The largest reported data leakage as of January 2025 was the Cam4 data breach in March 2020, which exposed more than 10 billion data records. The second-largest data breach in history so far, the Yahoo data breach, occurred in 2013. The company initially reported about one billion exposed data records, but after an investigation, the company updated the number, revealing that three billion accounts were affected. The National Public Data Breach was announced in August 2024. The incident became public when personally identifiable information of individuals became available for sale on the dark web. Overall, the security professionals estimate the leakage of nearly three billion personal records. The next significant data leakage was the March 2018 security breach of India's national ID database, Aadhaar, with over 1.1 billion records exposed. This included biometric information such as identification numbers and fingerprint scans, which could be used to open bank accounts and receive financial aid, among other government services.
Cybercrime - the dark side of digitalization As the world continues its journey into the digital age, corporations and governments across the globe have been increasing their reliance on technology to collect, analyze and store personal data. This, in turn, has led to a rise in the number of cyber crimes, ranging from minor breaches to global-scale attacks impacting billions of users – such as in the case of Yahoo. Within the U.S. alone, 1802 cases of data compromise were reported in 2022. This was a marked increase from the 447 cases reported a decade prior. The high price of data protection As of 2022, the average cost of a single data breach across all industries worldwide stood at around 4.35 million U.S. dollars. This was found to be most costly in the healthcare sector, with each leak reported to have cost the affected party a hefty 10.1 million U.S. dollars. The financial segment followed closely behind. Here, each breach resulted in a loss of approximately 6 million U.S. dollars - 1.5 million more than the global average.
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Version 3 with 517M hashes and counts of password usage ordered by most to least prevalent Pwned Passwords are 517,238,891 real world passwords previously exposed in data breaches. This exposure makes them unsuitable for ongoing use as they re at much greater risk of being used to take over other accounts. They re searchable online below as well as being downloadable for use in other online system. The entire set of passwords is downloadable for free below with each password being represented as a SHA-1 hash to protect the original value (some passwords contain personally identifiable information) followed by a count of how many times that password had been seen in the source data breaches. The list may be integrated into other systems and used to verify whether a password has previously appeared in a data breach after which a system may warn the user or even block the password outright.
In 2024, the number of data compromises in the United States stood at 3,158 cases. Meanwhile, over 1.35 billion individuals were affected in the same year by data compromises, including data breaches, leakage, and exposure. While these are three different events, they have one thing in common. As a result of all three incidents, the sensitive data is accessed by an unauthorized threat actor. Industries most vulnerable to data breaches Some industry sectors usually see more significant cases of private data violations than others. This is determined by the type and volume of the personal information organizations of these sectors store. In 2024 the financial services, healthcare, and professional services were the three industry sectors that recorded most data breaches. Overall, the number of healthcare data breaches in some industry sectors in the United States has gradually increased within the past few years. However, some sectors saw decrease. Largest data exposures worldwide In 2020, an adult streaming website, CAM4, experienced a leakage of nearly 11 billion records. This, by far, is the most extensive reported data leakage. This case, though, is unique because cyber security researchers found the vulnerability before the cyber criminals. The second-largest data breach is the Yahoo data breach, dating back to 2013. The company first reported about one billion exposed records, then later, in 2017, came up with an updated number of leaked records, which was three billion. In March 2018, the third biggest data breach happened, involving India’s national identification database Aadhaar. As a result of this incident, over 1.1 billion records were exposed.
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Access Leak Detector export import data including profitable buyers and suppliers with details like HSN code, Price, Quantity.
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License information was derived automatically
This database includes the code used to analyze and produce the results for the following research article: Minimizing Search Areas for Leak Detection in Water Distribution Networks by B. Snider, G. Lewis, A.S. Chen, L. Vamvakeridou-Lyroudia, S. Djordjevic, D.A. Savic. Journal of Hydroinformatics. (Accepted - awaiting publication).
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712 Global exporters importers export import shipment records of Leakage detector with prices, volume & current Buyer's suppliers relationships based on actual Global export trade database.
