Biblio

The development of autonomous agents have gained renewed interest, largely due to the recent successes of machine learning. Social robots can be considered a special class of autonomous agents that are often intended to be integrated into sensitive environments. We present experiences from our work with two specific humanoid social service robots, and highlight how eschewing privacy and security by design principles leads to implementations with serious privacy and security flaws. The paper introduces the robots as platforms and their associated features, ecosystems and cloud platforms that are required for certain use cases or tasks. The paper encourages design aims for privacy and security, and then in this light studies the implementation from two different manufacturers. The results show a worrisome lack of design focus in handling privacy and security. The paper aims not to cover all the security flaws and possible mitigations, but does look closer into the use of the WebSocket protocol and it’s challenges when used for operational control. The conclusions of the paper provide insights on how manufacturers can rectify the discovered security flaws and presents key policies like accountability when it comes to implementing technical features of autonomous agents.

In a previous article [1] we proposed a layered framework to support the assessment of the security risks associated with the use of autonomous vehicles in military operations and determine how to manage these risks appropriately. We established consistent terminology and defined the problem space, while exploring the first layer of the framework, namely risks from the mission assurance perspective. In this paper, we develop the second layer of the framework. This layer focuses on the risk assessment of the vehicles themselves and on producing a highlevel security design adequate for the mission defined in the first layer. To support this process, we also define a reference model for autonomous vehicles to use as a common basis for the assessment of risks and the design of the security controls.

The objective of this paper is to propose a model of a distributed intrusion detection system based on the multi-agent paradigm and the distributed file system (HDFS). Multi-agent systems (MAS) are very suitable to intrusion detection systems as they can address the issue of geographic data security in terms of autonomy, distribution and performance. The proposed system is based on a set of autonomous agents that cooperate and collaborate with each other to effectively detect intrusions and suspicious activities that may impact geographic information systems. Our system allows the detection of known and unknown computer attacks without any human intervention (Security Experts) unlike traditional intrusion detection systems that rely on knowledge bases as a mechanism to detect known attacks. The proposed model allows a real time detection of known and unknown attacks within large networks hosting geographic data.

Trust among humans affects the way we interact with each other. In autonomous systems, this trust is often predefined and hard-coded before the systems are deployed. However, when systems encounter unfolding situations, requiring them to interact with others, a notion of trust will be inevitable. In this paper, we discuss trust as a fundamental measure to enable an autonomous system to decide whether or not to interact with another system, whether biological or artificial. These decisions become increasingly important when continuously integrating with others during runtime.

Recent behavioral research in information security has focused on increasing employees' motivation to enhance the security performance in an organization. This empirical study investigated employees' information security policy (ISP) compliance intentions using self-determination theory (SDT). Relevant hypotheses were developed to test the proposed research model. Data obtained via a survey (N=3D407) from a Fortune 600 organization in Saudi Arabia provides empirical support for the model. The results confirmed that autonomy, competence and the concept of relatedness all positively affect employees' intentions to comply. The variable 'perceived value congruence' had a negative effect on ISP compliance intentions, and the perceived legitimacy construct did not affect employees' intentions. In general, the findings of this study suggest that SDT has value in research into employees' ISP compliance intentions.

The objective of this paper is to propose a distributed intrusion detection model based on a multi agent system. Mutli Agent Systems (MAS) are very suitable for intrusion detection systems as they meet the characteristics required by the networks and Big Data issues. The MAS agents cooperate and communicate with each other to ensure the effective detection of network intrusions without the intervention of an expert as used to be in the classical intrusion detection systems relying on signature matching to detect known attacks. The proposed model helped to detect known and unknown attacks within big computer infrastructure by responding to the network requirements in terms of distribution, autonomy, responsiveness and communication. The proposed model is capable of achieving a good and a real time intrusion detection using multi-agents paradigm and Hadoop Distributed File System (HDFS).

Recent behavioral research in information security has focused on increasing employees' motivation to enhance the security performance in an organization. This empirical study investigated employees' information security policy (ISP) compliance intentions using self-determination theory (SDT). Relevant hypotheses were developed to test the proposed research model. Data obtained via a survey (N=3D407) from a Fortune 600 organization in Saudi Arabia provides empirical support for the model. The results confirmed that autonomy, competence and the concept of relatedness all positively affect employees' intentions to comply. The variable 'perceived value congruence' had a negative effect on ISP compliance intentions, and the perceived legitimacy construct did not affect employees' intentions. In general, the findings of this study suggest that SDT has value in research into employees' ISP compliance intentions.