Biblio

Measuring the information leakage is critical for evaluating the practical security of cryptographic devices against side-channel analysis. Information-theoretic measures can be used (along with Fano’s inequality) to derive upper bounds on the success rate of any possible attack in terms of the number of side-channel measurements. Equivalently, this gives lower bounds on the number of queries for a given success probability of attack. In this paper, we consider cryptographic implementations protected by (first-order) masking schemes, and derive several information-theoretic bounds on the efficiency of any (second-order) attack. The obtained bounds are generic in that they do not depend on a specific attack but only on the leakage and masking models, through the mutual information between side-channel measurements and the secret key. Numerical evaluations confirm that our bounds reflect the practical performance of optimal maximum likelihood attacks.

Intelligent connected vehicle platoon technology can reduce traffic congestion and vehicle fuel. However, attacks on the data transmitted by the platoon are one of the primary challenges encountered by the platoon during its travels. The false data injection (FDI) attack can lead to road congestion and even vehicle collisions, which can impact the platoon. However, the complexity of the cellular - vehicle to everything (C-V2X) environment, the single source of the message and the poor data processing capability of the on board unit (OBU) make the traditional detection methods’ success rate and response time poor. This study proposes a platoon state information fusion method using the communication characteristics of the platoon in C-V2X and proposes a novel platoon intrusion detection model based on this fusion method combined with sequential importance sampling (SIS). The SIS is a measured strategy of Monte Carlo integration sampling. Specifically, the method takes the status information of the platoon members as the predicted value input. It uses the leader vehicle status information as the posterior probability of the observed value to the current moment of the platoon members. The posterior probabilities of the platoon members and the weights of the platoon members at the last moment are used as input to update the weights of the platoon members at the current moment and obtain the desired platoon status information at the present moment. Moreover, it compares the status information of the platoon members with the desired status information to detect attacks on the platoon. Finally, the effectiveness of the method is demonstrated by simulation.

The paper introduces and develops the new concept of current-mode multifunctional circuit, a computational structure that is able to implement, using the same functional core, a multitude of circuit functions: amplifying, squaring, square-rooting, multiplying, exponentiation or generation of any continuous mathematical function. As a single core computes a large number of circuit functions, the original approach of analog signal processing from the perspective of multifunctional structures presents the important advantages of a much smaller power consumption and design costs per implemented function comparing with classical designs. The current-mode operation, associated with the original concrete implementation of the proposed structure increase the accuracy of computed functions and the frequency behaviour of the designed circuit. Additionally, the temperature-caused errors are almost removed by specific design techniques. It will be also shown a new method for third-order approximating the exponential function using an original approximation function. A generalization of this method will represent the functional basis for realizing an improved accuracy function synthesizer circuit with a simple implementation in CMOS technology. The proposed circuits are compatible with low-power low voltage operations.

Since the cyber and physical layers in the distribution system are deeply integrated, the traditional distribution system has gradually developed into the cyber-physical distribution system (CPDS), and the failures of the cyber layer will affect the reliable and safe operation of the whole distribution system. Therefore, this paper proposes an CPDS planning method considering the reliability of the cyber-physical system. First, the reliability evaluation model of CPDS is proposed. Specifically, the functional reliability model of the cyber layer is introduced, based on which the physical equipment reliability model is further investigated. Second, an optimal planning model of CPDS considering cyber-physical random failures is developed, which is solved using the Monte Carlo Simulation technique. The proposed model is tested on the modified IEEE 33-node distribution system, and the results demonstrate the effectiveness of the proposed method.

The pre-magnetization of inertial confinement fusion capsules is a promising avenue for reaching hotspot ignition, as the magnetic field reduces electron thermal conduction losses during hotspot formation. However, in order to reach high yields, efficient burn-up of the cold fuel is vital. Suppression of heat flows out of the hotspot due to magnetization can restrict the propagation of burn and has been observed to reduce yields in previous studies [1] . This work investigates the potential suppression of burn in a magnetized plasma utilizing the radiation-MHD code ‘Chimera’ in a planar geometry.. This code includes extended-MHD effects, such as the Nernst term, and a Monte-Carlo model for magnetized alpha particle transport and heating. We observe 3 distinct regimes of magnetized burn in 1D as initial magnetization is increased: thermal conduction driven; alpha driven; and suppressed burn. Field transport due to extended-MHD is also observed to be important, enhancing magnetization near the burn front. In higher dimensions, burn front instabilities have the potential to degrade burn even more severely. Magneto-thermal type instabilities (previously observed in laser-heated plasmas [2] ) are of particular interest in this problem.