Full title: Using Decision Trees to Detect and Isolate Simulated Leaks in the J-2X Rocket Engine Mark Schwabacher, NASA Ames Research Center Robert Aguilar, Pratt & Whitney Rocketdyne Fernando Figueroa, NASA Stennis Space Center Abstract The goal of this work was to use data-driven methods to automatically detect and isolate faults in the J-2X rocket engine. It was decided to use decision trees, since they tend to be easier to interpret than other data-driven methods. The decision tree algorithm automatically “learns” a decision tree by performing a search through the space of possible decision trees to find one that fits the training data. The particular decision tree algorithm used is known as C4.5. Simulated J-2X data from a high-fidelity simulator developed at Pratt & Whitney Rocketdyne and known as the Detailed Real-Time Model (DRTM) was used to “train” and test the decision tree. Fifty-six DRTM simulations were performed for this purpose, with different leak sizes, different leak locations, and different times of leak onset. To make the simulations as realistic as possible, they included simulated sensor noise, and included a gradual degradation in both fuel and oxidizer turbine efficiency. A decision tree was trained using 11 of these simulations, and tested using the remaining 45 simulations. In the training phase, the C4.5 algorithm was provided with labeled examples of data from nominal operation and data including leaks in each leak _location. From the data, it “learned” a decision tree that can classify unseen data as having no leak or having a leak in one of the five leak locations. In the test phase, the decision tree produced very low false alarm rates and low missed detection rates on the unseen data. It had very good fault isolation rates for three of the five simulated leak locations, but it tended to confuse the remaining two locations, perhaps because a large leak at one of these two locations can look very similar to a small leak at the other _location. Introduction The J-2X rocket engine will be tested on Test Stand A-1 at NASA Stennis Space Center (SSC) in Mississippi. A team including people from SSC, NASA Ames Research Center (ARC), and Pratt & Whitney Rocketdyne (PWR) is developing a prototype end-to-end integrated systems health management (ISHM) system that will be used to monitor the test stand and the engine while the engine is on the test stand[1]. The prototype will use several different methods for detecting and diagnosing faults in the test stand and the engine, including rule-based, model-based, and data-driven approaches. SSC is currently using the G2 tool http://www.gensym.com to develop rule-based and model-based fault detection and diagnosis capabilities for the A-1 test stand. This paper describes preliminary results in applying the data-driven approach to detecting and diagnosing faults in the J-2X engine. The conventional approach to detecting and diagnosing faults in complex engineered systems such as rocket engines and test stands is to use large numbers of human experts. Test controllers watch the data in near-real time during each engine test. Engineers study the data after each test. These experts are aided by limit checks that signal when a particular variable goes outside of a predetermined range. The conventional approach is very labor intensive. Also, humans may not be able to recognize faults that involve the relationships among large numbers of variables. Further, some potential faults could happen too quickly for humans to detect them and react before they become catastrophic. Automated fault detection and diagnosis is therefore needed. One approach to automation is to encode human knowledge into rules or models. Another approach is use data-driven methods to automatically learn models from historical data or simulated data. Our prototype will combine the data-driven approach with the model-based and rule-based appro
Between the second quarter of 2022 and the third quarter of 2024, the number of records exposed to account breaches in Thailand fluctuated significantly. Over ******* datasets were reported as having been leaked in the third quarter of 2024, compared to around ******* during the same quarter of the previous year.
A possible effect of a carbon dioxide leak from an industrial sub-sea floor storage facility, utilised for Carbon Capture and Storage, is that escaping carbon dioxide gas will dissolve in sediment pore waters and reduce their pH. To quantify the scale and duration of such an impact, a novel, field scale experiment was conducted, whereby carbon dioxide gas was injected into unconsolidated sub-sea floor sediments for a sustained period of 37 days. During this time pore water pH in shallow sediment (5 mm depth) above the leak dropped >0.8 unit, relative to a reference zone that was unaffected by the carbon dioxide. After the gas release was stopped, the pore water pH returned to normal background values within a three-week recovery period. Further, the total mass of carbon dioxide dissolved within the sediment pore fluids above the release zone was modelled by the difference in DIC between the reference and release zones. Results showed that between 14 and 63% of the carbon dioxide released during the experiment could remain in the dissolved phase within the sediment pore water. This is a publication in QICS Special Issue - International Journal of Greenhouse Gas Control, Peter Taylor et. al. Doi:10.1016/j.ijggc.2014.09.006.
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UKCCSRC Flexible Funding 2020. Experimental data are the acoustic emission (AE) signals collected with three AE sensors when CO2 leak from a CO2 storage cylinder under different pressures. '5MPa_20kgh-1' means the data was collected when the pressure was 5MPa and the leakage rate was 20 kg/h. The sampling frequency of AE signals is 3MHz. UKCCSRC Flexible Funding 2020: Monitoring of CO2 flow under CCS conditions through multi-modal sensing and machine learning.
