The search for new authentication methods to replace passwords modern mobile devices such as smartphones and tablets has attracted a substantial amount of research in recent years. As result, several behavioral biometric schemes have been proposed. Most these schemes, however, are uni-modal. This paper presents new, bi-modal solution user authentication. proposed mechanism takes into account micro-movements phone movements the user's finger during writing or signing on touchscreen. More...

In recent years, massive development in the malware industry changed entire landscape for development. Therefore, cybercriminals became more sophisticated by advancing their techniques from file-based to fileless malware. As depends on files spread itself, other hand, does not require a traditional file system and uses benign processes carry out its malicious intent. it evades conventional detection remains stealthy. This paper briefly explains malware, life cycle, infection chain. Moreover,...

The exponential growth of the Internet Things (IoT) has led to rapid expansion interconnected systems, which also increased vulnerability IoT devices security threats such as distributed denial-of-service (DDoS) attacks. In this paper, we propose a machine learning pipeline that specifically addresses issue DDoS attack detection in networks. Our approach comprises (i) processing module prepare data for further analysis, (ii) dynamic attribute selection selects most adaptive and productive...

Smartphones are the most popular and widespread personal devices. Apart from their conventional use, that is, calling texting, they have also been used to perform multiple security sensitive activities, such as online banking shopping, social networking, taking pictures, e-mailing. On a positive side, smartphones improved quality of life by providing services users desire, for example, anytime-anywhere computing. However, on other pose privacy threats users’ stored data. User authentication...

This research aims to solve the problem of position-independent activity recognition, a critical aspect in accurately identifying human activities using smartphones. Our study addresses this challenge by employing Convolutional Neural Networks classify such as walking, sitting, running, and more, regardless smartphone’s position on body. Leveraging real-world publicly available dataset, we demonstrate 98% accuracy obtained solely from accelerometer data, surpassing state-of-the-art...

Smartphones provide anytime-anywhere communications and are being increasingly used for a variety of purposes, e.g, sending email, performing online transactions, connecting with friends acquaintances over social networks. As result, considerable amount sensitive personal information is often generated stored on smartphones. Thus, smartphone users may face financial as well sentimental consequences if such fall in the wrong hands. To address this problem all smartphones some form user...

Trojan Detection—the process of understanding the behaviour a suspicious file has been talk town these days. Existing approaches, e.g., signature-based, have not able to classify them accurately as Trojans. This paper proposes TrojanDetector—a simple yet effective multi-layer hybrid approach for detection. TrojanDetector analyses every downloaded application and extracts correlates its features on three layers (i.e., application-, user-, package layer) identify it either benign or Trojan....

Cryptojacking is a type of computer piracy in which hacker uses victim’s resources, without their knowledge or consent, to mine for cryptocurrency. This made possible by new memory-based cryptomining techniques and the growth web technologies such as WebAssembly, allowing mining occur within browser. Most research field cryptojacking has focused on detection methods rather than prevention methods. Some proposed literature include using static dynamic features in-browser malware, along with...

This paper introduces DIALERAUTH - a mechanism which leverages the way smartphone user taps/enters any text-independent 10-digit number (replicating dialing process) and hand's micro-movements she makes while doing so. authenticates on basis of timing differences in entered strokes. provides enhanced security by leveraging transparent unobservable layer based another modality user's hand micro-movements. Furthermore, increases usability acceptability utilizing users' familiarity with process...

Malware, short for malicious software, is any software program designed to cause harm a computer or network. Malware can take many forms, such as viruses, worms, Trojan horses, and ransomware. Because malware significant damage network, it important avoid its installation prevent potential harm. This paper proposes machine learning-based detection method called MalwD&C allow the secure of Programmable Executable (PE) files. The proposed uses learning classifiers analyze PE files classify...

In recent years, studies have explored the possibility of extracting ancillary information, such as gender, age, height, weight, etc., from primary biometric traits, namely, iris, fingerprint and face, however, estimation soft biometrics mobile data associated with behavioral modalities, e.g., touch phone movement, is still a much less area. This paper investigates to estimate attributes on smart devices. particular, we design scheme operating-hand using information originated keystrokes,...

Exploiting Radio Frequency Identification (RFID) technology in healthcare systems has become a common practice, as it ensures better patient care and safety. However, these are prone to security vulnerabilities that can jeopardize privacy the secure management of credentials. This paper aims advance state-of-the-art approaches by developing more private RFID-based systems. More specifically, we propose lightweight RFID protocol safeguards patients' Internet Healthcare Things (IoHT) domain...

This paper presents a bimodal scheme - the mechanism which exploits way user enters her 8-digit PIN/password and phone-movements while doing so, for authentication in mobile banking/financial applications (apps). The authenticates based on timing differences of entered strokes. Additionally, it provides an enhanced security by adding unobservable layer phone-movements. is assumed to be highly secure as mimicking invisible touch-timings could extremely difficult. Our analysis 2850 samples...

Recently, researches have shown to employ implicit behavioral biometrics via built-in sensors (e.g., gyroscope) for user identification on smartphones. The majority of prior studies are based unimodal systems, which suffer from low accuracy, spoofing and lower usability. In this paper, we present an unconstrained multimodal biometric system smartphones using touchstroke, phone-movement face patterns. proposed framework authenticates the by taking silently into account micro-movements phone...

Wireless Sensor Networks (WSN) is one of the fastest rising emerging technologies that find widespread use in various applications comprising military, health, agriculture, habitat etc. Seen as sensor network deployed at sites which can be considered remote and hostile, technology seriously faced with challenges to functional security cost their inherent limitations energy capacity computing power.In this paper we have delved upon summarized earlier research on poised WSNs, classified...