In order to ensure a company's Internet security, SIEM (Security Information and Event Management) system is in place to simplify the various preventive technologies and flag alerts for security events. Inspectors (SOC) investigate warnings to determine if this is true or not. However, the number of warnings in general is wrong with the majority and is more than the ability of SCO to handle all awareness. Because of this, malicious possibility. Attacks and compromised hosts may be wrong. Machine learning is a possible approach to improving the wrong positive rate and improving the productivity of SOC analysts. In this article, we create a user-centric engineer learning framework for the Internet Safety Functional Center in the real organizational context. We discuss regular data sources in SOC, their work flow, and how to process this data and create an effective machine learning system. This article is aimed at two groups of readers. The first group is intelligent researchers who have no knowledge of data scientists or computer safety fields but who engineer should develop machine learning systems for machine safety. The second groups of visitors are Internet security practitioners that have deep knowledge and expertise in Cyber Security, but do Machine learning experiences do not exist and I'd like to create one by themselves. At the end of the paper, we use the account as an example to demonstrate full steps from data collection, label creation, feature engineering, machine learning algorithm and sample performance evaluations using the computer built in the SOC production of Seyondike.
The main aim of this project is to control the cyber crimes. Cyber security incidents will cause significant financial and reputation impacts. In order to detect malicious activities, the SIEM (Security Information and Event Management) system is built. If any pre-defined use case is triggered, SOC analysts will generate OTRS in real time. So that user will be aware of threats
The main aim of this project is to control the cyber crimes. Cyber security incidents will cause significant financial and reputation impacts. In order to detect malicious activities, the SIEM (Security Information and Event Management) system is built. If any pre-defined use case is triggered, SOC analysts will generate OTRS in real time. So that user will be aware of threats
With the explosion of the public Internet and e-commerce, private computers and computer networks, if not adequately secured are increasingly vulnerable to damaging attacks. Hackers, viruses, vindictive employees and even human error all represent
clear and present dangers to networks. And all computer users from the most casual Internet surfers to large enterprises could be affected by network security breaches. However, security breaches can often be easily prevented. How? This white paper provides you an overview of the most common network security threats and its solution which protects you and your organization from threats, hackers and ensures that the
data traveling across your networks is safe.
The main aim of this project is to control the cyber crimes. Cyber security incidents will cause significant financial and reputation impacts. In order to detect malicious activities, the SIEM (Security Information and Event Management) system is built. If any pre-defined use case is triggered, SOC analysts will generate OTRS in real time. So that user will be aware of threats
The main aim of this project is to control the cyber crimes. Cyber security incidents will cause significant financial and reputation impacts. In order to detect malicious activities, the SIEM (Security Information and Event Management) system is built. If any pre-defined use case is triggered, SOC analysts will generate OTRS in real time. So that user will be aware of threats
With the explosion of the public Internet and e-commerce, private computers and computer networks, if not adequately secured are increasingly vulnerable to damaging attacks. Hackers, viruses, vindictive employees and even human error all represent
clear and present dangers to networks. And all computer users from the most casual Internet surfers to large enterprises could be affected by network security breaches. However, security breaches can often be easily prevented. How? This white paper provides you an overview of the most common network security threats and its solution which protects you and your organization from threats, hackers and ensures that the
data traveling across your networks is safe.
What is SIEM? A Brilliant Guide to the BasicsSagar Joshi
SIEM is a technological solution that collects and aggregates logs from various data sources, discovers trends, and alerts when it spots anomalous activity, like a possible security threat.
2021/0/15 - Solarwinds supply chain attack: why we should take it sereouslySirris
In this webinar we explain why the SolarWinds attack is different from all known scenarios and how to protect your company or manufacturing site from it. Act fast, be aware!
An in-depth look at:
1. Disruptive Technology and its impact on organizations.
2. Need for a Security Operations Center (SOC) for the 21st century businesses
3. Designing and operating an effective SOC - what it takes to run a successful SOC starting from how we should prepare our minds in terms of approach to the actual implementation and operation.
