arXiv subjects

Jason Jaskolka

Publications and source records attributed to Jason Jaskolka.

9 recordsLinked to original sources

arXiv2026

Teaching Machine Learning to Software Engineers

Machine learning (ML) and Artificial Intelligence (AI) components are increasingly embedded in software products, yet undergraduate software engineering (SE) curricula rarely provide systematic preparation for building, testing, deploying, and maintaining AI/ML-based software systems. This paper aims to provide evidence-based guidance for integrating AI/MLrelevant content into core SE education. We compile and define a structured inventory of topics relevant to SE practice in AI/MLbased software, then map these topics against required courses in a set of representative SE curricula to identify coverage gaps. To assess educational priorities and feasibility, we survey SE instructors on topic importance and integration constraints. Based on the crosswalk between topic definitions, curriculum coverage, and instructor prioritization, we derive a guideline that recommends where and how high-priority topics can be embedded within existing SE courses.

cs.SE↗

arXiv2026

A Multi-Perspective Study of the Internet Shutdown in Iran

Iran conducted two nationwide Internet shutdowns in 2026, on January 8-25 and March 1-May 26, the latter lasting 86 days. We characterize both using three complementary measurement planes: six months of daily Censys scan data, BGP analysis of RIPE RIS snapshots spanning 2019-2026, and continuous per-prefix TCP probing from five vantage points. Each plane captures a different aspect of Iranian connectivity, and interpreting any one in isolation can be misleading. Unlike the partial BGP withdrawal of 2019, the 2022 and 2026 shutdowns were enforced by forwarding-plane discard while 80-88% of Iranian prefixes remained announced, leaving control-plane monitors blind. Restoration is similarly invisible to BGP, appearing in our forwarding-plane measurements as a centrally coordinated step. Censys host counts overshoot to approximately 3.6 times their pre-shutdown baseline after both restorations, rather than returning to baseline. Active probing reveals this inflation to be an artifact: most of the 3M apparent hosts are injected UDP/5353 responses synthesized by an on-path element at Iran's international gateway. Finally, AS-path classification shows that some apparent shutdown survivors were routed through foreign upstreams and never traversed the enforcement point. Together, these results show that measuring shutdowns requires reading multiple planes against one another, as no single signal reliably distinguishes genuine connectivity from its absence.

cs.NI↗

arXiv2026

SecMLOps: A Comprehensive Framework for Integrating Security Throughout the MLOps Lifecycle

Machine Learning (ML) has emerged as a pivotal technology in the operation of large and complex systems, driving advancements in fields such as autonomous vehicles, healthcare diagnostics, and financial fraud detection. Despite its benefits, the deployment of ML models brings significant security challenges, such as adversarial attacks, which can compromise the integrity and reliability of these systems. To address these challenges, this paper builds upon the concept of Secure Machine Learning Operations (SecMLOps), providing a comprehensive framework designed to integrate robust security measures throughout the entire ML operations (MLOps) lifecycle. SecMLOps builds on the principles of MLOps by embedding security considerations from the initial design phase through to deployment and continuous monitoring. This framework is particularly focused on safeguarding against sophisticated attacks that target various stages of the MLOps lifecycle, thereby enhancing the resilience and trustworthiness of ML applications. A detailed advanced pedestrian detection system (PDS) use case demonstrates the practical application of SecMLOps in securing critical MLOps. Through extensive empirical evaluations, we highlight the trade-offs between security measures and system performance, providing critical insights into optimizing security without unduly impacting operational efficiency. Our findings underscore the importance of a balanced approach, offering valuable guidance for practitioners on how to achieve an optimal balance between security and performance in ML deployments across various domains.

cs.CR↗

arXiv2025

strideSEA: A STRIDE-centric Security Evaluation Approach

Microsoft's STRIDE methodology is at the forefront of threat modeling, supporting the increasingly critical quality attribute of security in software-intensive systems. However, in a comprehensive security evaluation process, the general consensus is that the STRIDE classification is only useful for threat elicitation, isolating threat modeling from the other security evaluation activities involved in a secure software development life cycle (SDLC). We present strideSEA, a STRIDE-centric Security Evaluation Approach that integrates STRIDE as the central classification scheme into the security activities of threat modeling, attack scenario analysis, risk analysis, and countermeasure recommendation that are conducted alongside software engineering activities in secure SDLCs. The application of strideSEA is demonstrated in a real-world online immunization system case study. Using STRIDE as a single unifying thread, we bind existing security evaluation approaches in the four security activities of strideSEA to analyze (1) threats using Microsoft threat modeling tool, (2) attack scenarios using attack trees, (3) systemic risk using NASA's defect detection and prevention (DDP) technique, and (4) recommend countermeasures based on their effectiveness in reducing the most critical risks using DDP. The results include a detailed quantitative assessment of the security of the online immunization system with a clear definition of the role and advantages of integrating STRIDE in the evaluation process. Overall, the unified approach in strideSEA enables a more structured security evaluation process, allowing easier identification and recommendation of countermeasures, thus supporting the security requirements and eliciting design considerations, informing the software development life cycle of future software-based information systems.

