About Detection of Code Reuse Attacks by Yury V. Kosolapov

“…At the heart of these attacks lies the detection, in the vulnerable program of suitable areas, of executable code — gadgets — and chaining these gadgets into chains. …”
Get full text

Android collusion attack detection model by Hongyu YANG, Zaiming WANG

“…In order to solve the problem of poor efficiency and low accuracy of Android collusion detection,an Android collusion attack model based on component communication was proposed.Firstly,the feature vector set was extracted from the known applications and the feature vector set was generated.Secondly,the security policy rule set was generated through training and classifying the privilege feature set.Then,the component communication finite state machine according to the component and communication mode feature vector set was generated,and security policy rule set was optimized.Finally,a new state machine was generated by extracting the unknown application’s feature vector set,and the optimized security policy rule set was matched to detect privilege collusion attacks.The experimental results show that the proposed model has better detective efficiency and higher accuracy.…”
Get full text

Network Attack Detection for Business Safety by Fadia Abduljabbar Saeed, Ghalia Nassreddine, Joumana Younis

“…In this paper, a machine learning-based approach was developed to detect network attacks. Two Machine learning models were used: Support vector machine and Artificial neural network. …”
Get full text

Matrix profile for DDoS attacks detection by Faisal Alotaibi, Alexei Lisitsa

Get full text

Detecting LDoS attack based on ASPQ by Jing ZHANG, Hua-ping HU, Bo LIU, Feng-tao XIAO

“…Based on the analysis of the effects on average size of packet in the queue which LDoS attack makes,the change of this value was got by simulation on NS2.So detection algorithm was proposed,and was applied on Droptail and RED,which were typical queue management algorithm.The result of simulation shows that the algorithm can effectively detect the LDoS attack.…”
Get full text

Fusion of Heterogeneous Intrusion Detection Systems for Network Attack Detection by Jayakumar Kaliappan, Revathi Thiagarajan, Karpagam Sundararajan

“…An intrusion detection system (IDS) helps to identify different types of attacks in general, and the detection rate will be higher for some specific category of attacks. …”
Get full text

Comprehensive Analysis of DDoS Anomaly Detection in Software-Defined Networks by Abdinasir Hirsi, Mohammed A. Alhartomi, Lukman Audah, Adeb Salh, Nan Mad Sahar, Salman Ahmed, Godwin Okon Ansa, Abdullahi Farah

Subjects: “…Amplification attacks…”
Get full text

Survey of Load-Altering Attacks Against Power Grids: Attack Impact, Detection, and Mitigation by Sajjad Maleki, Shijie Pan, Subhash Lakshminarayana, Charalambos Konstantinou

Subjects: “…Load-altering attacks…”
Get full text

Cooperative Control for Multi-Agent Systems with Deception Attack Based on an Attack Detection Mechanism by Shuhan Zhang, Kai Zhang, Zhijian Hu

Subjects: Get full text

DDoS attacks detection based on link character by SUN Hong-jie, FANG Bin-xing, ZHANG Hong-li

“…A new method based on link character was proposed for DDoS attacks detection.Maximum likelihood estima-tion was used to estimate the distribution of link character.SOM neural network is used for link activity profile learning and anomaly link detection.Experiment results indicate that the technique is effective and of a definite practicability.It has a further develop potential for DDoS attacks detection.…”
Get full text

DOG: An Object Detection Adversarial Attack Method by Jinpeng Li, Xiaoyu Ji, Wenyuan Xu, Yushi Cheng

“…This study presents an object detection adversarial attack method (DOG) based on the dynamic optimization of a multi-scale feature grid cluster, aimed at addressing the challenges of poor transferability in white-box attacks and long generation cycles in black-box attacks within the current adversarial example generation techniques. …”
Get full text

Efficient attack detection and data aggregation algorithm by Hong-bing CHENG, Chun-ming RONG, Xiao HUANG, Skjalg EGGEN, Qing-kai ZENG

Subjects: Get full text

Deep Learning Based DDoS Attack Detection by Xu Ziyi

“…Traditional approaches to detection, based on statistical thresholds and signature-based mechanisms, respectively, can hardly cope with the increasing complexity of such an attack. …”
Get full text

Incremental Adversarial Learning for Polymorphic Attack Detection by Ulya Sabeel, Shahram Shah Heydari, Khalil El-Khatib, Khalid Elgazzar

Subjects: Get full text

Detecting Unusual Repetitive Patterns of Behavior Indicative of a Loop-Based Attack in IoT by Asmaa Munshi

Subjects: Get full text

APPLYING TRANSFORMER ARCHITECTURE TO ENHANCE ATTACK DETECTION PERFORMANCE IN INTRUSION DETECTION SYSTEMS by Vu Thi Phuong*, Hoang Thi Hong Ha, Dinh Gia Truong, Tran Thi Yen

“…In this study, we propose a Transformer-based intrusion detection model to enhance attack recognition performance. …”
Get full text

Review of Recent Detection Methods for HTTP DDoS Attack by Ghafar A. Jaafar, Shahidan M. Abdullah, Saifuladli Ismail

“…This paper reviewed 12 recent detection of DDoS attack at the application layer published between January 2014 and December 2018. …”
Get full text

Time synchronization attack detection for industrial wireless network by Sichao ZHANG, Wei LIANG, Xudong YUAN, Yinlong ZHANG, Meng ZHENG

Subjects: Get full text

Towards automated detection of adversarial attacks on tabular data by Piotr Biczyk, Łukasz Wawrowski

Get full text

Leveraging Graph Neural Networks for IoT Attack Detection by Mevlüt Uysal, Erdal Özdoğan, Onur Ceran

“…High accuracy, precision, recall, and AUC values indicate the model's robustness in detecting attacks while minimizing false alarms. The study advances IoT security by introducing synergistic solutions and provides practical insights for implementing intrusion detection systems in real-world IoT environments.…”
Get full text