4. Qualities any SOC Analyst should possess
5. Measuring the success of a SOC - We discuss critical factors to consider when determining the success of a SOC.
The Presentation is about the Basic Introduction to Cybersecurity that talks about introduction and what is security means. Also the presentation talks about CIA Triad i.e confidentiality, integrity and availability
Threat Hunting vs. UEBA: Similarities, Differences, and How They Work Together Sqrrl
This presentation explains how security teams can leverage hunting and analytics to detect advanced threats faster, more reliably, and with common analyst skill sets. Watch the presentation with audio here: http://info.sqrrl.com/threat-hunting-and-ueba-webinar
Cyber crisis management refers to the plan that includes steps to recover IT Services from an emergency disruption. It is crucial to have a cyber crisis management plan to minimize the impact of incidents while quickly restoring security, operations, and credibility.
Security Operations Center (SOC) Essentials for the SMEAlienVault
Closing the gaps in security controls, systems, people and processes is not an easy feat, particularly for IT practitioners in smaller organizations with limited budgets and few (if any) dedicated security staff. So, what are the essential security capabilities needed to establish a security operations center and start closing those gaps?
Join Javvad Malik of 451 Research and Patrick Bedwell, VP of Product Marketing at AlienVault for this session covering:
*Developments in the threat landscape driving a shift from preventative to detective controls
*Essential security controls needed to defend against modern threats
*Fundamentals for evaluating a security approach that will work for you, not against you
*How a unified approach to security visibility can help you get from install to insight more quickly
I was invited to present a talk on "Artificial Intelligence for Cyber Security" for #GirlsInAIHack2021 by #TeenInAIFiji. It was my honor to be there and share my words with the participants and I wish all the participants the best wishes.
Girls from 25 counties aged 12-18 had participated in this Hackathon. They were using Hot Technologies like AI and ML to fight world problems to make good. The event was started on #InternationalWomensDay2021. Total of 1000 participations
500+ Mentors & Organizers
120+ International Speakers were part of it
You can watch it here - https://youtu.be/rhWyt68yuI0
If you want to invite me for a webinar or conference connect
mail: hello@priyanshuratnakar.com or priyanshuratnakar@protonmail.com
You can use the slides but give credit somewhere
“AI techniques in cyber-security applications”. Flammini lnu susec19Francesco Flammini
▪ “AI techniques in cyber-security applications”. Invited speech at “Sunetdagarna våren 2019” (conference of the association of Swedish universities), April 1-4 2019, Växjö, Sweden.
VAPT defines the security measures that are supposed to be put in place to address cyber threats. There are plenty of strategies that can be adopted in Pen Testing which include Black Box Pen Test, White Box Pen Text, Hidden Pen Test, Internal Pen Test, and Gray Box Testing. It is mandatory that VAPT is conducted in order to deter cyber-attacks that are on the upsurge daily. These VAPT ranges from Mobile, Network Penetration Testing, and Vulnerability Assessments.
There are many merits to VAPT in your business which include early error detection in program codes which will prevent cyber attacks. Most companies lose billions of dollars due to cyber-attacks. With VAPT, it guarantees that all loopholes are tightened before an intrusion transpires.
Cybersecurity roadmap : Global healthcare security architecturePriyanka Aash
Using NIST cybersecurity framework, one of the largest healthcare IT firms in the US developed the global security architecture and roadmap addressing security gaps by architecture domain and common security capability. This session will discuss the architecture framework, capability matrix, the architecture development methodology and key deliverables.
(Source : RSA Conference USA 2017)
Seminar Report | Network Intrusion Detection using Supervised Machine Learnin...Jowin John Chemban
Seminar Report : Network Intrusion Detection using Supervised Machine Learning Technique with Feature Selection
By:
Jowin John Chemban (jowinchemban@gmail.com)
HGW16CS022 (2016-2020 Batch)
S7 B.Tech Computer Science Engineering
Holy Grace Academy of Engineering, Mala
Date : November 2019
modeling and predicting cyber hacking breaches Venkat Projects
Analyzing cyber incident data sets is an important method for deepening our understanding of the evolution of the threat situation. This is a relatively new research topic, and many studies remain to be done. In this paper, we report a statistical analysis of a breach incident data set corresponding to 12 years (2005–2017) of cyber hacking activities that include malware attacks. We show that, in contrast to the findings reported in the literature, both hacking breach incident inter-arrival times and breach sizes should be modeled by stochastic processes, rather than by distributions because they exhibit autocorrelations. Then, we propose particular stochastic process models to, respectively, fit the inter-arrival times and the breach sizes. We also show that these models can predict the inter-arrival times and the breach sizes. In order to get deeper insights into the evolution of hacking breach incidents, we conduct both qualitative and quantitative trend analyses on the data set. We draw a set of cybersecurity insights, including that the threat of cyber hacks is indeed getting worse in terms of their frequency, but not in terms of the magnitude of their damage.
