Cybersecurity: Continued attention needed to protect our nation's critical infrastructure: Hearings before the Subcommittee on Oversight and Investigations, Committee on Energy and Commerce, House of Representatives, 112th Cong. (2011)(Statement of Gregory C. Wilshusen). Retrieved from https://www.hsdl.org/?view&did=682424
"Increasing computer interconnectivity, such as the growth of the Internet, has revolutionized the way our government, our nation, and much of the world communicate and conduct business. However, this widespread interconnectivity poses significant risks to the government's and the nation's computer systems, and to the critical infrastructures they support. These critical infrastructures include systems and assets--both physical and virtual--that are essential to the nation's security, economic prosperity, and public health, such as financial institutions, telecommunications networks, and energy production and transmission facilities. Because most of these infrastructures are owned by the private sector, establishing effective public-private partnerships is essential to securing them from pervasive cyber-based threats. Federal law and policy call for federal entities, such as the Department of Homeland Security (DHS), to work with private-sector partners to enhance the physical and cyber security of these critical infrastructures."
Kumar, P., & Selvakumar, S. (2011). Distributed denial of service attack detection using an ensemble of neural classifier. Computer Communications, 34(11), 1328-1341. doi:10.1016/j.comcom.2011.01.012 (full text available in the Science Direct database)
“The vulnerabilities in the Communication (TCP/IP) protocol stack and the availability of more sophisticated attack tools breed in more and more network hackers to attack the network intentionally or unintentionally, leading to Distributed Denial of Service (DDoS) attack. The DDoS attacks could be detected using the existing machine learning techniques such as neural classifiers. These classifiers lack generalization capabilities which result in less performance leading to high false positives. This paper evaluates the performance of a comprehensive set of machine learning algorithms for selecting the base classifier using the publicly available KDD Cup dataset. Based on the outcome of the experiments, Resilient Back Propagation (RBP) was chosen as base classifier for our research. The improvement in performance of the RBP classifier is the focus of this paper. Our proposed classification algorithm, RBPBoost, is achieved by combining ensemble of classifier outputs and Neyman Pearson cost minimization strategy, for final classification decision. Publicly available datasets such as KDD Cup, DARPA 1999, DARPA 2000, and CONFICKER were used for the simulation experiments. RBPBoost was trained and tested with DARPA, CONFICKER, and our own lab datasets. Detection accuracy and Cost per sample were the two metrics evaluated to analyze the performance of the RBPBoost classification algorithm. From the simulation results, it is evident that RBPBoost algorithm achieves high detection accuracy (99.4%) with fewer false alarms and outperforms the existing ensemble algorithms. RBPBoost algorithm outperforms the existing algorithms with maximum gain of 6.6% and minimum gain of 0.8%.”
The role of small business in strengthening cybersecurity efforts in the United States: Hearing before the Senate Committee on Small Business Entrepreneurship, 112th Cong. (2011) (testimony of Gregory von Lehmen). Retrieved from http://www.dnet.congress.org/congressorg/webreturn/?url=http://sbc.senate.gov (NOTE: click on Dr. von Lehmen’s name to obtain full text access to his testimony.)
Zetter, K. (2011, July 11). How digital detectives deciphered Stuxnet, the most menacing malware in history. Wired.com. Retrieved from http://www.wired.com/threatlevel/2011/07/how-digital-detectives-deciphered-stuxnet/all/1
“On the other side of the globe, a 52-year-old German named Ralph Langner was reading Symantec’s post with fascination. Langner had little interest in Windows systems or internet viruses — he doesn’t even have an internet connection at home. But he specializes in the obscure science of industrial-control-system security. It’s the only thing his three-man, boutique firm does. So he was particularly intrigued when Symantec wrote that Stuxnet was sabotaging PLCs…”
