A seminar presentation done for TUT's NoSQL course. A brief look into the possibility and the feasibility of using NoSQL databases to store RADIUS accounting and Syslog data. In this particular case, Syslog-NG, Radiator RADIUS server and MongoDB were used as trial platforms. The presentation includes configuration examples and also some code.
This is my internship presentation which I had done at AMR dairy, Amreli. AMR dairy is milk processing industry, where I had learnt about different department such as CIP, ETP, Packing, Utility, etc. I had got an awesome experience from my internship.
NEW INSTRUMENTS TO ENHANCE SAFETY, SUSTAINABILITY AND EFFICIENCY
IN THE DAIRY INDUSTRY | Look beyond the hygienic design of dairy equipment to reduce overall costs of cleaning
Roberto Massini | Italiafoodtec.com
This is my internship presentation which I had done at AMR dairy, Amreli. AMR dairy is milk processing industry, where I had learnt about different department such as CIP, ETP, Packing, Utility, etc. I had got an awesome experience from my internship.
NEW INSTRUMENTS TO ENHANCE SAFETY, SUSTAINABILITY AND EFFICIENCY
IN THE DAIRY INDUSTRY | Look beyond the hygienic design of dairy equipment to reduce overall costs of cleaning
Roberto Massini | Italiafoodtec.com
Apache Spark - Dataframes & Spark SQL - Part 1 | Big Data Hadoop Spark Tutori...CloudxLab
Big Data with Hadoop & Spark Training: http://bit.ly/2sf2z6i
This CloudxLab Introduction to Spark SQL & DataFrames tutorial helps you to understand Spark SQL & DataFrames in detail. Below are the topics covered in this slide:
1) Introduction to DataFrames
2) Creating DataFrames from JSON
3) DataFrame Operations
4) Running SQL Queries Programmatically
5) Datasets
6) Inferring the Schema Using Reflection
7) Programmatically Specifying the Schema
Using Spark to Load Oracle Data into Cassandra (Jim Hatcher, IHS Markit) | C*...DataStax
Spark is an execution framework designed to operate on distributed systems like Cassandra. It's a handy tool for many things, including ETL (extract, transform, and load) jobs. In this session, let me share with you some tips and tricks that I have learned through experience. I'm no oracle, but I can guarantee these tips will get you well down the path of pulling your relational data into Cassandra.
About the Speaker
Jim Hatcher Principal Architect, IHS Markit
Jim Hatcher is a software architect with a passion for data. He has spent most of his 20 year career working with relational databases, but he has been working with Big Data technologies such as Cassandra, Solr, and Spark for the last several years. He has supported systems with very large databases at companies like First Data, CyberSource, and Western Union. He is currently working at IHS, supporting an Electronic Parts Database which tracks half a billion electronic parts using Cassandra.
Using Spark to Load Oracle Data into CassandraJim Hatcher
This presentation describes how you can use Spark as an ETL tool to get data from a relational database into Cassandra. I go through the concept in general and then talk about some specific issues you might run into and how to fix them.
“Use the right tool for the right job” is one of the first thing they teach you when you start out in these waters. I would make “Get to really know your tools” a second.
In this talk we’re going to work on the architecture of an app that showcases some common features/scenarios we all probably already have in the apps we’re working on: counters, leaderboards, queuing, timelines, caching. But this time we’ll implement them with Redis, making the apps much faster, your hardware (and you) much cooler, your boss (and the clients) much happier and hopefully your salary a bit higher.
Sysdig is a new dynamic tracer for Linux, inspired by strace, dtrace, and tcpdump. Very useful as a super fast strace replacement and systemwide performance/security/etc. diagnostics.
Unlocking Your Hadoop Data with Apache Spark and CDH5SAP Concur
Spark/Mesos Seattle Meetup group shares the latest presentation from their recent meetup event on showcasing real world implementations of working with Spark within the context of your Big Data Infrastructure.
