The Spark

•Download as PPT, PDF•

0 likes•389 views

The document discusses error detection and checksum algorithms. It describes common checksum methods like parity checks, cyclic redundancy checks, and checksums. It explains how checksums work by adding redundant bits to detect errors. Applications are given such as verifying data integrity when transmitting over networks or storing on media. Advantages are error detection, but disadvantages are that checksums cannot detect all types of errors.

Technology Education

EKTA M.S.SUPRIYA MALINI.B.S MANASA.R GOWRI.P

[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

[object Object],[object Object],[object Object],ERROR DETECTION

[object Object],[object Object],[object Object]

[object Object],[object Object],[object Object],[object Object],[object Object]

[object Object],[object Object],[object Object],[object Object]

A problem of anomaly behavior detection for network server without traffic inspection is discussed. An importance of the problem is proved in a context of broad use of typical communication engines in servers and Internet of Things. A cross-correlation function for request-response characterization is introduced. An applicability of this approach was probed on SSH, DNS, HTTP and HTTPS real traffic. Two algorithms are provided to work with cross-correlation functions: one is based on Pearson correlation coefficient and another based on neural network one class classifier. Traffic of real HTTP and HTTPS servers is used to investigate algorithms and analyze their results. Key features and important parameters of both algorithms are highlighted. Not typical request-response events detection is demonstrated on test traffic series. Actuality and lightweight quality of the approach are emphasized regarding intrusion detection system implementation for typical servers, M2M and IoT applications.

ADRISYA: A FLOW BASED ANOMALY DETECTION SYSTEM FOR SLOW AND FAST SCAN

IJNSA Journal

Attackers perform port scan to find reachability, liveness and running services in a system or network. Current day scanning tools provide different scanning options and capable of evading various security tools like firewall, IDS and IPS. So in order to detect and prevent attacks in the early stages, an accurate detection of scanning activity in real time is very much essential. In this paper we present a flow based protocol behaviour analysis system to detect TCP based slow and fast scan. This system provides scalable, accurate and generic solution to TCP based scanning by means of automatic behaviour analysis of the network traffic. Detection capability of proposed system is compared with SNORT and result proves the high detection rate of the system over SNORT.

IRJET- Netreconner: An Innovative Method to Intrusion Detection using Regular...

IRJET Journal

RAT is one of the most infected malware in the hyper-connected world. Data is being leaked or disclosed every day because new remote access Trojans are emerging and they are used to steal confidential data from target hosts. Network behavior-based detection has been used to provide an effective detection model for Remote Access Trojans. However, there is still short comings: to detect as early as possible, some False Negative Rate and accuracy that may vary depending on ratio of normal and malicious RAT sessions. As typical network contains large amount of normal traffic and small amount of malicious traffic, the detection model was built based on the different ratio of normal and malicious sessions in previous works. At that time false negative rate is less than 2%, and it varies depending on different ratio of normal and malicious instances. An unbalanced dataset will bias the prediction model towards the more common class. In this paper, each RAT is run many times in order to capture variant behavior of a Remote Access Trojan in the early stage, and balanced instances of normal applications and Remote Access Trojans are used for detection model. Our approach achieves 99 % accuracy and 0.3% False Negative Rate by Random Forest Algorithm.

Crypto sim_cryptolog_cryptospot_v3

Mustafa Kuğu

Artificial neural network for misuse detectionLikan Patra

aniketnimaje

Internet ttraffic monitering anomalous behiviour detection

Gyan Prakash

Databse Intrusion Detection Using Data Mining Approach

Suraj Chauhan

aniketnimaje

RSA 2009 talk on GAO Technical Approach to Assessing Computer Security at Fed...

Naba Barkakati

Chapter 1 organizing data vantage domain action and validity

Phu Nguyen

Measuring black boxes

Phil Huggins FBCS CITP

CTAP

Lan & Wan Solutions

JPJ1431 top-k Query Result Completeness Verification

chennaijp

top-k query result completeness verification in tiered sensor networks

swathi78

Ip trace ppt

deepakmarndi

A KEY LEVEL SELECTION WITHIN HASH CHAINS FOR THE EFFICIENT ENERGY CONSUMPTION...

