Android source code vulnerability detection: a systematic literature review

J Senanayake, H Kalutarage, MO Al-Kadri… - ACM Computing …, 2023 - dl.acm.org
The use of mobile devices is rising daily in this technological era. A continuous and
increasing number of mobile applications are constantly offered on mobile marketplaces to …

A review on challenges and future research directions for machine learning-based intrusion detection system

A Thakkar, R Lohiya - Archives of Computational Methods in Engineering, 2023 - Springer
Research in the field of Intrusion Detection is focused on developing an efficient strategy that
can identify network attacks. One of the important strategies is to supervise the network …

Detecting unknown encrypted malicious traffic in real time via flow interaction graph analysis

C Fu, Q Li, K Xu - arXiv preprint arXiv:2301.13686, 2023 - arxiv.org
In this paper, we propose HyperVision, a realtime unsupervised machine learning (ML)
based malicious traffic detection system. Particularly, HyperVision is able to detect unknown …

{ARGUS}:{Context-Based} Detection of Stealthy {IoT} Infiltration Attacks

P Rieger, M Chilese, R Mohamed, M Miettinen… - 32nd USENIX Security …, 2023 - usenix.org
IoT application domains, device diversity and connectivity are rapidly growing. IoT devices
control various functions in smart homes and buildings, smart cities, and smart factories …

" Get in Researchers; We're Measuring Reproducibility": A Reproducibility Study of Machine Learning Papers in Tier 1 Security Conferences

D Olszewski, A Lu, C Stillman, K Warren… - Proceedings of the …, 2023 - dl.acm.org
Reproducibility is crucial to the advancement of science; it strengthens confidence in
seemingly contradictory results and expands the boundaries of known discoveries …

Malicious code detection in android: the role of sequence characteristics and disassembling methods

PG Balikcioglu, M Sirlanci, O A. Kucuk… - International Journal of …, 2023 - Springer
The acceptance and widespread use of the Android operating system drew the attention of
both legitimate developers and malware authors, which resulted in a significant number of …

Kalis2. 0-a SECaaS-Based Context-Aware Self-Adaptive Intrusion Detection System for the IoT

A Rullo, D Midi, A Mudjerikar… - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
The wide variety of application domains makes the Internet of Things (IoT) quite unique
among other types of computer networks: IoT networks can be made of devices of different …

TBAC: A Tokoin-based Accountable Access Control Scheme for the Internet of Things

C Liu, M Xu, H Guo, X Cheng, Y Xiao… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Overprivilege attack, a widely reported phenomenon in IoT that accesses unauthorized or
excessive resources, is notoriously hard to prevent, trace and mitigate. In this paper, we …

Iot anomaly detection via device interaction graph

J Wang, Z Li, M Sun, B Yuan… - 2023 53rd Annual IEEE …, 2023 - ieeexplore.ieee.org
With diverse functionalities and advanced platform applications, Internet of Things (IoT)
devices extensively interact with each other, and these interactions govern the legitimate …

Are we aware? an empirical study on the privacy and security awareness of smartphone sensors

AI Champa, MF Rabbi, FZ Eishita… - 2023 IEEE/ACIS 21st …, 2023 - ieeexplore.ieee.org
Smartphones are equipped with a wide variety of sensors, which can pose significant
security and privacy risks if not properly protected. To assess the privacy and security risks of …