Session are demo heavy and slide light focusing on getting your development environments up and running including getting up and running, configuration issues, SparkSQL vs. Hive, etc.
To learn more about the Seattle meetup: http://www.meetup.com/Seattle-Spark-Meetup/members/21698691/
Write a C program that reads the words the user types at the command.pdfSANDEEPARIHANT
Write a C program that reads the words the user types at the command prompt (using the \'int
argc, char * argv[] and store each unique letter in a Binary Search Tree. When a duplicate is
encountered do not store the letter again and instead keep track of the count in the tree. Once the
Binary Search tree has been created print out the tree both inorder and reverse order. Also print
the highest and lowest alphabetically letter in the tree if any.
Solution
# include
# include
# include
typedef struct BST {
int data;
struct BST *lchild, *rchild;
} node;
void insert(node *, node *);
void preorder(node *);
findMinimum(struct node* root)
findMaximum(struct node* root)
void reverseLevelOrder(struct node* root)
void main(int argc,char argv) {
char argv = \'N\';
int key;
node *new_node, *root, *tmp, *parent;
node *get_node();
root = NULL;
clrscr();
printf(\"\ Program For Binary Search Tree \");
do {
printf(\"\ 1.Create\");
printf(\"\ 2.Search\");
printf(\"\ 3.Recursive Traversals\");
printf(\"\ 4.Exit\");
printf(\"\ Enter your choice :\");
scanf(\"%d\", &argc);
switch (argc) {
case 1:
do {
new_node = get_node();
printf(\"\ Enter The Element \");
scanf(\"%d\", &new_node->data);
if (root == NULL) /* Tree is not Created */
root = new_node;
else
insert(root, new_node);
printf(\"\ Want To enter More Elements?(y/n)\");
argv= getch();
} while (argv == \'y\');
break;
case 2:
if (root == NULL)
printf(\"Tree Is Not Created\");
else {
printf(\"\ The Preorder display : \");
preorder(root);
}
break;
}
} while (argv != 4);
}
/*
Get new Node
*/
node *get_node() {
node *temp;
temp = (node *) malloc(sizeof(node));
temp->lchild = NULL;
temp->rchild = NULL;
return temp;
}
/*
This function is for creating a binary search tree
*/
void insert(node *root, node *new_node) {
if (new_node->data < root->data) {
if (root->lchild == NULL)
root->lchild = new_node;
return newNode(key);
else
insert(root->lchild, new_node);
}
if (new_node->data > root->data) {
if (root->rchild == NULL)
root->rchild = new_node;
return newNode(key);
else
insert(root->rchild, new_node);
}
}
if (key == node->key)
{
(node->count)++;
return node;
}
/*
This function displays the tree in preorder fashion
*/
void preorder(node *temp) {
if (temp != NULL) {
printf(\"%d\", temp->data);
preorder(temp->lchild);
preorder(temp->rchild);
}
}
// Returns maximum value in a given Binary Tree
int findMaximum(struct node* root)
{
// Base case
if (root == NULL)
return INT_MAXIMUM;
// Return maximum of 3 values:
// 1) Root\'s data 2) Max in Left Subtree
// 3) Max in right subtree
int res = root->data;
int lres = findMaximum (root->lchild);
int rres = findMaximum (root->rchild);
if (lres > res)
res = lres;
if (rres > res)
res = rres;
return res;
}
// Returns minimum value in a given Binary Tree
int findMinimum(struct node* root)
{
// Base case
if (root == NULL)
return INT_MINIMUM;
// Return minimum of 3 values:
// 1) Root\'s data 2) Max in Left Subtree
// 3) Max in right subtree
int res = root->data;
int lres = findMinimum(r.
Disobey 2024: Karri Huhtanen: Wi-Fi Roaming Security and PrivacyKarri Huhtanen
Karri Huhtanen's presentation about Wi-Fi Roaming Security and Privacy in Disobey 2024 on the 16th of February 2024 ( https://disobey.fi/2024/profile/disobey2024-154-wi-fi-roaming-security-and-privacy ).
