SlideShare ist ein Scribd-Unternehmen logo
1 von 26
MALICIOUS TRAFFIC
Presented by Ishraq Fataftah
Agenda
   Introduction.
   What is Malicious traffic.
   Malicious traffic types.
   Malicious traffic detection and prevention.
   Conclusion.
Introduction
   As the internet become more
    mature, management of its resources to
    provide guaranteed services is crucial.
   The success of the Internet has increased its
    vulnerability to misuse and performance
    problems.
Introduction
   It has been frequently abused by people
    mostly with hostile intentions.
   We have been under various kinds of attacks
    such as viruses, worms and commonly a
    bunch of spam mails every day.
Introduction
Malicious Traffic
   It is hard to detect and distinguish malicious
    packet and legitimate packets in the traffic.
   The behavior of Internet traffic is very far from
    being regular.
   Presents large variations in its throughput at
    all scales.
Malicious Traffic
   Any traffic anomalies that occur from hardware
    or software failures to internet packets with
    maliciously modified options.
   Generated from what is called botnets.
Malicious Traffic: Botnets
Malicious Traffic
   Monitoring the flow of packets.
   Malicious traffic usually exhausts the legitimate
    resources by sending a lot of traffic.
   Monitoring traffic targeting unused addresses
    in the network.
Malicious Traffic Types
   Scanners.
   Worms.
   Malicious Spam.
   Backscatters.
   DOS, DDOS.
Scanners
 Single source.
 Strikes the same port on many machines.

 Different ports on the same machine.

 Generates

a lot of flows.
Worms
   Self-replicating virus that does not alter files
    but resides in active memory and duplicates
    itself.
   CodeRed worm infected 395,000 computers
    and resulted in approximately $2.6 billion in
    damage.
   Results in an increase in service
    activity, especially if service is law traffic.
Worms
MyTob Worm, 2005
                              Copies itself as %System%msnmsgs.exe
                              Adds the value: “MSN” = “msnmsgs.exe” to
              IRC Server       registry:
                               HKEY_LOCAL_MACHINESoftwareMicrosoftWindowsCurrentVersionRun
                               HKEY_LOCAL_MACHINESoftwareMicrosoftWindowsCurrentVersion
                               RunServices
                               HKEY_CURRENT_USERSOFTWAREMicrosoftWindowsCurrentVersionRun
                               HKEY_CURRENT_USERSoftwareMicrosoftOLE
                               HKEY_CURRENT_USERSYSTEMCurrentControlSetControlLsa


                              W32.Mytob@mm runs every time Windows starts




  User Zone                    Server Zone
Malicious Spam
   Spamming is flooding the network with a huge
    amount of unsolicited email messages to force
    people to receive them.
   Contains malware or links to malicious sites.
Backscatter
   Email bounces for emails that a person didn’t
    send.
   Spammer is spoofing the Reply-to field in
    email.
   When sent to email server, it is bounces to the
    reply-to address rather than the sender.
   Used to overcome spam filters and in DOS
    attacks.
DOS, DDOS
   Generate a huge amount of adverse traffic to a
    target server to make it unavailable.
   Attempt to exhaust the resources of the victim.
   They are difficult to detect and prevent.
   DDOS attacks are simultaneously launched
    from several sources destined to the same
    target.
DOS, DDOS
Malicious traffic Detection and
Prevention
   Anomaly detection techniques.
   Signature-scan techniques.
   Intrusion detection and prevention systems.
   QoS metrics.
   Tools such as Snort.
   Network filters such as ACLs.
   Honeypots.
Anomaly detection techniques
   Differentiates between normal and malicious
    traffic by:
     Studying the normal behavior of users, resources.
     Create patterns for these activities.