This paper investigates the physical layer security of a cognitive radio (CR) non-orthogonal multiple-access (NOMA) network supported by an intelligent reflecting surface (IRS). In a CR network, a secondary base station (BS) serves a couple of users, i.e., near and far users, via NOMA transmission under eavesdropping from a malicious attacker. It is assumed that the direct transmission link from the BS and far user is absent due to obstacles. Thus, an IRS is utilized to support far user communication, however, the communication links between the IRS and near/primary users are neglected because of heavy attenuation. The exact secrecy outage probability (SOP) for the near user and approximate SOP for the far user are then derived in closed-form by using the Gauss-Chebyshev approach. The accuracy of the derived analytical SOP is then verified through Monte Carlo simulations. The simulation results also provide useful insights on the impacts of the number of IRS reflecting elements and limited interference temperature on the system SOP.

In this study, the parameters of the Jiles-Atherton (JA) model are investigated to determine suitable solution candidates for hysteresis models of a piezoelectric actuator (PEA). The methodology of this study is to perform Monte Carlo experiments on the JA model by randomly selecting parameters that generate hysteresis curves. The solution space is then restrained such that their normalized area and remnant displacements are comparable to those of the PEA. The data resulting from these Monte Carlo simulations show trends in the parameter space that can be used to further restrain parameter selection windows to find suitable JA parameters to model PEAs. In particular, the results show that selection of the reversibility coefficient and the pinning factor strongly affect both of the hysteresis characteristics studied. A large density of solutions is found in certain parameter distributions for both the area and the remnant displacement, but the remnant displacement generates the densest distributions. These results can be used to more effectively find suitable hysteresis models for modeling purposes.

One of the key topics in network security research is the autonomous COA (Couse-of-Action) attack search method. Traditional COA attack search methods that passively search for attacks can be difficult, especially as the network gets bigger. To address these issues, new autonomous COA techniques are being developed, and among them, an intelligent spatial algorithm is designed in this paper for efficient operations in scalable networks. On top of the spatial search, a Monte-Carlo (MC)-based temporal approach is additionally considered for taking care of time-varying network behaviors. Therefore, we propose a spatio-temporal attack COA search algorithm for scalable and time-varying networks.

In this paper, physical layer security (PLS) analysis of a cooperative wireless communication system in which the source and destination nodes communicate via a relay employing decode-and-forward protocol is performed for double Rayleigh fading channel model. For the system where the source, relay and target have single antenna, an eavesdropper with multiantenna listens the source and relay together by using maximum-ratio-combining, secrecy outage and positive secrecy capacity possibilities are obtained in closed-form. The theoretical results are verified by Monte-Carlo simulations. From the results, it is observed that as the number of antennas of the eavesdropper is increased, the PLS performance of the system worsens.

Network function virtualization (NFV) simplies the coniguration and management of security services by migrating the network security functions from dedicated hardware devices to software middle-boxes that run on commodity servers. Under the paradigm of NFV, the service function chain (SFC) consisting of a series of ordered virtual network security functions is becoming a mainstream form to carry network security services. Allocating the underlying physical network resources to the demands of SFCs under given constraints over time is known as the SFC deployment problem. It is a crucial issue for infrastructure providers. However, SFC deployment is facing new challenges in trading off between pursuing the objective of a high revenue-to-cost ratio and making decisions in an online manner. In this paper, we investigate the use of reinforcement learning to guide online deployment decisions for SFC requests and propose a Policy network Assisted Monte Carlo Tree search approach named PACT to address the above challenge, aiming to maximize the average revenue-to-cost ratio. PACT combines the strengths of the policy network, which evaluates the placement potential of physical servers, and the Monte Carlo Tree Search, which is able to tackle problems with large state spaces. Extensive experimental results demonstrate that our PACT achieves the best performance and is superior to other algorithms by up to 30% and 23.8% on average revenue-to-cost ratio and acceptance rate, respectively.

