Course trains law enforcement to spot terror

NEW YORK

At first glance, a man and a woman outside a building seem to be normal tourists in Midtown Manhattan, but are they really that innocent?

"To the average passerby, he would be taking a picture of her, but in reality he's taking a picture of an entrance," Sal Lifrieri said.

Lifrieri was demonstrating the training techniques his firm uses in a surveillance and counter-surveillance course taught to law enforcement officers and private security firms around the world.

"What we always instruct the team to look for is what's the view of the subject of the view behind being photographed, and in this case it's the loading dock," he said.

That couple was playing the role of would-be terrorists scouting out possible targets.

"It could be a tourist, it could be somebody that would operate as a delivery person," Lifrieri said.

The security personnel who take the course are sent out to try to pick out the bad guys in an anonymous crowd and do countersurveillance.

"If you go out and just look for suspicious behavior, you're not going to see it," Lifrieri said. "What you have to do is put yourself in that role of the person committing the crime or conducting surveillance."

Jim Desaye is an instructor.

"There's numerous red flags," Desaye said. "The suspect just walking down the street, walking slower than the rest of traffic, moving around traffic, looking around, looking up at cameras...Antyime he's not going with the flow, that's a red flag."

Security officer Juan Lopez recently went through the course and says it's made him see things very differently.

"You have to put yourself in their shoes," he said. "If I was going to do it, let's say how I was going to do it, where would I stand. You gotta step out of the box."

And that same strategy is designed to be used in a variety of venues, from high-rise buildings to open air stadiums.

The bigger the crowd, of course, the bigger the challenge. But Lifrieri recently put one of his counter-surveillance teams in a crowd of 60,000 people, and the team identified the three role players.

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