Papers by Muzzamil Mustafa
Skin diseases present a complex challenge for mechanical analysis due to the inherent irregularit... more Skin diseases present a complex challenge for mechanical analysis due to the inherent irregularities in skin texture, varying complexions, and the presence of hair and other surface features. The need for an accurate and automated system for skin disease detection is paramount. However, the task is compounded by issues such as dataset imbalance and stringent data privacy concerns associated with medical images. In this study, we harnessed the power of Convolutional Neural Networks (CNNs) in the domain of Medical Image Analysis (MIA) to classify skin diseases. Additionally, we employed a federated learning approach to safeguard data privacy. Our results demonstrate the remarkable performance of CNNs, achieving an accuracy score of 0.90 in skin disease classification. Building upon these findings, we propose the development of a mobile application tailored for skin disease classification, leveraging CNNs and the federated learning strategy. This mobile app offers an innovative solution for skin analysis while maintaining the highest data security and privacy standards. In conclusion, our research underscores the potential of CNNs and federated learning in the realm of skin disease classification. We introduce a promising path for the creation of an efficient mobile application for skin disease diagnosis, meeting the rigorous demands of modern medical data handling and analysis without compromising data security or privacy.
The DDoS (Distributed Denial of Service) attack is a type of Cyberattack in which multiple attack... more The DDoS (Distributed Denial of Service) attack is a type of Cyberattack in which multiple attackers aim to attack different network resources like a server or a website. Although many statistical methods have already been designed for DDoS attack detection, designing a real-time detector with low computational overhead is still one of the main concerns. The already existing datasets are highly important and can be used for constructing and checking new solutions. It is the most dangerous attack against IPv6 networks today. The attack uses Internet Control Message Protocol version 6 (ICMPv6) messages. DDoS attack can be detected in various ways like a sudden fluctuation in the traffic of a website or unreal raise in the requests to resources. DDoS attacks are among the four most malicious attacks, like social engineering, ransomware, and supply chain attacks. It’s relatively easy to confuse DDoS attacks with other cyber threats. As for now most of our application and infrastructure ...
Mobile Application Using CNN for Skin Disease Classification with user privacy, 2024
Skin diseases present a complex challenge for mechanical analysis due to the inherent irregularit... more Skin diseases present a complex challenge for mechanical analysis due to the inherent irregularities in skin texture, varying complexions, and the presence of hair and other surface features. The need for an accurate and automated system for skin disease detection is paramount. However, the task is compounded by issues such as dataset imbalance and stringent data privacy concerns associated with medical images. In this study, we harnessed the power of Convolutional Neural Networks (CNNs) in the domain of Medical Image Analysis (MIA) to classify skin diseases. Additionally, we employed a federated learning approach to safeguard data privacy. Our results demonstrate the remarkable performance of CNNs, achieving an accuracy score of 0.90 in skin disease classification. Building upon these findings, we propose the development of a mobile application tailored for skin disease classification, leveraging CNNs and the federated learning strategy. This mobile app offers an innovative solution for skin analysis while maintaining the highest data security and privacy standards. In conclusion, our research underscores the potential of CNNs and federated learning in the realm of skin disease classification. We introduce a promising path for the creation of an efficient mobile application for skin disease diagnosis, meeting the rigorous demands of modern medical data handling and analysis without compromising data security or privacy.
Research Square (Research Square), Feb 16, 2023
The DDoS (Distributed Denial of Service) attack is a type of Cyberattack in which multiple attack... more The DDoS (Distributed Denial of Service) attack is a type of Cyberattack in which multiple attackers aim to attack different network resources like a server or a website. Although many statistical methods have already been designed for DDoS attack detection, designing a real-time detector with low computational overhead is still one of the main concerns. The already existing datasets are highly important and can be used for constructing and checking new solutions. It is the most dangerous attack against IPv6 networks today. The attack uses Internet Control Message Protocol version 6 (ICMPv6) messages. DDoS attack can be detected in various ways like a sudden fluctuation in the traffic of a website or unreal raise in the requests to resources. DDoS attacks are among the four most malicious attacks, like social engineering, ransomware, and supply chain attacks. It's relatively easy to confuse DDoS attacks with other cyber threats. As for now most of our application and infrastructure resides on the cloud. As for cloud providers, the services provider must facilitate some tools to prevent the attack on their services and their user. Some of the major cloud providers give us this type of facility (AWS, Azure, and GCPThis cloud service provider offers cloud DDoS mitigation and prevention that operates entirely outside of your current network, inside the Internet cloud, and can identify and stop DDoS attacks before they even get to you. For bigger installations, routing is utilised to ensure that all network traffic, regardless of type, is filtered before delivery via a clean pipe. Domain name system (DNS) is used to direct inbound traffic through a scrubbing centre before delivery to the server. DDoS mitigation and prevention in the cloud is not only speedy, but also incredibly effective at stopping DDoS attacks.
Recent technological advances have indicated widespread use of Voice Over Long-Term Evolution (Vo... more Recent technological advances have indicated widespread use of Voice Over Long-Term Evolution (VoLTE) networks based on developing 5G networks. Despite its ease of design and deployment, VoLTE is vulnerable to many sorts of attacks at the control plane's Session Initiation Protocol (SIP), which exchanges signaling messages for calls via starting call setups, management, and termination. These SIP attacks may take the form of modified SIP messages that force the SIP devices to restart, or they may take the form of flooding the SIP devices with invite messages, register requests that cause the device to run out of memory, and denying genuine users access to the device. These attacks are commonly known as Distributed Denial of Service (DDoS) attacks. The SIP register injection attack, which might be injected during the commencement step by SIP equipped devices (SIP smartphones), prior to setting up the Secured Internet Protocol (IPsec) tunnel for the remaining SIP sessions, is of particular relevance, due to its characteristics of exhausting the available bandwidth, memory, and CPU resources, resulting in SIP device failure. Consequently, there is a need to address this difficulty by building an SIP register injection attack detection and mitigation technique. Prior to being processed by the Proxy Call Session Control Function. The proposed scheme verifies each initial register request from User Equipment (UE) at the home network of Internet Protocol Multimedia Subsystems (IMS) and compares it to the incoming SIP register request pattern with those stored on the scheme's table (P-CSCF). The proposed technique detects and drops every SIP register request with an abnormal pattern that is associated with an attack. The method proved promising with detection accuracy of over 96.67 percent, which is a solid potential as a preliminary setup towards the creation of a robust Real-time SIP detection and mitigation scheme for 5G networks.
2023 International Conference on Business Analytics for Technology and Security (ICBATS)
The DDoS (Distributed Denial of Service) attack is a type of Cyberattack in which multiple attack... more The DDoS (Distributed Denial of Service) attack is a type of Cyberattack in which multiple attackers aim to attack different network resources like a server or a website. Although many statistical methods have already been designed for DDoS attack detection, designing a real-time detector with low computational overhead is still one of the main concerns. The already existing datasets are highly important and can be used for constructing and checking new solutions. It is the most dangerous attack against IPv6 networks today. The attack uses Internet Control Message Protocol version 6 (ICMPv6) messages. DDoS attack can be detected in various ways like a sudden fluctuation in the traffic of a website or unreal raise in the requests to resources. DDoS attacks are among the four most malicious attacks, like social engineering, ransomware, and supply chain attacks. It’s relatively easy to confuse DDoS attacks with other cyber threats. As for now most of our application and infrastructure ...
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Papers by Muzzamil Mustafa