     Any behavior that deviates from this pattern is
      considered malicious.
Signature-scan techniques
   Uses a database that store signatures.
   Passive scan for network traffic, any patterns
    match these stored signatures are considered
    malicious traffic.
   Effective for known attacks.
Intrusion detection and prevention
systems
   Software or hardware that is designed to
    detect and prevent any malicious attack or
    activity on the network.
   Monitor the network traffic.
   Analyze any suspicious event.
   Log these events and report them to the
    network administrator for actions.
QoS metrics
   Studying the behavior of the network traffic
    under normal and malicious attacks.
   Extracting parameters from network traffic.
Snort
   Open source tool that is used in intrusion
    detection systems.
   Real time analysis on the network traffic.
   Intrusion detection system to monitor the
    traffic, analyzes it and inform the network
    administrator for suspicious activities.
ACLs
   Installed in routers and used to match packet
    headers against a pre-defined list of rules and
    takes pre-defined actions on any matching
    packets.
Honeypots
“a security resource whose value lies in being
  probed, attacked or compromised”

   Any attempt to interact with honeypots incurs a
    malicious activity or attack.
Conclusion
   Malicious traffic is any traffic anomalies occurs
    from failure in traffic packets that is
    intentionally modified for malicious acts.
   By studying malicious attacks we can obtain
    better understanding of malicious traffic and
    how to detect and prevent these attacks.
   An increase in the awareness toward the
    importance of security will help in mitigation
    against internet misuse.

Weitere ähnliche Inhalte

Was ist angesagt?

Malware Classification and Analysis
Malware Classification and AnalysisMalware Classification and Analysis
Malware Classification and AnalysisPrashant Chopra
 
Introduction to Network Security
Introduction to Network SecurityIntroduction to Network Security
Introduction to Network SecurityJohn Ely Masculino
 
Network security
Network securityNetwork security
Network securityNandini Raj
 
Introduction to foot printing
Introduction to foot printingIntroduction to foot printing
Introduction to foot printingCHETAN THAKRE
 
DDoS Attack Detection & Mitigation in SDN
DDoS Attack Detection & Mitigation in SDNDDoS Attack Detection & Mitigation in SDN
DDoS Attack Detection & Mitigation in SDNChao Chen
 
Security Requirements in IoT Architecture
Security	Requirements	in	IoT	Architecture Security	Requirements	in	IoT	Architecture
Security Requirements in IoT Architecture Vrince Vimal
 
DDoS Attack PPT by Nitin Bisht
DDoS Attack  PPT by Nitin BishtDDoS Attack  PPT by Nitin Bisht
DDoS Attack PPT by Nitin BishtNitin Bisht
 
Intrusion detection and prevention system
Intrusion detection and prevention systemIntrusion detection and prevention system
Intrusion detection and prevention systemNikhil Raj
 
Cyber security and current trends
Cyber security and current trendsCyber security and current trends
Cyber security and current trendsShreedeep Rayamajhi
 
Denial of Service Attacks (DoS/DDoS)
Denial of Service Attacks (DoS/DDoS)Denial of Service Attacks (DoS/DDoS)
Denial of Service Attacks (DoS/DDoS)Gaurav Sharma
 
Network Security Presentation
Network Security PresentationNetwork Security Presentation
Network Security PresentationAllan Pratt MBA
 
Fidelis - Live Demonstration of Deception Solution
Fidelis - Live Demonstration of Deception SolutionFidelis - Live Demonstration of Deception Solution
Fidelis - Live Demonstration of Deception SolutionFidelis Cybersecurity
 
Module 6 Session Hijacking
Module 6   Session HijackingModule 6   Session Hijacking
Module 6 Session Hijackingleminhvuong
 

Was ist angesagt? (20)

Malware Classification and Analysis
Malware Classification and AnalysisMalware Classification and Analysis
Malware Classification and Analysis
 
Introduction to Network Security
Introduction to Network SecurityIntroduction to Network Security
Introduction to Network Security
 
Network security
Network securityNetwork security
Network security
 
Password craking techniques
Password craking techniques Password craking techniques
Password craking techniques
 
Packet sniffers
Packet sniffersPacket sniffers
Packet sniffers
 
Email Forensics
Email ForensicsEmail Forensics
Email Forensics
 
Introduction to foot printing
Introduction to foot printingIntroduction to foot printing
Introduction to foot printing
 
DDoS Attack Detection & Mitigation in SDN
DDoS Attack Detection & Mitigation in SDNDDoS Attack Detection & Mitigation in SDN
DDoS Attack Detection & Mitigation in SDN
 
