Brute Force Technique Research Articles

Analysis of the Concept of Solving the Sudoku Game Using Backtracking and Brute Force Algorithms

Sudoku is a puzzle game that arranges numbers from one to nine on a board consisting of 9x9 squares. This game has a rule: the numbers arranged on a board cannot be the same in each row or column. The main goal of this Sudoku game is to complete the board and win by entering numbers into each empty box. Therefore, in this Sudoku game, there is only one valid solution. At the start of the game, several numbers are provided, which serve as clues for players to fill in the next box. The number of clues at the start of the game determines whether the Sudoku game level is difficult. The fewer the clues given, the more difficult it is to solve Sudoku. Solving Sudoku problems cannot be done manually, so several algorithms are needed, which require a lot of repetition and search functions. In this research, we will compare concepts in solving Sudoku using the Backtracking algorithm and the backtracking algorithm using the brute force technique. This comparison is seen from the effectiveness of solving Sudoku. The results of this research conclude that to solve Sudoku logic quickly and efficiently, the backtracking algorithm can be used compared to the Brute Force algorithm. This is because the backtracking algorithm has better complexity, and the solution steps are fast and “smart”. In contrast, the brute algorithm takes longer to complete because the brute force algorithm has to search for all the possibilities. The average time required to complete 10 9 x 9 puzzle tests with backtracking is 10910.96 ms, while the brute force algorithm takes longer, around 15871.90 ms.

PASS POINT SELECTION OF AUTOMATIC GRAPHICAL PASSWORD AUTHENTICATION TECHNIQUE BASED ON HISTOGRAM METHOD

Graphical passwords, as opposed to textual passwords, require the user to pick pictures or draw symbols rather than input written letters. They are an option that may be explored in order to get over the issues that are caused by the system of passwords that are based on text. It has been hypothesized that graphical passwords are more difficult to crack using a brute force technique or to figure out through guessing. This paper proposes an authentication system based on a graphical password method. The proposed system computes the password points using histogram arithmetic and encrypts the chosen password points using SHA512. The envisioned system has been realized as an android application and evaluated with existing research considering multiple measurements such as required login time, password space, and entropy. The findings reveal that the new suggested system outperforms the reference work by more than 85% in terms of login latency and more than 72% in terms of entropy results.

Comparing brute force to transition path sampling for gas hydrate nucleation with a flat interface: comments on time reversal symmetry.

Fluid to solid nucleation is often investigated with the rare event method transition path sampling (TPS). I claim that the inherent irreversibility of solid nucleation, even at stationary conditions, calls into question TPS's applicability for determining solid nucleation mechanisms, especially for pre-critical behavior. Even when applied to a phenomenon which displays time reversal asymmetry like solid nucleation, TPS is a good means of exploring phase space and giving trends in post-critical structure, and its ability to facilitate nucleation rate and free energy calculations remains outstanding. Forward-only splitting and ratcheting methods such as forward flux sampling are more attractive for understanding nucleation mechanisms as they do not require time reversal symmetry, but at low driving forces may suffer from the same limitations as brute force: they may never make it to the first ratchet. Here I briefly summarize the TPS method and gas hydrate nucleation simulation literature, focusing on topics within both to facilitate a comparison of brute force hydrate nucleation to transition path sampling of hydrate nucleation. Perhaps anecdotally, the brute force technique results in more crystalline trajectories despite having higher driving forces than TPS. I maintain this difference is because of the inherent irreversibility of hydrate nucleation, meaning its pre-critical behavior cannot accurately be determined by the melting trajectories that comprise approximately half of the configurations in TPS's path ensemble.

