Random numbers are fundamental building blocks of cryptographic systems and as such, play a key role in each of these elements. Random numbers are used to inject unpredictable or non-deterministic data into cryptographic algorithms and protocols to make the resulting data streams unrepeatable and virtually unguessable
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
This is a briefing about Random Number Generators.
Random Number Generators are important in the data center because of their role in cryptography. This briefing introduces Random Number Generators, types of Random Number Generators including TRNG and PRNG, and a visual example of "randomness." http://boblandstrom.com
Good cryptography requires good random numbers. This paper evaluates the hardwarebased Intel Random Number Generator (RNG) for use in cryptographic applications.
Almost all cryptographic protocols require the generation and use of secret values that must be unknown to attackers. For example, random number generators are required to generate public/private keypairs for asymmetric (public key) algorithms including RSA, DSA, and Diffie-Hellman. Keys for symmetric and hybrid cryptosystems are also generated randomly. RNGs are also used to create challenges, nonces (salts), padding bytes, and blinding values. The one time pad – the only provably-secure encryption system – uses as much key material as ciphertext and requires that the keystream be generated from a truly random process.
Information and data security pseudorandom number generation and stream cipherMazin Alwaaly
Information And Data Security Pseudorandom Number Generation and Stream Cipher seminar
Mustansiriya University
Department of Education
Computer Science
STEGANOGRAPHY BASED ASYMMETRIC KEY CRYPTOSYSTEM USING TRELLIS CODED GENETIC A...ijesajournal
This paper focuses on generating a random bit sequence using Trellis coded Genetic Algorithm (TCGA)
with boolean function as source of input. Randomness of the generated bit sequence is tested using the
methods proposed by National Institute of Standards and Technology (NIST) to be used as random key
for cryptographic applications. Generated random key is transmitted using Blue Pixel Least Significant
bit (BPLSB) steganographic technique. The extracted random key is then used for image encryption and
decryption for asymmetric key cryptosystem.
Biting into the Jawbreaker: Pushing the Boundaries of Threat Hunting AutomationAlex Pinto
Threat Hunting has been commonly definable as a series of investigative actions that should be performed by human teams in order to cover detection gaps where automated tools fail. However, as those techniques become more and more popular and standardized, wouldn't it be the case that we are able to automate a large part of those common threat hunting activities, creating what is basicaly a definition oxymoron?
In this session, we will demonstrate how some IOC-based threat hunting techniques can be automated or constructed to augment human activity by encoding analyst intuition into repeatable data extraction and processing techniques. Those techniques can be used to simplify the triage stage and get actionable information from potential threats with minimal human interaction. The more math-oriented parts will cover descriptive statistics, graph theory, and non-linear scoring techniques on the relationships of known network-based IOCs to an organization's log data.
Our goal here is to demonstrate that by elevating the quality of data available to our automation processes we can effectively simulate "analyst intuition" on some of the more time consuming aspects of network threat hunting. IR teams can then theoretically more productive as soon as the initial triage stages, with data products that provide a “sixth sense” on what events are the ones worth of additional analyst time.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
This is a briefing about Random Number Generators.
Random Number Generators are important in the data center because of their role in cryptography. This briefing introduces Random Number Generators, types of Random Number Generators including TRNG and PRNG, and a visual example of "randomness." http://boblandstrom.com
Good cryptography requires good random numbers. This paper evaluates the hardwarebased Intel Random Number Generator (RNG) for use in cryptographic applications.
Almost all cryptographic protocols require the generation and use of secret values that must be unknown to attackers. For example, random number generators are required to generate public/private keypairs for asymmetric (public key) algorithms including RSA, DSA, and Diffie-Hellman. Keys for symmetric and hybrid cryptosystems are also generated randomly. RNGs are also used to create challenges, nonces (salts), padding bytes, and blinding values. The one time pad – the only provably-secure encryption system – uses as much key material as ciphertext and requires that the keystream be generated from a truly random process.
Information and data security pseudorandom number generation and stream cipherMazin Alwaaly
Information And Data Security Pseudorandom Number Generation and Stream Cipher seminar
Mustansiriya University
Department of Education
Computer Science
STEGANOGRAPHY BASED ASYMMETRIC KEY CRYPTOSYSTEM USING TRELLIS CODED GENETIC A...ijesajournal
This paper focuses on generating a random bit sequence using Trellis coded Genetic Algorithm (TCGA)
with boolean function as source of input. Randomness of the generated bit sequence is tested using the
methods proposed by National Institute of Standards and Technology (NIST) to be used as random key
for cryptographic applications. Generated random key is transmitted using Blue Pixel Least Significant
bit (BPLSB) steganographic technique. The extracted random key is then used for image encryption and
decryption for asymmetric key cryptosystem.