Dynamic security assessment (DSA) is to ensure the power system being operated under a secure condition that can withstand potential contingencies. DSA normally proceeds periodically on a 5 to 15 minutes basis, where the system security condition over a complete time interval is merely determined upon the system snapshot captured at the beginning of the interval. With high wind power penetration, the minute-to-minute variations of wind power can lead to more volatile power system states within a single DSA time interval. This paper investigates the intra-interval variation (IIV) phenomenon in power system online DSA and analyze whether the IIV problem is deserved attention in future DSA research and applications. An IIV-contaminated testing environment based on hierarchical Monte-Carlo simulation is developed to evaluate the practical IIV impacts on power system security and DSA performance. The testing results show increase in system insecurity risk and significant degradation in DSA accuracy in presence of IIV. This result draws attention to the IIV phenomenon in DSA of wind-energy power systems and calls for more robust DSA approach to mitigate the IIV impacts.

We investigate cognitive radio networks where the unlicensed sender operates in the overlay mode to relay the information of the licensed transmitter as well as send its individual information. To secure information broadcasted by the unlicensed sender against the wire-tapper, we invoke jammers to limit eavesdropping. Also, to exploit efficiently radio frequency energy in licensed signals, we propose the unlicensed sender and all jammers to scavenge this energy source. To assess the security measures of both licensed and unlicensed networks, we first derive rigorous closed-form formulas of licensed/unlicensed secrecy outage probabilities. Next, we validate these formulas with Monte-Carlo simulations before using them to achieve insights into the security capability of the proposed jamming-aided energy harvesting cognitive radio networks in crucial system parameters.

A physical layer security (PLS) technique called Gray Code Hopping (GCH) is presented offering simplistic implementation and no bit error rate (BER) performance degradation over the main channel. A synchronized transmitter and receiver "hop" to an alternative binary reflected Gray code (BRGC) mapping of bits to symbols between each consecutive modulation symbol. Monte Carlo simulations show improved BER performance over a similar technique from the literature. Simulations also confirm compatibility of GCH with either hard or soft decision decoding methods. Simplicity of GCH allows for ready implementation in adaptive 5th Generation New Radio (5G NR) modulation coding schemes.

Mitigating cyber threats requires adequate understanding of the attacker characteristics in particular their patterns. Such knowledge is essential in addressing the defensive measures that mitigate the attack. If the attacker enters in the network system, the game tree model generates resources by to counter such threat. This is done by altering the parity in the next game tree iteration which yield an adequate response to counter it. If an attacker enters a network system, and a game tree models the resources he must interface with, then that game tree can be altered, by changing the parity on the next to last iteration. This paper analyzes the sequence of patterns based on incoming attacks. The detection of attacker’s pattern and subsequent changes in iterations to counter threat can be viewed as adequate resource or know how in cyber threat mitigations It was realized that changing the game tree of the hacker deprives the attacker of network resources and hence would represent a defensive measure against the attack; that is changing varying or understanding attacker paths, creates an effective defensive measure to protect the system against the incoming threats.. In this paper we analyze a unique combination of CFR and MCTS that attempts to detect the behavior of a hacker. Counterfactual Regret (CFR) is a game theory concept that helps identify patterns of attacks. The pattern recognition concept of Monte Carlo Tree Search (MCTS) is used in harmony with CFR in order to enhance the detection of attacks.

We study a problem of covert communication over binary symmetric channels (BSC) in an asynchronous setup. Here, Alice seeks to communicate to Bob over a BSC while trying to be covert with respect to Willie, who observes any communication through possibly a different BSC. When Alice communicates, she transmits a message (using a codeword of length n) at a random time uniformly distributed in a window of size Aw slots. We assume that Bob has side information about the time of transmission leading to a reduced uncertainty of Ab slots for Bob, where \$A\_b$\backslash$lt A\_w\$. In this setup, we seek to characterize the limits of covert communication as a function of the timing advantage. When Aw is increasing exponentially in n, we characterize the covert capacity as a function of Aw and Ab. When Aw is increasing sub-exponentially in n, we characterize lower and upper bounds on achievable covert bits and show that positive covert rates are not feasible irrespective of timing advantage. Using numerical work, we illustrate our results for different network scenarios, and also highlight a tradeoff between timing advantage and channel advantage (between Bob and Willie).