ijasa

A wireless sensor network is composed of a base station (BS) and numerous sensor nodes. The sensor nodes lack security because they operate in an open environment, such as the military. In particular, a false report injection attack captures and compromises sensor nodes. The attack then causes the compromised nodes to generate forward false reports. Owing to the false report injection attack, not only does the sensor network have a false alarm, but its limited energy is also drained. In order to defend the false report injection attack, over the past few years, several studies have been made looking for a solution to the attack. Ye et al. studied statistical en-route filtering (SEF). SEF is a method of stochastically verifying event reports in the en-route filtering phase. SEF can filter many false reports early using verification of intermediate nodes. However, because the number of keys in a sensor node is fixed by the system, the sensor network cannot control the event report verification probability depending on the circumstances of the network. Therefore, it is difficult to efficiently consume energy of the sensor network. In order to solve the problem, we propose a method which controls the event report verification probability by using a key sequence level of an event report. In the proposed method, when an intermediate node receives an event report, the node verifies the event report by comparing a key sequence level of the report and its key sequence level. Elements determining the key sequence level include the density of neighbour nodes in the sensing range of a center of stimulus (CoS), the number of hops from the CoS to the BS, and the average of the key sequence level of intermediate nodes in each path. We simulated the proposed method and the SEF method to evaluate the performance in terms of energy efficiency and security. In the simulation results, the proposed method consumed an average of 7.9% less energy of the sensor nodes compared to SEF method. The number of false reports arriving at the BS of the proposed method was also less, by an average of 6.4, compared to the SEF method. Through the results, we can see that when the number of false report is large in the sensor network, the proposed method is more energy-efficient and secure than the SEF method.

A Study on Data Mining Based Intrusion Detection System

AM Publications

In recent years security has remained unsecured for computers as well as data network systems. Intrusion detecting system used to safeguard the data confidentiality, integrity and system availability from various types of attacks. Data mining techniques that can be applied to intrusion detection system to detect normal and abnormal behavior patterns. This paper studies nature of network attacks and the current trends of data mining based intrusion detection techniques

Intrusion detection system based on web usage mining

IJCSEA Journal

This artical present a system developed to find cyber threats automatically based on web usage mining methods in application layer. This system is an off-line intrusion detection system which includes different part to detect attacks and as a result helps find different kinds of attacks with different dispersals. In this study web server access logs used as the input data and after pre-processing, scanners and all identified attacks will be detected. As the next step, vectors feature from web access logs and parameters sent by HTTP will derived by three different means and at the end by employment of two clustering algorithms based on K-Means, anomaly behaviour of data are detached. Tentative results derived from this system represent that used methods are more applicable than similar systems because this system covers different kinds of attacks and mostly increase the accuracy and decrease false alarms.

Intrusion detection using data miningbalbeerrawat

Error Detection And Correction

Renu Kewalramani

Lecture 5Mahesh Kumar Attri

What's hot

Vulnerability assessment-info-savvy

infosavvy

Criminal identification system

Akash Kumar Singh

Optimal remote access trojans detection based on network behavior

IJECEIAES

Crypto sim_cryptolog_cryptospot_v3

Mustafa Kuğu

Artificial neural network for misuse detectionLikan Patra

aniketnimaje

Internet ttraffic monitering anomalous behiviour detection

Gyan Prakash

Databse Intrusion Detection Using Data Mining Approach

Suraj Chauhan

aniketnimaje

RSA 2009 talk on GAO Technical Approach to Assessing Computer Security at Fed...

Naba Barkakati

Chapter 1 organizing data vantage domain action and validity

Phu Nguyen

Measuring black boxes

Phil Huggins FBCS CITP

CTAP

Lan & Wan Solutions

JPJ1431 top-k Query Result Completeness Verification

chennaijp

top-k query result completeness verification in tiered sensor networks

swathi78

Ip trace ppt

deepakmarndi

A KEY LEVEL SELECTION WITHIN HASH CHAINS FOR THE EFFICIENT ENERGY CONSUMPTION...

ijasa

A Study on Data Mining Based Intrusion Detection System

AM Publications

Intrusion detection system based on web usage mining

IJCSEA Journal

Intrusion detection using data miningbalbeerrawat

What's hot (20)

Vulnerability assessment-info-savvy

Criminal identification system

Optimal remote access trojans detection based on network behavior

Crypto sim_cryptolog_cryptospot_v3

Artificial neural network for misuse detection

Internet ttraffic monitering anomalous behiviour detection

Databse Intrusion Detection Using Data Mining Approach

RSA 2009 talk on GAO Technical Approach to Assessing Computer Security at Fed...

Chapter 1 organizing data vantage domain action and validity

Measuring black boxes

CTAP

JPJ1431 top-k Query Result Completeness Verification

top-k query result completeness verification in tiered sensor networks

Ip trace ppt

A KEY LEVEL SELECTION WITHIN HASH CHAINS FOR THE EFFICIENT ENERGY CONSUMPTION...

