D-SCENT: Raising challenges to deception attempts using data scent trails

D-SCENT：利用数据气味踪迹对欺骗尝试提出挑战

• 批准号: EP/F008600/1
• 负责人: Michael Jackson
• 金额: $ 39.71万
• 依托单位: University of Nottingham
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2007
• 资助国家: 英国
• 起止时间: 2007 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FF008600%2F1
• 关键词: SCENT; Raising; challenges; deception; attempts

Since 9-11 and 7-7, terrorism has been a major public concern. To ensure public safety and to protect the UK economy, research is needed that offers new methods to foil attacks before they are executed, to identify people and networks who might be preparing for or undertaking an attack, and to provide clear evidence that can be used to justify questioning, arrests and prosecutions.In this study, we will investigate whether deception can be identified and proved from 'scent trails', that is, coherent accounts of suspects' activities over time compiled from tracking their movements, communications and behaviours. We will develop software to derive inferences about what activities are consistent with suspects' scent trails and what are ruled out. These inferences will allow investigators to challenge suspects, both in real time (e.g., to encourage suspects to abandon an ongoing attack) and during interviews (e.g., to point out inconsistencies between a suspect's account and scent trail evidence that might change the course of an interview).The project will investigate scent trails in the context of people undertaking deceptive activities to gain advantage in adversarial 'treasure hunt'-type games. The games will be developed in consultation with stakeholders to provide a non-sensitive analogy to counter-terrorism contexts. Players, typically undergraduate students paid for participation, will be monitored during games via positional and communication data obtained from mobile devices enabled with geospatial positioning devices. Novel software for integrating these data will be developed to build up scent trails of players' activities during game play. Methods of artificial intelligence will be combined to derive inferences from the scent trails about what kinds of activity are possible and impossible given a player's location, trajectory, activities and links with others.We envision games with 3 teams: Team A represent the adversary, Team B the police or general public, and Team C the intelligence services. Team A scores points by visiting target locations within a time limit under a set of game rules that they must violate if they are to win. They must try to hide rule violations from Team B, who score points by preventing or identifying Team A's deceptions successfully. Team C can challenge Team A by sending them indications of the scent trails that are held or can feed Team B intelligence information. Moreover, the inferences from scent trails will support Team C in deciding how best to prove or falsify a suspicion during an interview with Team A players at key points during the games.By conducting observation of players during games, we can investigate how people change their behaviours when they are confronted with evidence that reveals their deceptions. We will also interview players at key points during games as a simulation of interviews with suspects, eliciting from players accounts of their activities before presenting them with challenges based on their own scent trails that are either consistent or inconsistent with legal game playing. This will allow interview and analysis techniques to be improved and will provide clues as to how people subsequently change their behaviour after they have been confronted with their deception. The results will also allow us to test between hypotheses deriving from forensic psychology as to how best to detect deception.The research also allows us to explore public awareness of, and response to, monitoring and surveillance in counter-terrorism. With an advisory panel of stakeholders and subject specialists representing key public and academic bodies, we will identify ethical and legal issues associated with collecting and using data on peoples' movements through public spaces. We will also conduct questionnaire studies with game players and others not involved in the games, to measure attitudes to monitoring and surveillance in game-playing and other contexts.

自“9·11”和“7·7”事件以来，恐怖主义一直是公众关注的主要问题。为了确保公共安全并保护英国经济，需要进行研究，提供新的方法来在攻击实施之前挫败攻击，识别可能正在准备或进行攻击的人员和网络，并提供可使用的明确证据在这项研究中，我们将调查是否可以通过“气味踪迹”来识别和证明欺骗行为，即通过跟踪犯罪嫌疑人的行动、通讯和行为，对嫌疑人随时间推移的活动进行连贯描述。我们将开发软件来推断哪些活动与嫌疑人的气味痕迹一致以及哪些活动被排除。这些推论将使调查人员能够实时向嫌疑人提出质疑（例如，鼓励嫌疑人放弃正在进行的攻击），并在访谈期间（例如，指出嫌疑人的叙述与气味线索证据之间的不一致之处，这些不一致可能会改变犯罪进程）该项目将调查人们进行欺骗性活动以在对抗性“寻宝”类游戏中获得优势的背景下的气味踪迹。这些游戏将与利益相关者协商开发，以提供与反恐背景不敏感的类比。玩家（通常是付费参与的本科生）将在游戏期间通过从具有地理空间定位设备的移动设备获得的位置和通信数据进行监控。将开发用于集成这些数据的新颖软件，以建立玩家在游戏过程中活动的气味轨迹。人工智能的方法将结合起来，根据玩家的位置、轨迹、活动以及与他人的联系，从气味轨迹中推断出哪些类型的活动是可能的和不可能的。我们设想由 3 支球队组成的比赛：A 队代表对手，Team 代表对手。 B 是警察或公众，C 组是情报部门。 A 队通过在规定时间内访问目标地点来得分，并遵守一组游戏规则，如果他们想获胜就必须违反这些规则。他们必须设法向 B 队隐瞒违规行为，而 B 队则通过成功阻止或识别 A 队的欺骗行为来得分。 C 队可以通过向 A 队发送所掌握的气味踪迹的指示来挑战 A 队，或者可以向 B 队提供情报信息。此外，气味踪迹的推断将支持C队在比赛过程中的关键时刻采访A队球员时决定如何最好地证明或证伪怀疑。通过在比赛期间对球员进行观察，我们可以调查人们如何改变他们的行为当他们面对揭露他们欺骗的证据时的行为。我们还将在游戏过程中的关键时刻采访玩家，就像模拟采访嫌疑人一样，从玩家那里获取他们的活动描述，然后根据他们自己的气味轨迹（与合法游戏玩法一致或不一致）向他们提出挑战。这将使访谈和分析技术得到改进，并为人们在面对欺骗后如何改变行为提供线索。研究结果还将使我们能够测试源自法医心理学的假设，以了解如何最好地检测欺骗。这项研究还使我们能够探索公众对反恐监测和监视的认识和反应。通过代表主要公共和学术机构的利益相关者和学科专家组成的咨询小组，我们将确定与收集和使用公共场所人们活动数据相关的道德和法律问题。我们还将对游戏玩家和其他未参与游戏的人进行问卷研究，以衡量对游戏和其他环境中的监控和监视的态度。

项目成果

Improving Professional Observers' Veracity Judgements by Tactical Interviewing

通过战术访谈提高专业观察者判断的准确性

• DOI: http://dx.10.1007/s11896-020-09391-1
• 发表时间: 2020
• 期刊: Journal of Police and Criminal Psychology
• 影响因子: 1.6
• 作者: Sandham A