Security Requirements in IoT Architecture
Security	Requirements	in	IoT	Architecture Security	Requirements	in	IoT	Architecture
Security Requirements in IoT Architecture
 
E mail Investigation
E mail InvestigationE mail Investigation
E mail Investigation
 
DDoS Attack PPT by Nitin Bisht
DDoS Attack  PPT by Nitin BishtDDoS Attack  PPT by Nitin Bisht
DDoS Attack PPT by Nitin Bisht
 
Denial of service
Denial of serviceDenial of service
Denial of service
 
Intrusion detection and prevention system
Intrusion detection and prevention systemIntrusion detection and prevention system
Intrusion detection and prevention system
 
Cyber security and current trends
Cyber security and current trendsCyber security and current trends
Cyber security and current trends
 
Denial of Service Attacks (DoS/DDoS)
Denial of Service Attacks (DoS/DDoS)Denial of Service Attacks (DoS/DDoS)
Denial of Service Attacks (DoS/DDoS)
 
Network Security Presentation
Network Security PresentationNetwork Security Presentation
Network Security Presentation
 
Ddos attacks
Ddos attacksDdos attacks
Ddos attacks
 
Network Forensic
Network ForensicNetwork Forensic
Network Forensic
 
Fidelis - Live Demonstration of Deception Solution
Fidelis - Live Demonstration of Deception SolutionFidelis - Live Demonstration of Deception Solution
Fidelis - Live Demonstration of Deception Solution
 
Module 6 Session Hijacking
Module 6   Session HijackingModule 6   Session Hijacking
Module 6 Session Hijacking
 

Andere mochten auch

Towards scalable locationaware
Towards scalable locationawareTowards scalable locationaware
Towards scalable locationawareIshraq Al Fataftah
 
Network Intrusion Detection System Using Snort
Network Intrusion Detection System Using SnortNetwork Intrusion Detection System Using Snort
Network Intrusion Detection System Using SnortDisha Bedi
 
Intrusion detection system
Intrusion detection systemIntrusion detection system
Intrusion detection systemAkhil Kumar
 
Intrusion Detection System(IDS)
Intrusion Detection System(IDS)Intrusion Detection System(IDS)
Intrusion Detection System(IDS)shraddha_b
 
Introduction to Snort Rule Writing
Introduction to Snort Rule WritingIntroduction to Snort Rule Writing
Introduction to Snort Rule WritingCisco DevNet
 
Intrusion detection system ppt
Intrusion detection system pptIntrusion detection system ppt
Intrusion detection system pptSheetal Verma
 
Intrusion detection system
Intrusion detection system Intrusion detection system
Intrusion detection system gaurav koriya
 
Hacking & its types
Hacking & its typesHacking & its types
Hacking & its typesSai Sakoji
 

Andere mochten auch (11)

Towards scalable locationaware
Towards scalable locationawareTowards scalable locationaware
Towards scalable locationaware
 
Optimizing spatial database
Optimizing spatial databaseOptimizing spatial database
Optimizing spatial database
 
Password based cryptography
Password based cryptographyPassword based cryptography
Password based cryptography
 
Network Intrusion Detection System Using Snort
Network Intrusion Detection System Using SnortNetwork Intrusion Detection System Using Snort
Network Intrusion Detection System Using Snort
 
Snort IDS/IPS Basics
Snort IDS/IPS BasicsSnort IDS/IPS Basics
Snort IDS/IPS Basics
 
Intrusion detection system
Intrusion detection systemIntrusion detection system
Intrusion detection system
 
Intrusion Detection System(IDS)
Intrusion Detection System(IDS)Intrusion Detection System(IDS)
Intrusion Detection System(IDS)
 
Introduction to Snort Rule Writing
Introduction to Snort Rule WritingIntroduction to Snort Rule Writing
Introduction to Snort Rule Writing
 
Intrusion detection system ppt
Intrusion detection system pptIntrusion detection system ppt
Intrusion detection system ppt
 
Intrusion detection system
Intrusion detection system Intrusion detection system
Intrusion detection system
 