Biting into the Jawbreaker: Pushing the Boundaries of Threat Hunting AutomationAlex Pinto
Threat Hunting has been commonly definable as a series of investigative actions that should be performed by human teams in order to cover detection gaps where automated tools fail. However, as those techniques become more and more popular and standardized, wouldn't it be the case that we are able to automate a large part of those common threat hunting activities, creating what is basicaly a definition oxymoron?
In this session, we will demonstrate how some IOC-based threat hunting techniques can be automated or constructed to augment human activity by encoding analyst intuition into repeatable data extraction and processing techniques. Those techniques can be used to simplify the triage stage and get actionable information from potential threats with minimal human interaction. The more math-oriented parts will cover descriptive statistics, graph theory, and non-linear scoring techniques on the relationships of known network-based IOCs to an organization's log data.
Our goal here is to demonstrate that by elevating the quality of data available to our automation processes we can effectively simulate "analyst intuition" on some of the more time consuming aspects of network threat hunting. IR teams can then theoretically more productive as soon as the initial triage stages, with data products that provide a “sixth sense” on what events are the ones worth of additional analyst time.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Random Number Generator Using Seven Segment Display In LabviewIJERA Editor
Random number generator [RNG] is use to generate random numbers between any given limit, RNG's are two kinds 1.True random number and 2.pseudom numbers. True random numbers are not predictable by any mathematical formula because they are mainly depends on the atmospheric noise, coming to the pseudo numbers are mainly used in most of computers, this randomness can be predictable by using mathematical formula and it is fine many purposes, but it may not be random in the way you expect if you are used to dice rolls and lottery drawings. In this mini project we are doing RNG [pseudo numbers] by using NI labview software and generating random numbers by pressing push button and coming output we are displaying on seven segment display. In the labview it easy to generate a random number by using different block‟s and main advantage of the labview is there is no need of any programming languages like[c,c++,java,matlab].Main function of this project is used for gaming and priority number generation and etc. A sequence of uniform random numbers, which is generated within the computer in a deterministic manner, is often referred to as a pseudo-random number sequence.[1]
Solving 800-90 Entropy Requirements in SoftwareRay Potter
In the fall of 2013, NIST reopened the public comment period for Special Publication 800-90A and released a supplemental ITL Security Bulletin, inciting a flurry of concern and activity about random number generation and entropy. The initial enforcement of these new and confusing entropy standards brought CMVP progress to a crawl while labs and vendor engineers scrambled to find answers. Potter will review an R&D effort to solve the entropy conundrum and keep open a fast track to validation. This research effort was launched as the CMVP issued a moratorium on entropy testing in a good faith move designed to keep the queue moving. This presentation will detail the results of this research effort for the first time in public.
Learn how to implement Bayesian workflows using CmdStanPy (a Python interface for Stan). In this hands-on workshop, we will be working with a very fun (surprise!) dataset and make predictions using Bayesian methods.
CmdStanPy allows pythonistas to add the power of Bayesian inference to their toolkit via a small set of functions and objects designed to use minimal memory and parallelize computation. Given a dataset and a statistical model written as a Stan program, CmdStanPy compiles the model, runs Stan’s MCMC sampler (via CmdStan) to obtain a sample from the posterior, and assembles this sample as a numpy nd-array or pandas.dataframe for downstream visualization and analysis.
Mitzi Morris is a member of the Stan development team and the developer of CmdStanPy ( https://mc-stan.org/about/team/ ).
She has worked as a software engineer in both academia and industry. She started out writing tools for Natural Language Processing in C and Java, then moved to genomics and biomedical informatics where she built pipelines for high-throughput sequencing electronic medical records data, all of which led to an increased interest in doing more and better statistics. She has been a Stan contributor since 2014 and joined the Stan team at Columbia in 2017.
Many information security systems rely on cryptographic schemes that need truly random numbers be secure. In recent months there have been several high profile news stories about weaknesses or potential compromises in both software and hardware random number generators. A compromised random number generator is difficult to catch because it can output random looking data that is predictable to an attacker only. In this talk I describe how to go from knowledge of a weakness in a random number generator to a full security compromise.