The goal of building a system for precise time measurement in pixel radiation detectors motivates the development of flexible design and verification environment. It should be suitable for quick simulations when individual elements of the system are developed and should be scalable so that systemlevel verification is possible as well. The approach presented in this paper is to utilize the power of SystemVerilog language and apply basic Object-Oriented Programming concepts to the test program. Since the design under test is a full-custom mixed-signal design, it must be simulated with AMS simulator and various features of analog design environment are used as well (Monte Carlo analysis, corner analysis, schematic capture GUI-related functions). The presented approach combines these two worlds and should be suitable for small academia projects, where design and verification is seldom done by separate teams.

Supervisory Control and Data Acquisition (SCADA) and Distributed Control Systems (DCS) use advanced computing, sensors, control systems, and communication networks to monitor and control industrial processes and distributed assets. The increased connectivity of these systems to corporate networks has exposed them to new security threats and made them a prime target for cyber-attacks with the potential of causing catastrophic economic, social, and environmental damage. Recent intensified sophisticated attacks on these systems have stressed the importance of methodologies and tools to assess the security risks of Industrial Control Systems (ICS). In this paper, we propose a novel game theory model and Monte Carlo simulations to assess the cybersecurity risks of an exemplary industrial control system under realistic assumptions. We present five game enrollments where attacker and defender agents make different preferences and we analyze the final outcome of the game. Results show that a balanced defense with uniform budget spending is the best strategy against a look-ahead attacker.

Intrusion alerts continue to grow in volume, variety, and complexity. Its cryptic nature requires substantial time and expertise to interpret the intended consequence of observed malicious actions. To assist security analysts in effectively diagnosing what alerts mean, this work develops a novel machine learning approach that translates alert descriptions to intuitively interpretable Action-Intent-Stages (AIS) with only 1% labeled data. We combine transfer learning, active learning, and pseudo labels and develop the Pseudo-Active Transfer Learning (PATRL) process. The PATRL process begins with an unsupervised-trained language model using MITRE ATT&CK, CVE, and IDS alert descriptions. The language model feeds to an LSTM classifier to train with 1% labeled data and is further enhanced with active learning using pseudo labels predicted by the iteratively improved models. Our results suggest PATRL can predict correctly for 85% (top-1 label) and 99% (top-3 labels) of the remaining 99% unknown data. Recognizing the need to build confidence for the analysts to use the model, the system provides Monte-Carlo Dropout Uncertainty and Pseudo-Label Convergence Score for each of the predicted alerts. These metrics give the analyst insights to determine whether to directly trust the top-1 or top-3 predictions and whether additional pseudo labels are needed. Our approach overcomes a rarely tackled research problem where minimal amounts of labeled data do not reflect the truly unlabeled data's characteristics. Combining the advantages of transfer learning, active learning, and pseudo labels, the PATRL process translates the complex intrusion alert description for the analysts with confidence.

Autonomous navigation of a robot is more challenging in an uncontrolled environment owing to the necessity of coordination among several activities. This includes, creating a map of the surrounding, localizing the robot inside the map, generating a motion plan consistent with the map, executing the plan with control and all other tasks involved concurrently. Moreover, autonomous navigation problems are significant for future robotics applications such as package delivery, security, cleaning, agriculture, surveillance, search and rescue, construction, and transportation which take place in uncontrolled environments. Therefore, an attempt has been made in this research to develop a robot which could function as a security agent for a house to address the aforesaid particulars. This robot has the capability to navigate autonomously in the prescribed map of the operating zone by the user. The desired map can be generated using a Light Detection and Ranging (LiDAR) sensor. For robot navigation, it requires to pick out the robot location accurately itself, otherwise robot will not move autonomously to a particular target. Therefore, Adaptive Monte Carlo Localization (AMCL) method was used to validate the accuracy of robot localization process. Moreover, additional sensors were placed around the building to sense the prevailing security threats from intruders with the aid of the robot.

There are a lot of emerging security equipment required to be tested on detection rate (DR) and false alarm rate (FAR) for prohibited items. This article imports Bayesian approach to accept or reject DR and FAR. The detailed quantitative predictions can be made through the posterior distribution obtained by Markov chain Monte Carlo method. Based on this, HDI + ROPE decision rule is established. For the tests that need to make early decision, HDI + ROPE stopping rule is presented with biased estimate value, and criterial precision rule is presented with unbiased estimate value. Choosing the stopping rule according to the test purpose can achieve the balance of efficiency and accuracy.