Hacking & its types
Hacking & its typesHacking & its types
Hacking & its types
 

Ähnlich wie Malicious traffic

Information security & EthicalHacking
Information security & EthicalHackingInformation security & EthicalHacking
Information security & EthicalHackingAve Nawsh
 
Computing safety
Computing safetyComputing safety
Computing safetyBrulius
 
Threat Hunting Playbook.pdf
Threat Hunting Playbook.pdfThreat Hunting Playbook.pdf
Threat Hunting Playbook.pdflaibaarsyila
 
CyberSecurity presentation for basic knowledge about this topic
CyberSecurity presentation for basic knowledge about this topicCyberSecurity presentation for basic knowledge about this topic
CyberSecurity presentation for basic knowledge about this topicpiyushkamble6
 
Type of Malware and its different analysis and its types !
Type of Malware and its different analysis and its types  !Type of Malware and its different analysis and its types  !
Type of Malware and its different analysis and its types !Mohammed Jaseem Tp
 
Malware Hunter: Building an Intrusion Detection System (IDS) to Neutralize Bo...
Malware Hunter: Building an Intrusion Detection System (IDS) to Neutralize Bo...Malware Hunter: Building an Intrusion Detection System (IDS) to Neutralize Bo...
Malware Hunter: Building an Intrusion Detection System (IDS) to Neutralize Bo...Editor IJCATR
 
An email worm vaccine architecture
An email worm vaccine architectureAn email worm vaccine architecture
An email worm vaccine architectureUltraUploader
 
Recipient Activated Malware Diffusion
Recipient Activated Malware DiffusionRecipient Activated Malware Diffusion
Recipient Activated Malware DiffusionBruce Fowler
 
Trojan horse and salami attack
Trojan horse and salami attackTrojan horse and salami attack
Trojan horse and salami attackguestc8c7c02bb
 
A review botnet detection and suppression in clouds
A review botnet detection and suppression in cloudsA review botnet detection and suppression in clouds
A review botnet detection and suppression in cloudsAlexander Decker
 
5 worms and other malware
5   worms and other malware5   worms and other malware
5 worms and other malwaredrewz lin
 
L N Yadav Cyber SECURITY.ppt
L N Yadav Cyber SECURITY.pptL N Yadav Cyber SECURITY.ppt
L N Yadav Cyber SECURITY.pptlowlesh1
 
L N Yadav Cyber SECURITY2.ppt
L N Yadav Cyber SECURITY2.pptL N Yadav Cyber SECURITY2.ppt
L N Yadav Cyber SECURITY2.pptlowlesh1
 
A REVIEW ON DDOS PREVENTION AND DETECTION METHODOLOGY
A REVIEW ON DDOS PREVENTION AND DETECTION METHODOLOGYA REVIEW ON DDOS PREVENTION AND DETECTION METHODOLOGY
A REVIEW ON DDOS PREVENTION AND DETECTION METHODOLOGYijasa
 
EXTERNAL - Whitepaper - How 3 Cyber ThreatsTransform Incident Response 081516
EXTERNAL - Whitepaper - How 3 Cyber ThreatsTransform Incident Response 081516EXTERNAL - Whitepaper - How 3 Cyber ThreatsTransform Incident Response 081516
EXTERNAL - Whitepaper - How 3 Cyber ThreatsTransform Incident Response 081516Yasser Mohammed
 
Chapter 2 konsep dasar keamanan
Chapter 2 konsep dasar keamananChapter 2 konsep dasar keamanan
Chapter 2 konsep dasar keamanannewbie2019
 
Types of attack -Part3 (Malware Part -2)
Types of attack -Part3 (Malware Part -2)Types of attack -Part3 (Malware Part -2)
Types of attack -Part3 (Malware Part -2)SHUBHA CHATURVEDI
 
computer virus ppt.pptx
computer virus ppt.pptxcomputer virus ppt.pptx
computer virus ppt.pptxAbiniyavk
 

Ähnlich wie Malicious traffic (20)

Security threats
Security threatsSecurity threats
Security threats
 
Information security & EthicalHacking
Information security & EthicalHackingInformation security & EthicalHacking
Information security & EthicalHacking
 