We will look at examples including how to fully decrypt a TLS stream, how to compromise a bitcoin wallet by looking at the ECDSA signatures on the public block chain, how to factor improperly generated RSA keys, and more. There will be live demos and discussions of interesting ways to pull off these attacks.
Quantum cryptography by Girisha Shankar, Sr. Manager, CiscoVishnu Pendyala
Quantum computing is said to break the Internet by making the underlying encryption ineffective. This session, hosted by ICON@Cisco tells you how Quantum cryptography, which has the potential to protect the Internet, works.
Anomaly Detection - Real World Scenarios, Approaches and Live ImplementationImpetus Technologies
Detecting anomalous patterns in data can lead to significant actionable insights in a wide variety of application domains, such as fraud detection, network traffic management, predictive healthcare, energy monitoring and many more.
However, detecting anomalies accurately can be difficult. What qualifies as an anomaly is continuously changing and anomalous patterns are unexpected. An effective anomaly detection system needs to continuously self-learn without relying on pre-programmed thresholds.
Join our speakers Ravishankar Rao Vallabhajosyula, Senior Data Scientist, Impetus Technologies and Saurabh Dutta, Technical Product Manager - StreamAnalytix, in a discussion on:
Importance of anomaly detection in enterprise data, types of anomalies, and challenges
Prominent real-time application areas
Approaches, techniques and algorithms for anomaly detection
Sample use-case implementation on the StreamAnalytix platform
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
Anomaly Detection and Spark Implementation - Meetup Presentation.pptxImpetus Technologies
StreamAnalytix sponsored a meetup on “Anomaly Detection Techniques and Implementation using Apache Spark” which took place on Tuesday December 5, 2017 at Larkspur Landing Milpitas Hotel, Milpitas, CA. The meetup was led by Maxim Shkarayev, Lead Data Scientist, Impetus Technologies along with Punit Shah, Solution Architect, StreamAnalytix and Anand Venugopal, Product Head & AVP, StreamAnalytix, who introduced and summarized the vast field of Anomaly Detection and its applications in various industry problems. The speakers at the event also offered a structured approach to choose the right anomaly detection techniques based on specific use-cases and data characteristics which was followed by a demonstration of some real-world anomaly detection use-cases on Apache Spark based analytics platform.
Towards a Threat Hunting Automation Maturity ModelAlex Pinto
Threat Hunting has been commonly definable as a series of investigative actions that should be performed by analyst teams to cover detection gaps where automated tools fail. However, as those techniques become more and more widespread and standardized, wouldn’t it be the case that we can automate a large part of those threat hunting activities, creating a definition oxymoron?
In this session, we will demonstrate how some threat hunting techniques can be automated or constructed to augment human activity by encoding analyst intuition into repeatable data extraction and processing technologies. Those techniques can be used to simplify the triage stage and get actionable information from potential threats with minimal human interaction. We then present a Hunting Automation Maturity Model (HAMM) that organizes these techniques around capability milestones, including internal and external context and analytical tooling.
Creating Your Own Threat Intel Through Hunting & VisualizationRaffael Marty
The security industry is talking a lot about threat intelligence; external information that a company can leverage to understand where potential threats are knocking on the door and might have already perpetrated the network boundaries. Conversations with many CERTs have shown that we have to stop relying on knowledge about how attacks have been conducted in the past and start 'hunting' for signs of compromises and anomalies in our own environments.
In this presentation we explore how the decade old field of security visualization has emerged. We show how we have applied advanced analytics and visualization to create our own threat intelligence and investigated lateral movement in a Fortune 50 company.
Visualization. Data science. No machine learning. But pretty pictures.
Here is a blog post I wrote a bit ago about the general theme of internal threat intelligence:
http://www.darkreading.com/analytics/creating-your-own-threat-intel-through-hunting-and-visualization/a/d-id/1321225?
Information and network security 47 authentication applicationsVaibhav Khanna
Kerberos provides a centralized authentication server whose function is to authenticate users to servers and servers to users. In Kerberos Authentication server and database is used for client authentication. Kerberos runs as a third-party trusted server known as the Key Distribution Center (KDC).