Performance Improvement Using ICIC for UAV-Assisted Public Safety Networks with Clustered Users during Emergency

The application of drones, also known as unmanned aerial vehicles deployed as unmanned aerial base stations (UABSs), has received extensive interest for public safety communications (PSC) to fill the coverage gaps and establish ubiquitous connectivity. In this article, we design a PSC LTE-Advanced air–ground-based HetNet (AG-HetNet) that is a scenario representation of a geographical area during and after a disaster. As part of the AG-HetNet infrastructure, we have UABSs and ground user equipment (GUE) flocking together in clusters at safe places or evacuation shelters. AG-HetNet uses cell range expansion (CRE), intercell interference coordination (ICIC), and 3D beamforming techniques to ensure ubiquitous connectivity. Through system-level simulations and using a brute-force technique, we evaluate the performance of the AG-HetNet in terms of fifth-percentile spectral efficiency (5pSE) and coverage probability. We compare system-wide 5pSE and coverage probability when UABSs are deployed on a hexagonal grid and for different clustering distributions of GUEs. The results show that reduced power subframes (FeICIC) defined in 3GPP Release-11 can provide practical gains in 5pSE and coverage probability than the 3GPP Release-10 with almost blank subframes (eICIC).

Optimizing Finite-Blocklength Nested Linear Secrecy Codes: Using the Worst Code to Find the Best Code.

Nested linear coding is a widely used technique in wireless communication systems for improving both security and reliability. Some parameters, such as the relative generalized Hamming weight and the relative dimension/length profile, can be used to characterize the performance of nested linear codes. In addition, the rank properties of generator and parity-check matrices can also precisely characterize their security performance. Despite this, finding optimal nested linear secrecy codes remains a challenge in the finite-blocklength regime, often requiring brute-force search methods. This paper investigates the properties of nested linear codes, introduces a new representation of the relative generalized Hamming weight, and proposes a novel method for finding the best nested linear secrecy code for the binary erasure wiretap channel by working from the worst nested linear secrecy code in the dual space. We demonstrate that our algorithm significantly outperforms the brute-force technique in terms of speed and efficiency.

LMP Sensitivity Calculation with Load Uncertainty by Using Combined Heuristic and Brute-force Technique

LMP Sensitivity Calculation with Load Uncertainty by Using Combined Heuristic and Brute-force Technique

Optimal reconfiguration for Extra high voltage transmission networks using an enhanced Brute-Force algorithm

Over the last decade, Extra high voltage (EHV) transmission networks are becoming excessively meshed to reliably accommodate different types of generation and meet the operational security constraints during steady state and transient conditions. However, excessive meshing, combined with the addition of new power plants, can result in short circuit levels that exceed the capability of switchgear components. As such, there is a growing need to limit, the degree of meshing to accommodate the short circuit capability of the existing network assets, thus avoid catastrophic implications that may lead to very expensive equipment damage and personal safety concerns during fault conditions. Under different network conditions, the operators may have to reconfigure the EHV transmission grid differently to avoid exceeding the short circuit rating of the network assets, while maintaining the grid reliability following the next contingency. This paper proposes a new deterministic optimization model for determining the best EHV transmission network reconfiguration for short circuit relief, while meeting the network steady state and transient security requirements. The optimization model is solved using an enhanced Brute force algorithm that limits the search space, hence improves the computation efficiency of the classical Brute Force technique. To test the accuracy and computation efficiency of the proposed optimization model and enhanced algorithm, the IEEE 39-bus model and a real-size practical EHV network model were used as testbeds. The results demonstrate that the algorithm managed to successfully identify optimum EHV grid reconfiguration that would limit the short circuit levels while satisfying the steady state and transient security requirements mandated by the network operators.

