A Petri Net and LSTM Hybrid Approach for Intrusion Detection Systems in Enterprise Networks.

Intrusion Detection Systems (IDSs) are a crucial component of modern corporate firewalls. The ability of IDS to identify malicious traffic is a powerful tool to prevent potential attacks and keep a corporate network secure. In this context, Machine Learning (ML)-based methods have proven to be very effective for attack identification.

On-line verification of initial-state opacity by Petri nets and integer linear programming.

This paper deals with a problem related to the observability of discrete event systems: the initial-state opacity. Given a set of system states (the secret), a system observation is called initial-state opaque if an agent (named intruder), who can partially observe the system, cannot determine whether the set of initial states consistent with an event sequence is included in the secret. Such a character can describe security problems in cyber-infrastructures, such as Internet and mobile communication networks or national defense service systems.