Startup

Cyberhaven / CodeTickler

Description

Cyberhaven, also known as CodeTickler, offers data protection solutions powered by AI to detect and prevent critical insider threats to important data. Their product, Data Detection and Response, provides a comprehensive approach to data security, allowing companies to understand how data flows within their organization, block data exfiltration through various channels, accelerate internal investigations, and detect and stop risky behavior. By analyzing billions of events using data lineage technology, Cyberhaven classifies and protects data based on its origin, ensuring that sensitive information remains secure even after it leaves the cloud. The company's mission is to safeguard the flow of data in the digital economy, enabling creators to maintain ownership and attribution of their work.

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Description

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Categories (3)

Information security

Information security, sometimes shortened to InfoSec, is the practice of protecting information by mitigating information risks. It is part of information risk management. It typically involves preventing or reducing the probability of unauthorized or inappropriate access to data or the unlawful use, disclosure, disruption, deletion, corruption, modification, inspection, recording, or devaluation of information. It also involves actions intended to reduce the adverse impacts of such incidents.

Topics in data science

Data science is an interdisciplinary academic field that uses statistics, scientific computing, scientific methods, processes, algorithms and systems to extract or extrapolate knowledge and insights from noisy, structured, and unstructured data. Data science also integrates domain knowledge from the underlying application domain (e.g., natural sciences, information technology, and medicine). Data science is multifaceted and can be described as a science, a research paradigm, a research method, a discipline, a workflow, and a profession.

Privacy

Privacy (UK, US) is the ability of an individual or group to seclude themselves or information about themselves, and thereby express themselves selectively. The domain of privacy partially overlaps with security, which can include the concepts of appropriate use and protection of information. Privacy may also take the form of bodily integrity. There have been many different conceptions of privacy throughout history. Most cultures recognize the right of an individual to withhold aspects of their personal lives from public record.

Related concepts (16)

Data

In common usage and statistics, data (USˈdætə; UKˈdeɪtə) is a collection of discrete or continuous values that convey information, describing the quantity, quality, fact, statistics, other basic units of meaning, or simply sequences of symbols that may be further interpreted formally. A datum is an individual value in a collection of data. Data is usually organized into structures such as tables that provide additional context and meaning, and which may themselves be used as data in larger structures.

Computer security

Computer security, cyber security, digital security or information technology security (IT security) is the protection of computer systems and networks from attacks by malicious actors that may result in unauthorized information disclosure, theft of, or damage to hardware, software, or data, as well as from the disruption or misdirection of the services they provide. The field is significant due to the expanded reliance on computer systems, the Internet, and wireless network standards such as Bluetooth and Wi-Fi.

Data analysis

Data analysis is the process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making. Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, and is used in different business, science, and social science domains. In today's business world, data analysis plays a role in making decisions more scientific and helping businesses operate more effectively.

Big data

Big data primarily refers to data sets that are too large or complex to be dealt with by traditional data-processing application software. Data with many entries (rows) offer greater statistical power, while data with higher complexity (more attributes or columns) may lead to a higher false discovery rate. Though used sometimes loosely partly because of a lack of formal definition, the interpretation that seems to best describe big data is the one associated with a large body of information that we could not comprehend when used only in smaller amounts.

Data mining

Data mining is the process of extracting and discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems. Data mining is an interdisciplinary subfield of computer science and statistics with an overall goal of extracting information (with intelligent methods) from a data set and transforming the information into a comprehensible structure for further use. Data mining is the analysis step of the "knowledge discovery in databases" process, or KDD.

Related people (9)

Olivier Schneider

After his thesis defense in particle physics in 1989 at University of Lausanne, Olivier Schneider joins LBL, the Lawrence Berkeley Laboratory (California), to work on the CDF experiment at the Tevatron in Fermilab (Illinois), first as a research fellow supported by the Swiss National Science Foundation, and later as a post-doc at LBL. He participates in the construction and commissioning of the first silicon vertex detector to operate successfully at a hadron collider; this detector enabled the discovery of the sixth quark, named "top". Since 1994, he comes back to Europe and participates in the ALEPH experiment at CERN's Large Electron-Positron Collider, as CERN fellow and then as CERN scientific staff. He specializes in heavy flavour physics. In 1998, he becomes associate professor at University of Lausanne, then extraordinary professor at the Swiss Institute of Technology Lausanne (EPFL) in 2003, and finally full professor at EPFL in 2010. Having worked since 1997 on the preparation of the LHCb experiment at CERN's Large Hadron Collider, which started operation in 2009, he is now analyzing the first data. He also contributes since 2001 to the exploitation of the data recorded at the Belle experiment (KEK laboratory, Tsukuba, Japan). These two experiments study mainly the decays of hadrons containing a b quark, as well CP violation, i.e. the non-invariance under the symmetry between matter and antimatter.

Konstantin Androsov

Lesya Shchutska

Current Work Our research is focused on testing the boundaries of the Standard Model of particle physics and on looking for new phenomena which might explain unanswered puzzles in the fundamental description of the Universe. The examples of such puzzles would be dark matter nature, matter-antimatter asymmetry of the Universe or very small but non-zero neutrino masses.The main instrument for these tasks is the LHCb detector at CERN, where the analyses of the data collected in the LHC proton-proton collisions

Related publications (30)

Related units (28)