Computing safety
Computing safetyComputing safety
Computing safety
 
Threat Hunting Playbook.pdf
Threat Hunting Playbook.pdfThreat Hunting Playbook.pdf
Threat Hunting Playbook.pdf
 
CyberSecurity presentation for basic knowledge about this topic
CyberSecurity presentation for basic knowledge about this topicCyberSecurity presentation for basic knowledge about this topic
CyberSecurity presentation for basic knowledge about this topic
 
Type of Malware and its different analysis and its types !
Type of Malware and its different analysis and its types  !Type of Malware and its different analysis and its types  !
Type of Malware and its different analysis and its types !
 
Malware Hunter: Building an Intrusion Detection System (IDS) to Neutralize Bo...
Malware Hunter: Building an Intrusion Detection System (IDS) to Neutralize Bo...Malware Hunter: Building an Intrusion Detection System (IDS) to Neutralize Bo...
Malware Hunter: Building an Intrusion Detection System (IDS) to Neutralize Bo...
 
An email worm vaccine architecture
An email worm vaccine architectureAn email worm vaccine architecture
An email worm vaccine architecture
 
Recipient Activated Malware Diffusion
Recipient Activated Malware DiffusionRecipient Activated Malware Diffusion
Recipient Activated Malware Diffusion
 
Modern Malware and Threats
Modern Malware and ThreatsModern Malware and Threats
Modern Malware and Threats
 
Trojan horse and salami attack
Trojan horse and salami attackTrojan horse and salami attack
Trojan horse and salami attack
 
A review botnet detection and suppression in clouds
A review botnet detection and suppression in cloudsA review botnet detection and suppression in clouds
A review botnet detection and suppression in clouds
 
5 worms and other malware
5   worms and other malware5   worms and other malware
5 worms and other malware
 
L N Yadav Cyber SECURITY.ppt
L N Yadav Cyber SECURITY.pptL N Yadav Cyber SECURITY.ppt
L N Yadav Cyber SECURITY.ppt
 
L N Yadav Cyber SECURITY2.ppt
L N Yadav Cyber SECURITY2.pptL N Yadav Cyber SECURITY2.ppt
L N Yadav Cyber SECURITY2.ppt
 
A REVIEW ON DDOS PREVENTION AND DETECTION METHODOLOGY
A REVIEW ON DDOS PREVENTION AND DETECTION METHODOLOGYA REVIEW ON DDOS PREVENTION AND DETECTION METHODOLOGY
A REVIEW ON DDOS PREVENTION AND DETECTION METHODOLOGY
 
EXTERNAL - Whitepaper - How 3 Cyber ThreatsTransform Incident Response 081516
EXTERNAL - Whitepaper - How 3 Cyber ThreatsTransform Incident Response 081516EXTERNAL - Whitepaper - How 3 Cyber ThreatsTransform Incident Response 081516
EXTERNAL - Whitepaper - How 3 Cyber ThreatsTransform Incident Response 081516
 
Chapter 2 konsep dasar keamanan
Chapter 2 konsep dasar keamananChapter 2 konsep dasar keamanan
Chapter 2 konsep dasar keamanan
 
Types of attack -Part3 (Malware Part -2)
Types of attack -Part3 (Malware Part -2)Types of attack -Part3 (Malware Part -2)
Types of attack -Part3 (Malware Part -2)
 
computer virus ppt.pptx
computer virus ppt.pptxcomputer virus ppt.pptx
computer virus ppt.pptx
 

Mehr von Ishraq Al Fataftah

Mehr von Ishraq Al Fataftah (6)

Edge detection
Edge detectionEdge detection
Edge detection
 
Peer to-peer mobile payments
Peer to-peer mobile paymentsPeer to-peer mobile payments
Peer to-peer mobile payments
 
Publish subscribe model overview
Publish subscribe model overviewPublish subscribe model overview
Publish subscribe model overview
 
Requirement engineering evaluation
Requirement engineering evaluationRequirement engineering evaluation
Requirement engineering evaluation
 