SecurityGen is your go-to provider for comprehensive telecom network incident investigation services that prioritize your organization's security. Our skilled team combines expertise in telecom systems, network security, and digital forensics to deliver in-depth investigations that uncover the intricacies of telecom incidents.
What is SIEM? A Brilliant Guide to the BasicsSagar Joshi
SIEM is a technological solution that collects and aggregates logs from various data sources, discovers trends, and alerts when it spots anomalous activity, like a possible security threat.
2021/0/15 - Solarwinds supply chain attack: why we should take it sereouslySirris
In this webinar we explain why the SolarWinds attack is different from all known scenarios and how to protect your company or manufacturing site from it. Act fast, be aware!
An in-depth look at:
1. Disruptive Technology and its impact on organizations.
2. Need for a Security Operations Center (SOC) for the 21st century businesses
3. Designing and operating an effective SOC - what it takes to run a successful SOC starting from how we should prepare our minds in terms of approach to the actual implementation and operation.
4. Qualities any SOC Analyst should possess
5. Measuring the success of a SOC - We discuss critical factors to consider when determining the success of a SOC.
The Presentation is about the Basic Introduction to Cybersecurity that talks about introduction and what is security means. Also the presentation talks about CIA Triad i.e confidentiality, integrity and availability
Threat Hunting vs. UEBA: Similarities, Differences, and How They Work Together Sqrrl
This presentation explains how security teams can leverage hunting and analytics to detect advanced threats faster, more reliably, and with common analyst skill sets. Watch the presentation with audio here: http://info.sqrrl.com/threat-hunting-and-ueba-webinar
Cyber crisis management refers to the plan that includes steps to recover IT Services from an emergency disruption. It is crucial to have a cyber crisis management plan to minimize the impact of incidents while quickly restoring security, operations, and credibility.
Security Operations Center (SOC) Essentials for the SMEAlienVault
Closing the gaps in security controls, systems, people and processes is not an easy feat, particularly for IT practitioners in smaller organizations with limited budgets and few (if any) dedicated security staff. So, what are the essential security capabilities needed to establish a security operations center and start closing those gaps?
Join Javvad Malik of 451 Research and Patrick Bedwell, VP of Product Marketing at AlienVault for this session covering:
*Developments in the threat landscape driving a shift from preventative to detective controls
*Essential security controls needed to defend against modern threats
*Fundamentals for evaluating a security approach that will work for you, not against you
*How a unified approach to security visibility can help you get from install to insight more quickly
I was invited to present a talk on "Artificial Intelligence for Cyber Security" for #GirlsInAIHack2021 by #TeenInAIFiji. It was my honor to be there and share my words with the participants and I wish all the participants the best wishes.
Girls from 25 counties aged 12-18 had participated in this Hackathon. They were using Hot Technologies like AI and ML to fight world problems to make good. The event was started on #InternationalWomensDay2021. Total of 1000 participations
500+ Mentors & Organizers
120+ International Speakers were part of it
You can watch it here - https://youtu.be/rhWyt68yuI0
If you want to invite me for a webinar or conference connect
mail: hello@priyanshuratnakar.com or priyanshuratnakar@protonmail.com
You can use the slides but give credit somewhere
“AI techniques in cyber-security applications”. Flammini lnu susec19Francesco Flammini
▪ “AI techniques in cyber-security applications”. Invited speech at “Sunetdagarna våren 2019” (conference of the association of Swedish universities), April 1-4 2019, Växjö, Sweden.
VAPT defines the security measures that are supposed to be put in place to address cyber threats. There are plenty of strategies that can be adopted in Pen Testing which include Black Box Pen Test, White Box Pen Text, Hidden Pen Test, Internal Pen Test, and Gray Box Testing. It is mandatory that VAPT is conducted in order to deter cyber-attacks that are on the upsurge daily. These VAPT ranges from Mobile, Network Penetration Testing, and Vulnerability Assessments.