A Study on Data Mining Based Intrusion Detection System

Intrusion detection system based on web usage mining

Intrusion detection using data mining

Viewers also liked

Error Detection And Correction

Renu Kewalramani

Lecture 5Mahesh Kumar Attri

10 Error Detection_and_Correction

Ahmar Hashmi

DCN Error Detection & Correction

Rohan Bhatkar

Error detection correction (CRC)

Karam Munir Butt

Error Detection N CorrectionAnkan Adhikari

Error Detection and CorrectionTechiNerd

Parity check(Error Detecting Codes)

Imesha Perera

Error detection and correction

Maria Akther

Error Detection and Correction - Data link Layer

Abdullaziz Tagawy

Networks must be able to transfer data from one device to another with acceptable accuracy. For most applications, a system must guarantee that the data received are identical to the data transmitted. Any time data are transmitted from one node to the next, they can become corrupted in passage. Many factors can alter one or more bits of a message. Some applications require a mechanism for detecting and correcting errors. Some applications can tolerate a small level of error. For example, random errors in audio or video transmissions may be tolerable, but when we transfer text, we expect a very high level of accuracy. At the data-link layer, if a frame is corrupted between the two nodes, it needs to be corrected before it continues its journey to other nodes. However, most link-layer protocols simply discard the frame and let the upper-layer protocols handle the retransmission of the frame. Some multimedia applications, however, try to correct the corrupted frame. This chapter is divided into five sections. ❑ The first section introduces types of errors, the concept of redundancy, and distinguishes between error detection and correction. ❑ The second section discusses block coding. It shows how error can be detected using block coding and also introduces the concept of Hamming distance. ❑ The third section discusses cyclic codes. It discusses a subset of cyclic code, CRC, that is very common in the data-link layer. The section shows how CRC can be easily implemented in hardware and represented by polynomials. ❑ The fourth section discusses checksums. It shows how a checksum is calculated for a set of data words. It also gives some other approaches to traditional checksum. ❑ The fifth section discusses forward error correction. It shows how Hamming distance can also be used for this purpose. The section also describes cheaper methods to achieve the same goal, such as XORing of packets, interleaving chunks, or compounding high and low resolutions packets.

Errror Detection and CorrectionMahesh Kumar Attri

Error detection and correction

Siddique Ibrahim

Error control, parity check, check sum, vrcHuawei Technologies

Computer Networks - Error Detection & Error Correction

Saikrishna Tanguturu

Viewers also liked (14)

Error Detection And Correction

Lecture 5

10 Error Detection_and_Correction

DCN Error Detection & Correction

Error detection correction (CRC)

Error Detection N Correction

Error Detection and Correction

Parity check(Error Detecting Codes)

Error detection and correction

Error Detection and Correction - Data link Layer

Errror Detection and Correction

Error detection and correction

Error control, parity check, check sum, vrc

Computer Networks - Error Detection & Error Correction

Similar to The Spark

Understanding Intrusion Detection & Prevention Systems (1).pptx

Rineri1

A lightweight secure scheme for detecting

jpstudcorner

HEAD OFFICE (CHENNAI): JP INFOTECH, Old No. 31, New No: 86, 1st Floor, 1st Avenue, Ashok Nagar (Ashok Pillar), Chennai – 83. Landmark: Next to Kotak Mahendra Bank / Bharath Scans MOBILE: (0)9952649690 LANDLINE: (044) 43012642 E-MAIL: jpinfotechprojects@gmail.com PUDUCHERRY / PONDICHERRY OFFICE: JP INFOTECH, #45, Kamaraj Salai, Thattanchavady, Pondy-Tindivanam High Road, Puducherry/Pondicherry – 605009. Landmark: Opp. To Thattanchavady Industrial Estate and Next to VVP Nagar Arch. MOBILE: (0)9952649690 / (0) 8608600246 LANDLINE: (0413)4300535 E-MAIL: jpinfotechprojects@gmail.com

Data Integrity Techniques: Aviation Best Practices for CRC & Checksum Error D...

