MALWARE DETECTION USING
MACHINE LEARNING
YASH TIWARI (CS-41)
SOHEB ANSARI(CS-41)
ARMAN RAJA (CS-41)
AYUSH UPADHYAY (CS-41)
CONTEN
TS
▶ MALWARE
▶ Malware Detection
▶ Malware Attacks and How to Prevent Them
▶ Malware Symptoms
▶ Machine learning
▶ Proposed solutions with algorithms
▶ Problem identified
▶ Conclusion
▶ References
MALWA
RE
▶ Malware is any software intentionally designed to cause damage to a
computer, server, client, or computer network. A wide variety of malware
types exist, including computer viruses, worms, Trojan horses, ransomware,
spyware, adware, rogue software, wiper and scareware.
▶ Types of malware : Trojan horse, Virus, Adware, bots, bugs, rootkits, spyware
▶ MALWARE DETECTOR :
Malware detection is the process of scanning the computer and files to
detect malware. It is effective at detecting malware because it involves multiple
tools and approaches. It's not a one way process, it's actually quite complex.
Malware
Detection
▶ Malware detection is the process of scanning the computer and files
to detect malware. It is effective at detecting malware because it
involves multiple tools and approaches. It's not a one way process,
it's actually quite complex.
▶ Malware Detection Methods :
Malware Attacks
▶ 1. Viruses
• Viruses require human intervention to propagate.
• Once users download the malicious code onto their devices -- often delivered
via malicious advertisements or phishing emails the virus spreads throughout
their systems.
• Viruses can modify computer functions and applications; copy, delete and
exfiltrate data.
▶ 2. Adware:
• It is capable of downloading or displaying advertisements to the device user.
• Not steel any data from the system but it forcing users to see ads.
• Some Irritating forms of adware display browser pop-ups that cannot be closed.
▶ 3. Ransomware
• Ransomware locks or encrypts files or devices and forces victims to pay a ransom
in exchange for reentry. While ransomware and malware are often used
synonymously, ransomware is a specific form of malware.
• Types of Ransomware : Locker ransomware, Crypto ransomware, Triple extortion
ransomware,
▶ 4. Rootkits
• A rootkits is malicious software that enables threat actors to
remotely access and control a device.
• Rootkits facilitate the spread of other types of malware, including
ransomware,
viruses and keyloggers.
• Rootkits often go undetected, because once inside a device,
they can deactivate antimalware and antivirus software.
• Rootkits typically enter devices and systems through
phishing emails and
malicious attachments.
▶ 5. Spyware
• Spyware is malware that downloads onto a device without
the user's knowledge.
• It steals users’ data to sell to advertisers and external
users.
• Spyware can track credentials and obtain bank details and
other sensitive data.
• It infects devices through malicious apps, links, websites
How To Prevent Malware
Attacks
Preventing malware attacks involves a combination of proactive measures
and good practices.
Here are some essential steps.
• Use security software
• Keep your system update
• Avoid clicking links and downloading attachments.
• Implement strong access control.
• Use a Firewall
• Partition your network
• Secure your network
• User security analytics
• Use strong password
Malware
Symptoms
▶ Computers, they all can produce similar symptoms.
Computers that are infected with malware can exhibit any of
the following symptoms:
• Increased CPU usage
• Slow computer or web browser speeds
• Problems connecting to networks
• Freezing or crashing
• Modified or deleted files
• Appearance of strange files, programs, or desktop icons
• Programs running, turning off
• Performance issues
• Unusual behavior
• Security warnings
MACHINE
LEARNING
▶ Machine learning is a method of data analysis that automates
analytical model building. It is a branch of artificial intelligence based
on the idea that systems can learn from data, identify patterns and
make decisions with minimal human intervention.
▶ Types of machine learning
Supervised learning
Unsupervised learning
Reinforcement learning
PROPOSED SOLUTION WITH
ALGORITHMS
▶ Machine learning can easily identify the malware in the data and
datasets
▶ Different types of machine learning algorithms are applied such
as :
DECISION TREE
SVM
Random forest
XG boost
EXISTING
SYSTEMS
▶ Malware detection by using window api sequence and machine
learning
▶ Detecting unknown malicious code by applying classification
techniques on
oppose patterns
▶ Detecting scareware by mining variable length instructions
sequence
▶ Accurate adware detection using oppose sequence extraction
▶ Detection of spyware by mining executable files
▶ Detection by using neural networks on the malware
CONCLUSI
ON
▶ A Malware is critical threat to user computer system in terms of
stealing
confidential information or disabling security.
▶ This project present some of the existing machine learning algorithms
directly applied on the data or datasets of malware
▶ It explains the how the algorithms will play a role in detecting
malware wit high accuracy and predictions
▶ We are also using data science and data mining techniques to
overcome the drawbacks of existing system
REFERENC
ES
▶https://en.wikipedia.org/wiki/Malware
▶https://en.wikipedia.org/wiki/Machine_learning
▶https://en.wikipedia.org/wiki/Supervised_learning
▶https://en.wikipedia.org/wiki/Spamming
▶
https://www.researchgate.net/publication/343499527_Project_report_M
alwa
re_analysis
▶
https://towardsdatascience.com/malware-detection-using-deep-lea
rning-
6c95dd235432
Thank
You