There are many merits to VAPT in your business which include early error detection in program codes which will prevent cyber attacks. Most companies lose billions of dollars due to cyber-attacks. With VAPT, it guarantees that all loopholes are tightened before an intrusion transpires.
Cybersecurity roadmap : Global healthcare security architecturePriyanka Aash
Using NIST cybersecurity framework, one of the largest healthcare IT firms in the US developed the global security architecture and roadmap addressing security gaps by architecture domain and common security capability. This session will discuss the architecture framework, capability matrix, the architecture development methodology and key deliverables.
(Source : RSA Conference USA 2017)
Seminar Report | Network Intrusion Detection using Supervised Machine Learnin...Jowin John Chemban
Seminar Report : Network Intrusion Detection using Supervised Machine Learning Technique with Feature Selection
By:
Jowin John Chemban (jowinchemban@gmail.com)
HGW16CS022 (2016-2020 Batch)
S7 B.Tech Computer Science Engineering
Holy Grace Academy of Engineering, Mala
Date : November 2019
modeling and predicting cyber hacking breaches Venkat Projects
Analyzing cyber incident data sets is an important method for deepening our understanding of the evolution of the threat situation. This is a relatively new research topic, and many studies remain to be done. In this paper, we report a statistical analysis of a breach incident data set corresponding to 12 years (2005–2017) of cyber hacking activities that include malware attacks. We show that, in contrast to the findings reported in the literature, both hacking breach incident inter-arrival times and breach sizes should be modeled by stochastic processes, rather than by distributions because they exhibit autocorrelations. Then, we propose particular stochastic process models to, respectively, fit the inter-arrival times and the breach sizes. We also show that these models can predict the inter-arrival times and the breach sizes. In order to get deeper insights into the evolution of hacking breach incidents, we conduct both qualitative and quantitative trend analyses on the data set. We draw a set of cybersecurity insights, including that the threat of cyber hacks is indeed getting worse in terms of their frequency, but not in terms of the magnitude of their damage.
SecurityGen is your go-to provider for comprehensive telecom network incident investigation services that prioritize your organization's security. Our skilled team combines expertise in telecom systems, network security, and digital forensics to deliver in-depth investigations that uncover the intricacies of telecom incidents.
Secure Horizons: Navigating the Future with Network Security SolutionsSecurityGen1
The realm of network security solutions extends far beyond traditional perimeter defense. Modern approaches to network security are characterized by their proactive stance and adaptive capabilities. Utilizing machine learning, artificial intelligence, and behavioral analysis, these solutions can identify and thwart emerging threats in real-time, minimizing potential damage. They also offer comprehensive visibility into network traffic, enabling organizations to detect anomalies and unusual patterns that might indicate a breach.
SecurityGen Telecom network security assessment - legacy versus BAS (1).pdfSecurity Gen
Cyberattacks pose a clear and present danger to businesses large and small. And the
telecom industry – with huge amount of sensitive customer data, and critical business
nature – offers adversaries rich pickings. Threat landscape is always increasing as
traditional telecom networks transform into smart, application and service-aware,
high speed and low latency infrastructure, which adopts a lot of new technologies.
Elevate your telecom infrastructure security with Security Gen, the vanguard of telecom security monitoring. In the dynamic landscape of telecommunications, where connectivity is paramount, Security Gen emerges as the guardian, offering unparalleled solutions for monitoring and safeguarding networks. With state-of-the-art technology and a proactive approach, Security Gen's telecom security monitoring services provide real-time threat detection and response, ensuring the integrity and confidentiality of communications.
SecurityGen's telecom security monitoring services are a game-changer for the industry. As cyber threats continue to grow in complexity and sophistication, having a dedicated partner like SecurityGen can make all the difference. Their state-of-the-art monitoring systems employ advanced algorithms and AI-driven analytics to identify suspicious activities and potential vulnerabilities in telecom networks. This proactive approach allows telecom providers to stay one step ahead of cybercriminals, providing a robust defense against data breaches and service disruptions.