A Systematic Survey of Multi-Factor Authentication for Cloud Infrastructure

The unauthorized usage of various services and resources in cloud computing is something that must be protected against. Authentication and access control are the most significant concerns in cloud computing. Several researchers in this field suggest numerous approaches to enhance cloud authentication towards robustness. User names and associated passwords have been a common practice for long as Single Factor Authentication. However, advancements in the speed of computing and the usage of simple methods, starting from the Brute Force technique to the implementation of advanced and efficient crytographic algorithms, have posed several threats and vulnerabilities for authentication systems, leading to the degradation of their effectiveness. Multi-factor authentication has emerged as a robust means of securing the cloud using simultaneous and multiple means of authentication factors. This employs multiple levels of cascaded authentication checks. This paper covers an extensive and systematic survey of various factors towards their adoption and suitability for authentication for multi-factor authentication mechanisms. The inference drawn from the survey is in terms of arriving at a unique authentication factor that does not require any additional, specialized hardware or software for multi-factor authentication. Such authentication also uses the distinct biometric characteristics of the concerned user in the process. This arrangement augments the secured and robust user authentication process. The mechanism is also assessed as an effective means against impersonation attacks.

Blockchain based energy efficient multi-tasking optimistic scenario for mobile edge computing

Mobile edge computational power faces the difficulty of balancing the energy consumption of many devices and workloads as science and technology advance. Most related research focuses on exploiting edge server computing performance to reduce mobile device energy consumption and task execution time during task processing. Existing research, however, shows that there is no adequate answer to the energy consumption balances between multi-device and multitasking. The present edge computing system model has been updated to address this energy consumption balance problem. We present a blockchain-based analytical method for the energy utilization balance optimization problem of multi-mobile devices and multitasking and an optimistic scenario on this foundation. An investigation of the corresponding approximation ratio is performed. Compared to the total energy demand optimization method and the random algorithm, many simulation studies have been carried out. Compared to the random process, the testing findings demonstrate that the suggested greedy algorithm can improve average performance by 66.59 percent in terms of energy balance. Furthermore, when the minimum transmission power of the mobile device is between five and six dBm, the greedy algorithm nearly achieves the best solution when compared to the brute force technique under the classical task topology.

Source attribution of nitrogen oxides across Germany: Comparing the labelling approach and brute force technique with LOTOS-EUROS

Millions of people are exposed to enhanced levels of nitrogen dioxide in urbanized areas, leading to severe health effects. Moreover, nitrogen oxides contribute to the formation of ozone and particulate matter, and as such have wider health related impacts. A substantial reduction of nitrogen oxides may offer considerable health benefits for the human society. As a first step, this requires a detailed understanding of source sector contributions to nitrogen oxide levels. Whereas many regions have information on the local (traffic) contributions, the source contributions to the rural and urban background levels are commonly not available. In this study we compared and evaluated the results of two source attribution techniques to quantify the contribution of 5 source sectors to background nitrogen oxide levels across Germany. The results of a labelling technique were compared to brute force simulations with variable emission reduction percentages. The labelled NO2 source contributions of the main sectors averaged for all urban background stations are road transport (45 ± 5%), non-road transport (24 ± 6%), energy & industry (20 ± 3%), households (10 ± 6%), and the remaining source sectors (1 ± 1%). For the brute force technique, the explained mass differs from the unperturbed baseline concentration after scaling the impact of each sensitivity simulation to 100%. The attributed concentration of NO2 is lower in urban background areas (−3 ± 5%) and larger in the rural background (4 ± 6%) than that of the labelling. Largest deviations up to −15% are calculated for the major cities along the Rhine and Main. The annual average overestimation for NO is about 53 ± 24% for urban and 40 ± 26% for rural background sites based on a 20% reduction of emissions. On shorter time scales the differences are larger. These deviations are caused by (the lack of) regime changes in the titration of ozone, most notably present at ozone-limiting conditions during nocturnal winter periods. As a consequence, the differences between the methodologies are larger for smaller emission reduction percentages applied in the brute force technique. Similarly, for small-sized emission source sectors larger deviations were found compared to large-sized sector categories. Hence, applying the brute force technique for the source attribution for a single sector should be avoided as there is no way to verify for consistency and quantify the error for the sector and total explained contribution. We recommend applying the labelling approach to estimate sector contributions in forthcoming studies for nitrogen oxides.