Information and network security 46 digital signature algorithmVaibhav Khanna
The Digital Signature Algorithm (DSA) is a Federal Information Processing Standard for digital signatures, based on the mathematical concept of modular exponentiation and the discrete logarithm problem. DSA is a variant of the Schnorr and ElGamal signature schemes
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International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Random Number Generator Using Seven Segment Display In LabviewIJERA Editor
Random number generator [RNG] is use to generate random numbers between any given limit, RNG's are two kinds 1.True random number and 2.pseudom numbers. True random numbers are not predictable by any mathematical formula because they are mainly depends on the atmospheric noise, coming to the pseudo numbers are mainly used in most of computers, this randomness can be predictable by using mathematical formula and it is fine many purposes, but it may not be random in the way you expect if you are used to dice rolls and lottery drawings. In this mini project we are doing RNG [pseudo numbers] by using NI labview software and generating random numbers by pressing push button and coming output we are displaying on seven segment display. In the labview it easy to generate a random number by using different block‟s and main advantage of the labview is there is no need of any programming languages like[c,c++,java,matlab].Main function of this project is used for gaming and priority number generation and etc. A sequence of uniform random numbers, which is generated within the computer in a deterministic manner, is often referred to as a pseudo-random number sequence.[1]
Solving 800-90 Entropy Requirements in SoftwareRay Potter
In the fall of 2013, NIST reopened the public comment period for Special Publication 800-90A and released a supplemental ITL Security Bulletin, inciting a flurry of concern and activity about random number generation and entropy. The initial enforcement of these new and confusing entropy standards brought CMVP progress to a crawl while labs and vendor engineers scrambled to find answers. Potter will review an R&D effort to solve the entropy conundrum and keep open a fast track to validation. This research effort was launched as the CMVP issued a moratorium on entropy testing in a good faith move designed to keep the queue moving. This presentation will detail the results of this research effort for the first time in public.
Learn how to implement Bayesian workflows using CmdStanPy (a Python interface for Stan). In this hands-on workshop, we will be working with a very fun (surprise!) dataset and make predictions using Bayesian methods.
CmdStanPy allows pythonistas to add the power of Bayesian inference to their toolkit via a small set of functions and objects designed to use minimal memory and parallelize computation. Given a dataset and a statistical model written as a Stan program, CmdStanPy compiles the model, runs Stan’s MCMC sampler (via CmdStan) to obtain a sample from the posterior, and assembles this sample as a numpy nd-array or pandas.dataframe for downstream visualization and analysis.
Mitzi Morris is a member of the Stan development team and the developer of CmdStanPy ( https://mc-stan.org/about/team/ ).
She has worked as a software engineer in both academia and industry. She started out writing tools for Natural Language Processing in C and Java, then moved to genomics and biomedical informatics where she built pipelines for high-throughput sequencing electronic medical records data, all of which led to an increased interest in doing more and better statistics. She has been a Stan contributor since 2014 and joined the Stan team at Columbia in 2017.
Many information security systems rely on cryptographic schemes that need truly random numbers be secure. In recent months there have been several high profile news stories about weaknesses or potential compromises in both software and hardware random number generators. A compromised random number generator is difficult to catch because it can output random looking data that is predictable to an attacker only. In this talk I describe how to go from knowledge of a weakness in a random number generator to a full security compromise.
We will look at examples including how to fully decrypt a TLS stream, how to compromise a bitcoin wallet by looking at the ECDSA signatures on the public block chain, how to factor improperly generated RSA keys, and more. There will be live demos and discussions of interesting ways to pull off these attacks.
Quantum cryptography by Girisha Shankar, Sr. Manager, CiscoVishnu Pendyala
Quantum computing is said to break the Internet by making the underlying encryption ineffective. This session, hosted by ICON@Cisco tells you how Quantum cryptography, which has the potential to protect the Internet, works.
Anomaly Detection - Real World Scenarios, Approaches and Live ImplementationImpetus Technologies
Detecting anomalous patterns in data can lead to significant actionable insights in a wide variety of application domains, such as fraud detection, network traffic management, predictive healthcare, energy monitoring and many more.
However, detecting anomalies accurately can be difficult. What qualifies as an anomaly is continuously changing and anomalous patterns are unexpected. An effective anomaly detection system needs to continuously self-learn without relying on pre-programmed thresholds.