In this study, we investigate the performance of FSO communication systems under more realistic channel model considering atmospheric turbulence, pointing errors and channel estimation errors together. For this aim, we first derived the composite probability density function (PDF) of imperfect Málaga turbulence channel with pointing errors. Then using this PDF, we obtained bit-error-rate (BER) and ergodic channel capacity (ECC) expressions in closed forms. Additionally, we present the BER and ECC metrics of imperfect Gamma-Gamma and K turbulence channels with pointing errors as special cases of Málaga channel. We further verified our analytic results through Monte-Carlo simulations.

This paper studies the physical layer security (PLS) of a vehicular network employing a reconfigurable intelligent surface (RIS). RIS technologies are emerging as an important paradigm for the realisation of smart radio environments, where large numbers of small, low-cost and passive elements, reflect the incident signal with an adjustable phase shift without requiring a dedicated energy source. Inspired by the promising potential of RIS-based transmission, we investigate two vehicular network system models: One with vehicle-to-vehicle communication with the source employing a RIS-based access point, and the other model in the form of a vehicular adhoc network (VANET), with a RIS-based relay deployed on a building. Both models assume the presence of an eavesdropper to investigate the average secrecy capacity of the considered systems. Monte-Carlo simulations are provided throughout to validate the results. The results show that performance of the system in terms of the secrecy capacity is affected by the location of the RIS-relay and the number of RIS cells. The effect of other system parameters such as source power and eavesdropper distances are also studied.

Given a selected complex orthogonal space-time block code (STBC), transformation algorithms are provided to build a set, S, of unique orthogonal STBCs with cardinality equal to \textbackslashtextbarS\textbackslashtextbar = 2r+c+k-1·r!·c!, where r, c, and k are the number of rows, columns, and data symbols in the STBC matrix, respectively. A communications link is discussed that encodes data symbols with a chosen STBC from the set known only to the transmitter and intended receiver as a means of providing physical layer security (PLS). Expected bit error rate (BER) and informationtheoretic results for an eavesdropper with a priori knowledge of the communications link parameters with the exception of the chosen STBC are presented. Monte Carlo simulations are provided to confirm the possible BER results expected when decoding the communications link with alternative STBCs from the set. Application of the transformation algorithms provided herein are shown to significantly increase the brute force decoding complexity of an eavesdropper compared to a related work in the literature.

Data dropouts in communication network can have a significant impact on wide-area oscillation damping control of a smart power grid with large-scale deployment of distributed and networked phasor measurement units and wind energy resources. Remote feedback signals sent through communication channels encounter data dropout, which is represented by the Gilbert-Elliott model. An observer-driven reduced copy (ORC) approach is presented, which uses the knowledge of the nominal system dynamics during data dropouts to improve the damping performance where conventional feedback would suffer. An expression for the expectation of the bound on the error norm between the actual and the estimated states relating uncertainties in the cyber system due to data dropout and physical system due to change in operating conditions is also derived. The key contribution comes from the analytical derivation of the impact of coupling between the cyber and the physical layer on ORC performance. Monte Carlo simulation is performed to calculate the dispersion of the error bound. Nonlinear time-domain simulations demonstrate that the ORC produces significantly better performance compared to conventional feedback under higher data drop situations.

In this paper, we investigate the local secure connectivity in terms of the probability of existing a secure wireless connection between two legitimate users and the isolated security probability of a legitimate user in stochastic wireless networks. Specifically, the closed-form expressions of the probability that there is a secure wireless communication between two legitimate users are derived first. Then, based on these equations, the corresponding isolated secure probability are given. The characteristics of local secure connectivity are examined in four scenarios combined from two wireless channel conditions (deterministic/Rayleigh fading) and two eavesdropper configurations (non-colluding/colluding). All the derived mathematical equations are validated by the Monte-Carlo simulation. The obtained numerical results in this paper reveal some interesting features of the impact of eavesdropper collusion, wireless channel fading, and density ratio on the secure connection probability and the isolated security probability of legitimate user in stochastic networks.