévy noise parameter and the degradation rate of information molecules, is studied. Our analysis suggests that an increase in the value of each of these parameters results in an improvement in the secrecy performance. Numerical results corroborate the derived analytical findings.

Cooperative Friendly Jamming Techniques for Drone-Based Mobile Secure Zone.

Threats of eavesdropping and information leakages have increased sharply owing to advancements in wireless communication technology. In particular, the Internet of Things (IoT) has become vulnerable to sniffing or jamming attacks because broadcast communication is usually conducted in open-network environments. Although improved security protocols have been proposed to overcome the limitations of wireless-communication technology and to secure safe communication channels, they are difficult to apply to mobile communication networks and IoT because complex hardware is required. Hence, a novel security model with a lighter weight and greater mobility is needed. In this paper, we propose a security model applying cooperative friendly jamming using artificial noise and drone mobility, which are autonomous moving objects, and we demonstrate the prevention of eavesdropping and improved security through simulations and field tests. The Cooperative Friendly Jamming Techniques for Drone-based Mobile Secure Zone (CFJ-DMZ) can set a secure zone in a target area to support a safe wireless mobile communication network through friendly jamming, which can effectively reduce eavesdropping threats. According to the experimental results, the average information leakage rate of the eavesdroppers in CFJ-DMZ-applied scenarios was less than or equal to 3%, an average improvement of 92% over conventional methods.

Secrecy Optimization for Diffusion-Based Molecular Timing Channels

Security in the context of molecular communication systems is an important design aspect that has not attracted much attention till date. This letter analyzes the information-theoretic secrecy of diffusive molecular timing channels when the distance of the eavesdropper is assumed to be random and uniformly distributed. Using an existing upper bound on the timing channel capacity, we calculate the optimal secrecy rate and optimal transmission rate for Bob which would help in achieving an improved secrecy throughput performance. Based on this optimal rate, we calculate the maximum achievable throughput. We then use this formulation to minimize the generalized secrecy outage probability (GSOP) by simultaneously maximizing the average fractional equivocation and minimizing the average information leakage rate. The numerical results show that while choosing the system parameters, there is always a trade-off between different performance metrics like GSOP, average fractional equivocation, and average information leakage rate. The proposed secrecy optimization provides a robust understanding of the physical layer secrecy at the molecular level, enabling the design of secure molecular communication systems.

Impacts of Unintended Nanomachine in Diffusion-Based Molecular Communication System

The effect of unintended nanomachine (UN) on the performance of a 3-dimensional (3-D) diffusive point-to-point molecular communication system is investigated in this article. To analyze the impacts of the presence of UN, two different scenarios are considered. In the first scenario, UN is considered as an unintended transmitter nanomachine (UTN). The expression for arrival probability of molecules received at the spherical absorbing receiver, considering exponential molecular degradation, is obtained. Moreover, this scenario is analyzed in terms of average probability of error (APoE) and maximum achievable rate (MAR), with and without Genie-aided assumptions. Further, in the second scenario, wherein we consider UN as a unintended receiver nanomachine (URN), the system is analyzed in terms of information leakage and maximum achievable secrecy rate (MASR). In second scenario, we consider two different models to find the arrival probability of molecules at the intended receiver nanomachine (IRN). In the first model, independence of the particle death in URN and IRN is assumed, and in second model, mutual influences of URN and IRN on each other are assumed. Moreover, in both the scenarios, to optimize the system performance, an optimal detector is used. In the end, the derived analytical expressions are verified through particle-based and Monte-Carlo simulations.

Top-N recommendation algorithm integrated neural network

With the gradual popularization of social informatization, people’s information security is gradually threatened. The development of the Internet has gradually exposed people’s privacy, and the protection of the privacy of people in the era of Internet information has become a topic of concern to all people. This research mainly discusses the research of the Top-N recommendation algorithm with integrated neural network. The purpose of protecting people’s privacy is achieved by interfering with the Top-N recommendation algorithm on the Internet signal. In response to people’s concerns, the Top-N recommendation algorithm with integrated neural network was used during the experiment. The experimenters were randomly selected from netizens who frequently used computers to measure the privacy and security of each group of researchers and the signal of the Top-N recommendation algorithm. Interference level. The use of the Top-N recommendation algorithm is divided into six levels, and the experimentally measured information protection rate is 88% when the use level of the Top-N recommendation algorithm is F level. In the case of signal interference, the interference intensity is divided into five levels. Similarly, when the signal interference intensity is 5, the information leakage rate is at least 10%. The selection of personnel throughout the experiment is random and the interference during the experiment and the use of the Top-N recommendation algorithm with integrated neural network are divided according to levels. The research results show that when the signal interference intensity is 5 and the recommended algorithm is F, the privacy protection of netizens is the best. The Top-N recommendation algorithm with integrated neural network has important potential value in protecting people’s privacy.