Join our speakers Ravishankar Rao Vallabhajosyula, Senior Data Scientist, Impetus Technologies and Saurabh Dutta, Technical Product Manager - StreamAnalytix, in a discussion on:
Importance of anomaly detection in enterprise data, types of anomalies, and challenges
Prominent real-time application areas
Approaches, techniques and algorithms for anomaly detection
Sample use-case implementation on the StreamAnalytix platform
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
Anomaly Detection and Spark Implementation - Meetup Presentation.pptxImpetus Technologies
StreamAnalytix sponsored a meetup on “Anomaly Detection Techniques and Implementation using Apache Spark” which took place on Tuesday December 5, 2017 at Larkspur Landing Milpitas Hotel, Milpitas, CA. The meetup was led by Maxim Shkarayev, Lead Data Scientist, Impetus Technologies along with Punit Shah, Solution Architect, StreamAnalytix and Anand Venugopal, Product Head & AVP, StreamAnalytix, who introduced and summarized the vast field of Anomaly Detection and its applications in various industry problems. The speakers at the event also offered a structured approach to choose the right anomaly detection techniques based on specific use-cases and data characteristics which was followed by a demonstration of some real-world anomaly detection use-cases on Apache Spark based analytics platform.
Towards a Threat Hunting Automation Maturity ModelAlex Pinto
Threat Hunting has been commonly definable as a series of investigative actions that should be performed by analyst teams to cover detection gaps where automated tools fail. However, as those techniques become more and more widespread and standardized, wouldn’t it be the case that we can automate a large part of those threat hunting activities, creating a definition oxymoron?
In this session, we will demonstrate how some threat hunting techniques can be automated or constructed to augment human activity by encoding analyst intuition into repeatable data extraction and processing technologies. Those techniques can be used to simplify the triage stage and get actionable information from potential threats with minimal human interaction. We then present a Hunting Automation Maturity Model (HAMM) that organizes these techniques around capability milestones, including internal and external context and analytical tooling.
Creating Your Own Threat Intel Through Hunting & VisualizationRaffael Marty
The security industry is talking a lot about threat intelligence; external information that a company can leverage to understand where potential threats are knocking on the door and might have already perpetrated the network boundaries. Conversations with many CERTs have shown that we have to stop relying on knowledge about how attacks have been conducted in the past and start 'hunting' for signs of compromises and anomalies in our own environments.
In this presentation we explore how the decade old field of security visualization has emerged. We show how we have applied advanced analytics and visualization to create our own threat intelligence and investigated lateral movement in a Fortune 50 company.
Visualization. Data science. No machine learning. But pretty pictures.
Here is a blog post I wrote a bit ago about the general theme of internal threat intelligence:
http://www.darkreading.com/analytics/creating-your-own-threat-intel-through-hunting-and-visualization/a/d-id/1321225?
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Information and network security 47 authentication applicationsVaibhav Khanna
Kerberos provides a centralized authentication server whose function is to authenticate users to servers and servers to users. In Kerberos Authentication server and database is used for client authentication. Kerberos runs as a third-party trusted server known as the Key Distribution Center (KDC).
Information and network security 46 digital signature algorithmVaibhav Khanna
The Digital Signature Algorithm (DSA) is a Federal Information Processing Standard for digital signatures, based on the mathematical concept of modular exponentiation and the discrete logarithm problem. DSA is a variant of the Schnorr and ElGamal signature schemes
Information and network security 45 digital signature standardVaibhav Khanna
The Digital Signature Standard is a Federal Information Processing Standard specifying a suite of algorithms that can be used to generate digital signatures established by the U.S. National Institute of Standards and Technology in 1994
Information and network security 44 direct digital signaturesVaibhav Khanna
The Direct Digital Signature is only include two parties one to send message and other one to receive it. According to direct digital signature both parties trust each other and knows there public key. The message are prone to get corrupted and the sender can declines about the message sent by him any time
Information and network security 43 digital signaturesVaibhav Khanna
Digital signatures are the public-key primitives of message authentication. In the physical world, it is common to use handwritten signatures on handwritten or typed messages. ... Digital signature is a cryptographic value that is calculated from the data and a secret key known only by the signer
Information and network security 42 security of message authentication codeVaibhav Khanna
Message Authentication Requirements
Disclosure: Release of message contents to any person or process not possess- ing the appropriate cryptographic key.
Traffic analysis: Discovery of the pattern of traffic between parties. ...