Algorithms for rapid digitalization of prescriptions

Prescription data are invaluable for healthcare research and intelligence, yet, extraction of these data is challenging as this information is intertwined in the unstructured and non-grammatical text in prescription images. Moreover, text extraction from images in itself is hard, particularly for handwritten text. While piecemeal solutions exist, they are either limited to a small set of entities of interest or have very low accuracy and are not scalable. In this paper, we present two algorithms: the C-Cube algorithm for digitization of computer-printed prescriptions and the 3-Step Filtering algorithm for handwritten prescriptions. While a brute-force approach would match every word that is received from an optical character reader (OCR) with all possible entries in the database, this approach is inefficient and imprecise. The premise of our algorithms is an application of pattern intelligence to select a much smaller set of words (from the words returned by the OCR) as potential entities of interest. We rigorously tested the two algorithms on a corpus of more than 10,000 prescriptions’ images, taking the brute-force technique as the baseline methodology. Regarding latencies, we found that the C-Cube and the 3-Step Filtering algorithms were 588 and 231 times faster than the brute-force approach. In terms of accuracies, we found that the F-score of the C-cube algorithm was 90% higher than the F-score of the brute-force approach whereas the F-score for the 3-Step filtering algorithm was found to be 8,600% higher. The algorithms are decidedly faster and more accurate than the brute-force approach. These attributes make them suitable for implementation in real-time environments as well as for use in batch-mode for various applications. We expect the algorithms to play a significant role in the digitalization of healthcare information and briefly discuss a few applications.

Molecular insights into a mechanism of resveratrol action using hybrid computational docking/CoMFA and machine learning approach

A phytoalexin, Resveratrol remains a legendary anticancer drug candidate in the archives of scientific literature. Although earlier wet-lab experiments rendering its multiple biological targets, for example, epidermal growth factors, Pro-apoptotic protein p53, sirtuins, and first apoptosis signal (Fas) receptor, Mouse double minute 2 (MDM2) ubiquitin-protein ligase, Estrogen receptor, Quinone reductase, etc. However, notwithstanding some notable successes, identification of an appropriate Resveratrol target(s) has remained a major challenge using physical methods, and hereby limiting its translation into an effective therapeutic(s). Thus, computational insights are much needed to establish proof-of-concept towards potential Resveratrol target(s) with minimum error rate, narrow down the search space, and to assess a more accurate Resveratrol signaling pathway/mechanism at the starting point. Herein, a brute-force technique combining computational receptor-, ligand-based virtual screening, and classification-based machine learning, reveals the precise mechanism of Resveratrol action. Overall, MDM2 ubiquitin-protein ligase (4OGN.pdb) and co-crystallized quinone reductases 2 (4QOH.pdb) were found two suitable drug targets in the case of Resveratrol derivatives. Indeed, carotenoid cleaving oxygenase together with later twos gave gigantic momentum in guiding the rational drug design of Resveratrol derivatives. These molecular modeling insights would be useful for Resveratrol lead optimization into a more precise science. Communicated by Ramaswamy H. Sarma

Genetic Behaviour of Zika Virus and Identification of Motif

ZIKV is a mosquito-borne disease. It is known to cause neurological disorders and congenital disabilities in newborns. The Genome Sequence of the Zika virus is used for the study. The essential cell functionalities like circadian behavior and expression of genes are studied. Regulatory proteins are alternating functionalities during daytime and night time. Identifying motif is made by understanding the features of motifs, finding the count matrix, and formulating the profile matrix. The consensus string of the Zika virus is to be computed, and the score motif is to be calculated. Different techniques of motif finding like the Brute Force technique and Greedy Search techniques are proposed. In the Brute Force technique, each motif is selected, its score is to be calculated, and then the minimum score can be obtained. The Brute Force technique will take an enormous amount of time, but it is guaranteed to find a solution. The Greedy Search technique is not guaranteed to find motif like the Brute Force technique but can give a close answer in a realistic time. This paper presents the identification of motif in the Zika virus genome using programming techniques.

