TY - GEN
T1 - Detecting unknown worms using randomness check
AU - Park, Hyundo
AU - Lee, Heejo
PY - 2006
Y1 - 2006
N2 - From the appearance of CodeRed and SQL Slammer worm, we have learned that the early detection of worm epidemics is important to reduce the damage caused by their outbreak. One prominent characteristic of Internet worms is to choose next targets randomly by using a random generator. In this paper, we propose a new worm detection mechanism by checking the random distribution of destination addresses. Our mechanism generates the traffic matrix and checks the value of rank of it to detect the spreading of Internet worms. From the fact that a random binary matrix holds a high value of rank, ADUR (Anomaly Detection Using Randomness check) is proposed for detecting unknown worms based on the rank of the traffic matrix. From the experiments on various environments, we show that the ADUR mechanism effectively detects the spread of new worms in an early stage, even when there is only one host infected in a monitoring network.
AB - From the appearance of CodeRed and SQL Slammer worm, we have learned that the early detection of worm epidemics is important to reduce the damage caused by their outbreak. One prominent characteristic of Internet worms is to choose next targets randomly by using a random generator. In this paper, we propose a new worm detection mechanism by checking the random distribution of destination addresses. Our mechanism generates the traffic matrix and checks the value of rank of it to detect the spreading of Internet worms. From the fact that a random binary matrix holds a high value of rank, ADUR (Anomaly Detection Using Randomness check) is proposed for detecting unknown worms based on the rank of the traffic matrix. From the experiments on various environments, we show that the ADUR mechanism effectively detects the spread of new worms in an early stage, even when there is only one host infected in a monitoring network.
UR - http://www.scopus.com/inward/record.url?scp=33845520684&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=33845520684&partnerID=8YFLogxK
U2 - 10.1007/11919568_77
DO - 10.1007/11919568_77
M3 - Conference contribution
AN - SCOPUS:33845520684
SN - 3540485635
SN - 9783540485636
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 775
EP - 784
BT - Information Networking
PB - Springer Verlag
T2 - International Conference on Information Networking, ICOIN 2006
Y2 - 16 January 2006 through 19 January 2006
ER -