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Search Publications by: Anoop Singhal (Fed)

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Displaying 1 - 25 of 72

Evaluating Large Language Models for Real World Vulnerability Repair in C/C++ Code

June 19, 2024
Author(s)
Lan Zhang, Qingtian Zou, Anoop Singhal, Xiaoyan Sun, Peng Liu
The advent of Large Language Models (LLMs) has enabled advancement in automated code generation, translation, and summarization. Despite their promise, evaluating the use of LLMs in repairing real-world code vulnerabilities remains underexplored. In this

Analysis of Neural Network Detectors for Network Attacks

June 17, 2024
Author(s)
Qingtian Zou, Lan Zhang, Anoop Singhal, Xiaoyan Sun, Peng Liu
While network attacks play a critical role in many advanced persistent threat (APT) campaigns, an arms race exists between the network defenders and the adversary: to make APT campaigns stealthy, the adversary is strongly motivated to evade the detection

The Design and Application of a Unified Ontology for Cyber Security

December 9, 2023
Author(s)
Ashrafi Akbar, Fariha Rahman, Anoop Singhal, Latifur Khan, Bhavani Thuriasingham
Ontology enables semantic interoperability, making it highly valuable for cyber threat hunting. Community-driven frameworks like MITRE ATT&CK, D3FEND, ENGAGE, CWE and CVE have been developed to combat cyber threats. However, manually navigating these

Security Analysis of Trust on the Controller in the Matter Protocol

June 11, 2023
Author(s)
Anoop Singhal, Shaswat Kumar, Francis Ha, Ximming Ou
Matter is an open-source connectivity standard for the purpose of allowing smart home IoT devices from different vendors to interoperate with one another. A controller in a Matter system commissions new devices into the Matter fabric. The device needs to

SMET: Semantic Mapping of CVE to ATT&CK and its Application to Cyber Security

July 12, 2023
Author(s)
Abdeen Basel, Ehab Al-Sheer, Anoop Singhal, Latifur Khan, Kevin Hamlen
Cybercriminals relentlessly pursue vulnerabilities across cyberspace to exploit software, threatening the security of individuals, organizations, and governments. Although security teams strive to establish defense measures to thwart attackers, the

Attacks on ML Systems: From Security Risk Analysis to Attack Mitigation

December 16, 2022
Author(s)
Qingtian Zou, Lan Zhang, Anoop Singhal, Xiaoyan Sun, Peng Liu
The past several years have witnessed rapidly increasing use of machine learning (ML) systems in multiple industry sectors. Since risk analysis is one of the most essential parts of the real-world ML system protection practice, there is an urgent need to

Advanced Persistent Threat Detection using Data Provenance and Metric Learning

November 14, 2022
Author(s)
Khandakar Ashrafi Akbar, Yigong Wang, Gbadebo Ayoade, Yang Gao, Anoop Singhal, Latifur Khan, Bhavani Thuraisingham, kangkook Jee
Advanced persistent threats (APT) have increased in recent times as a result of the rise in interest by nation states and sophisticated corporations to obtain high-profile information. Typically, APT attacks are more challenging to detect since they

Poisoning Attacks against Machine Learning: Can Machine Learning be Trustworthy?

October 24, 2022
Author(s)
Alina Oprea, Anoop Singhal, Apostol Vassilev
Many practical applications benefit from Machine Learning (ML) and Artificial Intelligence (AI) technologies, but their security needs to be studied in more depth before the methods and algorithms are actually deployed in critical settings. In this article

Knowledge Mining in Cybersecurity: From Attack to Defense

July 18, 2022
Author(s)
Khandakar Ashrafi Akbar, Sadaf MD Halim, Yibo Hu, Anoop Singhal, Latifur Khan, Bhavani Thuraisingham
In the fast-evolving world of Cybersecurity, an analyst often has the difficult task of responding to new threats and attack campaigns within a limited amount of time. If an analyst fails to do so, this can lead to severe consequences for the system under

Heterogenous Domain Adaptation for Multi stream Classification on Cyber Threat Data

June 13, 2022
Author(s)
Yi Fan Li, Yang Gao, G Ayoade, L Khan, Anoop Singhal, B Thuraisingham
Under a newly introduced setting of multi stream classification, two data streams are involved, which are referred to as source and target streams. The source stream continuously generates data instances from a certain domain with labels, while the target

Identifying Tactics of Advanced Persistent Threats with Limited Attack Traces

December 16, 2021
Author(s)
Khandakar Ashrafi Akbar, Yigong Wang, Md Islam, Anoop Singhal, Latifur Khan, Bhavani Thuraisingham1
The cyberworld being threatened by continuous imposters needs the development of intelligent methods for identifying threats while keeping in mind all the constraints that can be encountered. Advanced persistent threats (APT) have become an emerging issue

Security Auditing of Internet of Things Devices in a Smart Home

October 15, 2021
Author(s)
Suryadipta Mazumdar, Daniel Bostos, Anoop Singhal
Attacks on the Internet of Things are increasing. Unfortunately, transparency and accountability that are paramount to securing Internet of Things devices are either missing or implemented in a questionable manner. Security auditing is a promising solution

Deep Learning for Detecting Network Attacks: An End to End approach

July 19, 2021
Author(s)
Qingtian Zou, Anoop Singhal, Xiaoyan Sun, Peng Liu
Network attack is still a major security concern for organizations worldwide. Recently, researchers have started to apply neural networks to detect network attacks by leveraging network traÿc data. However, public network data sets have major drawbacks

An Approach for Detection of Advanced Persistent Threat Attacks

December 1, 2020
Author(s)
Qingtian Zou, Xiaoyan Sun, Peng Liu, Anoop Singhal
Advanced Persistent Threat (APT) campaigns employ sophisticated strategies and tactics to achieve their attack goal. The evolution of APT strategies and tactics compounds the challenge of detecting attack campaigns. This article introduces an approach

Evolving Advanced Persistent Threat Detection Using Provenance Graph and Metric Learning

June 29, 2020
Author(s)
Gbadebo Ayoade, Khandakar A. Akbar, Pracheta Sahoo, Yang Gao, Anoop Singhal, Kangkook Jee, Latifur Khan, Anmol Agarwal
Advanced persistent threats (APT) have increased in recent times as a result of the rise in interest by nationstates and sophisticated corporations to obtain high profile information. Typically, APT attacks are more challenging to detect since they

Defining Actionable Rules for Verifying IOT Safety and Security

May 18, 2020
Author(s)
Kayla Ibrahim, Suryadipta Majumdar, Daniel Bastos, Anoop Singhal
Internet of Things (IoT) is being widely adopted in recent years. Security, however, has lagged behind, as evidenced by the increasing number of attacks that use IoT devices (e.g., an arson that uses a smart oven, burglary via a smart lock). Therefore, the

Automatic Recognition of Advanced Persistent Threat Tactics for Enterprise Security

March 16, 2020
Author(s)
Qingtian Zou, Anoop Singhal, Xiaoyan Sun, Peng Liu
Advanced Persistent Threats (APT) has become the concern of many enterprise networks. APT can remain undetected for a long time span and lead to undesirable consequences such as stealing of sensitive data, broken workflow, and so on. To achieve the attack

Forensic Analysis of Advanced Persistent Threat Attacks in Cloud Environments

January 6, 2020
Author(s)
Changwei Liu, Anoop Singhal, Duminda Wijesekera
Due to the increasing cyber-activities and the use of diverse devices offered on cloud environments, post-attack cloud forensic investigations must deal with data in diverse formats and quantities from emerging attackable interfaces. The process of