Social networks threats
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SOCIAL NETWORKS THREATS AND TRENDS ALEXANDRU CATALIN COSOI ALEXANDRU CATALIN COSOI HEAD OF ONLINE THREATS HEAD OF ONLINE THREATS [email protected] [email protected]
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Transcript of Social networks threats
SOCIAL NETWORKSTHREATS AND TRENDS
ALEXANDRU CATALIN COSOIALEXANDRU CATALIN COSOIHEAD OF ONLINE THREATSHEAD OF ONLINE THREATS
[email protected]@BITDEFENDER.COM
Viruses
Email worms
Exploit worms
Rootkits
Backdoor Trojans
Sources of Attack
RemovableMedia
Instant Messaging
Clients
Types of Threats Proliferation Mediums
Email AttachmentsScript Kiddies
Threat landscape – Past Threat landscape – Past
2
3
Viruses
Email worms
Exploit worms
P2P worms
IM worms
Rootkits
Backdoor Trojans
Spyware
Adware
Greyware
Sources of Attack
Legitimate, Compromised Multi-media Websites
RemovableMedia
MobileDevices
Public WiFi Networks
Instant Messaging
Clients
Hackers
Web 2.0 Applications
Types of Threats
SPAM Email Attachments
Legitimate Businesses
P2P NetworksPhishingOrganized Crime
Foreign Governments
THREAT LANDSCAPE – PRESENT THREAT LANDSCAPE – PRESENT
Proliferation Mediums
What Urls Am I Talking About?What Urls Am I Talking About?
Where Do Urls Come From?Where Do Urls Come From?
SLIDE 2
Web 2.0Web 2.0
Nice Blue Birdie
SLIDE 3
TwitterTwitter
• Huge growth in the last years• Approximately 7 mil tweets / hour• In Sept 2008, Twitter had a growth of 343%
o (sept 2007 vs sept 2008. according to Nielsen-Online)
In Feb 2009, the growth was of 1382% (feb 2008 – feb 2009, according to Nielsen-Online)
SLIDE 4
Time on Site Time on Site
SLIDE 5
Types of Twitter SpamTypes of Twitter Spam
• Following Spam• Tweet Spam• Direct Message Spam• Trending Subject Spam• Reply/Trackback Spam• ReTweet Spam
SLIDE 16
Scale Free Networks Scale Free Networks
Social Connections are not random.Nodes with many connections will attract new connections easier than nodes with fewer connections
“The rich get richer and the poor get poorer”. Proverb provided by wikipedia
SLIDE 24
Imagine a malware URL from these guysImagine a malware URL from these guys
SLIDE 7
Facebook in NumbersFacebook in Numbers
• More Then 400 million active users• 5.14 % from total word population• 20.18% from worldwide internet users• Over 700 000 bussiness
SLIDE 8
Social Games on FacebookSocial Games on Facebook
SLIDE 9
Facebook’s “Russian Bride”Facebook’s “Russian Bride”
SLIDE 10
Facebook E-mail SpamFacebook E-mail Spam
SLIDE 12
Haiti Hoaxes and scamsHaiti Hoaxes and scams
SLIDE 13
Phishing for FacebookPhishing for Facebook
SLIDE 14
Phishing & Malware on FacebookPhishing & Malware on Facebook
• Facebook blocked an important number of phishing and malware attacks
• Facebook worms use short, provocative and catchy messages
The ads worm (this Tuesday)The ads worm (this Tuesday)
The ads worm (this Tuesday)The ads worm (this Tuesday)
The ads worm (this Tuesday)The ads worm (this Tuesday)
SLIDE 15
User AcceptanceUser Acceptance
• To see how many people accept connect with unknown users
• To see how many people follow unknown links from unknown users
• To see how many people really block unknown connections request
• 3 honeypot users: one profile without picture and containing as few details as possible(1st profile), another profile with a picture and a few details(2nd profile) and yet another profile with a large amount of details and pictures(3rd profile).
SLIDE 16
User Acceptance – SetupUser Acceptance – Setup
• 3 honeypot users• one profile without picture and containing as few
details as possible• one profile with a picture and a few details• one profile with a large amount of details and
pictures
SLIDE 18
User Acceptance - ResultsUser Acceptance - Results
The august study – user acceptanceThe august study – user acceptance
The august study – personal information lossThe august study – personal information loss
The august study – confidential information lossThe august study – confidential information loss
SafegoSafego