Wi-Fi network security presentations are often about breaking the link level (radio) encryption or deploying evil twin Wi-Fi access points to perform man-in-the-middle attacks. This presentation focuses instead to the security and privacy in Wi-Fi roaming, offloading and federated networks, where there are different issues and vectors to utilise or defend against.
Apache Spark - Dataframes & Spark SQL - Part 1 | Big Data Hadoop Spark Tutori...CloudxLab
Big Data with Hadoop & Spark Training: http://bit.ly/2sf2z6i
This CloudxLab Introduction to Spark SQL & DataFrames tutorial helps you to understand Spark SQL & DataFrames in detail. Below are the topics covered in this slide:
1) Introduction to DataFrames
2) Creating DataFrames from JSON
3) DataFrame Operations
4) Running SQL Queries Programmatically
5) Datasets
6) Inferring the Schema Using Reflection
7) Programmatically Specifying the Schema
Using Spark to Load Oracle Data into Cassandra (Jim Hatcher, IHS Markit) | C*...DataStax
Spark is an execution framework designed to operate on distributed systems like Cassandra. It's a handy tool for many things, including ETL (extract, transform, and load) jobs. In this session, let me share with you some tips and tricks that I have learned through experience. I'm no oracle, but I can guarantee these tips will get you well down the path of pulling your relational data into Cassandra.
About the Speaker
Jim Hatcher Principal Architect, IHS Markit
Jim Hatcher is a software architect with a passion for data. He has spent most of his 20 year career working with relational databases, but he has been working with Big Data technologies such as Cassandra, Solr, and Spark for the last several years. He has supported systems with very large databases at companies like First Data, CyberSource, and Western Union. He is currently working at IHS, supporting an Electronic Parts Database which tracks half a billion electronic parts using Cassandra.
Using Spark to Load Oracle Data into CassandraJim Hatcher
This presentation describes how you can use Spark as an ETL tool to get data from a relational database into Cassandra. I go through the concept in general and then talk about some specific issues you might run into and how to fix them.
“Use the right tool for the right job” is one of the first thing they teach you when you start out in these waters. I would make “Get to really know your tools” a second.
In this talk we’re going to work on the architecture of an app that showcases some common features/scenarios we all probably already have in the apps we’re working on: counters, leaderboards, queuing, timelines, caching. But this time we’ll implement them with Redis, making the apps much faster, your hardware (and you) much cooler, your boss (and the clients) much happier and hopefully your salary a bit higher.
Sysdig is a new dynamic tracer for Linux, inspired by strace, dtrace, and tcpdump. Very useful as a super fast strace replacement and systemwide performance/security/etc. diagnostics.
Unlocking Your Hadoop Data with Apache Spark and CDH5SAP Concur
Spark/Mesos Seattle Meetup group shares the latest presentation from their recent meetup event on showcasing real world implementations of working with Spark within the context of your Big Data Infrastructure.
Session are demo heavy and slide light focusing on getting your development environments up and running including getting up and running, configuration issues, SparkSQL vs. Hive, etc.
To learn more about the Seattle meetup: http://www.meetup.com/Seattle-Spark-Meetup/members/21698691/
Write a C program that reads the words the user types at the command.pdfSANDEEPARIHANT
Write a C program that reads the words the user types at the command prompt (using the \'int
argc, char * argv[] and store each unique letter in a Binary Search Tree. When a duplicate is
encountered do not store the letter again and instead keep track of the count in the tree. Once the
Binary Search tree has been created print out the tree both inorder and reverse order. Also print
the highest and lowest alphabetically letter in the tree if any.
