Anomaly Detection Using System Call Sequence Sets.

This paper discusses our research in developing a generalized and systematic method for anomaly detection. The key ideas are to represent normal program behaviour using system call frequencies and to incorporate probabilistic techniques for classification to detect anomalies and intrusions. Using experiments on the sendmail system call data, we demonstrate that concise and accurate classifiers can be constructed to detect anomalies. An overview of the approach that we have implemented is provided.

Process profiling using frequencies of system calls

In this paper we discuss our research in developing general and systematic method for anomaly detection. The key ideas are to represent normal program behaviour using system call frequencies and to incorporate probabilistic techniques for classification to detect anomalies and intrusions. Using experiments on the sendmail system call data, we demonstrate that we can construct concise and accurate classifiers to detect anomalies. We provide an overview of the approach that we have implemented

Detecting Motifs in System Call Sequences

The search for patterns or motifs in data represents an area of key interest to many researchers. In this paper we present the Motif Tracking Algorithm, a novel immune inspired pattern identification tool that is able to identify unknown motifs which repeat within time series data. The power of the algorithm is derived from its use of a small number of parameters with minimal assumptions. The algorithm searches from a completely neutral perspective that is independent of the data being analysed and the underlying motifs. In this paper the motif tracking algorithm is applied to the search for patterns within sequences of low level system calls between the Linux kernel and the operating system’s user space. The MTA is able to compress data found in large system call data sets to a limited number of motifs which summarise that data. The motifs provide a resource from which a profile of executed processes can be built. The potential for these profiles and new implications for security research are highlighted. A higher level system call language for measuring similarity between patterns of such calls is also suggested.

An Alternative Approach To Computer System Security Monitoring And Enhancement Through System Call Sequence Analysis

Modern computer systems are plagued with stability and security problems: applications lose data, web servers are hacked, and systems crash under heavy load. Many of these problems or anomalies arise from rare program behavior caused by attacks or errors. A substantial percentage of the web-based attacks are due to buffer overflows. Many methods have been devised to detect and prevent anomalous situations that arise from buffer overflows. The current state-of-art of anomaly detection systems is relatively primitive and mainly depend on static code checking to take care of buffer overflow attacks. For protection, Stack Guards and I-leap Guards are also used in wide varieties.This dissertation proposes an anomaly detection system, based on frequencies of system calls in the system call trace. System call traces represented as frequency sequences are profiled using sequence sets. A sequence set is identified by the starting sequence and frequencies of specific system calls. The deviations of the current input sequence from the corresponding normal profile in the frequency pattern of system calls is computed and expressed as an anomaly score. A simple Bayesian model is used for an accurate detection.Experimental results are reported which show that frequency of system calls represented using sequence sets, captures the normal behavior of programs under normal conditions of usage. This captured behavior allows the system to detect anomalies with a low rate of false positives. Data are presented which show that Bayesian Network on frequency variations responds effectively to induced buffer overflows. It can also help administrators to detect deviations in program flow introduced due to errors.

Status of Young Women in the Juvenile Justice System Preliminary Data, 2007

Young women involved in the juvenile justice system present with characteristics and experiences that differentiate them from their male counterparts. As such, the juvenile justice system in Iowa must consider these factors if it is to effectively and efficiently impact recidivism and rehabilitation.

Juvenile Justice System Planning Data Iowa’s Juvenile Justice Advisory Council Three Year Comprehensive Plan with Additional Juvenile Justice System Information, November 2015

This report provides key juvenile justice system planning data, most of which are taken from Iowa’s 2015 Juvenile Justice and Delinquency Prevention Act Three Year Plan. The data and related descriptions serve as an overview of decision making for major juvenile justice system processing points, and also assist state and local officials with policy and practice. Included in the report are school discipline data and data related to juvenile in the adult criminal justice system.

Juvenile Justice System Planning Data Iowa’s Juvenile Justice Advisory Council Three Year Comprehensive Plan with Additional Juvenile Justice System Information, November 2015

This report provides key juvenile justice system planning data, most of which are taken from Iowa’s 2015 Juvenile Justice and Delinquency Prevention Act Three Year Plan. The data and related descriptions serve as an overview of decision making for major juvenile justice system processing points, and also assist state and local officials with policy and practice. Included in the report are school discipline data and data related to juvenile in the adult criminal justice system.

An Italian to Catalan RBMT system reusing data from existing language pairs

This paper presents an Italian to CatalanRBMT system automatically built bycombining the linguistic data of theexisting pairs Spanish-Catalan andSpanish-Italian. A lightweight manualpostprocessing is carried out in order tofix inconsistencies in the automaticallyderived dictionaries and to add very frequentwords that are missing accordingto a corpus analysis. The system isevaluated on the KDE4 corpus and outperformsGoogle Translate by approximatelyten absolute points in terms ofboth TER and GTM.

Sliding Mode Control for Active Suspension System with Data Acquisition Delay

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

National accident sampling system crashworthiness data system 1988-1990.

Mode of access: Internet.

National accident sampling system crashworthiness data system 1991-1993.

Mode of access: Internet.

National automotive sampling system crashworthiness data system 1992-1994.

Mode of access: Internet.

National automotive sampling system crashworthiness data system 1993-1995.

Mode of access: Internet.