CompTIA CySA Domain 1 Threat and Vulnerability Management.pptxInfosectrain3
The CompTIA Cybersecurity Analyst (CySA+) certification is the industry standard for demonstrating that cybersecurity professionals can analyze data and interpret the results to detect vulnerabilities, threats, and risks to an organization.
Evasion Streamline Intruders Using Graph Based Attacker model Analysis and Co...Editor IJCATR
Network Intrusion detection and Countermeasure Election in virtual network systems (NICE) are used to establish a
defense-in-depth intrusion detection framework. For better attack detection, NICE incorporates attack graph analytical procedures into
the intrusion detection processes. We must note that the design of NICE does not intend to improve any of the existing intrusion
detection algorithms; indeed, NICE employs a reconfigurable virtual networking approach to detect and counter the attempts to
compromise VMs, thus preventing zombie VMs. NICE includes two main phases: deploy a lightweight mirroring-based network
intrusion detection agent (NICE-A) on each cloud server to capture and analyze cloud traffic. A NICE-A periodically scans the virtual
system vulnerabilities within a cloud server to establish Scenario Attack Graph (SAGs), and then based on the severity of identified
vulnerability toward the collaborative attack goals, NICE will decide whether or not to put a VM in network inspection state. Once a
VM enters inspection state, Deep Packet Inspection (DPI) is applied, and/or virtual network reconfigurations can be deployed to the
inspecting VM to make the potential attack behaviors prominent.
Systematic Review Automation in Cyber SecurityYogeshIJTSRD
Many aspects of cyber security are carried by automation systems and service applications. The initial steps of cyber chain mainly focus on different automation tools with almost same task objective. Automation operations are carried only after detail study on particular task pre engagement phase , the tool is going to perform, measurement of dataset handling of tool produced output. The algorithm is going to make use of after comparing the existing tools efficiency, the throughput time, output format for reusable input and mainly the resource’s consumption. In this paper we are going to study the existing methodology in application and system pen testing, automation tool’s efficiency over growing technology and their behaviour study on unintended platform assignment. Nitin | Dr. Lakshmi J. V. N "Systematic Review: Automation in Cyber Security" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-4 , June 2021, URL: https://www.ijtsrd.compapers/ijtsrd41315.pdf Paper URL: https://www.ijtsrd.comcomputer-science/computer-security/41315/systematic-review-automation-in-cyber-security/nitin
Top Cited Paper - The International Journal of Network Security & Its Applica...IJNSA Journal
The International Journal of Network Security & Its Applications (IJNSA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the computer Network Security & its applications. The journal focuses on all technical and practical aspects of security and its applications for wired and wireless networks. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern security threats and countermeasures, and establishing new collaborations in these areas.
This paper describes the concept of implementing the network vulnerability assessment process as a web service in Eucalyptus cloud.This paper is published in one of the international conferences.I implemented the mentioned concept during my M.E. thesis.
Securing the Digital Frontier: SecurityGen's Telecom Cybersecurity SolutionsSecurityGen1
In an increasingly interconnected world, the telecommunications industry serves as the backbone of global communication networks. However, with the rapid expansion of digital infrastructure comes the heightened risk of cyber threats. SecurityGen is at the forefront of telecom cybersecurity, offering comprehensive solutions designed to safeguard critical telecommunications infrastructure against evolving cyber risks. Our innovative approach combines cutting-edge technology, industry expertise, and proactive threat intelligence to ensure the resilience and security of telecom networks worldwide.
Guardians of Connection: Signalling Protection in the Digital AgeSecurityGen1
Signalling protection, a vital aspect of modern communication systems, plays a pivotal role in maintaining the integrity and security of data transmission. In today's interconnected world, where information flows through various networks, the need for robust protection mechanisms is paramount. SecurityGen, a leading innovator in the field of cybersecurity, has been at the forefront of developing cutting-edge technologies to safeguard signalling channels.
