Cyber Attacks Detection Using AI Algorithms
Here comes a short abstract of the project that summarizes what it is about
Keywords: AI, ML, DL, Cybersecurity, Cyber Attacks.
- Find literature about AI and Cyber Attacks on IoT Devices Dectection.
- Analyze the literature and explain how AI for Cyber Attacks on IOT Devices Detection are beneficial.
Types of Cyber Attacks
- Denial of service (DoS) Attack:
- Remote to Local Attack:
- User to Root Attack:
- Adversarial Attacks:
- Poisoning Attack:
- Evasion Attack:
- Integrity Attack:
- Malware Attack:
- Phising Attack:
- Zero Day Attack:
- Sinkhole Attack:
- Causative Attack:
Examples of AI Algorithms for Cyber Attacks Detection
- Convolutional Neural Network (CNN)
- Autoencoder (AE)
- Deep Belief Network (DBN)
- Recurrent Neural Network (RNN)
- Generative Adversal Network (GAN)
- Deep Reinforcement Learning (DIL)
- Finding data sets in IoT Devices Cyber Attacks.
- Can any of the data sets be used in AI?
- What are the challenges with IoT Devices Cyber Attacks data set? Privacy, HIPPA, Size, Avalibility
- Datasets can be huge and GitHub has limited space. Only very small datasets should be stored in GitHub.
However, if the data is publicly available you program must contain a download function instead that you customize.
Write it using pythons
request. You will get point deductions if you check-in data sets that are large and do not use the download function.
3. Using Images
- Place a cool image into projects images in my directory
- Correct the following link, replace the fa number with my su number and thne chart of png.
- If the image has been copied, you must use a reference such as shown in the Figure 1 caption.
Figure 1: Images can be included in the report, but if they are copied you must cite them 1.
Your project must include a benchmark. The easiest is to use cloudmesh-common [^2]
A convincing but not fake conclusion should summarize what the conclusion of the project is.
- Gregor von Laszewski
- Yohn Jairo Bautista
- Carlos Theran