Solution
# include
# include
# include
typedef struct BST {
int data;
struct BST *lchild, *rchild;
} node;
void insert(node *, node *);
void preorder(node *);
findMinimum(struct node* root)
findMaximum(struct node* root)
void reverseLevelOrder(struct node* root)
void main(int argc,char argv) {
char argv = \'N\';
int key;
node *new_node, *root, *tmp, *parent;
node *get_node();
root = NULL;
clrscr();
printf(\"\ Program For Binary Search Tree \");
do {
printf(\"\ 1.Create\");
printf(\"\ 2.Search\");
printf(\"\ 3.Recursive Traversals\");
printf(\"\ 4.Exit\");
printf(\"\ Enter your choice :\");
scanf(\"%d\", &argc);
switch (argc) {
case 1:
do {
new_node = get_node();
printf(\"\ Enter The Element \");
scanf(\"%d\", &new_node->data);
if (root == NULL) /* Tree is not Created */
root = new_node;
else
insert(root, new_node);
printf(\"\ Want To enter More Elements?(y/n)\");
argv= getch();
} while (argv == \'y\');
break;
case 2:
if (root == NULL)
printf(\"Tree Is Not Created\");
else {
printf(\"\ The Preorder display : \");
preorder(root);
}
break;
}
} while (argv != 4);
}
/*
Get new Node
*/
node *get_node() {
node *temp;
temp = (node *) malloc(sizeof(node));
temp->lchild = NULL;
temp->rchild = NULL;
return temp;
}
/*
This function is for creating a binary search tree
*/
void insert(node *root, node *new_node) {
if (new_node->data < root->data) {
if (root->lchild == NULL)
root->lchild = new_node;
return newNode(key);
else
insert(root->lchild, new_node);
}
if (new_node->data > root->data) {
if (root->rchild == NULL)
root->rchild = new_node;
return newNode(key);
else
insert(root->rchild, new_node);
}
}
if (key == node->key)
{
(node->count)++;
return node;
}
/*
This function displays the tree in preorder fashion
*/
void preorder(node *temp) {
if (temp != NULL) {
printf(\"%d\", temp->data);
preorder(temp->lchild);
preorder(temp->rchild);
}
}
// Returns maximum value in a given Binary Tree
int findMaximum(struct node* root)
{
// Base case
if (root == NULL)
return INT_MAXIMUM;
// Return maximum of 3 values:
// 1) Root\'s data 2) Max in Left Subtree
// 3) Max in right subtree
int res = root->data;
int lres = findMaximum (root->lchild);
int rres = findMaximum (root->rchild);
if (lres > res)
res = lres;
if (rres > res)
res = rres;
return res;
}
// Returns minimum value in a given Binary Tree
int findMinimum(struct node* root)
{
// Base case
if (root == NULL)
return INT_MINIMUM;
// Return minimum of 3 values:
// 1) Root\'s data 2) Max in Left Subtree
// 3) Max in right subtree
int res = root->data;
int lres = findMinimum(r.
Disobey 2024: Karri Huhtanen: Wi-Fi Roaming Security and PrivacyKarri Huhtanen
Karri Huhtanen's presentation about Wi-Fi Roaming Security and Privacy in Disobey 2024 on the 16th of February 2024 ( https://disobey.fi/2024/profile/disobey2024-154-wi-fi-roaming-security-and-privacy ).
Wi-Fi network security presentations are often about breaking the link level (radio) encryption or deploying evil twin Wi-Fi access points to perform man-in-the-middle attacks. This presentation focuses instead to the security and privacy in Wi-Fi roaming, offloading and federated networks, where there are different issues and vectors to utilise or defend against.
Adding OpenRoaming to existing IdP and roaming federation serviceKarri Huhtanen
The first deployment experiences of adding OpenRoaming functionality to existing IdP and roaming federation service. A presentation presented in the OpenRoaming Implementer's call on the 2nd of November 2022.
My presentation in the Radiator Software's webinar about OpenRoaming, how it works, what are its benefits and how Radiator Software can help to deploy it in your business.