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772 Global exporters importers export import shipment records of Helium leak detector with prices, volume & current Buyer's suppliers relationships based on actual Global export trade database.
DNA strand displacement (DSD) emerged as a prominent reaction motif for engineering nucleic acid-based computational devices with programmable behaviors. However, strand displacement circuits are susceptible to background noise that disrupts the circuit behavior, commonly known as leaks. The side effects of leaks are particularly severe in circuits with complex dynamical elements (e.g., feedback loops), as their leaks amplify nonlinearly, disrupting the circuit function. Shadow cancellation is a dynamic leak-elimination strategy originally proposed to control the leak growth in such circuits. However, the kinetic restrictions of the proposed method introduce a significant design overhead, making it less accessible. In this work, we use domain-level DSD simulations to examine the method's capabilities, the inner workings of its components, and, most importantly, robustness to practical deviations in its design requirements. First, we show that the method could stabilize the dynamics of s..., , , # Leak-resilient enzyme-free nucleic acid dynamical systems through shadow cancellation
To run the peppercorn command to generate the *_enum.pil
 file and the corresponding plotting data
$FOLDER
 - The folder containing the .pil
 file$NAME
 - The name of the .pil
 file without the file extension$INTERMEDIATE_PREFIX
 - Prefix of the intermediates generated$LABELS
 - Space separated list of the chemical species that need to be tracked$TIME
  - Time to run the simulation for ./sim.sh $FOLDER $TIME $NAME $LABELS $INTERMEDIATE_PREFIX
Â
To run the *_enum.pil
 file in the folder $FOLDER
$NAME
 - The name of the .*_enum_pil
 file without the _enum.pil
./pil.sh $FOLDER $TIME $NAME $LABELS $NAME
Â
`sLeakWaste = hcjr( fcr mcr scr + fcr( hckr...
Carbon capture and storage in sub-seabed geological formations (sub-seabed CCS) is currently being studied as a realistic option to mitigate the accumulation of anthropogenic CO2 in the atmosphere. In implementing sub-seabed CCS, detecting and monitoring the impact of the sequestered CO2 on the ocean environment is highly important. The first controlled CO2 release experiment, Quantifying and Monitoring Potential Ecosystem Impacts of Geological Carbon Storage (QICS), took place in Ardmucknish Bay, Oban, in May–September 2012. We applied the in situ pH/pCO2 sensor to the QICS experiment for detection and monitoring of leaked CO2, and carried out several observations. The cabled real-time sensor was deployed close to the CO2 leakage (bubbling) area, and the fluctuations of in situ pH and pCO2 above the seafloor were monitored in a land-based container. The long-term sensor was placed on seafloor in three different observation zones. The sediment pH sensor was inserted into the sediment at a depth of 50 cm beneath the seafloor near the CO2 leakage area. Wide-area mapping surveys of pH and pCO2 in water column around the CO2 leakage area were carried out by using an autonomous underwater vehicle (AUV) installed with sensors. Atmospheric CO2 above the leakage area was observed by using a CO2 analyzer that was attached to the bow of ship of 50 cm above the sea-surface. The behavior of the leaked CO2 is highly dependent on the tidal periodicity (low tide or high tide) during the CO2 gas release period. At low tide, the pH in sediment and overlying seawater decreased due to strong eruption of CO2 gas bubbles, and the CO2 ascended to sea-surface quickly with a little dissolution to seawater and dispersed into the atmosphere. On the other hand, the CO2 bubbles release was lower at high tide due to higher water pressure, and slight low pH seawater and high atmospheric CO2 were detected. After stopping CO2 gas injection, no remarkable variations of pH in sediment and overlying water column were observed for three months. This is a publication in QICS Special Issue - International Journal of Greenhouse Gas Control, Kiminori Shitashima et. al. Doi: 10.1016/j.ijggc.2014.12.011.
A two-fluid, small scale numerical ocean model was developed to simulate plume dynamics and increases in water acidity due to leakages of CO2 from potential sub-seabed reservoirs erupting, or pipeline breaching into the North Sea. The location of a leak of such magnitude is unpredictable; therefore, multiple scenarios are modelled with the physiochemical impact measured in terms of the movement and dissolution of the leaked CO2. A correlation for the drag coefficient of bubbles/droplets free rising in seawater is presented and a sub-model to predict the initial bubble/droplet size forming on the seafloor is proposed. With the case studies investigated, the leaked bubbles/droplets fully dissolve before reaching the water surface, where the solution will be dispersed into the larger scale ocean waters. The tools developed can be extended to various locations to model the sudden eruption, which is vital in determining the fate of the CO2 within the local waters. This is a publication in Marine Pollution Bulletin, Marius Dewar et. al. doi:10.1016/j.marpolbul.2013.03.005.
