Results 51 to 60 of about 1,022 (177)
Securing Machine‐Type Communications: A Survey on Privacy Threats and Countermeasures
IET Information Security, Volume 2026, Issue 1, 2026.Machine‐type communication (MTC) is a fundamental enabler of the Internet of Things (IoT) and emerging 5G/6G networks, supporting massive deployments of heterogeneous and resource‐constrained devices. However, large‐scale data collection, persistent connectivity, and limited device capabilities introduce critical privacy challenges that are not ...
Amirhosein Imani +2 more
wiley +1 more source
A Framework for Evaluation of SQL Injection Detection and Prevention Tools
International Journal of Information and Communication Technology Research, 2013 SQLIA is a hacking technique by which the attacker adds Structured Query Language code (SQL statements) through a web application's input fields or hidden parameters to access the resources.
Atefeh Tajpour, Suhaimi I brahim
doaj
Preventing SQL Injection Attacks
International Journal of Computer Applications, 2012 With the recent rapid increase in web based applications that employ back-end database services, results show that SQL Injection and Remote File Inclusion are the two frequently used exploits rather than using other complicated techniques. With the rise in use of web applications, SQL injection based attacks are gradually increasing and is now one of ...
Vaidhyanathan.G Vaidhyanathan.G +2 more
openaire +1 more source
AI‐Powered Defense: Leveraging Deep Learning for Effective Malware Detection
Applied Computational Intelligence and Soft Computing, Volume 2026, Issue 1, 2026.Traditional malware detection techniques frequently fail to detect and stop malicious activity in an era where cyber threats are becoming more complex. Any software that enters a computer system without the administrator’s consent is considered malicious software.
Nancy Awadallah Awad +1 more
wiley +1 more source
SQL-injection vulnerability scanning tool for automatic creation of SQL-injection attacks
Procedia Computer Science, 2011 AbstractSecuring the web against frequent cyber attacks is a big concern as attackers usually intend to snitch private information, financial information, deface and damages websites to prove their hacking capabilities. This type of vandalism may drive many corporations that conduct their business through the web to suffer financial and reputation ...
Abdul Bashah Mat Ali +3 more
openaire +2 more sources
Lightweight Deep Learning Approach for Intelligent Intrusion Detection in IoT Networks
International Journal of Distributed Sensor Networks, Volume 2026, Issue 1, 2026.Intrusion detection system (IDS) is designed to analyze and monitor the network traffic to identify unauthorized access or attacks in an Internet of Things (IoT). IDS assists in protecting IoT devices and networks by recognizing malicious activities and preventing potential breaches.
Srikanth Mudiyanuru Sriramappa +5 more
wiley +1 more source
Automated Fix Generator for SQL Injection Attacks [PDF]
2008 19th International Symposium on Software Reliability Engineering (ISSRE), 2008 A critical problem facing todaypsilas Internet community is the increasing number of attacks exploiting flaws found in Web applications. This paper specifically targets input validation vulnerabilities found in SQL queries that may lead to SQL Injection Attacks (SQLIAs).
Fred Dysart, Mark Sherriff
openaire +1 more source
Pentesting LLM Models With an Automated Framework
International Journal of Intelligent Systems, Volume 2026, Issue 1, 2026.Artificial intelligence (AI) has become an essential tool in modern cybersecurity, enabling faster and more accurate detection, prevention, and response to threats. Within this landscape, large language models (LLMs) have emerged as versatile systems capable of generating code, providing technical guidance, and automating complex tasks.
Juan Luis López-Delgado +2 more
wiley +1 more source
A Deep Learning Approach Using Optimized LSTM for Anomaly‐Based Network Intrusion Detection
Journal of Engineering, Volume 2026, Issue 1, 2026.With the exponential rise in cyber threats, anomaly‐based network intrusion detection systems (NIDSs) have become critical for maintaining robust cybersecurity. This article proposes an optimized long short‐term memory (LSTM) deep learning (DL) model specifically designed to detect anomalies in network traffic.
Samia Dardouri, Shikha Binwal
wiley +1 more source
Boosting Intrusion Detection Accuracy With a Multibranch Deep Learning Framework
Journal of Electrical and Computer Engineering, Volume 2026, Issue 1, 2026.To overcome the limitations of traditional intrusion detection methods in dealing with high‐dimensional sparse features, multiclass attack classification, and model robustness, this paper presents a fused multibranch intrusion detection model (FMB‐IDM). The proposed framework combines three complementary deep learning components.
Yang Li, Shonak Bansal
wiley +1 more source