Beyond eduroam: Combining eduroam, (5G) SIM authentication and OpenRoamingKarri Huhtanen
A presentation at FUNET Technical Days 2021 about research projects combining (5G) SIM authentication to eduroam Finland and ongoing work and benefits with OpenRoaming global Wi-Fi roaming in roam.fi or eduroam Finland networks.
Routing host certificates in eduroam/govroamKarri Huhtanen
A presentation for govroam stakeholders' meeting about issuing, configuring and deploying such host client certificates, which can be used in roaming federation networks such as eduroam, govroam, roam.fi, openroaming etc.
A presentation for KyLÄ project opening seminar ( https://projects.tuni.fi/kyla/tapahtumat/avausseminaari/ ) about experiences and lessons learned in building cooperative labs, testbeds and networks.
Privacy and traceability in Wi-Fi networksKarri Huhtanen
Tampere Smart City Week 2021 presentation about recent privacy and traceability developments in Wi-Fi networks and especially about MAC address randomisation and its implications.
Updated, extended presentation how to deploy EAP-TLS based certificate authentication and authorisation solution within organisation or enterprise. In addition to EAP-TLS in general, the presentation also covers some features of Radiator RADIUS server software, which are particularly useful when used with certificates and EAP-TLS. The presentation was originally presented in the JISC govroam stakeholder's meeting 23rd of October 2019 in London, United Kingdom.
Security issues in RADIUS based Wi-Fi AAA (aka WPA2 Enterprise AAA) presentation in alumni seminar for Tampere University of Technology information technology, software engineering and telecommunications alumni at Tampere University of Technology, 13th of October 2018.
If you think they are easy, you are (probably) doing them wrong. A presentation about issues with TLS and X.509 certificates for Tampere security people (TreSec, @TreSecCommunity) meetup on 21st of March 2018.
What is Network Function Virtualisation (NFV)?Karri Huhtanen
An updated presentation (v1.2) about what is the concept and the idea behind Network Function Virtualisation (NFV) for Tampere University of Technology Service oriented architectures course. Includes introduction to NFV and VNF (Virtualised Network Function) architecture, components and interfaces.
What is Network Function Virtualisation (NFV)?Karri Huhtanen
A presentation about what is the concept and the idea behind Network Function Virtualisation (NFV). Includes introduction to NFV and VNF (Virtualised Network Function) architecture, components and interfaces.
Building secure, privacy aware, quality Wi-Fi coverage via cooperationKarri Huhtanen
Building secure, privacy aware, quality Wi-Fi coverage via cooperation presentation for MindTrek 2015 ( #mtom2015 ) in Tampere, Finland. The presentation covers an idea to build community Wi-Fi networks by joining existing networks via federated RADIUS authentication just like eduroam, but for all organisations, cities, government organisations, operators and companies regardless if they are commercial or not.
Connecting the Dots: Integrating RADIUS to Network Measurement and MonitoringKarri Huhtanen
Nowadays data of the network usage is too often separated to various network components all around service provider network. Utilising RADIUS more efficiently is one approach to collect more data about network usage, combining it to network measurement, monitoring and management makes it even more efficient tool to use to get a real network situation and history overview.
Building city and nationwide Wi-Fi coverage via cooperationKarri Huhtanen
Building city and nationwide Wi-Fi coverage via cooperation presents the problem of building yet another overlapping citywide network instead of choosing cooperative approach to connect existing Wi-Fi networks via common policies, configurations and authentication decisions. The presentation promotes expanding eduroam(tm) model from academic world to regional, intercompany and government roaming.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024
Using NoSQL databases to store RADIUS and Syslog data
1. Using NoSQL databases to
store RADIUS and Syslog
data, part 1: Idea
Karri Huhtanen
18.9.2012
2. Some background
• currently RADIUS accounting data is stored usually
in SQL databases with fixed database schema
• for Syslog messages an SQL database can be used,
but commercial log analyzers (like Splunk) usually
use their own solutions which may or may not be
SQL databases
• Started thinking if NoSQL database could be
applied to both or one of these?