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The list contains every wordlist, dictionary, and password database leak that I could find on the internet (and I spent a LOT of time looking). It also contains every word in the Wikipedia databases (pages-articles, retrieved 2010, all languages) as well as lots of books from Project Gutenberg. It also includes the passwords from some low-profile database breaches that were being sold in the underground years ago. The format of the list is a standard text file sorted in non-case-sensitive alphabetical order. Lines are separated with a newline " " character. You can test the list without downloading it by giving SHA256 hashes to the free hash cracker or to @PlzCrack on twitter. Here s a tool for computing hashes easily. Here are the results of cracking LinkedIn s and eHarmony s password hash leaks with the list. The list is responsible for cracking about 30% of all hashes given to CrackStation s free hash cracker, but that figure should be taken with a grain of salt because s
Gas leak detectors are currently used to survey for below-ground leaks. However, measurements from gas detectors are not precise in quantifying the below-ground leak rate—data in this submission aimed to quantify the below-ground leak rate of a Natural Gas pipeline., This dataset consists of raw, unprocessed data. The data was collected at 2m Above ground level using a path-integrated methane detector (measurements were sampled using equipment that reports the mixing ratios in parts per million meter). Measurements were taken above a below-ground gas leak., , # Above-Ground Methane Measurements:
*Summary of dataset contents, contextualized in experimental procedures. *
This national digital GIS product produced by the British Geological Survey indicates the potential for leakage to have a negative effect on ground stability. It is largely derived from the digital geological map and expert knowledge. The GIS dataset contains seven fields. The first field is a summary map that gives an overview of where leakage may affect ground stability. The other six fields indicate the properties of the ground with respect to the extent to which hazards associated with soluble rocks, landslides, compressible ground, collapsible ground, swelling clays and running sands will be increased due to leakage. The data is useful to asset managers in water companies, local authorities and utility companies who would like to understand where. and to what extent, leaking underground pipes or other structures may initate or worsen ground stability.
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Overview
This dataset is part of a cybersecurity case study focused on public hospitals (Class B) in East Java, Indonesia, specifically analyzing their exposure to data leakage via Google Dorking techniques. The research investigates ethical considerations, risk severity, and common vulnerabilities in the healthcare sector.
Files Included
Key Features
Ethical Considerations
Suggested Use Cases
This dataset presents the amount of different magnesium carbonates under different conditions. Here, using batch reactor experiments and mineralogical characterization, we explored magnesite precipitation kinetics in chemically complex fluids whereby the impact of fluid acidity and alkalinity, NaCl, and MgO nanoparticles was investigated. The dataset was created within SECURe project (Subsurface Evaluation of CCS and Unconventional Risks) - https://www.securegeoenergy.eu/. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 764531
The largest reported data leakage as of January 2025 was the Cam4 data breach in March 2020, which exposed more than 10 billion data records. The second-largest data breach in history so far, the Yahoo data breach, occurred in 2013. The company initially reported about one billion exposed data records, but after an investigation, the company updated the number, revealing that three billion accounts were affected. The National Public Data Breach was announced in August 2024. The incident became public when personally identifiable information of individuals became available for sale on the dark web. Overall, the security professionals estimate the leakage of nearly three billion personal records. The next significant data leakage was the March 2018 security breach of India's national ID database, Aadhaar, with over 1.1 billion records exposed. This included biometric information such as identification numbers and fingerprint scans, which could be used to open bank accounts and receive financial aid, among other government services.
Cybercrime - the dark side of digitalization As the world continues its journey into the digital age, corporations and governments across the globe have been increasing their reliance on technology to collect, analyze and store personal data. This, in turn, has led to a rise in the number of cyber crimes, ranging from minor breaches to global-scale attacks impacting billions of users – such as in the case of Yahoo. Within the U.S. alone, 1802 cases of data compromise were reported in 2022. This was a marked increase from the 447 cases reported a decade prior. The high price of data protection As of 2022, the average cost of a single data breach across all industries worldwide stood at around 4.35 million U.S. dollars. This was found to be most costly in the healthcare sector, with each leak reported to have cost the affected party a hefty 10.1 million U.S. dollars. The financial segment followed closely behind. Here, each breach resulted in a loss of approximately 6 million U.S. dollars - 1.5 million more than the global average.