Masquerade: Insertion of messages into the network from a fraudulent source
Information and network security 41 message authentication codeVaibhav Khanna
In cryptography, a message authentication code, sometimes known as a tag, is a short piece of information used to authenticate a message—in other words, to confirm that the message came from the stated sender and has not been changed.
Information and network security 40 sha3 secure hash algorithmVaibhav Khanna
SHA-3 is the latest member of the Secure Hash Algorithm family of standards, released by NIST on August 5, 2015. Although part of the same series of standards, SHA-3 is internally different from the MD5-like structure of SHA-1 and SHA-2
Information and network security 39 secure hash algorithmVaibhav Khanna
The Secure Hash Algorithms are a family of cryptographic hash functions published by the National Institute of Standards and Technology as a U.S. Federal Information Processing Standard, including: SHA-0: A retronym applied to the original version of the 160-bit hash function published in 1993 under the name "SHA"
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Birthday attack can be used in communication abusage between two or more parties. ... The mathematics behind this problem led to a well-known cryptographic attack called the birthday attack, which uses this probabilistic model to reduce the complexity of cracking a hash function
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In number theory, the Chinese remainder theorem states that if one knows the remainders of the Euclidean division of an integer n by several integers, then one can determine uniquely the remainder of the division of n by the product of these integers, under the condition that the divisors are pairwise coprime.
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A primality test is an algorithm for determining whether an input number is prime. Among other fields of mathematics, it is used for cryptography. Unlike integer factorization, primality tests do not generally give prime factors, only stating whether the input number is prime or not
Information and network security 33 rsa algorithmVaibhav Khanna
RSA algorithm is asymmetric cryptography algorithm. Asymmetric actually means that it works on two different keys i.e. Public Key and Private Key. As the name describes that the Public Key is given to everyone and Private key is kept private
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Public-key cryptography, or asymmetric cryptography, is an encryption scheme that uses two mathematically related, but not identical, keys - a public key and a private key. Unlike symmetric key algorithms that rely on one key to both encrypt and decrypt, each key performs a unique function.
Information and network security 31 public key cryptographyVaibhav Khanna
Public-key cryptography, or asymmetric cryptography, is a cryptographic system that uses pairs of keys: public keys, and private keys. The generation of such key pairs depends on cryptographic algorithms which are based on mathematical problems termed one-way function
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Blowfish is a symmetric-key block cipher, designed in 1993 by Bruce Schneier and included in many cipher suites and encryption products. Blowfish provides a good encryption rate in software and no effective cryptanalysis of it has been found to date
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Part of what Triple DES does is to protect against brute force attacks. The original DES symmetric encryption algorithm specified the use of 56-bit keys -- not enough, by 1999, to protect against practical brute force attacks. Triple DES specifies the use of three distinct DES keys, for a total key length of 168 bits
Information and network security 26 aes decryption and implementational issuesVaibhav Khanna
To review the overall structure of AES and to focus particularly on the four steps used in each round of AES: (1) byte substitution, (2) shift rows, (3) mix columns, and (4) add round key
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However, this is neither the first nor the last activity of IntekBroker. We have compiled for you what happened in the last few days. To track such hacker activities on dark web sources like hacker forums, private Telegram channels, and other hidden platforms where cyber threats often originate, you can check SOCRadar’s Dark Web News.
Stay Informed on Threat Actors’ Activity on the Dark Web with SOCRadar!
Into the Box Keynote Day 2: Unveiling amazing updates and announcements for modern CFML developers! Get ready for exciting releases and updates on Ortus tools and products. Stay tuned for cutting-edge innovations designed to boost your productivity.
Gamify Your Mind; The Secret Sauce to Delivering Success, Continuously Improv...Shahin Sheidaei
Games are powerful teaching tools, fostering hands-on engagement and fun. But they require careful consideration to succeed. Join me to explore factors in running and selecting games, ensuring they serve as effective teaching tools. Learn to maintain focus on learning objectives while playing, and how to measure the ROI of gaming in education. Discover strategies for pitching gaming to leadership. This session offers insights, tips, and examples for coaches, team leads, and enterprise leaders seeking to teach from simple to complex concepts.
Listen to the keynote address and hear about the latest developments from Rachana Ananthakrishnan and Ian Foster who review the updates to the Globus Platform and Service, and the relevance of Globus to the scientific community as an automation platform to accelerate scientific discovery.
