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Malware-Aware Processors: A Framework for Efficient Online Malware Detection

by Meltem Ozsoy, Caleb Donovick, Iakov Gorelik, Nael Abu-ghazaleh, Dmitry Ponomarev
"... Security exploits and ensuant malware pose an increasing challenge to computing systems as the variety and complexity of attacks continue to increase. In response, software-based malware detection tools have grown in complexity, thus mak-ing it computationally difficult to use them to protect system ..."
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in the following ways: (1) We define and explore the use of sub-semantic features for online detection of mal-ware. (2) We explore hardware implementations and show that simple classifiers appropriate for such implementations can effectively classify malware. We also study different classifiers, develop

Machine

by Guido Schwenk, Technische Universität Berlin, Konrad Rieck, Technische Universität Berlin
"... Abstract—The infection of computer systems with malicious software is an enduring problem of computer security. Avoiding an infection in the first place is a hard task, as computer systems are often vulnerable to a multitude of attacks. However, to explore and control an infected system, an attacker ..."
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, it significantly improves on state-of-the-art methods and hardens networks against malware proliferation. This capability is demonstrated in an evaluation with 90 days of web traffic, where DUMONT uncovers the communication of malware, tunnels and backdoors with few false alarms.

Security Evaluation of Support Vector Machines in Adversarial Environments

by Giorgio Fumera, Giorgio Giacinto, Fabio Roli, Battista Biggio, Igino Corona, Davide Maiorca, Giorgio Fumera, Giorgio Giacinto, Fabio Roli, Blaine Nelson, Benjamin I. P. Rubinstein
"... Abstract Support Vector Machines (SVMs) are among the most popular classifi-cation techniques adopted in security applications like malware detection, intrusion detection, and spam filtering. However, if SVMs are to be incorporated in real-world security systems, they must be able to cope with attac ..."
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of the security of machine-learning systems. Second, according to our framework, we demonstrate the feasibility of evasion, poisoning and privacy at-tacks against SVMs in real-world security problems. For each attack technique, we evaluate its impact and discuss whether (and how) it can be countered through

BDRS PRICE DESCRIPTOR,

by unknown authors
"... This report focuses on the evidence about the health.consequences of smoking for women, and is intended to serve.the public health and medical communities as 'a unified source of existing scientific research. The major issues about tobacco use and women's health are examined, including tre ..."
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This report focuses on the evidence about the health.consequences of smoking for women, and is intended to serve.the public health and medical communities as 'a unified source of existing scientific research. The major issues about tobacco use and women's health are examined, including trends in consumption, biomedical evidence, and determinants of smoking ititiation, maintenance, and cessation. The biomedical aspects ofsmoking are presented in terms of mortality, morbiplity, cardiovasculaidiseases, cancer, pregnancy and infant,health,, Teptic ulcer disease, drug reactions and, interactions, food constituents, and responses to,diagnostic tests. The psychosocial and behavioraj. aspects, of smoking in women are discussed, along with the docffiented increases in- the risk of contracting lung cancer, heart,disease, or lung disease. The harmful effects of pregnant mothers smoking behaviors, are also docudented. Adhitionally, recent data are enumerated to indicate a trend of,decreasing tobacco usage among women in response to the warnings of the gavernMent, voluntary agencie, and physicrins. (Author /NRB)' DOCUMENT RESUME cc 015 465
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