An approximate analytical formula for estimating the weight of factors affecting the spread of COVID-19: a case study of the first wave

ABSTRACTCOVID-19 pandemic has changed the way we live our lives for the foreseen future. To date, there have been over 113 million reported cases and 2.5 million deaths worldwide. Many studies investigated the factors affecting the number of daily cases such as weather conditions, lockdown duration and other factors. In this study, we propose a COVID-19 analytical formula for factors contributing to the number of the new coronavirus daily cases. We have also calculated values of relative weights of those factors. We focus on the first wave data that are publically available. Seven countries were considered including the UK, Italy, Spain, Canada, South Korea, Germany and France. We considered the following factors: temperature, humidity, government expenditure, lockdown hours and the number of daily tests for COVID-19 performed. The weights were calculated based on the hypothesis that a high correlation between recorded data of a given pair of countries implies a high correlation of the pair’s COVID-19 proposed analytical formula. The factors are calculated using the brute-force technique. Our results showed that in five out of the seven countries; temperature, humidity, and lockdown duration were the most dominant with values of 26%, 32% and 38%, respectively. In other countries, however, humidity, government expenditure and the daily performed tests for COVID-19 were the most effective factors, with relative values of 35%, 26%, and 28%.

Sistem Monitoring Login Failure dengan Via Telegram dari Serangan Brutus pada Router Mikrotik

A monitoring system is needed to monitor a network topology from attacks that might occur at that time. A realtime monitoring system is needed to find out the attack. Therefore, in this study, an attack scenario on a proxy router was carried out using a brute force technique. The brute force technique is an efficient method that tries every possible login password character that the network administrator might use. This brute force technique already exists in the application used, namely Brutus. Brutus is executed by focusing the attack on port 23 telnet on the proxy router. The system log listed as a login failure caused by a brute attack on the proxy router will be forwarded by a script that is running to a notification with a network administrator telegram bot. From the results of research that has been carried out on the monitoring system on the proxy running in real time to notify the login failure message via telegram. The telegram notification will stop if the password has been found by Brutus or the Brutus dictionary does not find the password on the designed Mikrotik router network. Prevention is done by disabling open ports and activating the drop firewall menu if it finds a possible attacker's ip address on the mikrotik router to reduce attacks from the attacker.

Design scheme of multiple-subway lines for minimizing passengers transfers in mega-cities transit networks

ABSTRACT The integration of subway and bus networks has become an effective solution to reduce the growing congestion. This study presents a practical scheme of multiple subway line design to obviate the difficulty of dealing with large-scale networks that always suffer from severe combinatorial problems. The new lines are aimed to increase the overall transit network efficiency. A mathematical formulation is derived to minimize passenger transfer number (PTN) among public transportation facilities. A real case network of Greater Cairo city is used to validate the presented methodology. An algorithm is designed to optimize the number of needed transfers between stations. The analysis includes a multi-subway evaluation of three categories to identify the optimal solution depending on PTN variance and direct trips percentage. After testing many solutions using the brute force technique, two subway lines are recommended with their station structure to increase the overall network connectivity by more than 70%.

Heuristic approach for jointly optimising FeICIC and UAV locations in multi‐tier LTE‐advanced public safety HetNet