In 2015, I used to write extensions for Joomla, WordPress, phpBB3, etc and I ...Juraj Vysvader
In 2015, I used to write extensions for Joomla, WordPress, phpBB3, etc and I didn't get rich from it but it did have 63K downloads (powered possible tens of thousands of websites).
Code reviews are vital for ensuring good code quality. They serve as one of our last lines of defense against bugs and subpar code reaching production.
Yet, they often turn into annoying tasks riddled with frustration, hostility, unclear feedback and lack of standards. How can we improve this crucial process?
In this session we will cover:
- The Art of Effective Code Reviews
- Streamlining the Review Process
- Elevating Reviews with Automated Tools
By the end of this presentation, you'll have the knowledge on how to organize and improve your code review proces
Prosigns: Transforming Business with Tailored Technology SolutionsProsigns
Unlocking Business Potential: Tailored Technology Solutions by Prosigns
Discover how Prosigns, a leading technology solutions provider, partners with businesses to drive innovation and success. Our presentation showcases our comprehensive range of services, including custom software development, web and mobile app development, AI & ML solutions, blockchain integration, DevOps services, and Microsoft Dynamics 365 support.
Custom Software Development: Prosigns specializes in creating bespoke software solutions that cater to your unique business needs. Our team of experts works closely with you to understand your requirements and deliver tailor-made software that enhances efficiency and drives growth.
Web and Mobile App Development: From responsive websites to intuitive mobile applications, Prosigns develops cutting-edge solutions that engage users and deliver seamless experiences across devices.
AI & ML Solutions: Harnessing the power of Artificial Intelligence and Machine Learning, Prosigns provides smart solutions that automate processes, provide valuable insights, and drive informed decision-making.
Blockchain Integration: Prosigns offers comprehensive blockchain solutions, including development, integration, and consulting services, enabling businesses to leverage blockchain technology for enhanced security, transparency, and efficiency.
DevOps Services: Prosigns' DevOps services streamline development and operations processes, ensuring faster and more reliable software delivery through automation and continuous integration.
Microsoft Dynamics 365 Support: Prosigns provides comprehensive support and maintenance services for Microsoft Dynamics 365, ensuring your system is always up-to-date, secure, and running smoothly.
Learn how our collaborative approach and dedication to excellence help businesses achieve their goals and stay ahead in today's digital landscape. From concept to deployment, Prosigns is your trusted partner for transforming ideas into reality and unlocking the full potential of your business.
Join us on a journey of innovation and growth. Let's partner for success with Prosigns.
Developing Distributed High-performance Computing Capabilities of an Open Sci...Globus
COVID-19 had an unprecedented impact on scientific collaboration. The pandemic and its broad response from the scientific community has forged new relationships among public health practitioners, mathematical modelers, and scientific computing specialists, while revealing critical gaps in exploiting advanced computing systems to support urgent decision making. Informed by our team’s work in applying high-performance computing in support of public health decision makers during the COVID-19 pandemic, we present how Globus technologies are enabling the development of an open science platform for robust epidemic analysis, with the goal of collaborative, secure, distributed, on-demand, and fast time-to-solution analyses to support public health.
Enhancing Research Orchestration Capabilities at ORNL.pdfGlobus
Cross-facility research orchestration comes with ever-changing constraints regarding the availability and suitability of various compute and data resources. In short, a flexible data and processing fabric is needed to enable the dynamic redirection of data and compute tasks throughout the lifecycle of an experiment. In this talk, we illustrate how we easily leveraged Globus services to instrument the ACE research testbed at the Oak Ridge Leadership Computing Facility with flexible data and task orchestration capabilities.
Enhancing Research Orchestration Capabilities at ORNL.pdf
Information and network security 30 random numbers
1. Information and Network Security:30
Random Numbers
Prof Neeraj Bhargava
Vaibhav Khanna
Department of Computer Science
School of Engineering and Systems Sciences
Maharshi Dayanand Saraswati University Ajmer
2. Random Numbers
• many uses of random numbers in cryptography
• nonces in authentication protocols to prevent replay
• session keys
• public key generation
• keystream for a one-time pad
• in all cases its critical that these values be
• statistically random, uniform distribution, independent
• unpredictability of future values from previous values
• true random numbers provide this
• care needed with generated random numbers
3. • Random numbers play an important role in the use of encryption for
various network security applications.