cs.CR↗

arXiv2025

A Scalable Game-Theoretic Approach for Selecting Security Controls from Standardized Catalogues

Selecting the combination of security controls that will most effectively protect a system's assets is a difficult task. If the wrong controls are selected, the system may be left vulnerable to cyber-attacks that can impact the confidentiality, integrity, and availability of critical data and services. In practical settings, as standardized control catalogues can be quite large, it is not possible to select and implement every control possible. Instead, considerations, such as budget, effectiveness, and dependencies among various controls, must be considered to choose a combination of security controls that best achieve a set of system security objectives. In this paper, we present a game-theoretic approach for selecting effective combinations of security controls based on expected attacker profiles and a set budget. The control selection problem is set up as a two-person zero-sum one-shot game. Valid control combinations for selection are generated using an algebraic formalism to account for dependencies among selected controls. Using a software tool, we apply the approach on a fictional Canadian military system with Canada's standardized control catalogue, ITSG-33. Through this case study, we demonstrate the approach's scalability to assist in selecting an effective set of security controls for large systems. The results illustrate how a security analyst can use the proposed approach and supporting tool to guide and support decision-making in the control selection activity when developing secure systems of all sizes.

cs.SE↗

arXiv2024

A Game-Theoretic Approach for Security Control Selection

Selecting the combination of security controls that will most effectively protect a system's assets is a difficult task. If the wrong controls are selected, the system may be left vulnerable to cyber-attacks that can impact the confidentiality, integrity and availability of critical data and services. In practical settings, it is not possible to select and implement every control possible. Instead considerations, such as budget, effectiveness, and dependencies among various controls, must be considered to choose a combination of security controls that best achieve a set of system security objectives. In this paper, we propose a game-theoretic approach for selecting effective combinations of security controls based on expected attacker profiles and a set budget. The control selection problem is set up as a two-person zero-sum one-shot game. Valid control combinations for selection are generated using an algebraic formalism to account for dependencies among selected controls. We demonstrate the proposed approach on an illustrative financial system used in government departments under four different scenarios. The results illustrate how a security analyst can use the proposed approach to guide and support decision-making in the control selection activity when developing secure systems.

cs.CR↗

arXiv2022

Open Source Horizontal IoT Platforms: A Comparative Study on Functional Requirements

The growth in the deployment of Internet of Things (IoT) devices in various industries required the use of IoT platforms to manage, automate and control devices. This introduced different commercial and open source IoT platforms for developers and researchers to deploy. As a result, selecting one of these platforms for a specific application and use case became a challenge. In this study, a guideline for selecting an open source platform is presented. The process starts by identifying a list of functional requirements that would reflect the requirements of an IoT system in general. This list of requirements is used to compare between four major open source platforms: 1) OM2M (OneM2M standard), 2) IoTivity (OCF standard), LwM2M (OMA SpecWorks LwM2M standard), and 4) FIWARE (FIWARE standard). The purpose of this comparison is to indicate the capability and limitations of the different platforms and how they satisfy each requirement. Afterwards, two examples are presented to demonstrate how this guideline is used to select the most suitable platform for an e-health and a smart city use case. This includes how to define each use case and all the required information that could affect the process of selecting the most suitable platform for the development of the IoT platform.

cs.NI↗

arXiv2020

Evaluating the Exploitability of Implicit Interactions in Distributed Systems

Implicit interactions refer to those interactions among the components of a system that may be unintended and/or unforeseen by the system designers. As such, they represent cybersecurity vulnerabilities that can be exploited to mount cyber-attacks causing serious and destabilizing system effects. In this paper, we study implicit interactions in distributed systems specified using the algebraic modeling framework known as Communicating Concurrent Kleene Algebra (C$^2$KA). To identify and defend against a range of possible attack scenarios, we develop a new measure of exploitability for implicit interactions to aid in evaluating the threat posed by the existence of such vulnerabilities in system designs for launching cyber-attacks. The presented approach is based on the modeling and analysis of the influence and response of the system agents and their C$^2$KA specifications. We also demonstrate the applicability of the proposed approach using a prototype tool that supports the automated analysis. The rigorous, practical techniques presented here enable cybersecurity vulnerabilities in the designs of distributed systems to be more easily identified, assessed, and then mitigated, offering significant improvements to overall system resilience, dependability, and security.

cs.CR↗

arXiv2014

A Formulation of the Potential for Communication Condition using C2KA

An integral part of safeguarding systems of communicating agents from covert channel communication is having the ability to identify when a covert channel may exist in a given system and which agents are more prone to covert channels than others. In this paper, we propose a formulation of one of the necessary conditions for the existence of covert channels: the potential for communication condition. Then, we discuss when the potential for communication is preserved after the modification of system agents in a potential communication path. Our approach is based on the mathematical framework of Communicating Concurrent Kleene Algebra (C2KA). While existing approaches only consider the potential for communication via shared environments, the approach proposed in this paper also considers the potential for communication via external stimuli.

cs.LO↗