Similar to user centric machine learning framework for cyber security operations center (20)
2021 python projects list
A BI-OBJECTIVE HYPER-HEURISTIC SUPPORT VECTOR MACHINES FOR BIG DATA CYBER-SECURITY
AN ARTIFICIAL INTELLIGENCE AND CLOUD BASED COLLABORATIVE PLATFORM FOR PLANT DISEASE IDENTIFICATION, TRACKING AND FORECASTING FOR FARMERS
10.sentiment analysis of customer product reviews using machine learniVenkat Projects
10.sentiment analysis of customer product reviews using machine learning In this project author is detecting sentiments from amazon reviews by using various machine learning algorithms such as SVM, Decision Tree and Naïve Bayes. In all 3 algorithms SVM is giving better accuracy and to train this algorithms author has used AMAZON reviews dataset and this dataset is saved inside ‘Amazon_Reviews_dataset’ folder. Below screen shot show example reviews from dataset
9.data analysis for understanding the impact of covid–19 vaccinations on the ...Venkat Projects
9.data analysis for understanding the impact of covid–19 vaccinations on the society
In this paper author analysing vaccines dataset to forecast required vaccines compare to manufacturing or available vaccines and by using this forecasting manufacturers may increase and decrease their manufacturing quantity. This forecasting can impact society by taking decision on manufacturing vaccines and if in society more cases occurred then forecasting will be high and by seeing forecasting manufacturers may increase production.
Vaccines are manufacturing by multiple manufacturers such as JOHNSON AND JOHNSON, PFIZER and many more. In this forecasting will take all manufacturers and their production quantity as well as usage of vaccines and based on this Machine Learning algorithm called Decision Tree will forecast require vaccines for next 30 days
To implement this project we are using vaccines dataset to train decision tree algorithm and then this algorithm will predict require vaccines quantity for next 30 days. This dataset is saved inside ‘Dataset’ folder and below screen showing some records from dataset
6.iris recognition using machine learning techniqueVenkat Projects
In this project to recognize person from IRIS we are using CASIA IRIS dataset which contains images from 108 peoples and by using this dataset we are training CNN model and then we can use this CNN model to predict/recognize persons. To train CNN model we are extracting IRIS features by using HoughCircles algorithm which extract IRIS circle from eye images. Below screen shots showing dataset with person id and this dataset saved inside ‘CASIA1’ folder
Industrial Training at Shahjalal Fertilizer Company Limited (SFCL)MdTanvirMahtab2
This presentation is about the working procedure of Shahjalal Fertilizer Company Limited (SFCL). A Govt. owned Company of Bangladesh Chemical Industries Corporation under Ministry of Industries.
About
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Technical Specifications
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
Key Features
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface
• Compatible with MAFI CCR system
• Copatiable with IDM8000 CCR
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
Application
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
Hierarchical Digital Twin of a Naval Power SystemKerry Sado
A hierarchical digital twin of a Naval DC power system has been developed and experimentally verified. Similar to other state-of-the-art digital twins, this technology creates a digital replica of the physical system executed in real-time or faster, which can modify hardware controls. However, its advantage stems from distributing computational efforts by utilizing a hierarchical structure composed of lower-level digital twin blocks and a higher-level system digital twin. Each digital twin block is associated with a physical subsystem of the hardware and communicates with a singular system digital twin, which creates a system-level response. By extracting information from each level of the hierarchy, power system controls of the hardware were reconfigured autonomously. This hierarchical digital twin development offers several advantages over other digital twins, particularly in the field of naval power systems. The hierarchical structure allows for greater computational efficiency and scalability while the ability to autonomously reconfigure hardware controls offers increased flexibility and responsiveness. The hierarchical decomposition and models utilized were well aligned with the physical twin, as indicated by the maximum deviations between the developed digital twin hierarchy and the hardware.
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.
Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.
Overview of the fundamental roles in Hydropower generation and the components involved in wider Electrical Engineering.
This paper presents the design and construction of hydroelectric dams from the hydrologist’s survey of the valley before construction, all aspects and involved disciplines, fluid dynamics, structural engineering, generation and mains frequency regulation to the very transmission of power through the network in the United Kingdom.
Author: Robbie Edward Sayers
Collaborators and co editors: Charlie Sims and Connor Healey.
(C) 2024 Robbie E. Sayers
NO1 Uk best vashikaran specialist in delhi vashikaran baba near me online vas...Amil Baba Dawood bangali
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Governing Equations for Fundamental Aerodynamics_Anderson2010.pdf
user centric machine learning framework for cyber security operations center
1. Venkat Java Projects
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A User-Centric Machine Learning Framework for
Cyber Security Operations Center
ABSTRACT
In order to ensure a company's Internet security, SIEM (Security
Information and Event Management) system is in place to simplify the
various preventive technologies and flag alerts for security events.