• In this presentation, we provide a brief overview of the use of random
numbers in cryptography and network security and then focus on the
principles of pseudorandom number generation.
• Getting good random numbers is important, but difficult.
• You don't want someone guessing the key you're using to protect your
communications because your "random numbers" weren't (as happened in
an early release of Netscape SSL).
• Traditionally, the concern in the generation of a sequence of allegedly
random numbers has been that the sequence of numbers be random in
some well-defined statistical sense (with uniform distribution &
independent).
4. • In applications such as reciprocal authentication, session key generation,
and stream ciphers, the requirement is not just that the sequence of
numbers be statistically random but that the successive members of the
sequence are unpredictable
• (so that it is not possible to predict future values having observed previous
values).
• With "true" random sequences, each number is statistically independent of
other numbers in the sequence and therefore unpredictable.
• However, as is discussed shortly, true random numbers are seldom used;
rather, sequences of numbers that appear to be random are generated by
some algorithm.
5. Pseudorandom Number Generators (PRNGs)
• often use deterministic algorithmic techniques to create “random
numbers”
• although are not truly random
• can pass many tests of “randomness”
• known as “pseudorandom numbers”
• created by “Pseudorandom Number Generators (PRNGs)”
6. • Cryptographic applications typically make use of deterministic
algorithmic techniques for random number generation, producing
sequences of numbers that are not statistically random, but if the
algorithm is good, the resulting sequences will pass many reasonable
tests of randomness.
• Such numbers are referred to as pseudorandom numbers, created by
“Pseudorandom Number Generators (PRNGs)”.
8. • Stallings Figure above contrasts a true random number generator (TRNG)
with two forms of pseudorandom number generators.
• A TRNG takes as input a source that is effectively random; the source is
often referred to as an entropy source.
• In contrast, a PRNG takes as input a fixed value, called the seed, and
produces a sequence of output bits using a deterministic algorithm.
• Typically, as shown, there is some feedback path by which some of the
results of the algorithm are fed back as input as additional output bits are
produced.
• The important thing to note is that the output bit stream is determined
solely by the input value or values, so that an adversary who knows the
algorithm and the seed can reproduce the entire bit stream.
9. • Figure above shows two different forms of PRNGs, based on
application;
• • Pseudorandom number generator: An algorithm that is used to
produce an open-ended sequence of bits is referred to as a PRNG.
• A common application for an open-ended sequence of bits is as
input to a symmetric stream cipher
• • Pseudorandom function (PRF): A PRF is used to produced a
pseudorandom string of bits of some fixed length.
• Examples are the symmetric encryption keys and nonces.
• Typically, the PRF takes as input a seed plus some context specific
values, such as a user ID or an application ID.
10. PRNG Requirements
• randomness
• uniformity, scalability, consistency
• unpredictability
• forward & backward unpredictability
• use same tests to check
• characteristics of the seed
• secure
• if known adversary can determine output
• so must be random or pseudorandom number
11. PRNG Requirements
• When a PRNG or PRF is used for a cryptographic application, then the basic
requirement is that an adversary who does not know the seed is unable to
determine the pseudorandom string.
• This general requirement for secrecy of the output of a PRNG or PRF leads
to specific requirements in the areas of randomness, unpredictability, and
the characteristics of the seed.
• In terms of randomness, the requirement for a PRNG is that the generated
bit stream appear random even though it is deterministic.
• NIST SP 800-22 (A Statistical Test Suite for Random and Pseudorandom
Number Generators for Cryptographic Applications) specifies that the tests
should seek to establish the following three characteristics: uniformity,
scalability, consistency. SP 800-22 lists 15 separate tests of randomness.
•
12. PRNG Requirements
• A stream of pseudorandom numbers should exhibit two forms of
unpredictability: forward unpredictability, backward unpredictability. The
same set of tests for randomness also provide a test of unpredictability. If
the generated bit stream appears random, then it is not possible to predict
some bit or bit sequence from knowledge of any previous bits. Similarly, if
the bit sequence appears random, then there is no feasible way to deduce
the seed based on the bit sequence. That is, a random sequence will have
no correlation with a fixed value (the seed).
• For cryptographic applications, the seed that serves as input to the PRNG
must be secure. Because the PRNG is a deterministic algorithm, if the
adversary can deduce the seed, then the output can also be determined.
Therefore, the seed must be unpredictable. In fact, the seed itself must be
a random or pseudorandom number.
