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Atif Saeed

dblp:141/6171 · DBLP profile ↗
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5ranked-venue papers
3as first author
2since 2021 · last 2024
0000-0002-7889-8944ORCID · verified

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 3 · 2 first-authorSecurity and privacy · 1 · 1 first-author · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Network and information security
1 paper
Systems and software security · 100%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Cloud and datacenter computing · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Systems and software security
exploitation
0.612022
Cross-VM Network Channel Attacks and Countermeasures Within Cloud Computing Environments · IEEE Trans. Dependable Secur. Comput. 2022
Systems and software security
virtualization security
0.612022
Cross-VM Network Channel Attacks and Countermeasures Within Cloud Computing Environments · IEEE Trans. Dependable Secur. Comput. 2022
Cloud and datacenter computing › virtualization › virtualization security
virtual machine isolation
0.212022
Cross-VM Network Channel Attacks and Countermeasures Within Cloud Computing Environments · IEEE Trans. Dependable Secur. Comput. 2022

Methods — techniques the papers use, named apart from their topics

return-oriented programming · 1.1network traffic redirection · 1.1
YearPublicationVenuePosition
2024 A fusion of BERT, machine learning and manual approach for fake news detection
Mohammad A. Alghamdi, Muhammad Shahid Bhatti, Atif Saeed, Zeeshan Gillani, Sultan H. Almotiri
Multim. Tools Appl.3
2022 Cross-VM Network Channel Attacks and Countermeasures Within Cloud Computing Environments
abstract
Cloud providers attempt to maintain the highest levels of isolation between Virtual Machines (VMs) and inter-user processes to keep co-located VMs and processes separate. This logical isolation creates an internal virtual network to separate VMs co-residing within a shared physical network. However, as co-residing VMs share their underlying VMM (Virtual Machine Monitor), virtual network, and hardware are susceptible to cross VM attacks. It is possible for a malicious VM to potentially access or control other VMs through network connections, shared memory, other shared resources, or by gaining the privilege level of its non-root machine. This research presents a two novel zero-day cross-VM network channel attacks. In the first attack, a malicious VM can redirect the network traffic of target VMs to a specific destination by impersonating the Virtual Network Interface Controller (VNIC). The malicious VM can extract the decrypted information from target VMs by using open source decryption tools such as Aircrack. The second contribution of this research is a privilege escalation attack in a cross VM cloud environment with Xen hypervisor. An adversary having limited privileges rights may execute Return-Oriented Programming (ROP), establish a connection with the root domain by exploiting the network channel, and acquiring the tool stack (root domain) which it is not authorized to access directly. Countermeasures against this attacks are also presented
Atif Saeed, Peter Garraghan, Syed Asad Hussain
IEEE Trans. Dependable Secur. Comput.1
2018 A Cross-Virtual Machine Network Channel Attack via Mirroring and TAP Impersonation
abstract
Data privacy and security is a leading concern for providers and customers of cloud computing, where Virtual Machines (VMs) can co-reside within the same underlying physical machine. Side channel attacks within multi-tenant virtualized cloud environments are an established problem, where attackers are able to monitor and exfiltrate data from co-resident VMs. Virtualization services have attempted to mitigate such attacks by preventing VM-to-VM interference on shared hardware by providing logical resource isolation between co-located VMs via an internal virtual network. However, such approaches are also insecure, with attackers capable of performing network channel attacks which bypass mitigation strategies using vectors such as ARP Spoofing, TCP/IP steganography, and DNS poisoning. In this paper we identify a new vulnerability within the internal cloud virtual network, showing that through a combination of TAP impersonation and mirroring, a malicious VM can successfully redirect and monitor network traffic of VMs co-located within the same physical machine. We demonstrate the feasibility of this attack in a prominent cloud platform - OpenStack - under various security requirements and system conditions, and propose countermeasures for mitigation.
Atif Saeed, Peter Garraghan, Barnaby Craggs, Dirk van der Linden, Awais Rashid, Syed Asad Hussain
IEEE CLOUD1
2013 Smart Land Record Application Using Web GIS and GPS
Muhammad Shahid Bhatti, Muhammad Ajmal, Atif Saeed, Maqsood Ahmed, Rizwan Khalid, Nouman Arshad
WorldCIST3
2013 Android, GIS and Web Base Project, Emergency Management System (EMS) Which Overcomes Quick Emergency Response Challenges
Atif Saeed, Muhammad Shahid Bhatti, Muhammad Ajmal, Adil Waseem, Arsalan Akbar, Mahmood Adnan
WorldCIST1