Inspectors (SOC) investigate warnings to determine if this is true or not.
However, the number of warnings in general is wrong with the majority
and is more than the ability of SCO to handle all awareness. Because of
this, malicious possibility. Attacks and compromised hosts may be
wrong. Machine learning is a possible approach to improving the wrong
positive rate and improving the productivity of SOC analysts. In this
article, we create a user-centric engineer learning framework for the
Internet Safety Functional Center in the real organizational context. We
discuss regular data sources in SOC, their work flow, and how to
process this data and create an effective machine learning system. This
article is aimed at two groups of readers. The first group is intelligent
researchers who have no knowledge of data scientists or computer safety
fields but who engineer should develop machine learning systems for
machine safety. The second groups of visitors are Internet security
practitioners that have deep knowledge and expertise in Cyber Security,
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but do Machine learning experiences do not exist and I'd like to create
one by themselves. At the end of the paper, we use the account as an
example to demonstrate full steps from data collection, label creation,
feature engineering, machine learning algorithm and sample
performance evaluations using the computer built in the SOC production
of Seyondike.
ARCHITECTURE:
EXISTING SYSTEM:
Most approaches to security in the enterprise have focused on protecting the
network infrastructure with no or little attention to end users. As a result,
traditional security functions and associated devices, such as firewalls and
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intrusion detection and prevention devices, deal mainly with network level
protection. Although still part of the overall security story, such an approach has
limitations in light of the new security challenges described in the previous section.
Data Analysis for Network Cyber-Security focuses on monitoring and analyzing
network traffic data, with the intention of preventing, or quickly identifying,
malicious activity. Risk values were introduced in an information security
management system (ISMS) and quantitative evaluation was conducted for
detailed risk assessment. The quantitative evaluation showed that the proposed
countermeasures could reduce risk to some extent. Investigation into the cost-
effectiveness of the proposed countermeasures is an important future work.It
provides users with attack information such as the type of attack, frequency, and
target host ID and source host ID. Ten et al. proposed a cyber-security framework
of the SCADA system as a critical infrastructure using real-time monitoring,
anomaly detection, and impact analysis with an attack tree-based methodology,
and mitigation strategies
DISADVANTAGE:
1. Firewalls can be difficult to configure correctly.
2. Incorrectly configured firewalls may block users from performing
actions on the Internet, until the firewall configured correctly.
3. Makes the system slower than before.
4. Need to keep updating the new software in order to keep security up to date.
5. Could be costly for average user.
6. The user is the only constant
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PROPOSED SYSTEM:
User-centriccyber security helps enterprises reduce the risk
associated with fast-evolving end-user realities by reinforcing security
closer to end users. User-centriccyber security is not the same as user
security. User-centriccyber security is about answering peoples’ needs in
ways that preserve the integrity of the enterprise network and its assets.
User security can almost seem like a matter of protecting the network
from the user — securing it against vulnerabilities that user needs
introduce. User-centric security has the greater value for
enterprises.cyber-security systems are real-time and robust independent
systems with high performances requirements. They are used in many
application domains, including critical infrastructures, such as the
national power grid, transportation, medical, and defense. These
applications require the attainment of stability, performance, reliability,
efficiency, and robustness, which require tight integration of computing,
communication, and control technological systems. Critical
infrastructures have always been the target of criminals and are affected
by security threats because of their complexity and cyber-security
connectivity. These CPSs face security breaches when people, processes,
technology, or other components are being attacked or risk management
systems are missing, inadequate, or fail in any way. The attackers target
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confidentialdata. Main scope of this project in reduce the unwanted data
for the dataset.
ADVANTAGES:
1) Protects system against viruses, worms, spyware and other
2) Protection against data from theft.
3) Protects the computer from being hacked.
4) Minimizes computer freezing and crashes.
