S
Syed Ali Khayam
Researcher at University of the Sciences
Publications - 104
Citations - 2297
Syed Ali Khayam is an academic researcher from University of the Sciences. The author has contributed to research in topics: Network packet & Wireless sensor network. The author has an hindex of 24, co-authored 104 publications receiving 2170 citations. Previous affiliations of Syed Ali Khayam include Mashhad University of Medical Sciences & National University of Sciences and Technology.
Papers
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Book ChapterDOI
Revisiting traffic anomaly detection using software defined networking
TL;DR: This paper shows how four prominent traffic anomaly detection algorithms can be implemented in an SDN context using Openflow compliant switches and NOX as a controller and indicates that these algorithms are significantly more accurate in identifying malicious activities in the home networks as compared to the ISP.
Journal ArticleDOI
A Taxonomy of Botnet Behavior, Detection, and Defense
TL;DR: This paper structure existing botnet literature into three comprehensive taxonomies of botnet behavioral features, detection and defenses, and introduces the notion of a dimension to denote different criteria which can be used to classify botnet detection techniques.
Book ChapterDOI
Keystroke-Based User Identification on Smart Phones
TL;DR: It is demonstrated that keystroke dynamics of a smart phone user can be translated into a viable features' set for accurate user identification and the proposed technique consistently and considerably outperforms existing schemes.
Book ChapterDOI
Embedded Malware Detection Using Markov n-Grams
TL;DR: It is shown that the entropy rate of Markov n-grams gets significantly perturbed at malcode embedding locations, and therefore can act as a robust feature for embedded malware detection.
Journal ArticleDOI
Performance analysis and modeling of errors and losses over 802.11b LANs for high-bit-rate real-time multimedia
TL;DR: This paper addresses key questions regarding the viability of the above two options for the support of high-bit-rate wireless multimedia applications over 802.11b LANs and analyzes and model the error patterns within the “higher throughput” corrupted packets to evaluate their potential impact on multimedia applications.