APHRODITE: an Anomaly-based Architecture for False Positive Reduction

We present APHRODITE, an architecture designed to reduce false positives in network intrusion detection systems. APHRODITE works by detecting anomalies in the output traffic, and by correlating them with the alerts raised by the NIDS working on the input traffic. Benchmarks show a substantial reduction of false positives and that APHRODITE is effective also after a "quick setup", i.e. in the realistic case in which it has not been "trained" and set up optimall

ATLANTIDES: An Architecture for Alert Verification in Network Intrusion Detection Systems

We present an architecture designed for alert verification (i.e., to reduce false positives) in network intrusion-detection systems. Our technique is based on a systematic (and automatic) anomaly-based analysis of the system output, which provides useful context information regarding the network services. The false positives raised by the NIDS analyzing the incoming traffic (which can be either signature- or anomaly-based) are reduced by correlating them with the output anomalies. We designed our architecture for TCP-based network services which have a client/server architecture (such as HTTP). Benchmarks show a substantial reduction of false positives between 50% and 100%

ATLANTIDES: Automatic Configuration for Alert Verification in Network Intrusion Detection Systems

We present an architecture designed for alert verification (i.e., to reduce false positives) in network intrusion-detection systems. Our technique is based on a systematic (and automatic) anomaly-based analysis of the system output, which provides useful context information regarding the network services. The false positives raised by the NIDS analyzing the incoming traffic (which can be either signature- or anomaly-based) are reduced by correlating them with the output anomalies. We designed our architecture for TCP-based network services which have a client/server architecture (such as HTTP). Benchmarks show a substantial reduction of false positives between 50% and 100%

Poseidon: a 2-tier Anomaly-based Intrusion Detection System

We present Poseidon, a new anomaly based intrusion detection system. Poseidon is payload-based, and presents a two-tier architecture: the first stage consists of a Self-Organizing Map, while the second one is a modified PAYL system. Our benchmarks on the 1999 DARPA data set show a higher detection rate and lower number of false positives than PAYL and PHAD

Poseidon: a 2-tier Anomaly-based Network Intrusion Detection System

We present Poseidon, a new anomaly based intrusion detection system. Poseidon is payload-based, and presents a two-tier architecture: the first stage consists of a Self-Organizing Map, while the second one is a modified PAYL system. Our benchmarks on the 1999 DARPA data set show a higher detection rate and lower number of false positives than PAYL and PHAD

The HSS/SNiC : a conceptual framework for collapsing security down to the physical layer

This work details the concept of a novel network security model called the Super NIC (SNIC) and a Hybrid Super Switch (HSS). The design will ultimately incorporate deep packet inspection (DPI), intrusion detection and prevention (IDS/IPS) functions, as well as network access control technologies therefore making all end-point network devices inherently secure. The SNIC and HSS functions are modelled using a transparent GNU/Linux Bridge with the Netfilter framework

Secure Communication using Identity Based Encryption

Secured communication has been widely deployed to guarantee confidentiality and\ud integrity of connections over untrusted networks, e.g., the Internet. Although\ud secure connections are designed to prevent attacks on the connection, they hide\ud attacks inside the channel from being analyzed by Intrusion Detection Systems\ud (IDS). Furthermore, secure connections require a certain key exchange at the\ud initialization phase, which is prone to Man-In-The-Middle (MITM) attacks. In this paper, we present a new method to secure connection which enables Intrusion Detection and overcomes the problem of MITM attacks. We propose to apply Identity Based Encryption (IBE) to secure a communication channel. The key escrow property of IBE is used to recover the decryption key, decrypt network traffic on the fly, and scan for malicious content. As the public key can be generated based on the identity of the connected server and its exchange is not necessary, MITM attacks are not easy to be carried out any more. A prototype of a modified TLS scheme is implemented and proved with a simple client-server application. Based on this prototype, a new IDS sensor is developed to be capable of identifying IBE encrypted secure traffic on the fly. A deployment architecture of the IBE sensor in a company network is proposed. Finally, we show the applicability by a practical experiment and some preliminary performance measurements

CAREER: adaptive intrusion detection systems

Issued as final reportNational Science Foundation (U.S.

Post-Patch Retraining for Host-Based Anomaly Detection

Applying patches, although a disruptive activity, remains a vital part of software maintenance and defense. When host-based anomaly detection (AD) sensors monitor an application, patching the application requires a corresponding update of the sensor's behavioral model. Otherwise, the sensor may incorrectly classify new behavior as malicious (a false positive) or assert that old, incorrect behavior is normal (a false negative). Although the problem of "model drift" is an almost universally acknowledged hazard for AD sensors, relatively little work has been done to understand the process of re-training a "live" AD model --- especially in response to legal behavioral updates like vendor patches or repairs produced by a self-healing system. We investigate the feasibility of automatically deriving and applying a "model patch" that describes the changes necessary to update a "reasonable" host-based AD behavioral model ({\it i.e.,} a model whose structure follows the core design principles of existing host--based anomaly models). We aim to avoid extensive retraining and regeneration of the entire AD model when only parts may have changed --- a task that seems especially undesirable after the exhaustive testing necessary to deploy a patch