5) Gives privacy to users
6) Securing the user-aware network edge
7) Securing mobile users’ communications ‘
8) Managing user-centric security
MODULES:
CYBER ANALYSIS
Cyber threatanalysis is a process in which the knowledge of
internal and external information vulnerabilities pertinent to a particular
organization is matched against real-world cyber-attacks. With respect to
cyber security, this threat-oriented approach to combating cyber-attacks
represents a smooth transition from a state of reactive security to a state
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of proactive one. Moreover, the desired result of a threat assessment is to
give best practices on how to maximize the protective instruments with
respect to availability, confidentiality and integrity, without turning back
to usability and functionality conditions. CYPER
ANALYSIS.A threat could be anything that leads to interruption,
meddling or destruction of any valuable service or item existing in the
firm’s repertoire. Whether of “human” or “nonhuman” origin, the
analysis must scrutinize each element that may bring about conceivable
security risk.
DATASET MODIFICATION
If a dataset in your dashboard contains many dataset objects, you
can hide specific dataset objects from display in the Datasets panel. For
example, if you decide to import a large amount of data from a file, but
do not remove every unwanted data column before importing the data
into Web, you can hide the unwanted attributes and metrics, To hide
dataset objects in the Datasets panel, To show hidden objects in the
Datasets panel, To rename a dataset object, To create a metric based on
an attribute, To create an attribute based on a metric, To define the geo
role for an attribute, To create an attribute with additional time
information, To replace a dataset object in the dashboard
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DATA REDUCTION
Improve storage efficiency through data reduction techniques and
capacity optimization using datareduplication, compression, snapshots
and thin provisioning. Data reduction via simply deleting unwanted or
unneeded data is the most effective way to reduce a storing’s data
RISKY USER DETECTION
False alarm immunity to prevent customer embarrassment, High
detection rate to protect all kinds of goods from theft, Wide-exit
coverage offers greater flexibility for entrance/exit layouts, Wide range
of attractive designs complement any store décor, Sophisticated digital
controller technology for optimum system performance
ALGORITHM:
SUPPORT VECTOR MACHINE(SVM)
“Support Vector Machine” (SVM) is a supervised machine
learning algorithm which can be used for both classification or
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regression challenges. However, it is mostly used in classification
problems. In this algorithm, we plot each data item as a point in n-
dimensional space (where n is number of features you have) with the
value of each feature being the value of a particular coordinate. Then,
we perform classification by finding the hyper-plane that differentiate
the two classes very well (look at the below snapshot). The SVM
algorithm is implemented in practice using a kernel. The learning of the
hyperplane in linear SVM is done by transforming the problem using
some linear algebra, which is out of the scope of this introduction to
SVM. A powerful insight is that the linear SVM can be rephrased using
the inner product of any two given observations, rather than the
observations themselves. The inner product between two vectors is the
sum of the multiplication of each pair of input values. For example, the
inner product of the vectors [2, 3] and [5, 6] is 2*5 + 3*6 or 28. The
equation for making a prediction for a new input using the dot product
between the input (x) and each support vector (xi) is calculated as
follows:
f(x) = B0 + sum(ai * (x,xi))
This is an equation that involves calculating the inner products of a
new input vector (x) with all support vectors in training data. The
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coefficients B0 and ai (for each input) must be estimated from the
training data by the learning algorithm.
CONCLUSION
We provide a user-centered computer learning system that affects
large data from various security logs, awareness information, and
inspector intelligence. This method provides complete configuration and
solution for dangerous user detection for the Enterprise System
Operating Center. Select machine learning methods in the SOC product
environment, evaluate efficiency, IO, host and users to create user-
centric features. . Even with simple mechanical learning algorithms, we
prove that the learning system can understand more insights from the
rankings with the most unbalanced and limited labels. More than 20% of
the neurological model of modeling is 5 times that of the current rule-
based system. To improve the detection precision situation, we will
examine other learning methods to improve the data acquisition, daily
model renewal, real time estimate, fully enhance and organizational risk
detection and management. As for future work, let's examine other
learning methods to improve detection accuracy
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SYSTEM SPECIFICATION:
HARDWARE REQUIREMENTS:
System : Pentium IV 2.4 GHz.
Hard Disk : 40 GB.
Floppy Drive : 1.44 Mb.
Monitor : 14’ Colour Monitor.
Mouse : Optical Mouse.
Ram : 512 Mb.
SOFTWARE REQUIREMENTS:
Operating system : Windows 7 Ultimate.
Coding Language : Python.
Front-End : Python.
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Designing : Html,css,javascript.
Data Base : MySQL.