Packet sniffing in switched LANs
Packet sniffing in switched LANsPacket sniffing in switched LANs
Packet sniffing in switched LANs
 
Presentation skills
Presentation skillsPresentation skills
Presentation skills
 

Kürzlich hochgeladen

Driving Behavioral Change for Information Management through Data-Driven Gree...
Driving Behavioral Change for Information Management through Data-Driven Gree...Driving Behavioral Change for Information Management through Data-Driven Gree...
Driving Behavioral Change for Information Management through Data-Driven Gree...Enterprise Knowledge
 
Automating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps ScriptAutomating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps Scriptwesley chun
 
Advantages of Hiring UIUX Design Service Providers for Your Business
Advantages of Hiring UIUX Design Service Providers for Your BusinessAdvantages of Hiring UIUX Design Service Providers for Your Business
Advantages of Hiring UIUX Design Service Providers for Your BusinessPixlogix Infotech
 
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, AdobeApidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobeapidays
 
GenAI Risks & Security Meetup 01052024.pdf
GenAI Risks & Security Meetup 01052024.pdfGenAI Risks & Security Meetup 01052024.pdf
GenAI Risks & Security Meetup 01052024.pdflior mazor
 
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptxHampshireHUG
 
GenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day PresentationGenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day PresentationMichael W. Hawkins
 
2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...Martijn de Jong
 
presentation ICT roal in 21st century education
presentation ICT roal in 21st century educationpresentation ICT roal in 21st century education
presentation ICT roal in 21st century educationjfdjdjcjdnsjd
 
The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024Rafal Los
 
What Are The Drone Anti-jamming Systems Technology?
What Are The Drone Anti-jamming Systems Technology?What Are The Drone Anti-jamming Systems Technology?
What Are The Drone Anti-jamming Systems Technology?Antenna Manufacturer Coco
 
AWS Community Day CPH - Three problems of Terraform
AWS Community Day CPH - Three problems of TerraformAWS Community Day CPH - Three problems of Terraform
AWS Community Day CPH - Three problems of TerraformAndrey Devyatkin
 
Tech Trends Report 2024 Future Today Institute.pdf
Tech Trends Report 2024 Future Today Institute.pdfTech Trends Report 2024 Future Today Institute.pdf
Tech Trends Report 2024 Future Today Institute.pdfhans926745
 
Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024The Digital Insurer
 
Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tata AIG General Insurance Company - Insurer Innovation Award 2024Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tata AIG General Insurance Company - Insurer Innovation Award 2024The Digital Insurer
 
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemkeProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemkeProduct Anonymous
 
Artificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and MythsArtificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and MythsJoaquim Jorge
 
Scaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organizationScaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organizationRadu Cotescu
 
Understanding Discord NSFW Servers A Guide for Responsible Users.pdf
Understanding Discord NSFW Servers A Guide for Responsible Users.pdfUnderstanding Discord NSFW Servers A Guide for Responsible Users.pdf
Understanding Discord NSFW Servers A Guide for Responsible Users.pdfUK Journal
 
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...Drew Madelung
 

Kürzlich hochgeladen (20)

Driving Behavioral Change for Information Management through Data-Driven Gree...
Driving Behavioral Change for Information Management through Data-Driven Gree...Driving Behavioral Change for Information Management through Data-Driven Gree...
Driving Behavioral Change for Information Management through Data-Driven Gree...
 
Automating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps ScriptAutomating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps Script
 
Advantages of Hiring UIUX Design Service Providers for Your Business
Advantages of Hiring UIUX Design Service Providers for Your BusinessAdvantages of Hiring UIUX Design Service Providers for Your Business
Advantages of Hiring UIUX Design Service Providers for Your Business
 
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, AdobeApidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
 
GenAI Risks & Security Meetup 01052024.pdf
GenAI Risks & Security Meetup 01052024.pdfGenAI Risks & Security Meetup 01052024.pdf
GenAI Risks & Security Meetup 01052024.pdf
 
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
 
GenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day PresentationGenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day Presentation
 
2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...
 
presentation ICT roal in 21st century education
presentation ICT roal in 21st century educationpresentation ICT roal in 21st century education
presentation ICT roal in 21st century education
 
The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024
 
What Are The Drone Anti-jamming Systems Technology?
What Are The Drone Anti-jamming Systems Technology?What Are The Drone Anti-jamming Systems Technology?
What Are The Drone Anti-jamming Systems Technology?
 
