Visible to the public Biblio

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2019-02-14
Dauda, Ahmed, Mclean, Scott, Almehmadi, Abdulaziz, El-Khatib, Khalil.  2018.  Big Data Analytics Architecture for Security Intelligence. Proceedings of the 11th International Conference on Security of Information and Networks. :19:1-19:4.

The need for security1 continues to grow in distributed computing. Today's security solutions require greater scalability and convenience in cloud-computing architectures, in addition to the ability to store and process larger volumes of data to address very sophisticated attacks. This paper explores some of the existing architectures for big data intelligence analytics, and proposes an architecture that promises to provide greater security for data intensive environments. The architecture is designed to leverage the wealth in the multi-source information for security intelligence.

2018-03-05
Harrington, Joshua, Lacroix, Jesse, El-Khatib, Khalil, Lobo, Felipe Leite, Oliveira, Horácio A.B.F..  2017.  Proactive Certificate Distribution for PKI in VANET. Proceedings of the 13th ACM Symposium on QoS and Security for Wireless and Mobile Networks. :9–13.

Vehicular Ad-Hoc Networks (VANET) are the creation of several vehicles communicating with each other in order to create a network capable of communication and data exchange. One of the most promising methods for security and trust amongst vehicular networks is the usage of Public Key Infrastructure (PKI). However, current implementations of PKI as a security solution for determining the validity and authenticity of vehicles in a VANET is not efficient due to the usage of large amounts of delay and computational overhead. In this paper, we investigate the potential of PKI when predictively and preemptively passing along certificates to roadside units (RSU) in an effort to lower delay and computational overhead in a dynamic environment. We look to accomplish this through utilizing fog computing and propose a new protocol to pass certificates along the projected path.

2017-05-30
Lacroix, Jesse, El-Khatib, Khalil, Akalu, Rajen.  2016.  Vehicular Digital Forensics: What Does My Vehicle Know About Me? Proceedings of the 6th ACM Symposium on Development and Analysis of Intelligent Vehicular Networks and Applications. :59–66.

A major component of modern vehicles is the infotainment system, which interfaces with its drivers and passengers. Other mobile devices, such as handheld phones and laptops, can relay information to the embedded infotainment system through Bluetooth and vehicle WiFi. The ability to extract information from these systems would help forensic analysts determine the general contents that is stored in an infotainment system. Based off the data that is extracted, this would help determine what stored information is relevant to law enforcement agencies and what information is non-essential when it comes to solving criminal activities relating to the vehicle itself. This would overall solidify the Intelligent Transport System and Vehicular Ad Hoc Network infrastructure in combating crime through the use of vehicle forensics. Additionally, determining the content of these systems will allow forensic analysts to know if they can determine anything about the end-user directly and/or indirectly.

2017-04-24
Alam, Safwan, El-Khatib, Khalil.  2016.  Phishing Susceptibility Detection Through Social Media Analytics. Proceedings of the 9th International Conference on Security of Information and Networks. :61–64.

Phishing is one of the most dangerous information security threats present in the world today, with losses toping 5.9 billion dollars in 2013. Evolving from the original concept of phishing, spear phishing also attempts to scam individuals online, however it uses personalized mail to yield a far higher success rate. This paper suggests an increased threat of spear phishing success due to the presence of social media. Assessing this new threat is important not only to the individuals, but also to companies whose employees may specifically be targeted through their social media accounts. The paper presents the design and implementation of an architecture to determine phishing susceptibility of a user through their social media accounts, and methods to reduce the threat. Preliminary testing shows that social media provides a publicly accessible resource to assess targeted individuals for phishing attacks through their accounts.