Philip Koopman

Author: Prof. Philip Koopman, Carnegie Mellon University Abstract: This talk includes both a tutorial and explanation of research results on the proper use of Cyclic Redundancy codes (CRCs) and checksums in an aviation context. More than 50 years since the invention of the CRC, the proper use of these error detection codes is still hampered by a combination of misleading folklore, sub-optimality of standard approaches, general inaccessibility of research results, and the occasional typographical error in key reference materials. However, recent work has been able to exhaustively explore the CRC design space and identify optimal selection criteria based on key system characteristics. This talk will covers the following areas: checksum and CRC theory with an emphasis on intuitive understanding rather than heavy math; why using a standard or widely used CRC can be suboptimal (or worse); how to pick a good checksum/CRC; the key parameters that affect the error detection capability of a checksum/CRC; CRC pitfalls illustrated via examples from Controller Area Network and ARINC-825; an example CRC selection process for achieving a required level of functional criticality; and a “seven deadly sins” list for CRC/checksum use. Some key research findings that are discussed include: a well-chosen CRC is usually dramatically better than a checksum for relatively little additional computational cost; you can usually do a lot better than “standard” CRC (especially CRC-32); Hamming Distance at the target payload length is the predominant selection criterion of interest; and it is important to avoid bit encoding approaches that undermine CRC effectiveness. Bio: Dr. Philip Koopman is a professor at Carnegie Mellon University, with research interests in the areas of software robustness, embedded networking, dependable embedded computer systems, and autonomous vehicle safety. Previously, he was a US Navy submarine officer, an embedded CPU architect for Harris Semiconductor, and an embedded system researcher at United Technologies. In addition to a variety of academic publications and two dozen patents, he has authored the book Better Embedded System Software based on lessons learned from more than a hundred design reviews of industry software. He has affiliations with both the Carnegie Mellon Electrical & Computer Engineering Department (ECE) and the National Robotics Engineering Center (NREC). He is a senior member of IEEE, senior member of the ACM, and a member of IFIP WG 10.4 on Dependable Computing and Fault Tolerance.

Error correction and Detection technique while sending the message

Anil Kumar Sonkar Sonkar

Cybersecurity - Jim Butterworth

TechBiz Forense Digital

A study of cryptography for satellite applications

Rajesh Ishida

Antimalware

Mayank Chaudhari

Ebu class edgescan-2017

Eoin Keary

dccn ppt.pptx

FreefireGarena22

RAZORPOINT SECURITY GLOSSARY

Razorpoint Security

Distance-bounding facing both mafia and distance frauds

KaashivInfoTech Company

Contactless technologies such as RFID, NFC, and sensor networks are vulnerable to mafia and distance frauds. These frauds aim at successfully passing an authentication protocol by cheating on the actual distance between the prover and the verifier. Distance-bounding protocols have been designed to cope these security issues, but none of them properly resists to these two frauds without requiring additional memory and computation. The situation is even worse considering that just a few distance-bounding protocols are able to deal with the inherent background noise on the communication channels. This article introduces a noise-resilient distance-bounding protocol that resists to both mafia and distance frauds. The security of the protocol is analyzed against known attacks and illustrated by experimental results. The results demonstrate the significant advantage of the introduced lightweight design over the previous proposals. http://kaashivinfotech.com/ http://inplanttrainingchennai.com/ http://inplanttraining-in-chennai.com/ http://internshipinchennai.in/ http://inplant-training.org/ http://kernelmind.com/ http://inplanttraining-in-chennai.com/ http://inplanttrainingchennai.com/

Proposal for System Analysis and Desing

Md Khaza Main Uddin

Trial Course - CertMaster Learn and CertMaster Labs for Security+ (Exam SY0-6...

MohamedOmerMusa

Websecurity Merve Bilgen

A novel signature based traffic classification engine to reduce false alarms ...

IJCNCJournal

Pattern matching plays a significant role in ascertaining network attacks and the foremost prerequisite for a trusted intrusion detection system (IDS) is accurate pattern matching. During the pattern matching process packets are scanned against a pre-defined rule sets. After getting scanned, the packets are marked as alert or benign by the detection system. Sometimes the detection system generates false alarms i.e., good traffic being identified as bad traffic. The ratio of generating the false positives varies from the performance of the detection engines used to scan incoming packets. Intrusion detection systems use to deploy algorithmic procedures to reduce false positives though producing a good number of false alarms. As the necessities, we have been working on the optimization of the algorithms and procedures so that false positives can be reduced to a great extent. As an effort we have proposed a signature-based traffic classification technique that can categorize the incoming packets based on the traffic characteristics and behaviour which would eventually reduce the rate of false alarms

Why Penetration Testing Services Cyber51

martinvoelk

Bank World 2008 Kamens 04 29 08kamensm02

Cyber warfare introduction

jagadeesh katla

Presentation1.pptx

SubhashreddyPalleti

Overview of Vulnerability Scanning.pptx

AjayKumar73315

Similar to The Spark (20)

Understanding Intrusion Detection & Prevention Systems (1).pptx

A lightweight secure scheme for detecting

Data Integrity Techniques: Aviation Best Practices for CRC & Checksum Error D...

