Introduction

Artificial Intelligence for malware analysis has emerged as a promising tool in the arms race against sophisticated and stealthy cyber-attacks. The aim of this contest is to use AI to detect and analyse malware based on their run-time behavior. The data set for the contest is provided by RaDaR, supported by the Open Malware Research, which has run-time logs captured from the Operating System, hardware, and the network while a malware executes. 

We will have an online training session on 09 Sept 2024 on Open Malware Research, the RaDaR dataset and the problem statement. 

To participate you need to,

1. Fill in the Team Registration Form to register. This is Mandatory for every team. 

2. Submit a Design document that explains your solution to the Problem Statement. Submit this as a Project in the DevPost. This will be your completion for the Step-1 Design (Online) phase.

3. If selected, Implement the solution in an offline event @IIT Madras to be held on 19th and 20th October 2024. This will be the Step - 2 Solution Implementation (Offline) phase.

Important Note: Candidature of teams with only DevPost Registration and Project Submission while missing details in the Team Registration Form will not be entertained.

Requirements

The Problem Statement

To perform a multi class classification on Malware data (RaDaR), present in a tabular format. The RaDaR data consists of multiple features that have been collected for a large number of malware. The task would be to develop a solution pipeline/design (pre-processing and model application) that can perform classification of Malware in a time efficient and accurate manner.

Hackathon Sponsors

Prizes

454,500 in prizes
GOLD PRIZE
1 winner

SILVER PRIZE
1 winner

BRONZE PRIZE
1 winner

PARTICIPATION AWARD
17 winners

Devpost Achievements

Submitting to this hackathon could earn you:

Judges

To be announced soon

To be announced soon

Judging Criteria

  • (Stage 1 - Online) Design Evaluation
    The Design solution will be evaluated based on the basis of Solution Novelty, Technology stack, Ease of Scalability, Value Proposition.
  • (Stage 2-Offline) Solution Implementation
    A private Kaggle Competition will be created for the Offline Phase. The Leaderboard Rankings and Novelty of the solution will play a major role in deciding the Team rankings.

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