Zobrazeno 1 - 10
of 34
pro vyhledávání: '"Anwar, Afsah"'
Autor:
Abusnaina, Ahmed, Anwar, Afsah, Alshamrani, Sultan, Alabduljabbar, Abdulrahman, Jang, RhongHo, Nyang, Daehun, Mohaisen, David
The rapid growth of the Internet of Things (IoT) devices is paralleled by them being on the front-line of malicious attacks. This has led to an explosion in the number of IoT malware, with continued mutations, evolution, and sophistication. These mal
Externí odkaz:
http://arxiv.org/abs/2108.13373
Autor:
Alasmary, Hisham, Anwar, Afsah, Abusnaina, Ahmed, Alabduljabbar, Abdulrahman, Abuhamad, Mohammad, Wang, An, Nyang, DaeHun, Awad, Amro, Mohaisen, David
The Linux shell is a command-line interpreter that provides users with a command interface to the operating system, allowing them to perform a variety of functions. Although very useful in building capabilities at the edge, the Linux shell can be exp
Externí odkaz:
http://arxiv.org/abs/2103.14221
Autor:
Anwar, Afsah, Choi, Jinchun, Alabduljabbar, Abdulrahman, Alasmary, Hisham, Spaulding, Jeffrey, Wang, An, Chen, Songqing, Nyang, DaeHun, Awad, Amro, Mohaisen, David
The lack of security measures among the Internet of Things (IoT) devices and their persistent online connection gives adversaries a prime opportunity to target them or even abuse them as intermediary targets in larger attacks such as distributed deni
Externí odkaz:
http://arxiv.org/abs/2103.14217
The domain name system (DNS) is one of the most important components of today's Internet, and is the standard naming convention between human-readable domain names and machine-routable IP addresses of Internet resources. However, due to the vulnerabi
Externí odkaz:
http://arxiv.org/abs/2006.15277
Vulnerability databases are vital sources of information on emergent software security concerns. Security professionals, from system administrators to developers to researchers, heavily depend on these databases to track vulnerabilities and analyze s
Externí odkaz:
http://arxiv.org/abs/2006.15074
Autor:
Abusnaina, Ahmed, Abuhamad, Mohammed, Alasmary, Hisham, Anwar, Afsah, Jang, Rhongho, Salem, Saeed, Nyang, DaeHun, Mohaisen, David
The wide acceptance of Internet of Things (IoT) for both household and industrial applications is accompanied by several security concerns. A major security concern is their probable abuse by adversaries towards their malicious intent. Understanding
Externí odkaz:
http://arxiv.org/abs/2005.07145
Autor:
Abusnaina, Ahmed, Khormali, Aminollah, Alasmary, Hisham, Park, Jeman, Anwar, Afsah, Meteriz, Ulku, Mohaisen, Aziz
The main goal of this study is to investigate the robustness of graph-based Deep Learning (DL) models used for Internet of Things (IoT) malware classification against Adversarial Learning (AL). We designed two approaches to craft adversarial IoT soft
Externí odkaz:
http://arxiv.org/abs/1902.04416
Autor:
Alasmary, Hisham, Khormali, Aminollah, Anwar, Afsah, Park, Jeman, Choi, Jinchun, Nyang, DaeHun, Mohaisen, Aziz
The growth in the number of Android and Internet of Things (IoT) devices has witnessed a parallel increase in the number of malicious software (malware), calling for new analysis approaches. We represent binaries using their graph properties of the C
Externí odkaz:
http://arxiv.org/abs/1902.03955
Autor:
Choi, Jinchun, Anwar, Afsah, Alasmary, Hisham, Spaulding, Jeffrey, Nyang, DaeHun, Mohaisen, Aziz
The lack of security measures in the Internet of Things (IoT) devices and their persistent online connectivity give adversaries an opportunity to target them or abuse them as intermediary targets for larger attacks such as distributed denial-of-servi
Externí odkaz:
http://arxiv.org/abs/1902.03531
Publikováno v:
In Computer Networks 9 November 2022 217