3. RADIUS accounting message
Wed
Aug
8
13:49:33
2012
User-‐Name
=
"jotain@realm"
NAS-‐Port
=
8 One message
NAS-‐IP-‐Address
=
192.168.229.131 contains
Framed-‐IP-‐Address
=
192.168.163.226 undetermined
NAS-‐Identifier
=
"Cisco_66:77:88"
Airespace-‐WLAN-‐Id
=
4 number of
Acct-‐Session-‐Id
=
"50223ea9/00:11:22:33:44:55/2292" attributes.
Acct-‐Authentic
=
Remote
Tunnel-‐Type
=
0:VLAN
interpreted
Tunnel-‐Medium-‐Type
=
0:802 Some can be
attributes,
Tunnel-‐Private-‐Group-‐ID
=
0:222 interpreted, some
the unknown
Event-‐Timestamp
=
1344422780 stay unknown.
Acct-‐Status-‐Type
=
Alive
attributes are
Acct-‐Input-‐Octets
=
1262012
usually left in
Acct-‐Input-‐Gigawords
=
0 Because there can
OID:FieldDataTyp
Acct-‐Output-‐Octets
=
13518133 be a changing
Acct-‐Output-‐Gigawords
=
0
e binary format
Acct-‐Input-‐Packets
=
11692 number of
Acct-‐Output-‐Packets
=
11154 changing type of
Acct-‐Session-‐Time
=
1235 attributes I began
Acct-‐Delay-‐Time
=
19
Calling-‐Station-‐Id
=
"00:11:22:33:44:55" to wonder if
Called-‐Station-‐Id
=
"f4:7f:35:5e:bf:b0" NoSQL could be
cisco-‐avpair
=
"nas-‐update=true" used for storing
Digest-‐Response
=
"P"C<188>"
Digest-‐Response
=
"P"C<194>" these?
Timestamp
=
1344422954
4. Syslog message
Until researching The
syslog
message
has
the
following
ABNF
[RFC5234]
definition:
into this I thought
SYSLOG-‐MSG
=
HEADER
SP
STRUCTURED-‐DATA
[SP
MSG]
Syslog messages had
HEADER
=
PRI
VERSION
SP
TIMESTAMP
SP
HOSTNAME
SP
APP-‐NAME
SP
PROCID
SP
MSGID
fixed structure and
PRI
=
"<"
PRIVAL
">"
PRIVAL
=
1*3DIGIT
;
range
0
..
191
could be then
VERSION
=
NONZERO-‐DIGIT
0*2DIGIT
HOSTNAME
=
NILVALUE
/
1*255PRINTUSASCII
handled with fixed
APP-‐NAME
=
NILVALUE
/
1*48PRINTUSASCII
database schema.
PROCID
=
NILVALUE
/
1*128PRINTUSASCII
MSGID
=
NILVALUE
/
1*32PRINTUSASCII
TIMESTAMP
=
NILVALUE
/
FULL-‐DATE
"T"
FULL-‐TIME
Then I read the
FULL-‐DATE
=
DATE-‐FULLYEAR
"-‐"
DATE-‐MONTH
"-‐"
DATE-‐MDAY
DATE-‐FULLYEAR
=
4DIGIT
RFC5424: http://
DATE-‐MONTH
=
2DIGIT
;
01-‐12
DATE-‐MDAY
=
2DIGIT
;
01-‐28,
01-‐29,
01-‐30,
01-‐31
based
on
tools.ietf.org/html/
;
month/year
FULL-‐TIME
=
PARTIAL-‐TIME
TIME-‐OFFSET
rfc5424
PARTIAL-‐TIME
=
TIME-‐HOUR
":"
TIME-‐MINUTE
":"
TIME-‐SECOND
[TIME-‐SECFRAC]
TIME-‐HOUR
=
2DIGIT
;
00-‐23
TIME-‐MINUTE
=
2DIGIT
;
00-‐59
TIME-‐SECOND
=
2DIGIT
;
00-‐59
TIME-‐SECFRAC
=
"."