AWS Community Day CPH - Three problems of Terraform
AWS Community Day CPH - Three problems of TerraformAWS Community Day CPH - Three problems of Terraform
AWS Community Day CPH - Three problems of Terraform
 
Tech Trends Report 2024 Future Today Institute.pdf
Tech Trends Report 2024 Future Today Institute.pdfTech Trends Report 2024 Future Today Institute.pdf
Tech Trends Report 2024 Future Today Institute.pdf
 
Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024
 
Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tata AIG General Insurance Company - Insurer Innovation Award 2024Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tata AIG General Insurance Company - Insurer Innovation Award 2024
 
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemkeProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
 
Artificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and MythsArtificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and Myths
 
Scaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organizationScaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organization
 
Understanding Discord NSFW Servers A Guide for Responsible Users.pdf
Understanding Discord NSFW Servers A Guide for Responsible Users.pdfUnderstanding Discord NSFW Servers A Guide for Responsible Users.pdf
Understanding Discord NSFW Servers A Guide for Responsible Users.pdf
 
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
 

Malicious traffic

  • 2. Agenda  Introduction.  What is Malicious traffic.  Malicious traffic types.  Malicious traffic detection and prevention.  Conclusion.
  • 3. Introduction  As the internet become more mature, management of its resources to provide guaranteed services is crucial.  The success of the Internet has increased its vulnerability to misuse and performance problems.
  • 4. Introduction  It has been frequently abused by people mostly with hostile intentions.  We have been under various kinds of attacks such as viruses, worms and commonly a bunch of spam mails every day.
  • 6. Malicious Traffic  It is hard to detect and distinguish malicious packet and legitimate packets in the traffic.  The behavior of Internet traffic is very far from being regular.  Presents large variations in its throughput at all scales.
  • 7. Malicious Traffic  Any traffic anomalies that occur from hardware or software failures to internet packets with maliciously modified options.  Generated from what is called botnets.
  • 9. Malicious Traffic  Monitoring the flow of packets.  Malicious traffic usually exhausts the legitimate resources by sending a lot of traffic.  Monitoring traffic targeting unused addresses in the network.
  • 10. Malicious Traffic Types  Scanners.  Worms.  Malicious Spam.  Backscatters.  DOS, DDOS.
  • 11. Scanners  Single source.  Strikes the same port on many machines.  Different ports on the same machine.  Generates a lot of flows.
  • 12. Worms  Self-replicating virus that does not alter files but resides in active memory and duplicates itself.  CodeRed worm infected 395,000 computers and resulted in approximately $2.6 billion in damage.  Results in an increase in service activity, especially if service is law traffic.
  • 13. Worms MyTob Worm, 2005  Copies itself as %System%msnmsgs.exe  Adds the value: “MSN” = “msnmsgs.exe” to IRC Server registry: HKEY_LOCAL_MACHINESoftwareMicrosoftWindowsCurrentVersionRun HKEY_LOCAL_MACHINESoftwareMicrosoftWindowsCurrentVersion RunServices HKEY_CURRENT_USERSOFTWAREMicrosoftWindowsCurrentVersionRun HKEY_CURRENT_USERSoftwareMicrosoftOLE HKEY_CURRENT_USERSYSTEMCurrentControlSetControlLsa  W32.Mytob@mm runs every time Windows starts User Zone Server Zone
  • 14. Malicious Spam  Spamming is flooding the network with a huge amount of unsolicited email messages to force people to receive them.  Contains malware or links to malicious sites.
  • 15. Backscatter  Email bounces for emails that a person didn’t send.  Spammer is spoofing the Reply-to field in email.  When sent to email server, it is bounces to the reply-to address rather than the sender.  Used to overcome spam filters and in DOS attacks.
  • 16. DOS, DDOS  Generate a huge amount of adverse traffic to a target server to make it unavailable.  Attempt to exhaust the resources of the victim.  They are difficult to detect and prevent.  DDOS attacks are simultaneously launched from several sources destined to the same target.
  • 18. Malicious traffic Detection and Prevention  Anomaly detection techniques.  Signature-scan techniques.  Intrusion detection and prevention systems.  QoS metrics.  Tools such as Snort.  Network filters such as ACLs.  Honeypots.
  • 19. Anomaly detection techniques  Differentiates between normal and malicious traffic by:  Studying the normal behavior of users, resources.  Create patterns for these activities.  Any behavior that deviates from this pattern is considered malicious.
  • 20. Signature-scan techniques  Uses a database that store signatures.  Passive scan for network traffic, any patterns match these stored signatures are considered malicious traffic.  Effective for known attacks.
  • 21. Intrusion detection and prevention systems  Software or hardware that is designed to detect and prevent any malicious attack or activity on the network.  Monitor the network traffic.  Analyze any suspicious event.  Log these events and report them to the network administrator for actions.
  • 22. QoS metrics  Studying the behavior of the network traffic under normal and malicious attacks.  Extracting parameters from network traffic.
  • 23. Snort  Open source tool that is used in intrusion detection systems.  Real time analysis on the network traffic.  Intrusion detection system to monitor the traffic, analyzes it and inform the network administrator for suspicious activities.
  • 24. ACLs  Installed in routers and used to match packet headers against a pre-defined list of rules and takes pre-defined actions on any matching packets.
  • 25. Honeypots “a security resource whose value lies in being probed, attacked or compromised”  Any attempt to interact with honeypots incurs a malicious activity or attack.
  • 26. Conclusion  Malicious traffic is any traffic anomalies occurs from failure in traffic packets that is intentionally modified for malicious acts.  By studying malicious attacks we can obtain better understanding of malicious traffic and how to detect and prevent these attacks.  An increase in the awareness toward the importance of security will help in mitigation against internet misuse.