Unmanned aerial vehicles (UAVs) enabled networks can enhance wireless connectivity and support emerging services. However, this would require system-level understanding to modify and extend the existing terrestrial network infrastructure. In this study, the authors integrated UAVs as user equipment and base stations into an existing long term evolution (LTE)-Advanced heterogeneous network (HetNet) and provide system-level insights of this three-tier LTE-Advanced air-ground HetNet (AG-HetNet). The performance of AG-HetNet was evaluated through brute-force technique and heuristics algorithms in terms of the fifth percentile spectral efficiency (5pSE) and coverage probability. In particular, system-wide 5pSE and coverage probability were compared, when unmanned aerial base stations (UABSs) are deployed on a fixed hexagonal grid and when their locations are optimised using a genetic algorithm (GA) and elitist harmony search algorithm based on the genetic algorithm (eHSGA); while jointly optimising the inter-cell interference coordination (ICIC) and cell range expansion (CRE) network parameters for different ICIC techniques. The simulation results show that the heuristic algorithms (GA and eHSGA) outperform the brute-force technique and achieve better peak values of coverage probability and 5pSE. Simulation results also show that a trade-off exists between peak values and computation time when using heuristic algorithms. Furthermore, the three-tier hierarchical structuring of reduced power subframes further-enhanced ICIC (FeICIC) defined in 3GPP Rel-11 provides considerably better 5pSE and coverage probability than the 3GPP Rel-10 with almost blank subframes eICIC. They also investigated the network performance for different practical deployment heights of UABS and they found low-altitude UABSs to perform sparsely better than medium-altitude UABSs.

IMPLEMENTASI INTRUSION DETECTION SYSTEM (IDS) MENGGUNAKAN SURICATA PADA LINUX DEBIAN 9 BERBASIS CLOUD VIRTUAL PRIVATE SERVERS (VPS)

The development of information technology, especially on virtual Private server (VPS) technology in particular that uses Debian Linux operating system, increasingly facilitated with the service Adaya of some VPS providers both locally and non-local, but there is a problem vulnerability if, the server maintainers do not shame testing against the resilience of attacks from outside parties, with the Network Development Life Cycle (NDLC) method is one of the most popular in the Monitoring phase is using Suricata Intrusion Detection System (IDS) software. Suricata is a tool to detect any suspicious activity that could be threatening a network or server with Brute Force technique, DDOS, Port Scanning. Suricata is able to display logs from suspicious activity results in detail with the time, date and IP address of the activity even with the tools used to perform the activity. Also suricata can detect if there is suspicious activity associated with the network..

A Cryptographic Technique Involving Finite Fields and Logical Operators

Objectives: The aim of this study is to propose a new encryption/ decryption technique which involves logical operators and finite field. Methods/statistical analysis: The study proposes a new method for encrypting/decrypting messages which use logical operator XOR and finite field. The method involves sharing common keys between sender and receiver. Then converting plain text into ASCII values bit-form. XORing this with random matrix and then using finite field GF (2^5) for converting it into polynomial elements. These elements are then used for creating cipher text. Decrypting process is reverse of encrypting process. Findings: The technique uses 6×6 matrix form for encrypting messages which can be very difficult to crack with known plain text attacks. The use of XOR operations displaces bits in matrix which makes it difficult to break by brute force technique. Application/improvements: The technique is useful in areas where sensitive information is to be transferred like banking, military services. If the private key has got into third-party hands, the damage can be huge. To overcome this, the proposed algorithm can be used by randomizing the keys used for encrypting the messages which will provide different keys for encrypting different data blocks. Keywords: Encryption, Decryption, Finite Fields, Logical Operator XOR.

The m-delay Autoregressive Model with Application

The classical autoregressive (AR) model has been widely applied to predict future data using m past observations over five decades. As the classical AR model required m unknown parameters, this paper implements the AR model by reducing m parameters to two parameters to obtain a new model with an optimal delay called as the m-delay AR model. We derive the m-delay AR formula for approximating two unknown parameters based on the least squares method and develop an algorithm to determine optimal delay based on a brute-force technique. The performance of the m-delay AR model was tested by comparing with the classical AR model. The results, obtained from Monte Carlo simulation using the monthly mean minimum temperature in Perth Western Australia from the Bureau of Meteorology, are no significant difference compared to those obtained from the classical AR model. This confirms that the m-delay AR model is an effective model for time series analysis.