1*6DIGIT
TIME-‐OFFSET
=
"Z"
/
TIME-‐NUMOFFSET
TIME-‐NUMOFFSET
=
("+"
/
"-‐")
TIME-‐HOUR
":"
TIME-‐MINUTE Here we have once
STRUCTURED-‐DATA
=
NILVALUE
/
1*SD-‐ELEMENT
again parameters,
SD-‐ELEMENT
=
"["
SD-‐ID
*(SP
SD-‐PARAM)
"]"
SD-‐PARAM
=
PARAM-‐NAME
"="
%d34
PARAM-‐VALUE
%d34
although they are
SD-‐ID
=
SD-‐NAME
PARAM-‐NAME
=
SD-‐NAME
within one defined
PARAM-‐VALUE
=
UTF-‐8-‐STRING
;
characters
'"',
''
and
;
']'
MUST
be
escaped.
STRUCTURED-
SD-‐NAME
=
1*32PRINTUSASCII
;
except
'=',
SP,
']',
%d34
(")
DATA field.
MSG
=
MSG-‐ANY
/
MSG-‐UTF8
MSG-‐ANY
=
*OCTET
;
not
starting
with
BOM
MSG-‐UTF8
=
BOM
UTF-‐8-‐STRING
So could NoSQL be
BOM
=
%xEF.BB.BF used also for Syslog?
5. So what happens next?
• Selection of NoSQL database:
• Likely Column Family Store if no one can suggest a
better one?
• Something easy to setup and use, will concentrate into
getting RADIUS server and/or Syslogd transferring
data to database.
• Setting up a WiFi access point and/or controller to
provide real RADIUS and Syslog data
• Storing data, retrieving data, searching data, deleting data
to see what works
• Writing and presenting Part II: “Implementation and
Results” of these slides
6. Results (hopefully)
• Is storing RADIUS accounting and Syslog messages into
NoSQL database: a brilliant idea, brilliantly stupid idea or
something else?
• How hard can it be? What does it require to do this, is it
possible and how?
• Does it actually work? What can you do with data? Is
there some indication of performance improvements or
problems?
• Will not do complete performance measurements
though, designing and setting up reliable measurement
environment will probably take too much time.
7. Using NoSQL databases to
store RADIUS and Syslog data,
part 1I: The Saga Continues
Karri Huhtanen
27.11.2012
8. Happened earlier
• currently RADIUS accounting data is stored usually
in SQL databases with fixed database schema
• for Syslog messages an SQL database can be used,
but commercial log analyzers (like Splunk) usually
use their own solutions which may or may not be
SQL databases
• Started thinking if NoSQL database could be
applied to both or one of these?
9. Results (luckily)
• Is storing RADIUS accounting and Syslog messages into
NoSQL database: a brilliant idea, brilliantly stupid idea or
something else? a good idea
• How hard can it be? What does it require to do this, is it
possible and how? easy, 1 night before
presentation required
• Does it actually work? What can you do with data? Is
there some indication of performance improvements or
problems? Yes. Store and Process. Unknown.
Some issues to be considered.
• Will not do complete performance measurements
though, designing and setting up reliable measurement
environment will probably take too much time.
Coded one Python script.
10. So what happened?
• Selection of NoSQL database:
• Likely Column Family Store if no one can suggest a
MongoDB
better one?
• Something easy to setup and use, will concentrate into
getting RADIUS server and/or Syslogd transferring
data to database.
• Setting up a WiFi access point and/or controller to
provide real RADIUS and Syslog data
• Storing data, retrieving data, searching data, deleting data
to see what works Done, but not thoroughly
• Writing and presenting Part II: “Implementation and
Results” of these slides Done
13. storing RADIUS accounting and Syslog
messages into NoSQL database
• It is a good idea because:
• When we have massive amount of log or accounting data, we need massive
database clusters.