Hinweis der Redaktion

  1. threats may range from simple to severe functional and financial damage to the network infrastructure. Adding the legal perspective, these threats should be clearly and carefully identified, analyzed and managed.
  2. data is encapsulated in packets.
  3. Most flows are roughly symmetric at the packet levelWhenever a packet is sent, a packet is received within some reasonable interval (round trip time)This can me measured (and enforced) at the edge router inexpensively
  4. these botnets launch malicious traffic that attacks network hosts and internet service provider (ISPS).
  5. Malicious traffic can be detected by monitoring the network traffic using packet monitoring tools and studying any up normal or suspected behavior in the network. By monitoring the flow of packets, maliciously changed packets can be identified and infected computers can be determined based on its signature. In addition, malicious traffic usually exhausts the legitimate resources by sending a lot of traffic to halt its functionality. Another measurement can be by monitoring traffic targeting unused addresses in the network [3]. Unused addresses should expect a very limited load of traffic not mentioning that no device should be connected to it.
  6. Among all attacks, the denial-of-service (DoS) attack is one ofthe attacks rather difficult to detect and prevent since they exploitregular services, and overwhelm such services with tremendousmalicious traffic.
  7. Anomaly-detection first establishes a normal behavior pattern forusers, programs or resources in the system, and then looks for deviationfrom this behavior.signature-scan techniques passively monitor traffic seen on a network and detect an attack when patterns within the packet match predefined signatures in a database.They are a resource that has no authorized activity, they do not have any production value. Theoreticlly, a honeypot should see no traffic because it has no legitimate activity. This means any interaction with a honeypot is most likely unauthorized or malicious activity. Any connection attempts to a honeypot are most likely a probe, attack, or compromise. Snort’s open source network-based intrusion detection system (NIDS) has the ability to perform real-time traffic analysis and packet logging on Internet Protocol (IP) networks. Snort can be configured in three main modes: sniffer, packet logger, and network intrusion detection. Snort can be configured in three main modes: sniffer, packet logger, and network intrusion detection. the program will monitor network traffic and analyze it against a ruleset defined by the user. The program will then perform a specific action based on what has been identified