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IT IS VERY IMPORTANT TO READ THE INSTRUCTIONS!!! THIS IS DOCTORAL WORK. Turnitin and Waypoint are being used to check for plagiarism, and please use APA format. Please pay close attention I NEED...

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https://www.dropbox.com/s/nog0nuhgbjg35uy/SoundLibrary.zip?dl=0


Purpose


This assignment will sum up the Animatesection of the course. You will work independently to create unique artwork that meets specific technical standards.


Getting Started




  • Downloadthe file archives linked above. Read through the assignment instructions and explore the sample files and resources.


  • Brainstorm. Try to come up with an engaging idea for this project before you turn on the computer. Consider sketching or outlining potential ideas to help you zero-in on the one that seems the most engaging.



  • Step-by-step suggestionsfor planning and building this file are included in the assignment instructions!





Project Requirements




  • File specs:900 x 600 pixels. 5-10 second animation.

  • One pixel element created in Photoshop.

  • At least two vector elements from your final Illustrator project.

  • A layer containing type.

  • A layer containing sound.

  • No fewer than 4 separate tweens [motion, shape]



Delivery


You will turn in only the native FLA when you have completed this project




  • Wong_WingTung_ANFinal


Answered 1 days After Nov 05, 2024

Solution

Shubham answered on Nov 06 2024
3 Votes
Introduction
Intrusion Detection Systems are important for identifying and responding to potential security
eaches in organizational networks. The systems use different methodologies to detect anomalies and malicious activity. The study explores three primary IDS malware detection methodologies that are signature-based, anomaly-based and stateful protocol analysis. It provides analysis based on recent research. The assignment will outline effective strategies for deploying and maintaining IDS to remain safe against cyber threats.
Malware Detection Methodologies
Signature-Based Detection
Signature-based detection is widely used methodologies in IDS because of efficiency and accuracy in identifying known threats. The method relies on matching cu
ent network traffic with database of identified malware patterns. When a known signature is detected, the IDS generates an alert that allows the system administrators to respond quickly. Signature-based IDS is effective in environments with well-defined threats that can quickly identify and halt known attacks without generating false positives (Scarfone & Mell, 2021). It is primary limitation that is inability to detect new and evolving malware that is unknown threats that lack existing signatures in the database. Signature-based detection is more effective as the part of layered IDS strategy that includes other detection methods.
Anomaly-Based Detection
Anomaly-based detection uses machine learning and statistical models to detect deviations from normal network behaviour. It can identify potential threats based on i
egular activities. The method is adaptable that allowing it to detect unknown threats that do not match any signature that is useful in dynamic environments. Anomaly-based detection is especially valuable for detecting zero-day attacks that signature-based systems can miss (Patra & Sharma, 2022). The sensitivity of the method to i
egular behaviour can lead to higher rates of false positives. Along with the routine changes and network updates may trigger alerts even when no malicious activity is present. Continuous tuning and contextual understanding are important to optimize anomaly-based IDS settings and reduce unnecessary...
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