Error correction and Detection technique while sending the message

Cybersecurity - Jim Butterworth

A study of cryptography for satellite applications

Antimalware

Ebu class edgescan-2017

dccn ppt.pptx

RAZORPOINT SECURITY GLOSSARY

Distance-bounding facing both mafia and distance frauds

Proposal for System Analysis and Desing

Trial Course - CertMaster Learn and CertMaster Labs for Security+ (Exam SY0-6...

Websecurity

A novel signature based traffic classification engine to reduce false alarms ...

Why Penetration Testing Services Cyber51

Bank World 2008 Kamens 04 29 08

Cyber warfare introduction

Presentation1.pptx

Overview of Vulnerability Scanning.pptx

Recently uploaded

Mission to Decommission: Importance of Decommissioning Products to Increase E...

Product School

Epistemic Interaction - tuning interfaces to provide information for AI support

Alan 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.

Knowledge engineering: from people to machines and back

Elena Simperl

Leading Change strategies and insights for effective change management pdf 1.pdf

OnBoard

Designing Great Products: The Power of Design and Leadership by Chief Designe...

Product School

FIDO Alliance Osaka Seminar: Overview.pdf

FIDO Alliance

How world-class product teams are winning in the AI era by CEO and Founder, P...

Product School

PHP Frameworks: I want to break free (IPC Berlin 2024)

Ralf Eggert

In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development. This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.

"Impact of front-end architecture on development cost", Viktor Turskyi

Fwdays

I have heard many times that architecture is not important for the front-end. Also, many times I have seen how developers implement features on the front-end just following the standard rules for a framework and think that this is enough to successfully launch the project, and then the project fails. How to prevent this and what approach to choose? I have launched dozens of complex projects and during the talk we will analyze which approaches have worked for me and which have not.

Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf

91mobiles

FIDO Alliance Osaka Seminar: Passkeys and the Road Ahead.pdf

FIDO Alliance

Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024

Tobias Schneck

As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other? Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.

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.

From Siloed Products to Connected Ecosystem: Building a Sustainable and Scala...

Product School

Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...

Jeffrey Haguewood

Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows. We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases. This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams. Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.

GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...

James Anderson

Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management. The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM). Speakers: Bob Boule Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle. Gopinath Rebala Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.

Assuring Contact Center Experiences for Your Customers With ThousandEyes

ThousandEyes

FIDO Alliance Osaka Seminar: Passkeys at Amazon.pdf

FIDO Alliance

The Art of the Pitch: WordPress Relationships and Sales

Laura Byrne

Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes? All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.

De-mystifying Zero to One: Design Informed Techniques for Greenfield Innovati...

Product School

Recently uploaded (20)

Mission to Decommission: Importance of Decommissioning Products to Increase E...

Epistemic Interaction - tuning interfaces to provide information for AI support

Knowledge engineering: from people to machines and back

Leading Change strategies and insights for effective change management pdf 1.pdf

Designing Great Products: The Power of Design and Leadership by Chief Designe...

FIDO Alliance Osaka Seminar: Overview.pdf

How world-class product teams are winning in the AI era by CEO and Founder, P...

PHP Frameworks: I want to break free (IPC Berlin 2024)

"Impact of front-end architecture on development cost", Viktor Turskyi

Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf

FIDO Alliance Osaka Seminar: Passkeys and the Road Ahead.pdf

Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024

Transcript: Selling digital books in 2024: Insights from industry leaders - T...

From Siloed Products to Connected Ecosystem: Building a Sustainable and Scala...

Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...

GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...

Assuring Contact Center Experiences for Your Customers With ThousandEyes

FIDO Alliance Osaka Seminar: Passkeys at Amazon.pdf

The Art of the Pitch: WordPress Relationships and Sales

De-mystifying Zero to One: Design Informed Techniques for Greenfield Innovati...

The Spark

1. EKTA M.S.SUPRIYA MALINI.B.S MANASA.R GOWRI.P

10.

11.

12.

13.

14.

15.

16.

17.

18.

19.

20.

The Spark

Recommended

Recommended

More Related Content

What's hot

What's hot (20)

Viewers also liked

Viewers also liked (14)

Similar to The Spark

Similar to The Spark (20)

Recently uploaded

Recently uploaded (20)

The Spark