Deep Learning (DL) is a disruptive technology that has changed the landscape of cyber
security research. Deep learning models have many advantages over traditional Machine …

App Store Analysis studies information about applications obtained from app stores. App
stores provide a wealth of information derived from users that would not exist had the …

With the growing processing power of computing systems and the increasing availability of
massive datasets, machine learning algorithms have led to major breakthroughs in many …

Purpose The purpose of this paper is to empirically examine the factors that influence a
consumer's attitude and intention to use mobile wallets using a sample representative of …

方便地从互联网获取信息和服务, 移动互联网应运而生并迅猛发展. 然而,
移动互联网在移动终端, 接入网络, 应用服务, 安全与隐私保护等方面还面临着一系列的挑战 …

This research paper presents MLDroid—a web-based framework—which helps to detect
malware from Android devices. Due to increase in the popularity of Android devices …

Most existing Android malware detection and categorization techniques are static
approaches, which suffer from evasion attacks, such as obfuscation. By analyzing program …

Malicious applications pose a threat to the security of the Android platform. The growing
amount and diversity of these applications render conventional defenses largely ineffective …

Abstract The Affect-in-the-Wild (Aff-Wild) Challenge proposes a new comprehensive
benchmark for assessing the performance of facial affect/behaviour analysis …

Smartphones have become pervasive due to the availability of office applications, Internet,
games, vehicle guidance using location-based services apart from conventional services …