On designing an unaided authentication service with threat detection and leakage control for defeating opportunistic adversaries

Unaided authentication services provide the flexibility to login without being dependent on any additional device. The power of recording attack resilient unaided authentication services (RARUAS) is undeniable as, in some aspects, they are even capable of offering better security than the biometric based authentication systems. However, high login complexity of these RARUAS makes them far from usable in practice. The adopted information leakage control strategies have often been identified as the primary cause behind such high login complexities. Though recent proposals have made some significant efforts in designing a usable RARUAS by reducing its login complexity, most of them have failed to achieve the desired usability standard. In this paper, we have introduced a new notion of controlling the information leakage rate. By maintaining a good security standard, the introduced idea helps to reduce the login complexity of our proposed mechanism — named as Textual-Graphical Password-based Mechanism or TGPM, by a significant extent. Along with resisting the recording attack, TGPM also achieves a remarkable property of threat detection. To the best of our knowledge, TGPM is the first RARUAS, which can both prevent and detect the activities of the opportunistic recording attackers who can record the complete login activity of a genuine user for a few login sessions. Our study reveals that TGPM assures much higher session resiliency compared to the existing authentication services, having the same or even higher login complexities. Moreover, TGPM stores the password information in a distributed way and thus restricts the adversaries to learn the complete secret from a single compromised server. A thorough theoretical analysis has been performed to prove the strength of our proposal from both the security and usability perspectives. We have also conducted an experimental study to support the theoretical argument made on the usability standard of TGPM.

On the Secrecy Performance and Power Allocation in Relaying Networks With Untrusted Relay in the Partial Secrecy Regime

Recently, three useful secrecy metrics based on the partial secrecy regime were proposed to analyze secure transmissions on wireless systems over quasi-static fading channels, namely: generalized secrecy outage probability, average fractional equivocation, and average information leakage. These metrics were devised from the concept of fractional equivocation, which is related to the decoding error probability at the eavesdropper, so as to provide a comprehensive insight on the practical implementation of wireless systems with different levels of secrecy requirements. Considering the partial secrecy regime, in this paper we examine the secrecy performance of an amplify-and-forward relaying network with an untrusted relay node, where a destination-based jamming is employed to enable secure transmissions. In this regard, a closed-form approximation is derived for the generalized secrecy outage probability, and integral-form expressions are obtained for the average fractional equivocation and the average information leakage rate. Additionally, equal and optimal power allocation schemes are investigated and compared for the three metrics. From this analysis, we show that different power allocation approaches lead to different system design criteria. The obtained expressions are validated via Monte Carlo simulations.

Physical-Layer Security in TDD Massive MIMO

We consider a single-cell downlink time-division duplex-based massive MIMO communication in the presence of an adversary capable of jamming and eavesdropping simultaneously. We show that the massive MIMO communication is naturally resilient to no training-phase jamming attack in which the adversary jams only the data communication and eavesdrops both the data communication and the training. Specifically, we show that the secure degrees of freedom (SDoF) attained in the presence of such an attack are identical to the maximum DoF attainable under no attack. Furthermore, we evaluate the number of base station (BS) antennas necessary in order to establish information theoretic security without even a need for Wyner encoding for a given rate of information leakage to the attacker. Next, we show that things are completely different once the adversary starts jamming the training phase. Specifically, we consider the pilot contamination attack, called training-phase jamming in which the adversary jams and eavesdrops both the training and the data communication. We show that under such an attack, the maximum achieved SDoF is identical to zero. Furthermore, the maximum achievable secure rates of users also vanish, even in the asymptotic regime in the number of the BS antennas. We finally address this attack and show that, under training-phase jamming , if the number of pilot signals is scaled in a certain way and the pilot signal assignments can be hidden from the adversary, the users achieve an SDoF identical to the maximum achievable DoF under no attack.

Collective Secrecy Over the <inline-formula> <tex-math notation="LaTeX">$K$ </tex-math> </inline-formula>-Transmitter Multiple Access Channel

This paper studies the problem of secure communication over a $K$ -transmitter multiple access channel (MAC) in the presence of an external eavesdropper, subject to a collective secrecy constraint (i.e., information leakage rate to an eavesdropper on a collection of messages that are from a pre-specified subset of the $K$ transmitters, say $\mathcal {S}\subseteq \mathcal {K}=\{1,2,\ldots, K\}$ , is made vanishing). Since secrecy is of concern only to transmitters $\{i|i\in \mathcal {S}\}$ but not to transmitters $\{i|i\in \mathcal {S}^{c}\}$ , where $\mathcal {S}^{c}=\mathcal {K}\backslash \mathcal {S}$ , different transmission strategies could be employed at transmitters $\{i|i\in \mathcal {S}^{c}\}$ . Consider the following two scenarios: 1) transmitters $\{i|i\in \mathcal {S}^{c}\}$ use deterministic encoders (which are conventionally used for MAC without secrecy), competing for the channel resource (i.e., being competitive) and 2) transmitters $\{i|i\in \mathcal {S}^{c}\}$ use stochastic encoders, helping to hide other transmitters’ messages from the eavesdropper (i.e., being cooperative). As a result, we establish the respective $\mathcal {S}$ -collective secrecy achievable rate regions and demonstrate the advantage of being cooperative theoretically and numerically. To this end, in addition to the standard techniques, our results build upon two techniques. The first is a generalization of Chia-El Gamal’s lemma on entropy bound for a set of codewords given partial information. The second is to utilize a compact representation of a list of sets that, together with submodular properties of mutual information functions involved, leads to an efficient Fourier-Motzkin elimination. These two approaches allow us to derive achievable regions in this work, and could also be of independent interest in other context.

