Results 41 to 50 of about 1,173,800 (295)

On the Feasibility of Adversarial Sample Creation Using the Android System API

Information, 2020
Due to its popularity, the Android operating system is a critical target for malware attacks. Multiple security efforts have been made on the design of malware detection systems to identify potentially harmful applications.
Fabrizio Cara, Michele Scalas, Giorgio Giacinto, Davide Maiorca   +3 more
doaj   +1 more source

Deep Reinforcement Adversarial Learning Against Botnet Evasion Attacks

IEEE Transactions on Network and Service Management, 2020
As cybersecurity detectors increasingly rely on machine learning mechanisms, attacks to these defenses escalate as well. Supervised classifiers are prone to adversarial evasion, and existing countermeasures suffer from many limitations. Most solutions degrade performance in the absence of adversarial perturbations; they are unable to face novel attack ...
Apruzzese G., Andreolini M., Marchetti M., Venturi A., Colajanni M.   +4 more
openaire   +3 more sources

Attacks and Evasion in Wireless Security Network

International Journal of Advanced Research in Science, Communication and Technology, 2022
Wireless Sensor Network is a vast topic with a lot of aspects. As Users of WSN are increasing Day by Day the threats of WSN are also increasing. The Architectural structure of WSN is very Unstable and therefore its Transmission is very Vulnerable. In this Study it is Evaluated the threats and Evasion from various type of Attacks. Due to the limitations
null Darshan Tumaney, null Miss. Nidhi Poonia   +1 more
openaire   +1 more source

Testing the theory of immune selection in cancers that break the rules of transplantation [PDF]

, 2009
Modification of cancer cells likely to reduce their immunogenicity, including loss or down-regulation of MHC molecules, is now well documented and has become the main support for the concept of immune surveillance.
A Garcia-Lora, A Scheffold, AF Setiadi, AM Pearse, Ariberto Fassati, B Comin-Anduix, B Kavanagh, B Muller-Hilke, C Murgia, CA Rebbeck, CC Chang, CL Yauk, CM Gonzalez, CM Koebel, CY Lin, D Cohen, D Cohen, D Cohen, D Cohen, E Ambrosino, E Klein, E Mozos, ED Carosella, ED Carosella, EK Geissler, FR Depontieu, G Willimsky, GD Snell, GP Dunn, GP Dunn, GP Dunn, H Ikeda, H McCallum, H Wajant, HV Siddle, HV Siddle, I Kryczek, J Galon, J Hori, J Perez, J Zhou, K Kretschmer, K Masuda, K Milne, KJ Malmberg, KL Wright, L Tian, L Vago, L Yip, M Bleakley, M Campoli, M Gerloni, M Mammolenti, M Mehling, M Novinski, M Pierobon, M Shackleton, M Thornley, MA Cheever, MN Scherer, N Mitchison, N Schwinn, N. Avrion Mitchison, NA Mitchison, NM Moutsopoulos, P Jimenez, PC Chou, R Mendez, R Mendez, R Uppaluri, S Lob, S Verheyden, SM Kang, SR Choudhury, T Akagi, T Cabrera, T Isoda, T Marchal, T Rodriguez, TJ Yang, TJ Yang, W Reith, YC Chang, YW Hsiao, YW Hsiao   +84 more
core   +2 more sources

Initiation and spread of escape waves within animal groups [PDF]

, 2015
The exceptional reactivity of animal collectives to predatory attacks is thought to be due to rapid, but local, transfer of information between group members. These groups turn together in unison and produce escape waves.
Buhl, Jerome, Herbert-Read, James, Hu, Feng, Sumpter, David, Ward, Ashley   +4 more
core   +2 more sources

Evading Classifiers by Morphing in the Dark

, 2017
Learning-based systems have been shown to be vulnerable to evasion through adversarial data manipulation. These attacks have been studied under assumptions that the adversary has certain knowledge of either the target model internals, its training ...
Chang, Ee-Chien, Dang, Hung, Huang, Yue
core   +1 more source

Staphylococcus aureus uses the ArlRS and MgrA cascade to regulate immune evasion during skin infection

Cell Reports, 2021
Summary: Skin is one of the most common sites of host immune response against Staphylococcus aureus infection. Here, through a combination of in vitro assays, mouse models, and intravital imaging, we find that S.
Jakub M. Kwiecinski, Rachel M. Kratofil, Corey P. Parlet, Bas G.J. Surewaard, Paul Kubes, Alexander R. Horswill   +5 more
doaj   +1 more source

Evasion Attacks against Machine Learning at Test Time [PDF]

, 2013
In this paper, in 2013, we were the first to introduce the notion of evasion attacks (adversarial examples) created with high confidence (instead of minimum-distance misclassifications), and the notion of surrogate learners (substitute models). These two concepts are now widely re-used in developing attacks against deep networks (even if not always ...
BIGGIO, BATTISTA, CORONA, IGINO, MAIORCA, DAVIDE, Nelson B, Srndic N, Laskov P, GIACINTO, GIORGIO, ROLI, FABIO   +7 more
openaire   +3 more sources

Detecting Backdoor Attacks via Class Difference in Deep Neural Networks

IEEE Access, 2020
A backdoor attack implies that deep neural networks misrecognize data that have a specific trigger by additionally training the malicious training data, including the specific trigger to the deep neural network model.
Hyun Kwon
doaj   +1 more source

The immune evasion ability of Delta variant is comparable to that of Beta variant in South Africa

BMC Public Health, 2023
Background The high immune evasion ability of SARS-COV-2 Omicron variant surprised the world and appears to be far stronger than any previous variant.
Daihai He, Boqiang Chen, Shi Zhao, Lewi Stone   +3 more
doaj   +1 more source