• Data is mainly stored, read, analyzed and occasionally deleted. Data will not be
updated or changed and is relatively simple (few tables with a lot of columns).
• NoSQL may provide better way to scale this horizontally by distribution and
sharding.
• It is already being done. Several log analyzers, stores already use NoSQL
databases as backends. There exists projects such as Greylog2 etc. which
provide complete solutions from log storage, visualization, analysis etc.
• Logs and accounting data are actually use cases for some NoSQL databases, for
example: http://docs.mongodb.org/manual/use-cases/storing-log-data/
14. storing RADIUS accounting and Syslog
messages into NoSQL database
• It is not a brilliant idea because:
• If we look what we need to do to optimize the performance it starts to look
like a lot like designing and optimizing a SQL database: http://docs.mongodb.org/
manual/use-cases/storing-log-data/
• You cannot forget datatypes or database design even with NoSQL databases
especially when going into production.
• Prototypes may be faster and easier for developers, but creating a design and
configuration which survices production use may be as hard as it has ever been.
The difference is that instead of SQL database expert, you know need a NoSQL
expert.
• ... but it is not a brilliantly stupid idea either, it is an idea
worth considering depending of the project.
15. How hard can it be?
• With Ubuntu Linux Server 12.04 LTS:
• sudo apt-get install python-pymongo mongodb syslog-ng
syslog-ng-mod-mongodb
• for Syslog-NG, just some configuration
• for Radiator, some configuration and coding an external
Python script to handle accounting messages
• But this is far from production use, it is more like proto or
proof of concept implementation done in 1 work day.
18. Radiator RADIUS server
# /etc/radiator/radiator.cfg
#
# send all RADIUS accounting requests to external script
#
<Handler Request-Type = Accounting-Request>
<AuthBy EXTERNAL>
Command %D/acct2mongo.py
</AuthBy>
AcctLogFileName %L/acct-acct2mongodb-%Y-%M.log
</Handler>
19. #!/usr/bin/env python
from pymongo import Connection
import datetime
acct2mongo.py
import sys
def main():
line = str()
post = dict()
# opening connection
connection = Connection( 'localhost', 27017)
# database 'radius'
db = connection['radius']
# collection 'accounting'
collection = db['accounting']
post['acct2mongotimestamp'] = datetime.datetime.utcnow()
for line in sys.stdin.readlines():
pieces = line.split(' = ', 1)
if len(pieces) == 2:
post[pieces[0].strip().strip('"')]=pieces[1].strip().strip('"')
collection.insert(post)
connection.end_request()
connection.disconnect()
# 0 Means reply with an acceptance. For Access-Requests,
# an Access-Accept will be sent. For Accounting-Requests,
# an Accounting-Response will be sent.
return 0
if __name__ == '__main__':
main()
20. Does it actually work? What
can you do with data?
• Yes it does actually work, but once again it does not solve or be
applicable to everything.
• One can store, read, search and delete data supposedly very
efficiently, but anything more complicated is harder and must be
implemented by developer.
• For example: MongoDB does not have a reliable decimal datatype. It
is better to keep numbers as a string and convert them when
processing data.
• Repeating earlier statement: “You cannot forget datatypes or
database design even with NoSQL databases especially when going
into production.”
21. Performance?
• Would need to be measured and verified and with
real production environment or solution.
• Would also need to be compared with well
designed and optimised SQL database, maybe even
one functioning as NoSQL one.
• In the implementation this was not tested as the
datasets were very small compared to real datasets.
22. Conclusions
• NoSQL should be at least considered as an option
when designing and implementing large scale Syslog or
Radius Accounting storages.
• For development it is flexible.
• For production use NoSQL solution still needs design,
careful planning and testing to verify if the
performance, reliability and security is enough. Probably
as much as SQL database design.
• Key issue will probably be can the SQL database handle
the data or is horizontal scaling required.