Information-Theoretic Privacy for Smart Metering Systems with a Rechargeable Battery

Smart-metering systems report electricity usage of a user to the utility provider on almost real-time basis. This could leak private information about the user to the utility provider. In this paper, we investigate the use of a rechargeable battery in order to provide privacy to the user. We assume that the user load sequence is a first-order Markov process, the battery satisfies ideal charge conservation, and that privacy is measured using normalized mutual information (leakage rate) between the user load and the battery output. We study the optimal battery charging policy that minimizes the leakage rate among the class of battery policies that satisfy causality and charge conservation. We propose a series reduction on the original problem and ultimately recast it as a Markov Decision Process (MDP) that can be solved using a dynamic program. In the special case of i.i.d. demand, we explicitly characterize the optimal policy and show that the associated leakage rate can be expressed as a single-letter mutual information expression. In this case, we show that the optimal charging policy admits an intuitive interpretation of preserving a certain invariance property of the state. Interestingly an alternative proof of optimality can be provided that does not rely on the MDP approach, but is based on purely information theoretic reductions.

Path-dependent behavior and information leakage in financial markets

I develop a new mechanism that exploits the leakage of information in financial markets to deliver herding and contrarian behavior, which I label “path-dependent behavior.” The mechanism is related to the role of word-of-mouth communication in transmitting information about stocks among traders. In practice, this occurs via dealing interactions and a notable phenomenon called “the broker’s ear.” I find that, for a suitably long trading history, path-dependent behavior is more likely the better the quality of traders’ private information. Herding in the direction of the true state of the world occurs almost surely for any initial beliefs, and it improves price informativeness. An external observer who underestimates/overestimates the rate of information leakage will always overestimate/underestimate the quality of private information. I also show that when the quality of private information is very high and the asymmetry of information between traders and market maker is pronounced, the market is expected to herd 50% of the time. Nonetheless, this has little impact on order imbalance, excluding cases exhibiting catastrophic price behavior.

Smart Meter Privacy With Renewable Energy and an Energy Storage Device

A smart meter (SM) measures a consumer’s electricity consumption and reports it automatically to a utility provider (UP) in almost real time. Despite many advantages of SMs, their use also leads to serious concerns about consumer privacy. In this paper, SM privacy is studied by considering the presence of a renewable energy source (RES) and a rechargeable battery (RB), which can be used to partially hide the consumer’s energy consumption behavior. Privacy is measured by the information leakage rate , which denotes the average mutual information between the user’s real energy consumption and the energy requested from the grid, which the SM reads and reports to the UP. The impact of the knowledge of the amount of energy generated by the RES at the UP is also considered. The minimum information leakage rate is characterized as a computable information theoretic single-letter expression in the two extreme cases, that is, when the battery capacity is infinite or zero. Numerical results are presented for the finite battery capacity case to illustrate the potential privacy gains from the existence of an RB. It is shown that, while the information leakage rate decreases with increasing availability of an RES, larger storage capacity is needed to fully exploit the available energy to improve the privacy.

Information-Theoretic Privacy in Smart Metering Systems Using Cascaded Rechargeable Batteries

A rechargeable battery may alleviate the issue of privacy loss in a smart metering system by distorting a household's load profile. However, existing studies involve a single rechargeable battery, whereas in a network scenario, there could be multiple batteries connected together. In this letter, we study the extension where a user's electricity load is input into a network of two rechargeable batteries, connected in series, and operating individually. This battery network attempts to mask the user load from the utility provider. We focus on the case of independent identically distributed load profile and a system of ideal batteries with no conversion loss, and use normalized mutual information (leakage rate) as the privacy metric. We derive upper and lower bounds on the leakage rate in terms of (single-letter) mutual information expressions. On the achievability side, our information-theoretic upper bound captures the novel tension between minimizing the leakage across each individual battery and the effect of their joint interaction. For the lower bound, we show that a system with a single battery, whose storage capacity is the sum of the two individual batteries, can achieve a leakage rate at least as small as our proposed setup. Furthermore, we use simulations to compare achievable leakage of our proposed scheme with several baseline schemes. The achievable leakage rates obtained in this study could help us to elucidate the privacy performance of a network of batteries.